large well-defined clusters: Topics by Science.gov

Sample records for large well-defined clusters

Covalent Binding with Neutrons on the Femto-scale

NASA Astrophysics Data System (ADS)

von Oertzen, W.; Kanada-En'yo, Y.; Kimura, M.

2017-06-01

In light nuclei we have well defined clusters, nuclei with closed shells, which serve as centers for binary molecules with covalent binding by valence neutrons. Single neutron orbitals in light neutron-excess nuclei have well defined shell model quantum numbers. With the combination of two clusters and their neutron valence states, molecular two-center orbitals are defined; in the two-center shell model we can place valence neutrons in a large variety of molecular two-center states, and the formation of Dimers becomes possible. The corresponding rotational bands point with their large moments of inertia and the Coriolis decoupling effect (for K = 1/2 bands) to the internal molecular orbital structure in these states. On the basis of these the neutron rich isotopes allow the formation of a large variety molecular structures on the nuclear scale. An extended Ikeda diagram can be drawn for these cases. Molecular bands in Be and Ne-isotopes are discussed as text-book examples.
Just the right age: well-clustered exposure ages from a global glacial 10Be compilation

NASA Astrophysics Data System (ADS)

Heyman, Jakob; Margold, Martin

2017-04-01

Cosmogenic exposure dating has been used extensively for defining glacial chronologies, both in ice sheet and alpine settings, and the global set of published ages today reaches well beyond 10,000 samples. Over the last few years, a number of important developments have improved the measurements (with well-defined AMS standards) and exposure age calculations (with updated data and methods for calculating production rates), in the best case enabling high precision dating of past glacial events. A remaining problem, however, is the fact that a large portion of all dated samples have been affected by prior and/or incomplete exposure, yielding erroneous exposure ages under the standard assumptions. One way to address this issue is to only use exposure ages that can be confidently considered as unaffected by prior/incomplete exposure, such as groups of samples with statistically identical ages. Here we use objective statistical criteria to identify groups of well-clustered exposure ages from the global glacial "expage" 10Be compilation. Out of ˜1700 groups with at least 3 individual samples ˜30% are well-clustered, increasing to ˜45% if allowing outlier rejection of a maximum of 1/3 of the samples (still requiring a minimum of 3 well-clustered ages). The dataset of well-clustered ages is heavily dominated by ages <30 ka, showing that well-defined cosmogenic chronologies primarily exist for the last glaciation. We observe a large-scale global synchronicity in the timing of the last deglaciation from ˜20 to 10 ka. There is also a general correlation between the timing of deglaciation and latitude (or size of the individual ice mass), with earlier deglaciation in lower latitudes and later deglaciation towards the poles. Grouping the data into regions and comparing with available paleoclimate data we can start to untangle regional differences in the last deglaciation and the climate events controlling the ice mass loss. The extensive dataset and the statistical analysis enables an unprecedented global view on the last deglaciation.
Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion

NASA Astrophysics Data System (ADS)

Scott, Charles J. C.; Thom, Alex J. W.

2017-09-01

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behavior of a coupled cluster wavefunction representation, we propose new approaches based on an intuitive, well-defined condition for sampling weights and on sampling the expansion in cluster operators of different excitation levels. We term these modifications even and truncated selections, respectively. Utilising both approaches demonstrates dramatically improved calculation stability as well as reduced computational and memory costs. These modifications are particularly effective at higher truncation levels owing to the large number of terms within the cluster expansion that can be neglected, as demonstrated by the reduction of the number of terms to be sampled when truncating at triple excitations by 77% and hextuple excitations by 98%.
Accurate age determinations of several nearby open clusters containing magnetic Ap stars

NASA Astrophysics Data System (ADS)

Silaj, J.; Landstreet, J. D.

2014-06-01

Context. To study the time evolution of magnetic fields, chemical abundance peculiarities, and other characteristics of magnetic Ap and Bp stars during their main sequence lives, a sample of these stars in open clusters has been obtained, as such stars can be assumed to have the same ages as the clusters to which they belong. However, in exploring age determinations in the literature, we find a large dispersion among different age determinations, even for bright, nearby clusters. Aims: Our aim is to obtain ages that are as accurate as possible for the seven nearby open clusters α Per, Coma Ber, IC 2602, NGC 2232, NGC 2451A, NGC 2516, and NGC 6475, each of which contains at least one magnetic Ap or Bp star. Simultaneously, we test the current calibrations of Te and luminosity for the Ap/Bp star members, and identify clearly blue stragglers in the clusters studied. Methods: We explore the possibility that isochrone fitting in the theoretical Hertzsprung-Russell diagram (i.e. log (L/L⊙) vs. log Te), rather than in the conventional colour-magnitude diagram, can provide more precise and accurate cluster ages, with well-defined uncertainties. Results: Well-defined ages are found for all the clusters studied. For the nearby clusters studied, the derived ages are not very sensitive to the small uncertainties in distance, reddening, membership, metallicity, or choice of isochrones. Our age determinations are all within the range of previously determined values, but the associated uncertainties are considerably smaller than the spread in recent age determinations from the literature. Furthermore, examination of proper motions and HR diagrams confirms that the Ap stars identified in these clusters are members, and that the presently accepted temperature scale and bolometric corrections for Ap stars are approximately correct. We show that in these theoretical HR diagrams blue stragglers are particularly easy to identify. Conclusions: Constructing the theoretical HR diagram of a nearby open cluster makes possible an accurate age determination, with well defined uncertainty. This diagnostic of a cluster also provides a useful tool for studying unusual stars such as Ap stars and blue stragglers. Table 3 is available in electronic form at http://www.aanda.org
Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

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

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less
Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

DOE PAGES

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang; ...

2016-08-19

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less
Efficient clustering aggregation based on data fragments.

PubMed

Wu, Ou; Hu, Weiming; Maybank, Stephen J; Zhu, Mingliang; Li, Bing

2012-06-01

Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.
HIGH RESOLUTION SPECTROSCOPY IN THE GAS PHASE: Even Large Molecules Have Well-Defined Shapes

NASA Astrophysics Data System (ADS)

Pratt, David W.

1998-10-01

A review of recent high-resolution microwave, infrared, and optical spectroscopy experiments demonstrates that remarkable progress has been made in the past 20 years in determining the equilibrium geometries of large polyatomic molecules and their clusters in the gas phase, and how these geometries change when the photon is absorbed. A special focus is on the dynamical information that can be obtained from such studies, particularly of electronically excited states.
Automated Classification and Analysis of Non-metallic Inclusion Data Sets

NASA Astrophysics Data System (ADS)

Abdulsalam, Mohammad; Zhang, Tongsheng; Tan, Jia; Webler, Bryan A.

2018-05-01

The aim of this study is to utilize principal component analysis (PCA), clustering methods, and correlation analysis to condense and examine large, multivariate data sets produced from automated analysis of non-metallic inclusions. Non-metallic inclusions play a major role in defining the properties of steel and their examination has been greatly aided by automated analysis in scanning electron microscopes equipped with energy dispersive X-ray spectroscopy. The methods were applied to analyze inclusions on two sets of samples: two laboratory-scale samples and four industrial samples from a near-finished 4140 alloy steel components with varying machinability. The laboratory samples had well-defined inclusions chemistries, composed of MgO-Al2O3-CaO, spinel (MgO-Al2O3), and calcium aluminate inclusions. The industrial samples contained MnS inclusions as well as (Ca,Mn)S + calcium aluminate oxide inclusions. PCA could be used to reduce inclusion chemistry variables to a 2D plot, which revealed inclusion chemistry groupings in the samples. Clustering methods were used to automatically classify inclusion chemistry measurements into groups, i.e., no user-defined rules were required.
Molecular growth from a Mo176 to a Mo248 cluster

NASA Astrophysics Data System (ADS)

Müller, A.; Shah, Syed Q. N.; Bögge, H.; Schmidtmann, M.

1999-01-01

In polyoxometalate chemistry a large variety of compounds, clusters and solid-state structures can be formed by the linking together of well-defined metal-oxygen building blocks, . These species exhibit unusual topological and electronic properties, andfind applications ranging from medicine to industrial processes. The recently reported ring-shaped mixed-valence polyoxomolybdates of the type {Mo154} (refs 5, 6) and {Mo176} (refs 7, 8) represent a new class of giant clusters with nanometre-sized cavities and interesting properties for host-guest chemistry. Here we describe the formation of related clusters of the type {Mo248} formed by addition of further units to the inner surface of the {Mo176 } `wheel'. The additional units arrange themselves into two {Mo36} `hub-caps' on the initial wheel-clusters that are not stable in isolation. These findings reveal a new pathway to the development of complex coordination clusters.
Genuine non-self-averaging and ultraslow convergence in gelation.

PubMed

Cho, Y S; Mazza, M G; Kahng, B; Nagler, J

2016-08-01

In irreversible aggregation processes droplets or polymers of microscopic size successively coalesce until a large cluster of macroscopic scale forms. This gelation transition is widely believed to be self-averaging, meaning that the order parameter (the relative size of the largest connected cluster) attains well-defined values upon ensemble averaging with no sample-to-sample fluctuations in the thermodynamic limit. Here, we report on anomalous gelation transition types. Depending on the growth rate of the largest clusters, the gelation transition can show very diverse patterns as a function of the control parameter, which includes multiple stochastic discontinuous transitions, genuine non-self-averaging and ultraslow convergence of the transition point. Our framework may be helpful in understanding and controlling gelation.
Planck/SDSS Cluster Mass and Gas Scaling Relations for a Volume-Complete redMaPPer Sample

NASA Astrophysics Data System (ADS)

Jimeno, Pablo; Diego, Jose M.; Broadhurst, Tom; De Martino, I.; Lazkoz, Ruth

2018-04-01

Using Planck satellite data, we construct Sunyaev-Zel'dovich (SZ) gas pressure profiles for a large, volume-complete sample of optically selected clusters. We have defined a sample of over 8,000 redMaPPer clusters from the Sloan Digital Sky Survey (SDSS), within the volume-complete redshift region 0.100 < z < 0.325, for which we construct SZ effect maps by stacking Planck data over the full range of richness. Dividing the sample into richness bins we simultaneously solve for the mean cluster mass in each bin together with the corresponding radial pressure profile parameters, employing an MCMC analysis. These profiles are well detected over a much wider range of cluster mass and radius than previous work, showing a clear trend towards larger break radius with increasing cluster mass. Our SZ-based masses fall ˜16% below the mass-richness relations from weak lensing, in a similar fashion as the "hydrostatic bias" related with X-ray derived masses. Finally, we derive a tight Y500-M500 relation over a wide range of cluster mass, with a power law slope equal to 1.70 ± 0.07, that agrees well with the independent slope obtained by the Planck team with an SZ-selected cluster sample, but extends to lower masses with higher precision.
A quasi-static approach to structure formation in black hole universes

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

Durk, Jessie; Clifton, Timothy, E-mail: j.durk@qmul.ac.uk, E-mail: t.clifton@qmul.ac.uk

Motivated by the existence of hierarchies of structure in the Universe, we present four new families of exact initial data for inhomogeneous cosmological models at their maximum of expansion. These data generalise existing black hole lattice models to situations that contain clusters of masses, and hence allow the consequences of cosmological structures to be considered in a well-defined and non-perturbative fashion. The degree of clustering is controlled by a parameter λ, in such a way that for λ ∼ 0 or 1 we have very tightly clustered masses, whilst for λ ∼ 0.5 all masses are separated by cosmological distancemore » scales. We study the consequences of structure formation on the total net mass in each of our clusters, as well as calculating the cosmological consequences of the interaction energies both within and between clusters. The locations of the shared horizons that appear around groups of black holes, when they are brought sufficiently close together, are also identified and studied. We find that clustering can have surprisingly large effects on the scale of the cosmology, with models that contain thousands of black holes sometimes being as little as 30% of the size of comparable Friedmann models with the same total proper mass. This deficit is comparable to what might be expected to occur from neglecting gravitational interaction energies in Friedmann cosmology, and suggests that these quantities may have a significant influence on the properties of the large-scale cosmology.« less
Identification of chronic rhinosinusitis phenotypes using cluster analysis.

PubMed

Soler, Zachary M; Hyer, J Madison; Ramakrishnan, Viswanathan; Smith, Timothy L; Mace, Jess; Rudmik, Luke; Schlosser, Rodney J

2015-05-01

Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the Sino-Nasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Medical Outcomes Study Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT, and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Clustering was largely determined by age, severity of patient reported outcome measures, depression, and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures, including polyp/atopic status, prior surgery, B-SIT and asthma, did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score, and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. © 2015 ARS-AAOA, LLC.
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale

PubMed Central

Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters. PMID:27391786
X-ray morphological study of the ESZ sample

NASA Astrophysics Data System (ADS)

Lovisari, L.; Forman, W.; Jones, C.; Andrade-Santos, F.; Democles, J.; Pratt, G.; Ettori, S.; Arnaud, M.; Randall, S.; Kraft, R.

2017-10-01

An accurate knowledge of the scaling relations between X-ray observables and cluster mass is a crucial step for studies that aim to constrain cosmological parameters using galaxy clusters. The measure of the dynamical state of the systems offers important information to obtain precise scaling relations and understand their scatter. Unfortunately, characterize the dynamical state of a galaxy cluster requires to access a large set of information in different wavelength which are available only for a few individual systems. An alternative is to compute well defined morphological parameters making use of the relatively cheap X-ray images and profiles. Due to different projection effects none of the methods is good in all the cases and a combination of them is more effective to quantify the level of substructures. I will present the cluster morphologies that we derived for the ESZ sample. I will show their dependence on different cluster properties like total mass, redshift, and luminosity and how they differ from the ones obtained for X-ray selected clusters.
Prospects for AGN Science using the ART-XC on the SRG Mission

NASA Technical Reports Server (NTRS)

Swartz, Douglas A.; Elsner, Ronald F.; Gubarev, Mikhail V.; O'Dell, Stephen L.; Ramsey, Brian D.; Bonamente, Massimiliano

2012-01-01

The enhanced hard X-ray sensitivity provided by the Astronomical Roentgen Telescope to the Spectrum Roentgen Gamma mission facilitates the detection of heavily obscured and other hard-spectrum cosmic X-ray sources. The SRG all-sky survey will obtain large, statistically-well-defined samples of active galactic nuclei (AGN) including a significant population of local heavily-obscured AGN. In anticipation of the SRG all-sky survey, we investigate the prospects for refining the bright end of the AGN luminosity function and determination of the local black hole mass function and comparing the spatial distribution of AGN with large-scale structure defined by galaxy clusters and groups. Particular emphasis is placed on studies of the deep survey Ecliptic Pole regions.
Dark energy and the structure of the Coma cluster of galaxies

NASA Astrophysics Data System (ADS)

Chernin, A. D.; Bisnovatyi-Kogan, G. S.; Teerikorpi, P.; Valtonen, M. J.; Byrd, G. G.; Merafina, M.

2013-05-01

Context. We consider the Coma cluster of galaxies as a gravitationally bound physical system embedded in the perfectly uniform static dark energy background as implied by ΛCDM cosmology. Aims: We ask if the density of dark energy is high enough to affect the structure of a large and rich cluster of galaxies. Methods: We base our work on recent observational data on the Coma cluster, and apply our theory of local dynamical effects of dark energy, including the zero-gravity radius RZG of the local force field as the key parameter. Results: 1) Three masses are defined that characterize the structure of a regular cluster: the matter mass MM, the dark-energy effective mass MDE (<0), and the gravitating mass MG (=MM + MDE). 2) A new matter-density profile is suggested that reproduces the observational data well for the Coma cluster in the radius range from 1.4 Mpc to 14 Mpc and takes the dark energy background into account. 3) Using this profile, we calculate upper limits for the total size of the Coma cluster, R ≤ RZG ≈ 20 Mpc, and its total matter mass, MM ≲ MM(RZG) = 6.2 × 1015 M⊙. Conclusions: The dark energy antigravity affects the structure of the Coma cluster strongly at large radii R ≳ 14 Mpc and should be considered when its total mass is derived.
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

PubMed

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.
Planck/SDSS cluster mass and gas scaling relations for a volume-complete redMaPPer sample

NASA Astrophysics Data System (ADS)

Jimeno, Pablo; Diego, Jose M.; Broadhurst, Tom; De Martino, I.; Lazkoz, Ruth

2018-07-01

Using Planck satellite data, we construct Sunyaev-Zel'dovich (SZ) gas pressure profiles for a large, volume-complete sample of optically selected clusters. We have defined a sample of over 8000 redMaPPer clusters from the Sloan Digital Sky Survey, within the volume-complete redshift region 0.100

Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach.

PubMed

Sharma, Kiran; Gopalakrishnan, Balagopal; Chakrabarti, Anindya S; Chakraborti, Anirban

2017-08-14

We demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16).
Community structure from spectral properties in complex networks

NASA Astrophysics Data System (ADS)

Servedio, V. D. P.; Colaiori, F.; Capocci, A.; Caldarelli, G.

2005-06-01

We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.
Structure-related frustrated magnetism of nanosized polyoxometalates: aesthetics and properties in harmony.

PubMed

Kögerler, Paul; Tsukerblat, Boris; Müller, Achim

2010-01-07

The structural versatility characterizing polyoxometalate chemistry, in combination with the option to deliberately use well-defined building blocks, serves as the foundation for the generation of a large family of magnetic clusters, frequently comprising highly symmetric spin arrays. If the spin centers are coupled by antiferromagnetic exchange, some of these systems exhibit spin frustration, which can result in novel magnetic properties of purely molecular origins. We discuss here the magnetic properties of selected nanosized polyoxometalate clusters featuring spin triangles as their magnetic 'building blocks' or fragments. This includes unique porous Keplerate clusters of the type {(Mo)Mo(5)}(12)M(30) (M = Fe(III), Cr(III), V(IV)) with the spin centers defining a regular icosidodecahedron and the {V(15)As(6)}-type cluster sphere containing a single equilateral spin triangle; these species are widely discussed and studied in the literature for their role in materials science as molecular representations of Kagomé lattices and in relation to quantum computing, respectively. Exhibiting fascinating and unique structural features, these magnetic molecules allow the study of the implications of frustrated spin ordering. Furthermore, this perspective covers the impact of spin frustration on the degeneracy of the ground state and related problems, namely strong magnetic anisotropy and the interplay of antisymmetric exchange and structural Jahn-Teller effects.
Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.
GASP. IX. Jellyfish galaxies in phase-space: an orbital study of intense ram-pressure stripping in clusters

NASA Astrophysics Data System (ADS)

Jaffé, Yara L.; Poggianti, Bianca M.; Moretti, Alessia; Gullieuszik, Marco; Smith, Rory; Vulcani, Benedetta; Fasano, Giovanni; Fritz, Jacopo; Tonnesen, Stephanie; Bettoni, Daniela; Hau, George; Biviano, Andrea; Bellhouse, Callum; McGee, Sean

2018-06-01

It is well known that galaxies falling into clusters can experience gas stripping due to ram pressure by the intra-cluster medium. The most spectacular examples are galaxies with extended tails of optically bright stripped material known as `jellyfish'. We use the first large homogeneous compilation of jellyfish galaxies in clusters from the WINGS and OmegaWINGS surveys, and follow-up MUSE observations from the GASP MUSE programme to investigate the orbital histories of jellyfish galaxies in clusters and reconstruct their stripping history through position versus velocity phase-space diagrams. We construct analytic models to define the regions in phase-space where ram-pressure stripping is at play. We then study the distribution of cluster galaxies in phase-space and find that jellyfish galaxies have on average higher peculiar velocities (and higher cluster velocity dispersion) than the overall population of cluster galaxies at all cluster-centric radii, which is indicative of recent infall into the cluster and radial orbits. In particular, the jellyfish galaxies with the longest gas tails reside very near the cluster cores (in projection) and are moving at very high speeds, which coincides with the conditions of the most intense ram pressure. We conclude that many of the jellyfish galaxies seen in clusters likely formed via fast (˜1-2 Gyr), incremental, outside-in ram-pressure stripping during first infall into the cluster in highly radial orbits.
A spin-down clock for cool stars from observations of a 2.5-billion-year-old cluster.

PubMed

Meibom, Søren; Barnes, Sydney A; Platais, Imants; Gilliland, Ronald L; Latham, David W; Mathieu, Robert D

2015-01-29

The ages of the most common stars--low-mass (cool) stars like the Sun, and smaller--are difficult to derive because traditional dating methods use stellar properties that either change little as the stars age or are hard to measure. The rotation rates of all cool stars decrease substantially with time as the stars steadily lose their angular momenta. If properly calibrated, rotation therefore can act as a reliable determinant of their ages based on the method of gyrochronology. To calibrate gyrochronology, the relationship between rotation period and age must be determined for cool stars of different masses, which is best accomplished with rotation period measurements for stars in clusters with well-known ages. Hitherto, such measurements have been possible only in clusters with ages of less than about one billion years, and gyrochronology ages for older stars have been inferred from model predictions. Here we report rotation period measurements for 30 cool stars in the 2.5-billion-year-old cluster NGC 6819. The periods reveal a well-defined relationship between rotation period and stellar mass at the cluster age, suggesting that ages with a precision of order 10 per cent can be derived for large numbers of cool Galactic field stars.
Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale

PubMed Central

Schmidt, Thomas S. B.; Matias Rodrigues, João F.; von Mering, Christian

2014-01-01

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale. PMID:24763141
LCGbase: A Comprehensive Database for Lineage-Based Co-regulated Genes.

PubMed

Wang, Dapeng; Zhang, Yubin; Fan, Zhonghua; Liu, Guiming; Yu, Jun

2012-01-01

Animal genes of different lineages, such as vertebrates and arthropods, are well-organized and blended into dynamic chromosomal structures that represent a primary regulatory mechanism for body development and cellular differentiation. The majority of genes in a genome are actually clustered, which are evolutionarily stable to different extents and biologically meaningful when evaluated among genomes within and across lineages. Until now, many questions concerning gene organization, such as what is the minimal number of genes in a cluster and what is the driving force leading to gene co-regulation, remain to be addressed. Here, we provide a user-friendly database-LCGbase (a comprehensive database for lineage-based co-regulated genes)-hosting information on evolutionary dynamics of gene clustering and ordering within animal kingdoms in two different lineages: vertebrates and arthropods. The database is constructed on a web-based Linux-Apache-MySQL-PHP framework and effective interactive user-inquiry service. Compared to other gene annotation databases with similar purposes, our database has three comprehensible advantages. First, our database is inclusive, including all high-quality genome assemblies of vertebrates and representative arthropod species. Second, it is human-centric since we map all gene clusters from other genomes in an order of lineage-ranks (such as primates, mammals, warm-blooded, and reptiles) onto human genome and start the database from well-defined gene pairs (a minimal cluster where the two adjacent genes are oriented as co-directional, convergent, and divergent pairs) to large gene clusters. Furthermore, users can search for any adjacent genes and their detailed annotations. Third, the database provides flexible parameter definitions, such as the distance of transcription start sites between two adjacent genes, which is extendable to genes that flanking the cluster across species. We also provide useful tools for sequence alignment, gene ontology (GO) annotation, promoter identification, gene expression (co-expression), and evolutionary analysis. This database not only provides a way to define lineage-specific and species-specific gene clusters but also facilitates future studies on gene co-regulation, epigenetic control of gene expression (DNA methylation and histone marks), and chromosomal structures in a context of gene clusters and species evolution. LCGbase is freely available at http://lcgbase.big.ac.cn/LCGbase.
Information sharing and sorting in a community

NASA Astrophysics Data System (ADS)

Bhattacherjee, Biplab; Manna, S. S.; Mukherjee, Animesh

2013-06-01

We present the results of a detailed numerical study of a model for the sharing and sorting of information in a community consisting of a large number of agents. The information gathering takes place in a sequence of mutual bipartite interactions where randomly selected pairs of agents communicate with each other to enhance their knowledge and sort out the common information. Although our model is less restricted compared to the well-established naming game, the numerical results strongly indicate that the whole set of exponents characterizing this model are different from those of the naming game and they assume nontrivial values. Finally, it appears that in analogy to the emergence of clusters in the phenomenon of percolation, one can define clusters of agents here having the same information. We have studied in detail the growth of the largest cluster in this article and performed its finite-size scaling analysis.
Compositional variability in Mediterranean archaeofaunas from Upper Paleolithic Southwest Europe

NASA Astrophysics Data System (ADS)

Jones, Emily Lena

2018-03-01

Recent meta-analyses of Upper Paleolithic Southwestern European archaeofaunas (Jones, 2015, 2016) have identified a consistent "Mediterranean" cluster from the Last Glacial Maximum through the early Holocene, suggesting similarities in environment and/or consistency in hunting strategy across this region through time despite radical changes in climate. However, while these archaeofaunas from this cluster all derive from sites located within today's Mediterranean bioclimatic region, many of them are from locations far from the Mediterranean Sea - Atlantic Portugal, the Spanish Meseta - which today differ significantly from each other in biotic composition. In this paper, I explore clustering (through cluster analysis and non-metric multidimensional scaling) within the Mediterranean archaeofaunal group. I test for the influence of sample size as well as the geographic variables of site elevation, latitude, and longitude on variability in the large mammal portions of archaeofaunal assemblages. ANOVA shows no relationship between cluster-defined groups and site elevation or longitude; instead, site latitude appears to be a primary contributor to patterning. However, the overall compositional similarity of the Mediterranean archaeofaunas in this dataset suggests more consistency than variability in Upper Paleolithic hunting strategy in this region.
Dissipation and Rheology of Sheared Soft-Core Frictionless Disks Below Jamming

NASA Astrophysics Data System (ADS)

Vâgberg, Daniel; Olsson, Peter; Teitel, S.

2014-05-01

We use numerical simulations to investigate the effect that different models of energy dissipation have on the rheology of soft-core frictionless disks, below jamming in two dimensions. We find that it is not necessarily the mass of the particles that determines whether a system has Bagnoldian or Newtonian rheology, but rather the presence or absence of large connected clusters of particles. We demonstrate the key role that tangential dissipation plays in the formation of such clusters and in several models find a transition from Bagnoldian to Newtonian rheology as the packing fraction ϕ is varied. For each model, we show that appropriately scaled rheology curves approach a well defined limit as the mass of the particles decreases and collisions become strongly inelastic.
Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.
Investigation of glutathione-derived electrostatic and hydrogen-bonding interactions and their role in defining Grx5 [2Fe-2S] cluster optical spectra and transfer chemistry.

PubMed

Sen, Sambuddha; Bonfio, Claudia; Mansy, Sheref S; Cowan, J A

2018-03-01

Human glutaredoxin 5 (Grx5) is one of the core components of the Isc (iron-sulfur cluster) assembly and trafficking machinery, and serves as an intermediary cluster carrier, putatively delivering cluster from the Isu scaffold protein to target proteins. The tripeptide glutathione is intimately involved in this role, providing cysteinyl coordination to the iron center of the Grx5-bound [2Fe-2S] cluster. Grx5 has a well-defined glutathione-binding pocket with protein amino acid residues providing many ionic and hydrogen binding contacts to the bound glutathione. In this report, we investigated the importance of these interactions in cluster chirality and exchange reactivity by systematically perturbing the crucial contacts by use of natural and non-natural amino acid substitutions to disrupt the binding contacts from both the protein and glutathione. Native Grx5 could be reconstituted with all of the glutathione analogs used, as well as other thiol ligands, such as DTT or L-cysteine, by in vitro chemical reconstitution, and the holo proteins were found to transfer [2Fe-2S] cluster to apo ferredoxin 1 at comparable rates. However, the circular dichroism spectra of these derivatives displayed prominent differences that reflect perturbations in local cluster chirality. These studies provided a detailed molecular understanding of glutathione-protein interactions in holo Grx5 that define both cluster spectroscopy and exchange chemistry.
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.
Evaluating the component contribution to nonlinear optical performances using stable [Ni4O4] cuboidal clusters as models.

PubMed

Hao, Zhi-Min; Chao, Meng-Yao; Liu, Yan; Song, Ying-Lin; Yang, Jun-Yi; Ding, Lifeng; Zhang, Wen-Hua; Lang, Jian-Ping

2018-06-19

Five stable clusters sharing the cuboidal [Ni4O4] skeleton are subjected to third-order nonlinear optical (NLO) property measurements. Preliminary results suggest that the NLO property is largely defined by the cluster core skeleton and the directly coordinated atoms, with limited contribution from the heavy atoms peripherally attached to the aromatic ligands.
Next-generation sequencing for typing and detection of resistance genes: performance of a new commercial method during an outbreak of extended-spectrum-beta-lactamase-producing Escherichia coli.

PubMed

Veenemans, J; Overdevest, I T; Snelders, E; Willemsen, I; Hendriks, Y; Adesokan, A; Doran, G; Bruso, S; Rolfe, A; Pettersson, A; Kluytmans, J A J W

2014-07-01

Next-generation sequencing (NGS) has the potential to provide typing results and detect resistance genes in a single assay, thus guiding timely treatment decisions and allowing rapid tracking of transmission of resistant clones. We evaluated the performance of a new NGS assay (Hospital Acquired Infection BioDetection System; Pathogenica) during an outbreak of sequence type 131 (ST131) Escherichia coli infections in a nursing home in The Netherlands. The assay was performed on 56 extended-spectrum-beta-lactamase (ESBL) E. coli isolates collected during 2 prevalence surveys (March and May 2013). Typing results were compared to those of amplified fragment length polymorphism (AFLP), whereby we visually assessed the agreement of the BioDetection phylogenetic tree with clusters defined by AFLP. A microarray was considered the gold standard for detection of resistance genes. AFLP identified a large cluster of 31 indistinguishable isolates on adjacent departments, indicating clonal spread. The BioDetection phylogenetic tree showed that all isolates of this outbreak cluster were strongly related, while the further arrangement of the tree also largely agreed with other clusters defined by AFLP. The BioDetection assay detected ESBL genes in all but 1 isolate (sensitivity, 98%) but was unable to discriminate between ESBL and non-ESBL TEM and SHV beta-lactamases or to specify CTX-M genes by group. The performance of the hospital-acquired infection (HAI) BioDetection System for typing of E. coli isolates compared well with the results of AFLP. Its performance with larger collections from different locations, and for typing of other species, was not evaluated and needs further study. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks.

PubMed

Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano

2012-02-21

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks

PubMed Central

Gallos, Lazaros K.; Makse, Hernán A.; Sigman, Mariano

2012-01-01

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are “large-world” self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the “strength of weak ties” crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain. PMID:22308319
EXTENDED STAR FORMATION IN THE INTERMEDIATE-AGE LARGE MAGELLANIC CLOUD STAR CLUSTER NGC 2209

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

Keller, Stefan C.; Mackey, A. Dougal; Da Costa, Gary S.

2012-12-10

We present observations of the 1 Gyr old star cluster NGC 2209 in the Large Magellanic Cloud made with the GMOS imager on the Gemini South Telescope. These observations show that the cluster exhibits a main-sequence turnoff that spans a broader range in luminosity than can be explained by a single-aged stellar population. This places NGC 2209 amongst a growing list of intermediate-age (1-3 Gyr) clusters that show evidence for extended or multiple epochs of star formation of between 50 and 460 Myr in extent. The extended main-sequence turnoff observed in NGC 2209 is a confirmation of the prediction inmore » Keller et al. made on the basis of the cluster's large core radius. We propose that secondary star formation is a defining feature of the evolution of massive star clusters. Dissolution of lower mass clusters through evaporation results in only clusters that have experienced secondary star formation surviving for a Hubble time, thus providing a natural connection between the extended main-sequence turnoff phenomenon and the ubiquitous light-element abundance ranges seen in the ancient Galactic globular clusters.« less
Data Characterization Using Artificial-Star Tests: Performance Evaluation

NASA Astrophysics Data System (ADS)

Hu, Yi; Deng, Licai; de Grijs, Richard; Liu, Qiang

2011-01-01

Traditional artificial-star tests are widely applied to photometry in crowded stellar fields. However, to obtain reliable binary fractions (and their uncertainties) of remote, dense, and rich star clusters, one needs to recover huge numbers of artificial stars. Hence, this will consume much computation time for data reduction of the images to which the artificial stars must be added. In this article, we present a new method applicable to data sets characterized by stable, well-defined, point-spread functions, in which we add artificial stars to the retrieved-data catalog instead of to the raw images. Taking the young Large Magellanic Cloud cluster NGC 1818 as an example, we compare results from both methods and show that they are equivalent, while our new method saves significant computational time.

Understanding the interface of six-shell cuboctahedral and icosahedral palladium clusters on reduced graphene oxide: experimental and theoretical study.

PubMed

Gracia-Espino, Eduardo; Hu, Guangzhi; Shchukarev, Andrey; Wågberg, Thomas

2014-05-07

Studies on noble-metal-decorated carbon nanostructures are reported almost on a daily basis, but detailed studies on the nanoscale interactions for well-defined systems are very rare. Here we report a study of reduced graphene oxide (rGOx) homogeneously decorated with palladium (Pd) nanoclusters with well-defined shape and size (2.3 ± 0.3 nm). The rGOx was modified with benzyl mercaptan (BnSH) to improve the interaction with Pd clusters, and N,N-dimethylformamide was used as solvent and capping agent during the decoration process. The resulting Pd nanoparticles anchored to the rGOx-surface exhibit high crystallinity and are fully consistent with six-shell cuboctahedral and icosahedral clusters containing ~600 Pd atoms, where 45% of these are located at the surface. According to X-ray photoelectron spectroscopy analysis, the Pd clusters exhibit an oxidized surface forming a PdO(x) shell. Given the well-defined experimental system, as verified by electron microscopy data and theoretical simulations, we performed ab initio simulations using 10 functionalized graphenes (with vacancies or pyridine, amine, hydroxyl, carboxyl, or epoxy groups) to understand the adsorption process of BnSH, their further role in the Pd cluster formation, and the electronic properties of the graphene-nanoparticle hybrid system. Both the experimental and theoretical results suggest that Pd clusters interact with functionalized graphene by a sulfur bridge while the remaining Pd surface is oxidized. Our study is of significant importance for all work related to anchoring of nanoparticles on nanocarbon-based supports, which are used in a variety of applications.
A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

NASA Astrophysics Data System (ADS)

Klein, M.; Mohr, J. J.; Desai, S.; Israel, H.; Allam, S.; Benoit-Lévy, A.; Brooks, D.; Buckley-Geer, E.; Carnero Rosell, A.; Carrasco Kind, M.; Cunha, C. E.; da Costa, L. N.; Dietrich, J. P.; Eifler, T. F.; Evrard, A. E.; Frieman, J.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; James, D. J.; Kuehn, K.; Lima, M.; Maia, M. A. G.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Plazas, A. A.; Reil, K.; Romer, A. K.; Sanchez, E.; Santiago, B.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Collaboration, the DES

2018-03-01

We describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF-redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity-λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF-mass relation.
Unconventional nozzle tradeoff study. [space tug propulsion

NASA Technical Reports Server (NTRS)

Obrien, C. J.

1979-01-01

Plug cluster engine design, performance, weight, envelope, operational characteristics, development cost, and payload capability, were evaluated and comparisons were made with other space tug engine candidates using oxygen/hydrogen propellants. Parametric performance data were generated for existing developed or high technology thrust chambers clustered around a plug nozzle of very large diameter. The uncertainties in the performance prediction of plug cluster engines with large gaps between the modules (thrust chambers) were evaluated. The major uncertainty involves, the aerodynamics of the flow from discrete nozzles, and the lack of this flow to achieve the pressure ratio corresponding to the defined area ratio for a plug cluster. This uncertainty was reduced through a cluster design that consists of a plug contour that is formed from the cluster of high area ratio bell nozzles that have been scarfed. Light-weight, high area ratio, bell nozzles were achieved through the use of AGCarb (carbon-carbon cloth) nozzle extensions.
Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.
Worldwide clustering of the corruption perception

NASA Astrophysics Data System (ADS)

Paulus, Michal; Kristoufek, Ladislav

2015-06-01

We inspect a possible clustering structure of the corruption perception among 134 countries. Using the average linkage clustering, we uncover a well-defined hierarchy in the relationships among countries. Four main clusters are identified and they suggest that countries worldwide can be quite well separated according to their perception of corruption. Moreover, we find a strong connection between corruption levels and a stage of development inside the clusters. The ranking of countries according to their corruption perfectly copies the ranking according to the economic performance measured by the gross domestic product per capita of the member states. To the best of our knowledge, this study is the first one to present an application of hierarchical and clustering methods to the specific case of corruption.
Seizure clustering.

PubMed

Haut, Sheryl R

2006-02-01

Seizure clusters, also known as repetitive or serial seizures, occur commonly in epilepsy. Clustering implies that the occurrence of one seizure may influence the probability of a subsequent seizure; thus, the investigation of the clustering phenomenon yields insights into both specific mechanisms of seizure clustering and more general concepts of seizure occurrence. Seizure clustering has been defined clinically as a number of seizures per unit time and, statistically, as a deviation from a random distribution, or interseizure interval dependence. This review explores the pathophysiology, epidemiology, and clinical implications of clustering, as well as other periodic patterns of seizure occurrence. Risk factors for experiencing clusters and potential precipitants of clustering are also addressed.
Synthesis, characterization and optical properties of an amino-functionalized gold thiolate cluster: Au10(SPh-pNH2)10.

PubMed

Lavenn, Christophe; Albrieux, Florian; Tuel, Alain; Demessence, Aude

2014-03-15

Research interest in ultra small gold thiolate clusters has been rising in recent years for the challenges they offer to bring together properties of nanoscience and well-defined materials from molecular chemistry. Here, a new atomically well-defined Au10 gold nanocluster surrounded by ten 4-aminothiophenolate ligands is reported. Its synthesis followed the similar conditions reported for the elaboration of Au144(SR)60, but because the reactivity of thiophenol ligands is different from alkanethiol derivates, smaller Au10 clusters were formed. Different techniques, such as ESI-MS, elemental analysis, XRD, TGA, XPS and UV-vis-NIR experiments, have been carried out to determine the Au10(SPh-pNH2)10 formula. Photoemission experiment has been done and reveals that the Au10 clusters are weakly luminescent as opposed to the amino-based ultra-small gold clusters. This observation points out that the emission of gold thiolate clusters is highly dependent on both the structure of the gold core and the type of the ligands at the surface. In addition, ultra-small amino-functionalized clusters offer the opportunity for extended work on self-assembling networks or deposition on substrates for nanotechnologies or catalytic applications. Copyright © 2013 Elsevier Inc. All rights reserved.
Nature vs. Nurture: The influence of OB star environments on proto-planetary disk evolution

NASA Astrophysics Data System (ADS)

Bouwman, Jeroen

2006-09-01

We propose a combined IRAC/IRS study of a large, well-defined and unbiased X-ray selected sample of pre-main-sequence stars in three OB associations: Pismis 24 in NGC 6357, NGC 2244 in the Rosette Nebula, and IC 1795 in the W3 complex. The samples are based on recent Chandra X-ray Observatory studies which reliably identify hundreds of cluster members and were carefully chosen to avoid high infrared nebular background. A new Chandra exposure of IC 1795 is requested, and an optical followup to characterise the host stars is planned.
Cluster analysis of sputum cytokine-high profiles reveals diversity in T(h)2-high asthma patients.

PubMed

Seys, Sven F; Scheers, Hans; Van den Brande, Paul; Marijsse, Gudrun; Dilissen, Ellen; Van Den Bergh, Annelies; Goeminne, Pieter C; Hellings, Peter W; Ceuppens, Jan L; Dupont, Lieven J; Bullens, Dominique M A

2017-02-23

Asthma is characterized by a heterogeneous inflammatory profile and can be subdivided into T(h)2-high and T(h)2-low airway inflammation. Profiling of a broader panel of airway cytokines in large unselected patient cohorts is lacking. Patients (n = 205) were defined as being "cytokine-low/high" if sputum mRNA expression of a particular cytokine was outside the respective 10 th /90 th percentile range of the control group (n = 80). Unsupervised hierarchical clustering was used to determine clusters based on sputum cytokine profiles. Half of patients (n = 108; 52.6%) had a classical T(h)2-high ("IL-4-, IL-5- and/or IL-13-high") sputum cytokine profile. Unsupervised cluster analysis revealed 5 clusters. Patients with an "IL-4- and/or IL-13-high" pattern surprisingly did not cluster but were equally distributed among the 5 clusters. Patients with an "IL-5-, IL-17A-/F- and IL-25- high" profile were restricted to cluster 1 (n = 24) with increased sputum eosinophil as well as neutrophil counts and poor lung function parameters at baseline and 2 years later. Four other clusters were identified: "IL-5-high or IL-10-high" (n = 16), "IL-6-high" (n = 8), "IL-22-high" (n = 25). Cluster 5 (n = 132) consists of patients without "cytokine-high" pattern or patients with only high IL-4 and/or IL-13. We identified 5 unique asthma molecular phenotypes by biological clustering. Type 2 cytokines cluster with non-type 2 cytokines in 4 out of 5 clusters. Unsupervised analysis thus not supports a priori type 2 versus non-type 2 molecular phenotypes. www.clinicaltrials.gov NCT01224938. Registered 18 October 2010.
Chapter 7. Cloning and analysis of natural product pathways.

PubMed

Gust, Bertolt

2009-01-01

The identification of gene clusters of natural products has lead to an enormous wealth of information about their biosynthesis and its regulation, and about self-resistance mechanisms. Well-established routine techniques are now available for the cloning and sequencing of gene clusters. The subsequent functional analysis of the complex biosynthetic machinery requires efficient genetic tools for manipulation. Until recently, techniques for the introduction of defined changes into Streptomyces chromosomes were very time-consuming. In particular, manipulation of large DNA fragments has been challenging due to the absence of suitable restriction sites for restriction- and ligation-based techniques. The homologous recombination approach called recombineering (referred to as Red/ET-mediated recombination in this chapter) has greatly facilitated targeted genetic modifications of complex biosynthetic pathways from actinomycetes by eliminating many of the time-consuming and labor-intensive steps. This chapter describes techniques for the cloning and identification of biosynthetic gene clusters, for the generation of gene replacements within such clusters, for the construction of integrative library clones and their expression in heterologous hosts, and for the assembly of entire biosynthetic gene clusters from the inserts of individual library clones. A systematic approach toward insertional mutation of a complete Streptomyces genome is shown by the use of an in vitro transposon mutagenesis procedure.
Web service discovery among large service pools utilising semantic similarity and clustering

NASA Astrophysics Data System (ADS)

Chen, Fuzan; Li, Minqiang; Wu, Harris; Xie, Lingli

2017-03-01

With the rapid development of electronic business, Web services have attracted much attention in recent years. Enterprises can combine individual Web services to provide new value-added services. An emerging challenge is the timely discovery of close matches to service requests among large service pools. In this study, we first define a new semantic similarity measure combining functional similarity and process similarity. We then present a service discovery mechanism that utilises the new semantic similarity measure for service matching. All the published Web services are pre-grouped into functional clusters prior to the matching process. For a user's service request, the discovery mechanism first identifies matching services clusters and then identifies the best matching Web services within these matching clusters. Experimental results show that the proposed semantic discovery mechanism performs better than a conventional lexical similarity-based mechanism.
Diffuse light and building history of the galaxy cluster Abell 2667

NASA Astrophysics Data System (ADS)

Covone, G.; Adami, C.; Durret, F.; Kneib, J.-P.; Lima Neto, G. B.; Slezak, E.

2006-12-01

Aims.We searched for diffuse intracluster light in the galaxy cluster Abell 2667 (z=0.233) from HST images in three broad band-filters. Methods: .We applied an iterative multi-scale wavelet analysis and reconstruction technique to these images, which allows to subtract stars and galaxies from the original images. Results: .We detect a zone of diffuse emission southwest of the cluster center (DS1) and a second faint object (ComDif) within DS1. Another diffuse source (DS2) may be detected at lower confidence level northeast of the center. These sources of diffuse light contribute to 10-15% of the total visible light in the cluster. Whether they are independent entities or part of the very elliptical external envelope of the central galaxy remains unclear. Deep VLT VIMOS integral field spectroscopy reveals a faint continuum at the positions of DS1 and ComDif but do not allow a redshift to be computed, so we conclude if these sources are part of the central galaxy or not. A hierarchical substructure detection method reveals the presence of several galaxy pairs and groups defining a similar direction to the one drawn by the DS1 - central galaxy - DS2 axis. The analysis of archive XMM-Newton and Chandra observations shows X-ray emission elongated in the same direction. The X-ray temperature map shows the presence of a cool core, a broad cool zone stretching from north to south, and hotter regions towards the northeast, southwest, and northwest. This might suggest shock fronts along these directions produced by infalling material, even if uncertainties remain quite large on the temperature determination far from the center. Conclusions: .These various data are consistent with a picture in which diffuse sources are concentrations of tidal debris and harassed matter expelled from infalling galaxies by tidal stripping and undergoing an accretion process onto the central cluster galaxy; as such, they are expected to be found along the main infall directions. Note, however, that the limited signal to noise of the various data and the apparent lack of large numbers of well-defined independent tidal tails, besides the one named ComDif, preclude definitive conclusions on this scenario.
Automatic Clustering Using FSDE-Forced Strategy Differential Evolution

NASA Astrophysics Data System (ADS)

Yasid, A.

2018-01-01

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

PubMed

Meester, V; Kraft, D J

2018-02-14

We investigate the mechanisms underlying the reconfiguration of random aggregates of spheres through capillary interactions, the so-called "colloidal recycling" method, to fabricate a wide variety of patchy particles. We explore the influence of capillary forces on clusters of deformable seed particles by systematically varying the crosslink density of the spherical seeds. Spheres with a poorly crosslinked polymer network strongly deform due to capillary forces and merge into large spheres. With increasing crosslink density and therefore rigidity, the shape of the spheres is increasingly preserved during reconfiguration, yielding patchy particles of well-defined shape for up to five spheres. In particular, we find that the aspect ratio between the length and width of dumbbells, L/W, increases with the crosslink density (cd) as L/W = B - A·exp(-cd/C). For clusters consisting of more than five spheres, the particle deformability furthermore determines the patch arrangement of the resulting particles. The reconfiguration pathway of clusters of six densely or poorly crosslinked seeds leads to octahedral and polytetrahedral shaped patchy particles, respectively. For seven particles several geometries were obtained with a preference for pentagonal dipyramids by the rigid spheres, while the soft spheres do rarely arrive in these structures. Even larger clusters of over 15 particles form non-uniform often aspherical shapes. We discuss that the reconfiguration pathway is largely influenced by confinement and geometric constraints. The key factor which dominates during reconfiguration depends on the deformability of the spherical seed particles.
Atlas-guided cluster analysis of large tractography datasets.

PubMed

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.
New Theoretical Developments in Exploring Electronically Excited States: Including Localized Configuration Interaction Singles and Application to Large Helium Clusters

NASA Astrophysics Data System (ADS)

Closser, Kristina Danielle

This thesis presents new developments in excited state electronic structure theory. Contrasted with the ground state, the electronically excited states of atoms and molecules often are unstable and have short lifetimes, exhibit a greater diversity of character and are generally less well understood. The very unusual excited states of helium clusters motivated much of this work. These clusters consist of large numbers of atoms (experimentally 103--109 atoms) and bands of nearly degenerate excited states. For an isolated atom the lowest energy excitation energies are from 1s → 2s and 1s → 2 p transitions, and in clusters describing the lowest energy band minimally requires four states per atom. In the ground state the clusters are weakly bound by van der Waals interactions, however in the excited state they can form well-defined covalent bonds. The computational cost of quantum chemical calculations rapidly becomes prohibitive as the size of the systems increase. Standard excited-state methods such as configuration interaction singles (CIS) and time-dependent density functional theory (TD-DFT) can be used with ≈100 atoms, and are optimized to treat only a few states. Thus, one of our primary aims is to develop a method which can treat these large systems with large numbers of nearly degenerate excited states. Additionally, excited states are generally formed far from their equilibrium structures. Vertical excitations from the ground state induce dynamics in the excited states. Thus, another focus of this work is to explore the results of these forces and the fate of the excited states. Very little was known about helium cluster excited states when this work began, thus we first investigated the excitations in small helium clusters consisting of 7 or 25 atoms using CIS. The character of these excited states was determined using attachment/detachment density analysis and we found that in the n = 2 manifold the excitations could generally be interpreted as superpositions of atomic states with surface states appearing close to the atomic excitation energies and interior states being blue shifted by up to ≈2 eV. The dynamics resulting from excitation of He_7 were subsequently explored using ab initio molecular dynamics (AIMD). These simulations were performed with classical adiabatic dynamics coupled to a new state-following algorithm on CIS potential energy surfaces. Most clusters were found to completely dissociate and resulted in a single excited atomic state (90%), however, some trajectories formed bound, He*2 (3%), and a few yielded excited trimers (<0.5%). Comparisons were made with available experimental information on much larger clusters. Various applications of this state following algorithm are also presented. In addition to AIMD, these include excited-state geometry optimization and minimal energy path finding via the growing string method. When using state following we demonstrate that more physical results can be obtained with AIMD calculations. Also, the optimized geometries of three excited states of cytosine, two of which were not found without state following, and the minimal energy path between the lowest two singlet excited states of protonated formaldimine are offered as example applications. Finally, to address large clusters, a local variation of CIS was developed. This method exploits the properties of absolutely localized molecular orbitals (ALMOs) to limit the total number of excitations to scaling only linearly with cluster size, which results in formal scaling with the third power of the system size. The derivation of the equations and design of the algorithm are discussed in detail, and computational timings as well as a pilot application to the size dependence of the helium cluster spectrum are presented.
Inorganic material profiling using Arn+ cluster: Can we achieve high quality profiles?

NASA Astrophysics Data System (ADS)

Conard, T.; Fleischmann, C.; Havelund, R.; Franquet, A.; Poleunis, C.; Delcorte, A.; Vandervorst, W.

2018-06-01

Retrieving molecular information by sputtering of organic systems has been concretized in the last years due to the introduction of sputtering by large gas clusters which drastically eliminated the compound degradation during the analysis and has led to strong improvements in depth resolution. Rapidly however, a limitation was observed for heterogeneous systems where inorganic layers or structures needed to be profiled concurrently. As opposed to organic material, erosion of the inorganic layer appears very difficult and prone to many artefacts. To shed some light on these problems we investigated a simple system consisting of aluminum delta layer(s) buried in a silicon matrix in order to define the most favorable beam conditions for practical analysis. We show that counterintuitive to the small energy/atom used and unlike monoatomic ion sputtering, the information depth obtained with large cluster ions is typically very large (∼10 nm) and that this can be caused both by a large roughness development at early stages of the sputtering process and by a large mixing zone. As a consequence, a large deformation of the Al intensity profile is observed. Using sample rotation during profiling significantly improves the depth resolution while sample temperature has no significant effect. The determining parameter for high depth resolution still remains the total energy of the cluster instead of the energy per atom in the cluster.
Topology of Large-Scale Structure by Galaxy Type: Hydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Gott, J. Richard, III; Cen, Renyue; Ostriker, Jeremiah P.

1996-07-01

The topology of large-scale structure is studied as a function of galaxy type using the genus statistic. In hydrodynamical cosmological cold dark matter simulations, galaxies form on caustic surfaces (Zeldovich pancakes) and then slowly drain onto filaments and clusters. The earliest forming galaxies in the simulations (defined as "ellipticals") are thus seen at the present epoch preferentially in clusters (tending toward a meatball topology), while the latest forming galaxies (defined as "spirals") are seen currently in a spongelike topology. The topology is measured by the genus (number of "doughnut" holes minus number of isolated regions) of the smoothed density-contour surfaces. The measured genus curve for all galaxies as a function of density obeys approximately the theoretical curve expected for random- phase initial conditions, but the early-forming elliptical galaxies show a shift toward a meatball topology relative to the late-forming spirals. Simulations using standard biasing schemes fail to show such an effect. Large observational samples separated by galaxy type could be used to test for this effect.
X-Ray Temperatures, Luminosities, and Masses from XMM-Newton Follow-up of the First Shear-selected Galaxy Cluster Sample

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

Deshpande, Amruta J.; Hughes, John P.; Wittman, David, E-mail: amrejd@physics.rutgers.edu, E-mail: jph@physics.rutgers.edu, E-mail: dwittman@physics.ucdavis.edu

We continue the study of the first sample of shear-selected clusters from the initial 8.6 square degrees of the Deep Lens Survey (DLS); a sample with well-defined selection criteria corresponding to the highest ranked shear peaks in the survey area. We aim to characterize the weak lensing selection by examining the sample’s X-ray properties. There are multiple X-ray clusters associated with nearly all the shear peaks: 14 X-ray clusters corresponding to seven DLS shear peaks. An additional three X-ray clusters cannot be definitively associated with shear peaks, mainly due to large positional offsets between the X-ray centroid and the shearmore » peak. Here we report on the XMM-Newton properties of the 17 X-ray clusters. The X-ray clusters display a wide range of luminosities and temperatures; the L {sub X} − T {sub X} relation we determine for the shear-associated X-ray clusters is consistent with X-ray cluster samples selected without regard to dynamical state, while it is inconsistent with self-similarity. For a subset of the sample, we measure X-ray masses using temperature as a proxy, and compare to weak lensing masses determined by the DLS team. The resulting mass comparison is consistent with equality. The X-ray and weak lensing masses show considerable intrinsic scatter (∼48%), which is consistent with X-ray selected samples when their X-ray and weak lensing masses are independently determined.« less
Finding SDSS Galaxy Clusters in 4-dimensional Color Space Using the False Discovery Rate

NASA Astrophysics Data System (ADS)

Nichol, R. C.; Miller, C. J.; Reichart, D.; Wasserman, L.; Genovese, C.; SDSS Collaboration

2000-12-01

We describe a recently developed statistical technique that provides a meaningful cut-off in probability-based decision making. We are concerned with multiple testing, where each test produces a well-defined probability (or p-value). By well-known, we mean that the null hypothesis used to determine the p-value is fully understood and appropriate. The method is entitled False Discovery Rate (FDR) and its largest advantage over other measures is that it allows one to specify a maximal amount of acceptable error. As an example of this tool, we apply FDR to a four-dimensional clustering algorithm using SDSS data. For each galaxy (or test galaxy), we count the number of neighbors that fit within one standard deviation of a four dimensional Gaussian centered on that test galaxy. The mean and standard deviation of that Gaussian are determined from the colors and errors of the test galaxy. We then take that same Gaussian and place it on a random selection of n galaxies and make a similar count. In the limit of large n, we expect the median count around these random galaxies to represent a typical field galaxy. For every test galaxy we determine the probability (or p-value) that it is a field galaxy based on these counts. A low p-value implies that the test galaxy is in a cluster environment. Once we have a p-value for every galaxy, we use FDR to determine at what level we should make our probability cut-off. Once this cut-off is made, we have a final sample of galaxies that are cluster-like galaxies. Using FDR, we also know the maximum amount of field contamination in our cluster galaxy sample. We present our preliminary galaxy clustering results using these methods.

The Role of Large-Scale Structure and Assembly in the Quenching of Star Formation in Cluster Galaxies at z 0.2

NASA Astrophysics Data System (ADS)

Moran, Sean; Smith, G.; Haines, C.; Egami, E.; Hardegree-Ullman, E.; Heckman, T.

2010-01-01

We present results from LoCuSS, the Local Cluster Substructure Survey, on the distribution and abundance of cluster galaxies showing signatures of recently quenched star formation, within a sample of 15 z 0.2 clusters. Combining LoCuSS' wide-field UV through NIR photometry with weak-lensing derived mass maps for these clusters, we identify passive galaxies that have undergone recent quenching via both rapid (100Myr) and slow (1Gyr) mechanisms. By studying their abundance in a statistically significant sample of z 0.2 clusters, we explore how the effectiveness of environmental quenching of star formation varies as a function of the level of cluster substructure, in addition to global cluster characteristics such as mass or X-ray luminosity and temperature, with the aim of understanding the role that pre-processing of galaxies within groups and filaments plays in the overall buildup of the morphology-density and SFR-density relations. We find that clusters with large levels of substructure indicative of recent assembly or cluster-cluster mergers host a higher fraction of galaxies with signs of recent ram-pressure stripping by the hot intra-cluster gas. In addition, we find that the fraction of post-starburst galaxies increases with cluster mass (M500), but fractions of optically-selected AGN and GALEX-defined "Green Valley" galaxies show the opposite trend, being most abundant in rather low-mass clusters. These trends suggest a picture where quenching of star formation occurs most vigorously in actively assembling structures, with comparatively little activity in the most massive structures where most of the nearby large-scale structure has already been accreted and Virialized into the main cluster body.
SEARCHING FOR COOLING SIGNATURES IN STRONG LENSING GALAXY CLUSTERS: EVIDENCE AGAINST BARYONS SHAPING THE MATTER DISTRIBUTION IN CLUSTER CORES

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

Blanchard, Peter K.; Bayliss, Matthew B.; McDonald, Michael

2013-07-20

The process by which the mass density profile of certain galaxy clusters becomes centrally concentrated enough to produce high strong lensing (SL) cross-sections is not well understood. It has been suggested that the baryonic condensation of the intracluster medium (ICM) due to cooling may drag dark matter to the cores and thus steepen the profile. In this work, we search for evidence of ongoing ICM cooling in the first large, well-defined sample of SL selected galaxy clusters in the range 0.1 < z < 0.6. Based on known correlations between the ICM cooling rate and both optical emission line luminositymore » and star formation, we measure, for a sample of 89 SL clusters, the fraction of clusters that have [O II]{lambda}{lambda}3727 emission in their brightest cluster galaxy (BCG). We find that the fraction of line-emitting BCGs is constant as a function of redshift for z > 0.2 and shows no statistically significant deviation from the total cluster population. Specific star formation rates, as traced by the strength of the 4000 A break, D{sub 4000}, are also consistent with the general cluster population. Finally, we use optical imaging of the SL clusters to measure the angular separation, R{sub arc}, between the arc and the center of mass of each lensing cluster in our sample and test for evidence of changing [O II] emission and D{sub 4000} as a function of R{sub arc}, a proxy observable for SL cross-sections. D{sub 4000} is constant with all values of R{sub arc}, and the [O II] emission fractions show no dependence on R{sub arc} for R{sub arc} > 10'' and only very marginal evidence of increased weak [O II] emission for systems with R{sub arc} < 10''. These results argue against the ability of baryonic cooling associated with cool core activity in the cores of galaxy clusters to strongly modify the underlying dark matter potential, leading to an increase in SL cross-sections.« less
Common Variable Immunodeficiency Non-Infectious Disease Endotypes Redefined Using Unbiased Network Clustering in Large Electronic Datasets.

PubMed

Farmer, Jocelyn R; Ong, Mei-Sing; Barmettler, Sara; Yonker, Lael M; Fuleihan, Ramsay; Sullivan, Kathleen E; Cunningham-Rundles, Charlotte; Walter, Jolan E

2017-01-01

Common variable immunodeficiency (CVID) is increasingly recognized for its association with autoimmune and inflammatory complications. Despite recent advances in immunophenotypic and genetic discovery, clinical care of CVID remains limited by our inability to accurately model risk for non-infectious disease development. Herein, we demonstrate the utility of unbiased network clustering as a novel method to analyze inter-relationships between non-infectious disease outcomes in CVID using databases at the United States Immunodeficiency Network (USIDNET), the centralized immunodeficiency registry of the United States, and Partners, a tertiary care network in Boston, MA, USA, with a shared electronic medical record amenable to natural language processing. Immunophenotypes were comparable in terms of native antibody deficiencies, low titer response to pneumococcus, and B cell maturation arrest. However, recorded non-infectious disease outcomes were more substantial in the Partners cohort across the spectrum of lymphoproliferation, cytopenias, autoimmunity, atopy, and malignancy. Using unbiased network clustering to analyze 34 non-infectious disease outcomes in the Partners cohort, we further identified unique patterns of lymphoproliferative (two clusters), autoimmune (two clusters), and atopic (one cluster) disease that were defined as CVID non-infectious endotypes according to discrete and non-overlapping immunophenotypes. Markers were both previously described {high serum IgE in the atopic cluster [odds ratio (OR) 6.5] and low class-switched memory B cells in the total lymphoproliferative cluster (OR 9.2)} and novel [low serum C3 in the total lymphoproliferative cluster (OR 5.1)]. Mortality risk in the Partners cohort was significantly associated with individual non-infectious disease outcomes as well as lymphoproliferative cluster 2, specifically (OR 5.9). In contrast, unbiased network clustering failed to associate known comorbidities in the adult USIDNET cohort. Together, these data suggest that unbiased network clustering can be used in CVID to redefine non-infectious disease inter-relationships; however, applicability may be limited to datasets well annotated through mechanisms such as natural language processing. The lymphoproliferative, autoimmune, and atopic Partners CVID endotypes herein described can be used moving forward to streamline genetic and biomarker discovery and to facilitate early screening and intervention in CVID patients at highest risk for autoimmune and inflammatory progression.
Strain rates, stress markers and earthquake clustering (Invited)

NASA Astrophysics Data System (ADS)

Fry, B.; Gerstenberger, M.; Abercrombie, R. E.; Reyners, M.; Eberhart-Phillips, D. M.

2013-12-01

The 2010-present Canterbury earthquakes comprise a well-recorded sequence in a relatively low strain-rate shallow crustal region. We present new scientific results to test the hypothesis that: Earthquake sequences in low-strain rate areas experience high stress drop events, low-post seismic relaxation, and accentuated seismic clustering. This hypothesis is based on a physical description of the aftershock process in which the spatial distribution of stress accumulation and stress transfer are controlled by fault strength and orientation. Following large crustal earthquakes, time dependent forecasts are often developed by fitting parameters defined by Omori's aftershock decay law. In high-strain rate areas, simple forecast models utilizing a single p-value fit observed aftershock sequences well. In low-strain rate areas such as Canterbury, assumptions of simple Omori decay may not be sufficient to capture the clustering (sub-sequence) nature exhibited by the punctuated rise in activity following significant child events. In Canterbury, the moment release is more clustered than in more typical Omori sequences. The individual earthquakes in these clusters also exhibit somewhat higher stress drops than in the average crustal sequence in high-strain rate regions, suggesting the earthquakes occur on strong Andersonian-oriented faults, possibly juvenile or well-healed . We use the spectral ratio procedure outlined in (Viegas et al., 2010) to determine corner frequencies and Madariaga stress-drop values for over 800 events in the sequence. Furthermore, we will discuss the relevance of tomographic results of Reyners and Eberhart-Phillips (2013) documenting post-seismic stress-driven fluid processes following the three largest events in the sequence as well as anisotropic patterns in surface wave tomography (Fry et al., 2013). These tomographic studies are both compatible with the hypothesis, providing strong evidence for the presence of widespread and hydrated regional upper crustal cracking parallel to sub-parallel to the dominant transverse failure plane in the sequence. Joint interpretation of the three separate datasets provide a positive first attempt at testing our fundamental hypothesis.
Synthesis of Densely Packaged, Ultrasmall Pt02 Clusters within a Thioether-Functionalized MOF: Catalytic Activity in Industrial Reactions at Low Temperature.

PubMed

Mon, Marta; Rivero-Crespo, Miguel A; Ferrando-Soria, Jesús; Vidal-Moya, Alejandro; Boronat, Mercedes; Leyva-Pérez, Antonio; Corma, Avelino; Hernández-Garrido, Juan C; López-Haro, Miguel; Calvino, José J; Ragazzon, Giulio; Credi, Alberto; Armentano, Donatella; Pardo, Emilio

2018-05-22

The gram-scale synthesis, stabilization, and characterization of well-defined ultrasmall subnanometric catalytic clusters on solids is a challenge. The chemical synthesis and X-ray snapshots of Pt 0 2 clusters, homogenously distributed and densely packaged within the channels of a metal-organic framework, is presented. This hybrid material catalyzes efficiently, and even more importantly from an economic and environmental viewpoint, at low temperature (25 to 140 °C), energetically costly industrial reactions in the gas phase such as HCN production, CO 2 methanation, and alkene hydrogenations. These results open the way for the design of precisely defined catalytically active ultrasmall metal clusters in solids for technically easier, cheaper, and dramatically less-dangerous industrial reactions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Atlas-Guided Cluster Analysis of Large Tractography Datasets

PubMed Central

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment. PMID:24386292
Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity

PubMed Central

Pope, Welkin H; Bowman, Charles A; Russell, Daniel A; Jacobs-Sera, Deborah; Asai, David J; Cresawn, Steven G; Jacobs, William R; Hendrix, Roger W; Lawrence, Jeffrey G; Hatfull, Graham F; Abbazia, Patrick; Ababio, Amma; Adam, Naazneen

2015-01-01

The bacteriophage population is large, dynamic, ancient, and genetically diverse. Limited genomic information shows that phage genomes are mosaic, and the genetic architecture of phage populations remains ill-defined. To understand the population structure of phages infecting a single host strain, we isolated, sequenced, and compared 627 phages of Mycobacterium smegmatis. Their genetic diversity is considerable, and there are 28 distinct genomic types (clusters) with related nucleotide sequences. However, amino acid sequence comparisons show pervasive genomic mosaicism, and quantification of inter-cluster and intra-cluster relatedness reveals a continuum of genetic diversity, albeit with uneven representation of different phages. Furthermore, rarefaction analysis shows that the mycobacteriophage population is not closed, and there is a constant influx of genes from other sources. Phage isolation and analysis was performed by a large consortium of academic institutions, illustrating the substantial benefits of a disseminated, structured program involving large numbers of freshman undergraduates in scientific discovery. DOI: http://dx.doi.org/10.7554/eLife.06416.001 PMID:25919952
Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity.

PubMed

Pope, Welkin H; Bowman, Charles A; Russell, Daniel A; Jacobs-Sera, Deborah; Asai, David J; Cresawn, Steven G; Jacobs, William R; Hendrix, Roger W; Lawrence, Jeffrey G; Hatfull, Graham F

2015-04-28

The bacteriophage population is large, dynamic, ancient, and genetically diverse. Limited genomic information shows that phage genomes are mosaic, and the genetic architecture of phage populations remains ill-defined. To understand the population structure of phages infecting a single host strain, we isolated, sequenced, and compared 627 phages of Mycobacterium smegmatis. Their genetic diversity is considerable, and there are 28 distinct genomic types (clusters) with related nucleotide sequences. However, amino acid sequence comparisons show pervasive genomic mosaicism, and quantification of inter-cluster and intra-cluster relatedness reveals a continuum of genetic diversity, albeit with uneven representation of different phages. Furthermore, rarefaction analysis shows that the mycobacteriophage population is not closed, and there is a constant influx of genes from other sources. Phage isolation and analysis was performed by a large consortium of academic institutions, illustrating the substantial benefits of a disseminated, structured program involving large numbers of freshman undergraduates in scientific discovery.
Chemical models for simulating single-walled nanotube production in arc vaporization and laser ablation processes

NASA Technical Reports Server (NTRS)

Scott, Carl D.

2004-01-01

Chemical kinetic models for the nucleation and growth of clusters and single-walled carbon nanotube (SWNT) growth are developed for numerical simulations of the production of SWNTs. Two models that involve evaporation and condensation of carbon and metal catalysts, a full model involving all carbon clusters up to C80, and a reduced model are discussed. The full model is based on a fullerene model, but nickel and carbon/nickel cluster reactions are added to form SWNTs from soot and fullerenes. The full model has a large number of species--so large that to incorporate them into a flow field computation for simulating laser ablation and arc processes requires that they be simplified. The model is reduced by defining large clusters that represent many various sized clusters. Comparisons are given between these models for cases that may be applicable to arc and laser ablation production. Solutions to the system of chemical rate equations of these models for a ramped temperature profile show that production of various species, including SWNTs, agree to within about 50% for a fast ramp, and within 10% for a slower temperature decay time.
Phylogenetic continuum indicates "galaxies" in the protein universe: preliminary results on the natural group structures of proteins.

PubMed

Ladunga, I

1992-04-01

The markedly nonuniform, even systematic distribution of sequences in the protein "universe" has been analyzed by methods of protein taxonomy. Mapping of the natural hierarchical system of proteins has revealed some dense cores, i.e., well-defined clusterings of proteins that seem to be natural structural groupings, possibly seeds for a future protein taxonomy. The aim was not to force proteins into more or less man-made categories by discriminant analysis, but to find structurally similar groups, possibly of common evolutionary origin. Single-valued distance measures between pairs of superfamilies from the Protein Identification Resource were defined by two chi 2-like methods on tripeptide frequencies and the variable-length subsequence identity method derived from dot-matrix comparisons. Distance matrices were processed by several methods of cluster analysis to detect phylogenetic continuum between highly divergent proteins. Only well-defined clusters characterized by relatively unique structural, intracellular environmental, organismal, and functional attribute states were selected as major protein groups, including subsets of viral and Escherichia coli proteins, hormones, inhibitors, plant, ribosomal, serum and structural proteins, amino acid synthases, and clusters dominated by certain oxidoreductases and apolar and DNA-associated enzymes. The limited repertoire of functional patterns due to small genome size, the high rate of recombination, specific features of the bacterial membranes, or of the virus cycle canalize certain proteins of viruses and Gram-negative bacteria, respectively, to organismal groups.
Galaxy clusters in the context of superfluid dark matter

NASA Astrophysics Data System (ADS)

Hodson, Alistair O.; Zhao, Hongsheng; Khoury, Justin; Famaey, Benoit

2017-11-01

Context. The mass discrepancy in the Universe has not been solved by the cold dark matter (CDM) or the modified Newtonian dynamics (MOND) paradigms so far. The problems and solutions of either scenario are mutually exclusive on large and small scales. It has recently been proposed, by assuming that dark matter is a superfluid, that MOND-like effects can be achieved on small scales whilst preserving the success of ΛCDM on large scales. Detailed models within this "superfluid dark matter" (SfDM) paradigm are yet to be constructed. Aims: Here, we aim to provide the first set of spherical models of galaxy clusters in the context of SfDM. We aim to determine whether the superfluid formulation is indeed sufficient to explain the mass discrepancy in galaxy clusters. Methods: The SfDM model is defined by two parameters. Λ can be thought of as a mass scale in the Lagrangian of the scalar field that effectively describes the phonons, and it acts as a coupling constant between the phonons and baryons. m is the mass of the DM particles. Based on these parameters, we outline the theoretical structure of the superfluid core and the surrounding "normal-phase" dark halo of quasi-particles. The latter are thought to encompass the largest part of galaxy clusters. Here, we set the SfDM transition at the radius where the density and pressure of the superfluid and normal phase coincide, neglecting the effect of phonons in the superfluid core. We then apply the formalism to a sample of galaxy clusters, and directly compare the SfDM predicted mass profiles to data. Results: We find that the superfluid formulation can reproduce the X-ray dynamical mass profile of clusters reasonably well, but with a slight under-prediction of the gravity in the central regions. This might be partly related to our neglecting of the effect of phonons in these regions. Two normal-phase halo profiles are tested, and it is found that clusters are better defined by a normal-phase halo resembling an Navarro-Frenk-White-like structure than an isothermal profile. Conclusions: In this first exploratory work on the topic, we conclude that depending on the amount of baryons present in the central galaxy and on the actual effect of phonons in the inner regions, this superfluid formulation could be successful in describing galaxy clusters. In the future, our model could be made more realistic by exploring non-sphericity and a more realistic SfDM to normal phase transition. The main result of this study is an estimate of the order of magnitude of the theory parameters for the superfluid formalism to be reasonably consistent with clusters. These values will have to be compared to the true values needed in galaxies.
Finding and testing network communities by lumped Markov chains.

PubMed

Piccardi, Carlo

2011-01-01

Identifying communities (or clusters), namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called "persistence probability" is associated to a cluster, which is then defined as an "α-community" if such a probability is not smaller than α. Consistently, a partition composed of α-communities is an "α-partition." These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired α-level allows one to immediately select the α-partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.
Deep CCD Photometry of the Rich Galaxy Cluster Abel 1656 Characteristics of the Dwarf Elliptical Galaxy Population in the Cluster Core

NASA Astrophysics Data System (ADS)

Secker, Jeffrey Alan

1995-01-01

We have developed a statistically rigorous and automated method to implement the detection, photometry and classification of faint objects on digital images. We use these methods to analyze deep R- and B-band CCD images of the central ~ 700 arcmin ^2 of the Coma cluster core, and an associated control field. We have detected and measured total R magnitudes and (B-R) colors for a sample of 3741 objects on the galaxy cluster fields, and 1164 objects on a remote control field, complete to a limiting magnitude of R = 22.5 mag. The typical uncertainties are +/- 0.06 and +/-0.12 mag in total magnitude and color respectively. The dwarf elliptical (dE) galaxies are confined to a well-defined sequence in the color range given by 0.7<= (B-R)<= 1.9 mag: within this interval there are 2535 dE candidates on our fields in the cluster core, and 694 objects on the control field. With an image scale of 0.53 arcsec/pixel and seeing near 1.2 arcsec, a large fraction of the dE galaxy candidates are resolved. We find a significant metallicity gradient in the radial distribution of the dwarf elliptical galaxies, which goes as Z~ R^{-0.32 } outwards from the cluster center at NGC 4874. As well, there is a strong color-luminosity correlation, in the sense that more luminous dE galaxies are redder in the mean. These effects give rise to a radial variation in the cluster luminosity function. The spatial distribution of the faint dE galaxies is well fit by a standard King model with a central surface density of Sigma _0 = 1.44 dEs arcmin^{ -2}, a core radius R_{ rm c} = 18.7 arcmin (~eq 0.44 Mpc), and a tidal radius of 1.44 deg ( ~eq 2.05 Mpc). This core is significantly larger than R_{rm c} = 12.3 arcmin (~eq 0.29 Mpc) found for the bright cluster galaxies. The composite luminosity function for Coma galaxies is modeled as the sum of a log -normal distribution for the giant galaxies and a Schechter function for the dwarf elliptical galaxies, with a faint -end slope of alpha = -1.41, consistent with known faint-end slopes for the Virgo and Fornax clusters. The early-type dwarf-to-giant ratio for the Coma cluster core is consistent with that of the Virgo cluster, and thus with the rich Coma cluster being formed as the merger of multiple less-rich galaxy clusters.
Large-scale motions in the universe: Using clusters of galaxies as tracers

NASA Technical Reports Server (NTRS)

Gramann, Mirt; Bahcall, Neta A.; Cen, Renyue; Gott, J. Richard

1995-01-01

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).
Insulin Resistance: Regression and Clustering

PubMed Central

Yoon, Sangho; Assimes, Themistocles L.; Quertermous, Thomas; Hsiao, Chin-Fu; Chuang, Lee-Ming; Hwu, Chii-Min; Rajaratnam, Bala; Olshen, Richard A.

2014-01-01

In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with “main effects” is not satisfactory, but prediction that includes interactions may be. PMID:24887437
Thematic clustering of text documents using an EM-based approach

PubMed Central

2012-01-01

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

USGS Publications Warehouse

Giron, Ricardo Garza; Brodsky, Emily E.; Prejean, Stephanie

2018-01-01

swarms and mainshock-aftershock sequences. The former is commonly thought to dominate in volcanic and geothermal regions, but aftershock production, including within swarms, is not well studied in volcanic regions. Here we compare mainshock-aftershock clustering in active volcanic regions in Japan to nearby nonvolcanic regions. We find that aftershock production is similar in both areas by two separate metrics: (1) Both volcanic and nonvolcanic regions have similar proportions of areas that cluster into mainshock-aftershock sequences. (2) Volcanic areas with mainshock-aftershock sequences have aftershock productivity at least as high as nonvolcanic regions. We also find that volcano-tectonic events that are precursors to an eruption are more common at volcanoes without mainshock-aftershock clusters than at volcanoes with well-defined mainshock-aftershock clusters. This last finding hints at a strategy to identify volcanic systems where cataloged earthquakes are good predictors of behavior.
Hybrid Assembly of Different-Sized Supertetrahedral Clusters into a Unique Non-Interpenetrated Mn-In-S Open Framework with Large Cavity.

PubMed

Wang, Hongxiang; Wang, Wei; Hu, Dandan; Luo, Min; Xue, Chaozhuang; Li, Dongsheng; Wu, Tao

2018-06-04

Reported here is a unique crystalline semiconductor open-framework material built from the large-sized supertetrahedral T4 and T5 clusters with the Mn-In-S compositions. The hybrid assembly between T4 and T5 clusters by sharing terminal μ 2 -S 2- is for the first time observed among the cluster-based chalcogenide open frameworks. Such three-dimensional structure displays non-interpenetrated diamond-type topology with extra-large nonframework volume of 82%. Moreover, ion exchange, CO 2 adsorption, as well as photoluminescence properties of the title compound are also investigated.
The Nature and Origin of UCDs in the Coma Cluster

NASA Astrophysics Data System (ADS)

Chiboucas, Kristin; Tully, R. Brent; Madrid, Juan; Phillipps, Steven; Carter, David; Peng, Eric

2018-01-01

UCDs are super massive star clusters found largely in dense regions but have also been found around individual galaxies and in smaller groups. Their origin is still under debate but currently favored scenarios include formation as giant star clusters, either as the brightest globular clusters or through mergers of super star clusters, themselves formed during major galaxy mergers, or as remnant nuclei from tidal stripping of nucleated dwarf ellipticals. Establishing the nature of these enigmatic objects has important implications for our understanding of star formation, star cluster formation, the missing satellite problem, and galaxy evolution. We are attempting to disentangle these competing formation scenarios with a large survey of UCDs in the Coma cluster. Using ACS two-passband imaging from the HST/ACS Coma Cluster Treasury Survey, we are using colors and sizes to identify the UCD cluster members. With a large size limited sample of the UCD population within the core region of the Coma cluster, we are investigating the population size, properties, and spatial distribution, and comparing that with the Coma globular cluster and nuclear star cluster populations to discriminate between the threshing and globular cluster scenarios. In previous work, we had found a possible correlation of UCD colors with host galaxy and a possible excess of UCDs around a non-central giant galaxy with an unusually large globular cluster population, both suggestive of a globular cluster origin. With a larger sample size and additional imaging fields that encompass the regions around these giant galaxies, we have found that the color correlation with host persists and the giant galaxy with unusually large globular cluster population does appear to host a large UCD population as well. We present the current status of the survey.
X-Ray Temperatures, Luminosities, and Masses from XMM-Newton Follow-upof the First Shear-selected Galaxy Cluster Sample

NASA Astrophysics Data System (ADS)

Deshpande, Amruta J.; Hughes, John P.; Wittman, David

2017-04-01

We continue the study of the first sample of shear-selected clusters from the initial 8.6 square degrees of the Deep Lens Survey (DLS); a sample with well-defined selection criteria corresponding to the highest ranked shear peaks in the survey area. We aim to characterize the weak lensing selection by examining the sample’s X-ray properties. There are multiple X-ray clusters associated with nearly all the shear peaks: 14 X-ray clusters corresponding to seven DLS shear peaks. An additional three X-ray clusters cannot be definitively associated with shear peaks, mainly due to large positional offsets between the X-ray centroid and the shear peak. Here we report on the XMM-Newton properties of the 17 X-ray clusters. The X-ray clusters display a wide range of luminosities and temperatures; the L X -T X relation we determine for the shear-associated X-ray clusters is consistent with X-ray cluster samples selected without regard to dynamical state, while it is inconsistent with self-similarity. For a subset of the sample, we measure X-ray masses using temperature as a proxy, and compare to weak lensing masses determined by the DLS team. The resulting mass comparison is consistent with equality. The X-ray and weak lensing masses show considerable intrinsic scatter (˜48%), which is consistent with X-ray selected samples when their X-ray and weak lensing masses are independently determined. 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.

Explaining the luminosity spread in young clusters: proto and pre-main sequence stellar evolution in a molecular cloud environment

NASA Astrophysics Data System (ADS)

Jensen, Sigurd S.; Haugbølle, Troels

2018-02-01

Hertzsprung-Russell diagrams of star-forming regions show a large luminosity spread. This is incompatible with well-defined isochrones based on classic non-accreting protostellar evolution models. Protostars do not evolve in isolation of their environment, but grow through accretion of gas. In addition, while an age can be defined for a star-forming region, the ages of individual stars in the region will vary. We show how the combined effect of a protostellar age spread, a consequence of sustained star formation in the molecular cloud, and time-varying protostellar accretion for individual protostars can explain the observed luminosity spread. We use a global magnetohydrodynamic simulation including a sub-scale sink particle model of a star-forming region to follow the accretion process of each star. The accretion profiles are used to compute stellar evolution models for each star, incorporating a model of how the accretion energy is distributed to the disc, radiated away at the accretion shock, or incorporated into the outer layers of the protostar. Using a modelled cluster age of 5 Myr, we naturally reproduce the luminosity spread and find good agreement with observations of the Collinder 69 cluster, and the Orion Nebular Cluster. It is shown how stars in binary and multiple systems can be externally forced creating recurrent episodic accretion events. We find that in a realistic global molecular cloud model massive stars build up mass over relatively long time-scales. This leads to an important conceptual change compared to the classic picture of non-accreting stellar evolution segmented into low-mass Hayashi tracks and high-mass Henyey tracks.
Congruent population structure inferred from dispersal behaviour and intensive genetic surveys of the threatened Florida scrub-jay (Aphelocoma cœrulescens)

USGS Publications Warehouse

Coulon, A.; Fitzpatrick, J.W.; Bowman, R.; Stith, B.M.; Makarewich, C.A.; Stenzler, L.M.; Lovette, I.J.

2008-01-01

The delimitation of populations, defined as groups of individuals linked by gene flow, is possible by the analysis of genetic markers and also by spatial models based on dispersal probabilities across a landscape. We combined these two complimentary methods to define the spatial pattern of genetic structure among remaining populations of the threatened Florida scrub-jay, a species for which dispersal ability is unusually well-characterized. The range-wide population was intensively censused in the 1990s, and a metapopulation model defined population boundaries based on predicted dispersal-mediated demographic connectivity. We subjected genotypes from more than 1000 individual jays screened at 20 microsatellite loci to two Bayesian clustering methods. We describe a consensus method for identifying common features across many replicated clustering runs. Ten genetically differentiated groups exist across the present-day range of the Florida scrub-jay. These groups are largely consistent with the dispersal-defined metapopulations, which assume very limited dispersal ability. Some genetic groups comprise more than one metapopulation, likely because these genetically similar metapopulations were sundered only recently by habitat alteration. The combined reconstructions of population structure based on genetics and dispersal-mediated demographic connectivity provide a robust depiction of the current genetic and demographic organization of this species, reflecting past and present levels of dispersal among occupied habitat patches. The differentiation of populations into 10 genetic groups adds urgency to management efforts aimed at preserving what remains of genetic variation in this dwindling species, by maintaining viable populations of all genetically differentiated and geographically isolated populations.
Lifestyle and accidents among young drivers.

PubMed

Gregersen, N P; Berg, H Y

1994-06-01

This study covers the lifestyle component of the problems related to young drivers' accident risk. The purpose of the study is to measure the relationship between lifestyle and accident risk, and to identify specific high-risk and low-risk groups. Lifestyle is measured through a questionnaire, where 20-year-olds describe themselves and how often they deal with a large number of different activities, like sports, music, movies, reading, cars and driving, political engagement, etc. They also report their involvement in traffic accidents. With a principal component analysis followed by a cluster analysis, lifestyle profiles are defined. These profiles are finally correlated to accidents, which makes it possible to define high-risk and low-risk groups. The cluster analysis defined 15 clusters including four high-risk groups with an average overrisk of 150% and two low-risk groups with an average underrisk of 75%. The results are discussed from two perspectives. The first is the importance of theoretical understanding of the contribution of lifestyle factors to young drivers' high accident risk. The second is how the findings could be used in practical road safety measures, like education, campaigns, etc.
Underestimated role of the secondary electron emission in the space

NASA Astrophysics Data System (ADS)

Nemecek, Zdenek; Richterova, Ivana; Safrankova, Jana; Pavlu, Jiri; Vaverka, Jakub; Nouzak, Libor

2016-07-01

Secondary electron emission (SEE) is one of many processes that charges surfaces of bodies immersed into a plasma. Until present, a majority of considerations in theories and experiments is based on the sixty year old description of an interaction of planar metallic surfaces with electrons, thus the effects of a surface curvature, roughness, presence of clusters as well as an influence of the material conductance on different aspects of this interaction are neglected. Dust grains or their clusters can be frequently found in many space environments - interstellar clouds, atmospheres of planets, tails of comets or planetary rings are only typical examples. The grains are exposed to electrons of different energies and they can acquire positive or negative charge during this interaction. We review the progress in experimental investigations and computer simulations of the SEE from samples relevant to space that was achieved in course of the last decade. We present a systematic study of well-defined systems that starts from spherical grains of various diameters and materials, and it continues with clusters consisting of different numbers of small spherical grains that can be considered as examples of real irregularly shaped space grains. The charges acquired by investigated objects as well as their secondary emission yields are calculated using the SEE model. We show that (1) the charge and surface potential of clusters exposed to the electron beam are influenced by the number of grains and by their geometry within a particular cluster, (2) the model results are in an excellent agreement with the experiment, and (3) there is a large difference between charging of a cluster levitating in the free space and that attached to a planar surface. The calculation provides a reduction of the secondary electron emission yield of the surface covered by dust clusters by a factor up to 1.5 with respect to the yield of a smooth surface. (4) These results are applied on charging of the lunar surface and the dust grains levitating above it, and it is shown that the SEE is more important for isolated dust grains than for the lunar surface covered by them.
Comparison and Evaluation of Clustering Algorithms for Tandem Mass Spectra.

PubMed

Rieder, Vera; Schork, Karin U; Kerschke, Laura; Blank-Landeshammer, Bernhard; Sickmann, Albert; Rahnenführer, Jörg

2017-11-03

In proteomics, liquid chromatography-tandem mass spectrometry (LC-MS/MS) is established for identifying peptides and proteins. Duplicated spectra, that is, multiple spectra of the same peptide, occur both in single MS/MS runs and in large spectral libraries. Clustering tandem mass spectra is used to find consensus spectra, with manifold applications. First, it speeds up database searches, as performed for instance by Mascot. Second, it helps to identify novel peptides across species. Third, it is used for quality control to detect wrongly annotated spectra. We compare different clustering algorithms based on the cosine distance between spectra. CAST, MS-Cluster, and PRIDE Cluster are popular algorithms to cluster tandem mass spectra. We add well-known algorithms for large data sets, hierarchical clustering, DBSCAN, and connected components of a graph, as well as the new method N-Cluster. All algorithms are evaluated on real data with varied parameter settings. Cluster results are compared with each other and with peptide annotations based on validation measures such as purity. Quality control, regarding the detection of wrongly (un)annotated spectra, is discussed for exemplary resulting clusters. N-Cluster proves to be highly competitive. All clustering results benefit from the so-called DISMS2 filter that integrates additional information, for example, on precursor mass.
Looking for Photometric Signatures of Fast Rotation in Intermediate-Age Star Clusters in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2017-08-01

Recently, deep color-magnitude diagrams from HST data revealed that several massive intermediate-age star clusters in the Magellanic Clouds exhibit extended main-sequence turn-offs (eMSTOs). This discovery posed serious questions regarding the mechanisms responsible for the formation of massive globular clusters and their well-known multiple stellar populations. The nature of eMSTOs is a hotly debated topic of study. Several studies argued that the eMSTOs are caused by an age range of up to a few hundred Myr, while other studies indicate that eMSTOs can instead be caused by a coeval population in which the stars span a range of rotation velocities. Formal evidence to (dis-)prove either scenario still remains at large, in part because stellar tracks that incorporate the effects of rotation have so far only been available for masses > 1.7 Msun whereas the stars in the known eMSTOs of intermediate-age star clusters are less massive. In this proposal we aim to look for photometric signatures of fast rotators in eMSTO clusters that have been observed by HST in three passbands including (at least) F336W and F814W. We will study spreads in different stellar colors, testing against those predicted with the aid of von Zeipel's geometric study for a population of rotating stars with a significant spread in their inclination. Importantly, this spread due to the presence of rotation is predicted to occur along well-defined lines in color-color diagrams, in directions that are distinct from those in color-magnitude diagrams and distinct from the spread predicted for the age range scenario.
Fine-scale phylogenetic architecture of a complex bacterial community.

PubMed

Acinas, Silvia G; Klepac-Ceraj, Vanja; Hunt, Dana E; Pharino, Chanathip; Ceraj, Ivica; Distel, Daniel L; Polz, Martin F

2004-07-29

Although molecular data have revealed the vast scope of microbial diversity, two fundamental questions remain unanswered even for well-defined natural microbial communities: how many bacterial types co-exist, and are such types naturally organized into phylogenetically discrete units of potential ecological significance? It has been argued that without such information, the environmental function, population biology and biogeography of microorganisms cannot be rigorously explored. Here we address these questions by comprehensive sampling of two large 16S ribosomal RNA clone libraries from a coastal bacterioplankton community. We show that compensation for artefacts generated by common library construction techniques reveals fine-scale patterns of community composition. At least 516 ribotypes (unique rRNA sequences) were detected in the sample and, by statistical extrapolation, at least 1,633 co-existing ribotypes in the sampled population. More than 50% of the ribotypes fall into discrete clusters containing less than 1% sequence divergence. This pattern cannot be accounted for by interoperon variation, indicating a large predominance of closely related taxa in this community. We propose that such microdiverse clusters arise by selective sweeps and persist because competitive mechanisms are too weak to purge diversity from within them.
Topology in two dimensions. II - The Abell and ACO cluster catalogues

NASA Astrophysics Data System (ADS)

Plionis, Manolis; Valdarnini, Riccardo; Coles, Peter

1992-09-01

We apply a method for quantifying the topology of projected galaxy clustering to the Abell and ACO catalogues of rich clusters. We use numerical simulations to quantify the statistical bias involved in using high peaks to define the large-scale structure, and we use the results obtained to correct our observational determinations for this known selection effect and also for possible errors introduced by boundary effects. We find that the Abell cluster sample is consistent with clusters being identified with high peaks of a Gaussian random field, but that the ACO shows a slight meatball shift away from the Gaussian behavior over and above that expected purely from the high-peak selection. The most conservative explanation of this effect is that it is caused by some artefact of the procedure used to select the clusters in the two samples.
Clusters of isoleucine, leucine, and valine side chains define cores of stability in high-energy states of globular proteins: Sequence determinants of structure and stability.

PubMed

Kathuria, Sagar V; Chan, Yvonne H; Nobrega, R Paul; Özen, Ayşegül; Matthews, C Robert

2016-03-01

Measurements of protection against exchange of main chain amide hydrogens (NH) with solvent hydrogens in globular proteins have provided remarkable insights into the structures of rare high-energy states that populate their folding free-energy surfaces. Lacking, however, has been a unifying theory that rationalizes these high-energy states in terms of the structures and sequences of their resident proteins. The Branched Aliphatic Side Chain (BASiC) hypothesis has been developed to explain the observed patterns of protection in a pair of TIM barrel proteins. This hypothesis supposes that the side chains of isoleucine, leucine, and valine (ILV) residues often form large hydrophobic clusters that very effectively impede the penetration of water to their underlying hydrogen bond networks and, thereby, enhance the protection against solvent exchange. The linkage between the secondary and tertiary structures enables these ILV clusters to serve as cores of stability in high-energy partially folded states. Statistically significant correlations between the locations of large ILV clusters in native conformations and strong protection against exchange for a variety of motifs reported in the literature support the generality of the BASiC hypothesis. The results also illustrate the necessity to elaborate this simple hypothesis to account for the roles of adjacent hydrocarbon moieties in defining stability cores of partially folded states along folding reaction coordinates. © 2015 The Protein Society.
Quantum cluster algebras and quantum nilpotent algebras.

PubMed

Goodearl, Kenneth R; Yakimov, Milen T

2014-07-08

A major direction in the theory of cluster algebras is to construct (quantum) cluster algebra structures on the (quantized) coordinate rings of various families of varieties arising in Lie theory. We prove that all algebras in a very large axiomatically defined class of noncommutative algebras possess canonical quantum cluster algebra structures. Furthermore, they coincide with the corresponding upper quantum cluster algebras. We also establish analogs of these results for a large class of Poisson nilpotent algebras. Many important families of coordinate rings are subsumed in the class we are covering, which leads to a broad range of applications of the general results to the above-mentioned types of problems. As a consequence, we prove the Berenstein-Zelevinsky conjecture [Berenstein A, Zelevinsky A (2005) Adv Math 195:405-455] for the quantized coordinate rings of double Bruhat cells and construct quantum cluster algebra structures on all quantum unipotent groups, extending the theorem of Geiß et al. [Geiß C, et al. (2013) Selecta Math 19:337-397] for the case of symmetric Kac-Moody groups. Moreover, we prove that the upper cluster algebras of Berenstein et al. [Berenstein A, et al. (2005) Duke Math J 126:1-52] associated with double Bruhat cells coincide with the corresponding cluster algebras.
Quantum cluster algebras and quantum nilpotent algebras

PubMed Central

Goodearl, Kenneth R.; Yakimov, Milen T.

2014-01-01

A major direction in the theory of cluster algebras is to construct (quantum) cluster algebra structures on the (quantized) coordinate rings of various families of varieties arising in Lie theory. We prove that all algebras in a very large axiomatically defined class of noncommutative algebras possess canonical quantum cluster algebra structures. Furthermore, they coincide with the corresponding upper quantum cluster algebras. We also establish analogs of these results for a large class of Poisson nilpotent algebras. Many important families of coordinate rings are subsumed in the class we are covering, which leads to a broad range of applications of the general results to the above-mentioned types of problems. As a consequence, we prove the Berenstein–Zelevinsky conjecture [Berenstein A, Zelevinsky A (2005) Adv Math 195:405–455] for the quantized coordinate rings of double Bruhat cells and construct quantum cluster algebra structures on all quantum unipotent groups, extending the theorem of Geiß et al. [Geiß C, et al. (2013) Selecta Math 19:337–397] for the case of symmetric Kac–Moody groups. Moreover, we prove that the upper cluster algebras of Berenstein et al. [Berenstein A, et al. (2005) Duke Math J 126:1–52] associated with double Bruhat cells coincide with the corresponding cluster algebras. PMID:24982197
Mainshock-Aftershock Clustering in Volcanic Regions

NASA Astrophysics Data System (ADS)

Garza-Giron, Ricardo; Brodsky, Emily E.; Prejean, Stephanie G.

2018-02-01

Earthquakes break their general Poissonean behavior through two types of seismic bursts: swarms and mainshock-aftershock sequences. The former is commonly thought to dominate in volcanic and geothermal regions, but aftershock production, including within swarms, is not well studied in volcanic regions. Here we compare mainshock-aftershock clustering in active volcanic regions in Japan to nearby nonvolcanic regions. We find that aftershock production is similar in both areas by two separate metrics: (1) Both volcanic and nonvolcanic regions have similar proportions of areas that cluster into mainshock-aftershock sequences. (2) Volcanic areas with mainshock-aftershock sequences have aftershock productivity at least as high as nonvolcanic regions. We also find that volcano-tectonic events that are precursors to an eruption are more common at volcanoes without mainshock-aftershock clusters than at volcanoes with well-defined mainshock-aftershock clusters. This last finding hints at a strategy to identify volcanic systems where cataloged earthquakes are good predictors of behavior.
Quantum dynamics of small H2 and D2 clusters in the large cage of structure II clathrate hydrate: Energetics, occupancy, and vibrationally averaged cluster structures

NASA Astrophysics Data System (ADS)

Sebastianelli, Francesco; Xu, Minzhong; Bačić, Zlatko

2008-12-01

We report diffusion Monte Carlo (DMC) calculations of the quantum translation-rotation (T-R) dynamics of one to five para-H2 (p-H2) and ortho-D2 (o-D2) molecules inside the large hexakaidecahedral (51264) cage of the structure II clathrate hydrate, which was taken to be rigid. These calculations provide a quantitative description of the size evolution of the ground-state properties, energetics, and the vibrationally averaged geometries, of small (p-H2)n and (o-D2)n clusters, n=1-5, in nanoconfinement. The zero-point energy (ZPE) of the T-R motions rises steeply with the cluster size, reaching 74% of the potential well depth for the caged (p-H2)4. At low temperatures, the rapid increase of the cluster ZPE as a function of n is the main factor that limits the occupancy of the large cage to at most four H2 or D2 molecules, in agreement with experiments. Our DMC results concerning the vibrationally averaged spatial distribution of four D2 molecules, their mean distance from the cage center, the D2-D2 separation, and the specific orientation and localization of the tetrahedral (D2)4 cluster relative to the framework of the large cage, agree very well with the low-temperature neutron diffraction experiments involving the large cage with the quadruple D2 occupancy.
Quantum dynamics of small H2 and D2 clusters in the large cage of structure II clathrate hydrate: energetics, occupancy, and vibrationally averaged cluster structures.

PubMed

Sebastianelli, Francesco; Xu, Minzhong; Bacić, Zlatko

2008-12-28

We report diffusion Monte Carlo (DMC) calculations of the quantum translation-rotation (T-R) dynamics of one to five para-H(2) (p-H(2)) and ortho-D(2) (o-D(2)) molecules inside the large hexakaidecahedral (5(12)6(4)) cage of the structure II clathrate hydrate, which was taken to be rigid. These calculations provide a quantitative description of the size evolution of the ground-state properties, energetics, and the vibrationally averaged geometries, of small (p-H(2))(n) and (o-D(2))(n) clusters, n=1-5, in nanoconfinement. The zero-point energy (ZPE) of the T-R motions rises steeply with the cluster size, reaching 74% of the potential well depth for the caged (p-H(2))(4). At low temperatures, the rapid increase of the cluster ZPE as a function of n is the main factor that limits the occupancy of the large cage to at most four H(2) or D(2) molecules, in agreement with experiments. Our DMC results concerning the vibrationally averaged spatial distribution of four D(2) molecules, their mean distance from the cage center, the D(2)-D(2) separation, and the specific orientation and localization of the tetrahedral (D(2))(4) cluster relative to the framework of the large cage, agree very well with the low-temperature neutron diffraction experiments involving the large cage with the quadruple D(2) occupancy.
Comparison between volatility return intervals of the S&P 500 index and two common models

NASA Astrophysics Data System (ADS)

Vodenska-Chitkushev, I.; Wang, F. Z.; Weber, P.; Yamasaki, K.; Havlin, S.; Stanley, H. E.

2008-01-01

We analyze the S&P 500 index data for the 13-year period, from January 1, 1984 to December 31, 1996, with one data point every 10 min. For this database, we study the distribution and clustering of volatility return intervals, which are defined as the time intervals between successive volatilities above a certain threshold q. We find that the long memory in the volatility leads to a clustering of above-median as well as below-median return intervals. In addition, it turns out that the short return intervals form larger clusters compared to the long return intervals. When comparing the empirical results to the ARMA-FIGARCH and fBm models for volatility, we find that the fBm model predicts scaling better than the ARMA-FIGARCH model, which is consistent with the argument that both ARMA-FIGARCH and fBm capture the long-term dependence in return intervals to a certain extent, but only fBm accounts for the scaling. We perform the Student's t-test to compare the empirical data with the shuffled records, ARMA-FIGARCH and fBm. We analyze separately the clusters of above-median return intervals and the clusters of below-median return intervals for different thresholds q. We find that the empirical data are statistically different from the shuffled data for all thresholds q. Our results also suggest that the ARMA-FIGARCH model is statistically different from the S&P 500 for intermediate q for both above-median and below-median clusters, while fBm is statistically different from S&P 500 for small and large q for above-median clusters and for small q for below-median clusters. Neither model can fully explain the entire regime of q studied.
Epitaxial ferromagnetic single clusters and smooth continuous layers on large area MgO/CVD graphene substrates

NASA Astrophysics Data System (ADS)

Godel, Florian; Meny, Christian; Doudin, Bernard; Majjad, Hicham; Dayen, Jean-François; Halley, David

2018-02-01

We report on the fabrication of ferromagnetic thin layers separated by a MgO dielectric barrier from a graphene-covered substrate. The growth of ferromagnetic metal layers—Co or Ni0.8Fe0.2—is achieved by Molecular Beam Epitaxy (MBE) on a 3 nm MgO(111) epitaxial layer deposited on graphene. In the case of a graphene, grown by chemical vapor deposition (CVD) over Ni substrates, an annealing at 450 °C, under ultra-high-vacuum (UHV) conditions, leads to the dewetting of the ferromagnetic layers, forming well-defined flat facetted clusters whose shape reflects the substrate symmetry. In the case of CVD graphene transferred on SiO2, no dewetting is observed after same annealing. We attribute this difference to the mechanical stress states induced by the substrate, illustrating how it matters for epitaxial construction through graphene. Controlling the growth parameters of such magnetic single objects or networks could benefit to new architectures for catalysis or spintronic applications.
Accurately tuning the charge on giant polyoxometalate type Keplerates through stoichiometric interaction with cationic surfactants.

PubMed

Kistler, Melissa L; Patel, Komal G; Liu, Tianbo

2009-07-07

We report an approach of exploring the interaction between cationic surfactants and a type of structurally well-defined, spherical "Keplerate" polyoxometalate (POM) macroanionic molecular clusters, {Mo72V30}, in aqueous solution. The effectiveness of the interaction can be determined by monitoring the size change of the "blackberry" supramolecular structures formed by the self-assembly of {Mo72V30} macroions, which is determined by the effective charge density on the macroions. Long-chain surfactants (CTAB and CTAT) can interact with {Mo72V30} macroions stoichiometrically and lower their charge density. Consequently, the blackberry size decreases continuously with increasing surfactant concentration in solution. On the other hand, for short-chain surfactants (e.g., OTAB), a larger fraction of surfactants exist as discrete chains in solution and do not strongly interact with the macroions. This approach shows that a controllable amount of suitable surfactants can accurately tune the charge on large molecular clusters.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Norman A.; /SLAC

Maximizing the physics performance of detectors being designed for the International Linear Collider, while remaining sensitive to cost constraints, requires a powerful, efficient, and flexible simulation, reconstruction and analysis environment to study the capabilities of a large number of different detector designs. The preparation of Letters Of Intent for the International Linear Collider involved the detailed study of dozens of detector options, layouts and readout technologies; the final physics benchmarking studies required the reconstruction and analysis of hundreds of millions of events. We describe the Java-based software toolkit (org.lcsim) which was used for full event reconstruction and analysis. The componentsmore » are fully modular and are available for tasks from digitization of tracking detector signals through to cluster finding, pattern recognition, track-fitting, calorimeter clustering, individual particle reconstruction, jet-finding, and analysis. The detector is defined by the same xml input files used for the detector response simulation, ensuring the simulation and reconstruction geometries are always commensurate by construction. We discuss the architecture as well as the performance.« less
Employment relations and global health: a typological study of world labor markets.

PubMed

Chung, Haejoo; Muntaner, Carles; Benach, Joan

2010-01-01

In this study, the authors investigate the global labor market and employment relations, which are central building blocks of the welfare state; the aim is to propose a global typology of labor markets to explain global inequalities in population health. Countries are categorized into core (21), semi-peripheral (42), and peripheral (71) countries, based on gross national product per capita (Atlas method). Labor market-related variables and factors are then used to generate clusters of countries with principal components and cluster analysis methods. The authors then examine the relationship between the resulting clusters and health outcomes. The clusters of countries are largely geographically defined, each cluster with similar historical background and developmental strategy. However, there are interesting exceptions, which warrant further elaboration. The relationship between health outcomes and clusters largely follows the authors' expectations (except for communicable diseases): more egalitarian labor institutions have better health outcomes. The world system, then, can be divided according to different types of labor markets that are predictive of population health outcomes at each level of economic development. As is the case for health and social policies, variability in labor market characteristics is likely to reflect, in part, the relative strength of a country's political actors.
Rapid Detection of Positive Selection in Genes and Genomes Through Variation Clusters

PubMed Central

Wagner, Andreas

2007-01-01

Positive selection in genes and genomes can point to the evolutionary basis for differences among species and among races within a species. The detection of positive selection can also help identify functionally important protein regions and thus guide protein engineering. Many existing tests for positive selection are excessively conservative, vulnerable to artifacts caused by demographic population history, or computationally very intensive. I here propose a simple and rapid test that is complementary to existing tests and that overcomes some of these problems. It relies on the null hypothesis that neutrally evolving DNA regions should show a Poisson distribution of nucleotide substitutions. The test detects significant deviations from this expectation in the form of variation clusters, highly localized groups of amino acid changes in a coding region. In applying this test to several thousand human–chimpanzee gene orthologs, I show that such variation clusters are not generally caused by relaxed selection. They occur in well-defined domains of a protein's tertiary structure and show a large excess of amino acid replacement over silent substitutions. I also identify multiple new human–chimpanzee orthologs subject to positive selection, among them genes that are involved in reproductive functions, immune defense, and the nervous system. PMID:17603100

EMBEDDED CLUSTERS IN THE LARGE MAGELLANIC CLOUD USING THE VISTA MAGELLANIC CLOUDS SURVEY

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

Romita, Krista; Lada, Elizabeth; Cioni, Maria-Rosa, E-mail: k.a.romita@ufl.edu, E-mail: elada@ufl.edu, E-mail: mcioni@aip.de

We present initial results of the first large-scale survey of embedded star clusters in molecular clouds in the Large Magellanic Cloud (LMC) using near-infrared imaging from the Visible and Infrared Survey Telescope for Astronomy Magellanic Clouds Survey. We explored a ∼1.65 deg{sup 2} area of the LMC, which contains the well-known star-forming region 30 Doradus as well as ∼14% of the galaxy’s CO clouds, and identified 67 embedded cluster candidates, 45 of which are newly discovered as clusters. We have determined the sizes, luminosities, and masses for these embedded clusters, examined the star formation rates (SFRs) of their corresponding molecularmore » clouds, and made a comparison between the LMC and the Milky Way. Our preliminary results indicate that embedded clusters in the LMC are generally larger, more luminous, and more massive than those in the local Milky Way. We also find that the surface densities of both embedded clusters and molecular clouds is ∼3 times higher than in our local environment, the embedded cluster mass surface density is ∼40 times higher, the SFR is ∼20 times higher, and the star formation efficiency is ∼10 times higher. Despite these differences, the SFRs of the LMC molecular clouds are consistent with the SFR scaling law presented in Lada et al. This consistency indicates that while the conditions of embedded cluster formation may vary between environments, the overall process within molecular clouds may be universal.« less
Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.

PubMed

Pascual-García, Alberto; Abia, David; Ortiz, Angel R; Bastolla, Ugo

2009-03-01

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php.
Using cluster ensemble and validation to identify subtypes of pervasive developmental disorders.

PubMed

Shen, Jess J; Lee, Phil-Hyoun; Holden, Jeanette J A; Shatkay, Hagit

2007-10-11

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior. Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.
Using Cluster Ensemble and Validation to Identify Subtypes of Pervasive Developmental Disorders

PubMed Central

Shen, Jess J.; Lee, Phil Hyoun; Holden, Jeanette J.A.; Shatkay, Hagit

2007-01-01

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior.1 Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes19. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.2 PMID:18693920
Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias

NASA Astrophysics Data System (ADS)

Medezinski, Elinor; Battaglia, Nicholas; Coupon, Jean; Cen, Renyue; Gaspari, Massimo; Strauss, Michael A.; Spergel, David N.

2017-02-01

There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (I.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determining their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.
Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias

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

Medezinski, Elinor; Battaglia, Nicholas; Cen, Renyue

2017-02-10

There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (i.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determiningmore » their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6 σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.« less
Room-temperature current blockade in atomically defined single-cluster junctions

NASA Astrophysics Data System (ADS)

Lovat, Giacomo; Choi, Bonnie; Paley, Daniel W.; Steigerwald, Michael L.; Venkataraman, Latha; Roy, Xavier

2017-11-01

Fabricating nanoscopic devices capable of manipulating and processing single units of charge is an essential step towards creating functional devices where quantum effects dominate transport characteristics. The archetypal single-electron transistor comprises a small conducting or semiconducting island separated from two metallic reservoirs by insulating barriers. By enabling the transfer of a well-defined number of charge carriers between the island and the reservoirs, such a device may enable discrete single-electron operations. Here, we describe a single-molecule junction comprising a redox-active, atomically precise cobalt chalcogenide cluster wired between two nanoscopic electrodes. We observe current blockade at room temperature in thousands of single-cluster junctions. Below a threshold voltage, charge transfer across the junction is suppressed. The device is turned on when the temporary occupation of the core states by a transiting carrier is energetically enabled, resulting in a sequential tunnelling process and an increase in current by a factor of ∼600. We perform in situ and ex situ cyclic voltammetry as well as density functional theory calculations to unveil a two-step process mediated by an orbital localized on the core of the cluster in which charge carriers reside before tunnelling to the collector reservoir. As the bias window of the junction is opened wide enough to include one of the cluster frontier orbitals, the current blockade is lifted and charge carriers can tunnel sequentially across the junction.
Relationship between damage clustering and mortality in systemic lupus erythematosus in early and late stages of the disease: cluster analyses in a large cohort from the Spanish Society of Rheumatology Lupus Registry.

PubMed

Pego-Reigosa, José María; Lois-Iglesias, Ana; Rúa-Figueroa, Íñigo; Galindo, María; Calvo-Alén, Jaime; de Uña-Álvarez, Jacobo; Balboa-Barreiro, Vanessa; Ibáñez Ruan, Jesús; Olivé, Alejandro; Rodríguez-Gómez, Manuel; Fernández Nebro, Antonio; Andrés, Mariano; Erausquin, Celia; Tomero, Eva; Horcada Rubio, Loreto; Uriarte Isacelaya, Esther; Freire, Mercedes; Montilla, Carlos; Sánchez-Atrio, Ana I; Santos-Soler, Gregorio; Zea, Antonio; Díez, Elvira; Narváez, Javier; Blanco-Alonso, Ricardo; Silva-Fernández, Lucía; Ruiz-Lucea, María Esther; Fernández-Castro, Mónica; Hernández-Beriain, José Ángel; Gantes-Mora, Marian; Hernández-Cruz, Blanca; Pérez-Venegas, José; Pecondón-Español, Ángela; Marras Fernández-Cid, Carlos; Ibáñez-Barcelo, Mónica; Bonilla, Gema; Torrente-Segarra, Vicenç; Castellví, Iván; Alegre, Juan José; Calvet, Joan; Marenco de la Fuente, José Luis; Raya, Enrique; Vázquez-Rodríguez, Tomás Ramón; Quevedo-Vila, Víctor; Muñoz-Fernández, Santiago; Otón, Teresa; Rahman, Anisur; López-Longo, Francisco Javier

2016-07-01

To identify patterns (clusters) of damage manifestations within a large cohort of SLE patients and evaluate the potential association of these clusters with a higher risk of mortality. This is a multicentre, descriptive, cross-sectional study of a cohort of 3656 SLE patients from the Spanish Society of Rheumatology Lupus Registry. Organ damage was ascertained using the Systemic Lupus International Collaborating Clinics Damage Index. Using cluster analysis, groups of patients with similar patterns of damage manifestations were identified. Then, overall clusters were compared as well as the subgroup of patients within every cluster with disease duration shorter than 5 years. Three damage clusters were identified. Cluster 1 (80.6% of patients) presented a lower amount of individuals with damage (23.2 vs 100% in clusters 2 and 3, P < 0.001). Cluster 2 (11.4% of patients) was characterized by musculoskeletal damage in all patients. Cluster 3 (8.0% of patients) was the only group with cardiovascular damage, and this was present in all patients. The overall mortality rate of patients in clusters 2 and 3 was higher than that in cluster 1 (P < 0.001 for both comparisons) and in patients with disease duration shorter than 5 years as well. In a large cohort of SLE patients, cardiovascular and musculoskeletal damage manifestations were the two dominant forms of damage to sort patients into clinically meaningful clusters. Both in early and late stages of the disease, there was a significant association of these clusters with an increased risk of mortality. Physicians should pay special attention to the early prevention of damage in these two systems. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Testing approximate predictions of displacements of cosmological dark matter halos

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

Munari, Emiliano; Monaco, Pierluigi; Borgani, Stefano

We present a test to quantify how well some approximate methods, designed to reproduce the mildly non-linear evolution of perturbations, are able to reproduce the clustering of DM halos once the grouping of particles into halos is defined and kept fixed. The following methods have been considered: Lagrangian Perturbation Theory (LPT) up to third order, Truncated LPT, Augmented LPT, MUSCLE and COLA. The test runs as follows: halos are defined by applying a friends-of-friends (FoF) halo finder to the output of an N-body simulation. The approximate methods are then applied to the same initial conditions of the simulation, producing formore » all particles displacements from their starting position and velocities. The position and velocity of each halo are computed by averaging over the particles that belong to that halo, according to the FoF halo finder. This procedure allows us to perform a well-posed test of how clustering of the matter density and halo density fields are recovered, without asking to the approximate method an accurate reconstruction of halos. We have considered the results at z =0,0.5,1, and we have analysed power spectrum in real and redshift space, object-by-object difference in position and velocity, density Probability Distribution Function (PDF) and its moments, phase difference of Fourier modes. We find that higher LPT orders are generally able to better reproduce the clustering of halos, while little or no improvement is found for the matter density field when going to 2LPT and 3LPT. Augmentation provides some improvement when coupled with 2LPT, while its effect is limited when coupled with 3LPT. Little improvement is brought by MUSCLE with respect to Augmentation. The more expensive particle-mesh code COLA outperforms all LPT methods, and this is true even for mesh sizes as large as the inter-particle distance. This test sets an upper limit on the ability of these methods to reproduce the clustering of halos, for the cases when these objects are reconstructed at the object-by-object level.« less
Testing approximate predictions of displacements of cosmological dark matter halos

NASA Astrophysics Data System (ADS)

Munari, Emiliano; Monaco, Pierluigi; Koda, Jun; Kitaura, Francisco-Shu; Sefusatti, Emiliano; Borgani, Stefano

2017-07-01

We present a test to quantify how well some approximate methods, designed to reproduce the mildly non-linear evolution of perturbations, are able to reproduce the clustering of DM halos once the grouping of particles into halos is defined and kept fixed. The following methods have been considered: Lagrangian Perturbation Theory (LPT) up to third order, Truncated LPT, Augmented LPT, MUSCLE and COLA. The test runs as follows: halos are defined by applying a friends-of-friends (FoF) halo finder to the output of an N-body simulation. The approximate methods are then applied to the same initial conditions of the simulation, producing for all particles displacements from their starting position and velocities. The position and velocity of each halo are computed by averaging over the particles that belong to that halo, according to the FoF halo finder. This procedure allows us to perform a well-posed test of how clustering of the matter density and halo density fields are recovered, without asking to the approximate method an accurate reconstruction of halos. We have considered the results at z=0,0.5,1, and we have analysed power spectrum in real and redshift space, object-by-object difference in position and velocity, density Probability Distribution Function (PDF) and its moments, phase difference of Fourier modes. We find that higher LPT orders are generally able to better reproduce the clustering of halos, while little or no improvement is found for the matter density field when going to 2LPT and 3LPT. Augmentation provides some improvement when coupled with 2LPT, while its effect is limited when coupled with 3LPT. Little improvement is brought by MUSCLE with respect to Augmentation. The more expensive particle-mesh code COLA outperforms all LPT methods, and this is true even for mesh sizes as large as the inter-particle distance. This test sets an upper limit on the ability of these methods to reproduce the clustering of halos, for the cases when these objects are reconstructed at the object-by-object level.
Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778
FIDUCIAL STELLAR POPULATION SEQUENCES FOR THE VJK{sub S} PHOTOMETRIC SYSTEM

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

Brasseur, Crystal M.; VandenBerg, Don A.; Stetson, Peter B.

2010-12-15

We have obtained broadband near-infrared photometry for seven Galactic star clusters (M 92, M 15, M 13, M 5, NGC 1851, M 71, and NGC 6791) using the WIRCam wide-field imager on the Canada-France-Hawaii Telescope, supplemented by images of NGC 1851 taken with HAWK-I on the Very Large Telescope. In addition, Two Micron All Sky Survey (2MASS) observations of the [Fe/H] {approx}0.0 open cluster M 67 were added to the cluster database. From the resultant (V - J) - V and (V - K{sub S} ) - V color-magnitude diagrams (CMDs), fiducial sequences spanning the range in metallicity, -2.4 {approx}
Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.
Amino acid alphabet reduction preserves fold information contained in contact interactions in proteins.

PubMed

Solis, Armando D

2015-12-01

To reduce complexity, understand generalized rules of protein folding, and facilitate de novo protein design, the 20-letter amino acid alphabet is commonly reduced to a smaller alphabet by clustering amino acids based on some measure of similarity. In this work, we seek the optimal alphabet that preserves as much of the structural information found in long-range (contact) interactions among amino acids in natively-folded proteins. We employ the Information Maximization Device, based on information theory, to partition the amino acids into well-defined clusters. Numbering from 2 to 19 groups, these optimal clusters of amino acids, while generated automatically, embody well-known properties of amino acids such as hydrophobicity/polarity, charge, size, and aromaticity, and are demonstrated to maintain the discriminative power of long-range interactions with minimal loss of mutual information. Our measurements suggest that reduced alphabets (of less than 10) are able to capture virtually all of the information residing in native contacts and may be sufficient for fold recognition, as demonstrated by extensive threading tests. In an expansive survey of the literature, we observe that alphabets derived from various approaches-including those derived from physicochemical intuition, local structure considerations, and sequence alignments of remote homologs-fare consistently well in preserving contact interaction information, highlighting a convergence in the various factors thought to be relevant to the folding code. Moreover, we find that alphabets commonly used in experimental protein design are nearly optimal and are largely coherent with observations that have arisen in this work. © 2015 Wiley Periodicals, Inc.
Personalising care of adults with asthma from Asia: a modified e-Dephi consensus study to inform management tailored to attitude and control profiles.

PubMed

Chisholm, Alison; Price, David B; Pinnock, Hilary; Lee, Tan Tze; Roa, Camilo; Cho, Sang-Heon; David-Wang, Aileen; Wong, Gary; van der Molen, Thys; Ryan, Dermot; Castillo-Carandang, Nina; Yong, Yee Vern

2017-01-05

REALISE Asia-an online questionnaire-based study of Asian asthma patients-identified five patient clusters defined in terms of their control status and attitude towards their asthma (categorised as: 'Well-adjusted and at least partly controlled'; 'In denial about symptoms'; 'Tolerating with poor control'; 'Adrift and poorly controlled'; 'Worried with multiple symptoms'). We developed consensus recommendations for tailoring management of these attitudinal-control clusters. An expert panel undertook a three-round electronic Delphi (e-Delphi): Round 1: panellists received descriptions of the attitudinal-control clusters and provided free text recommendations for their assessment and management. Round 2: panellists prioritised Round 1 recommendations and met (or joined a teleconference) to consolidate the recommendations. Round 3: panellists voted and prioritised the remaining recommendations. Consensus was defined as Round 3 recommendations endorsed by >50% of panellists. Highest priority recommendations were those receiving the highest score. The multidisciplinary panellists (9 clinicians, 1 pharmacist and 1 health social scientist; 7 from Asia) identified consensus recommendations for all clusters. Recommended pharmacological (e.g., step-up/down; self-management; simplified regimen) and non-pharmacological approaches (e.g., trigger management, education, social support; inhaler technique) varied substantially according to each cluster's attitude to asthma and associated psychosocial drivers of behaviour. The attitudinal-control clusters defined by REALISE Asia resonated with the international panel. Consensus was reached on appropriate tailored management approaches for all clusters. Summarised and incorporated into a structured management pathway, these recommendations could facilitate personalised care. Generalisability of these patient clusters should be assessed in other socio-economic, cultural and literacy groups and nationalities in Asia.
Titanium oxo-clusters: precursors for a Lego-like construction of nanostructured hybrid materials.

PubMed

Rozes, Laurence; Sanchez, Clément

2011-02-01

Titanium oxo-clusters, well-defined monodispersed nano-objects, are appropriate nano-building blocks for the preparation of organic-inorganic materials by a bottom up approach. This critical review proposes to present the different structures of titanium oxo-clusters referenced in the literature and the different strategies followed to build up hybrid materials with these versatile building units. In particular, this critical review cites and reports on the most important papers in the literature, concentrating on recent developments in the field of synthesis, characterization, and the use of titanium oxo-clusters for the construction of advanced hybrid materials (137 references).
The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies.

PubMed

Harispe, Sébastien; Ranwez, Sylvie; Janaqi, Stefan; Montmain, Jacky

2014-03-01

The semantic measures library and toolkit are robust open-source and easy to use software solutions dedicated to semantic measures. They can be used for large-scale computations and analyses of semantic similarities between terms/concepts defined in terminologies and ontologies. The comparison of entities (e.g. genes) annotated by concepts is also supported. A large collection of measures is available. Not limited to a specific application context, the library and the toolkit can be used with various controlled vocabularies and ontology specifications (e.g. Open Biomedical Ontology, Resource Description Framework). The project targets both designers and practitioners of semantic measures providing a JAVA library, as well as a command-line tool that can be used on personal computers or computer clusters. Downloads, documentation, tutorials, evaluation and support are available at http://www.semantic-measures-library.org.
Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

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

NASA Technical Reports Server (NTRS)

Harrington, Patrick M.; Melott, Adrian L.; Shandarin, Sergei F.

1993-01-01

We present in this paper a quantitative method for defining void size in large-scale structure based on percolation threshold density. Beginning with two-dimensional gravitational clustering simulations smoothed to the threshold of nonlinearity, we perform percolation analysis to determine the large scale structure. The resulting objective definition of voids has a natural scaling property, is topologically interesting, and can be applied immediately to redshift surveys.
The young SMC cluster NGC 330

NASA Technical Reports Server (NTRS)

Carney, B. W.; Janes, K. A.; Flower, P. J.

1985-01-01

A color-magnitude diagram has been obtained for the young SMC cluster NGC 330. The diagram shows a well-defined main sequence, a group of blue supergiants, a group of red supergiants between B-V = 1.2 m and 1.6 m about one magnitude fainter, and an empty Hertzsprung gap. The surrounding field is a composite of a very gold population resembling galactic globular clusters and a very young population. DDO and infrared photometry strongly suggest that the cluster is metal-poor, but a definitive measure could not be made because of calibration difficulties. The cluster's age is estimated at 12 million years, with the surrounding field about 50 percent older. The cluster will prove very useful in testing stellar evolution models for young, metal-poor stars if the cluster's metallicity can be established via high-resolution spectroscopy.

Cluster Analysis to Identify Possible Subgroups in Tinnitus Patients.

PubMed

van den Berge, Minke J C; Free, Rolien H; Arnold, Rosemarie; de Kleine, Emile; Hofman, Rutger; van Dijk, J Marc C; van Dijk, Pim

2017-01-01

In tinnitus treatment, there is a tendency to shift from a "one size fits all" to a more individual, patient-tailored approach. Insight in the heterogeneity of the tinnitus spectrum might improve the management of tinnitus patients in terms of choice of treatment and identification of patients with severe mental distress. The goal of this study was to identify subgroups in a large group of tinnitus patients. Data were collected from patients with severe tinnitus complaints visiting our tertiary referral tinnitus care group at the University Medical Center Groningen. Patient-reported and physician-reported variables were collected during their visit to our clinic. Cluster analyses were used to characterize subgroups. For the selection of the right variables to enter in the cluster analysis, two approaches were used: (1) variable reduction with principle component analysis and (2) variable selection based on expert opinion. Various variables of 1,783 tinnitus patients were included in the analyses. Cluster analysis (1) included 976 patients and resulted in a four-cluster solution. The effect of external influences was the most discriminative between the groups, or clusters, of patients. The "silhouette measure" of the cluster outcome was low (0.2), indicating a "no substantial" cluster structure. Cluster analysis (2) included 761 patients and resulted in a three-cluster solution, comparable to the first analysis. Again, a "no substantial" cluster structure was found (0.2). Two cluster analyses on a large database of tinnitus patients revealed that clusters of patients are mostly formed by a different response of external influences on their disease. However, both cluster outcomes based on this dataset showed a poor stability, suggesting that our tinnitus population comprises a continuum rather than a number of clearly defined subgroups.
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.
Earth Science Data Analytics: Bridging Tools and Techniques with the Co-Analysis of Large, Heterogeneous Datasets

NASA Technical Reports Server (NTRS)

Kempler, Steve; Mathews, Tiffany

2016-01-01

The continuum of ever-evolving data management systems affords great opportunities to the enhancement of knowledge and facilitation of science research. To take advantage of these opportunities, it is essential to understand and develop methods that enable data relationships to be examined and the information to be manipulated. This presentation describes the efforts of the Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster to understand, define, and facilitate the implementation of ESDA to advance science research. As a result of the void of Earth science data analytics publication material, the cluster has defined ESDA along with 10 goals to set the framework for a common understanding of tools and techniques that are available and still needed to support ESDA.
KinFin: Software for Taxon-Aware Analysis of Clustered Protein Sequences.

PubMed

Laetsch, Dominik R; Blaxter, Mark L

2017-10-05

The field of comparative genomics is concerned with the study of similarities and differences between the information encoded in the genomes of organisms. A common approach is to define gene families by clustering protein sequences based on sequence similarity, and analyze protein cluster presence and absence in different species groups as a guide to biology. Due to the high dimensionality of these data, downstream analysis of protein clusters inferred from large numbers of species, or species with many genes, is nontrivial, and few solutions exist for transparent, reproducible, and customizable analyses. We present KinFin, a streamlined software solution capable of integrating data from common file formats and delivering aggregative annotation of protein clusters. KinFin delivers analyses based on systematic taxonomy of the species analyzed, or on user-defined, groupings of taxa, for example, sets based on attributes such as life history traits, organismal phenotypes, or competing phylogenetic hypotheses. Results are reported through graphical and detailed text output files. We illustrate the utility of the KinFin pipeline by addressing questions regarding the biology of filarial nematodes, which include parasites of veterinary and medical importance. We resolve the phylogenetic relationships between the species and explore functional annotation of proteins in clusters in key lineages and between custom taxon sets, identifying gene families of interest. KinFin can easily be integrated into existing comparative genomic workflows, and promotes transparent and reproducible analysis of clustered protein data. Copyright © 2017 Laetsch and Blaxter.
Color-magnitude diagram of Palomar 4 - CCD photometry

NASA Astrophysics Data System (ADS)

Christian, C. A.; Heasley, J. N.

1986-04-01

Photometry of the globular cluster Pal 4 was obtained with the RCA CCD camera on the 3.6 m Canada-France-Hawaii Telescope on Mauna Kea. The color-magnitude diagram of the cluster shows a well-defined red horizontal branch, typical of outer halo systems, and an asymptotic giant branch well separated from the giant branch. The population of Pal 4 has been sampled to the main-sequence turnoff region (V = 25), allowing a detailed comparison of this distant object with theoretical models. The cluster parameters consistent with the CCD data are (m - M)0 = 20.1 + or - 0.1 mag, E(B - V) = 0.02 + or - 0.02, and Fe/H forbidden line = -1.7 + or - 0.1 with Y =0.2. The age of the cluster, determined by comparison with the isochrones of VandenBerg and Bell (1985) is consistent with an age of 15 + or - 1 Gyr, similar to inner halo globular clusters with ages determined in the same way.
Silver enhancement of nanogold and undecagold

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

Hainfield, J.F.; Furuya, F.R.

1995-07-01

A recent advance in immunogold technology has been the use of molecular gold instead of colloidal gold. A number of advantages are realized by this approach, such as stable covalent, site-specific attachment, small probe size and absence of aggregates for improved penetration. Silver enhancement has led to improved and unique results for electron and light microscopy, as well as their use with blots and gels. Most previous work with immunogold silver staining has been done with colloidal gold particles. More recently, large gold compounds (``clusters``) having a definite number of gold atoms and defined organic shell, have been used, frequentlymore » with improved results. These gold dusters, large compared to simple compounds, are, however, at the small end of the colloidal gold scale in size; undecagold is 0.8 nm and Nanogold is 1.4 nm. They may be used in practically all applications where colloidal gold is used (Light and electron microscopy, dot blots, etc.) and in some unique applications, where at least the larger colloidal golds don`t work, such as running gold labeled proteins on gels (which are later detected by silver enhancement). The main differences between gold clusters and colloidal golds are the small size of the dusters and their covalent attachment to antibodies or other molecules.« less
Defining the Architecture of the Core Machinery for the Assembly of Fe-S Clusters in Human Mitochondria.

PubMed

Gakh, Oleksandr; Ranatunga, Wasantha; Galeano, Belinda K; Smith, Douglas S; Thompson, James R; Isaya, Grazia

2017-01-01

Although Fe-S clusters may assemble spontaneously from elemental iron and sulfur in protein-free systems, the potential toxicity of free Fe 2+ , Fe 3+ , and S 2- ions in aerobic environments underscores the requirement for specialized proteins to oversee the safe assembly of Fe-S clusters in living cells. Prokaryotes first developed multiprotein systems for Fe-S cluster assembly, from which mitochondria later derived their own system and became the main Fe-S cluster suppliers for eukaryotic cells. Early studies in yeast and human mitochondria indicated that Fe-S cluster assembly in eukaryotes is centered around highly conserved Fe-S proteins (human ISCU) that serve as scaffolds upon which new Fe-S clusters are assembled from (i) elemental sulfur, provided by a pyridoxal phosphate-dependent cysteine desulfurase (human NFS1) and its stabilizing-binding partner (human ISD11), and (ii) elemental iron, provided by an iron-binding protein of the frataxin family (human FXN). Further studies revealed that all of these proteins could form stable complexes that could reach molecular masses of megadaltons. However, the protein-protein interaction surfaces, catalytic mechanisms, and overall architecture of these macromolecular machines remained undefined for quite some time. The delay was due to difficulties inherent in reconstituting these very large multiprotein complexes in vitro or isolating them from cells in sufficient quantities to enable biochemical and structural studies. Here, we describe approaches we developed to reconstitute the human Fe-S cluster assembly machinery in Escherichia coli and to define its remarkable architecture. © 2017 Elsevier Inc. All rights reserved.
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.
Background Noises Versus Intraseasonal Variation Signals: Small vs. Large Convective Cloud Objects From CERES Aqua Observations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

During inactive phases of Madden-Julian Oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep cloud clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large cloud clusters during the MJO life cycle. We analyze the cloud object data from Aqua CERES (Clouds and the Earth's Radiant Energy System) observations between July 2006 and June 2010 for tropical deep convective (DC) and cirrostratus (CS) cloud object types according to the real-time multivariate MJO index, which assigns the tropics to one of the eight MJO phases each day. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The criteria for defining these cloud types are overcast footprints and cloud top pressures less than 400 hPa, but DC has higher cloud optical depths (=10) than those of CS (<10). The size distributions, defined as the footprint numbers as a function of cloud object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large cloud-object diameters due to the reduced/increased numbers of cloud objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all cloud objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of cloud objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and cloud physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS types. These results suggest that the intreseasonal variation signals reside at the large cloud clusters while the small cloud clusters represent the background noises resulting from various types of the tropical waves with different wavenumbers and propagation speeds/directions.
Spectral Entropies as Information-Theoretic Tools for Complex Network Comparison

NASA Astrophysics Data System (ADS)

De Domenico, Manlio; Biamonte, Jacob

2016-10-01

Any physical system can be viewed from the perspective that information is implicitly represented in its state. However, the quantification of this information when it comes to complex networks has remained largely elusive. In this work, we use techniques inspired by quantum statistical mechanics to define an entropy measure for complex networks and to develop a set of information-theoretic tools, based on network spectral properties, such as Rényi q entropy, generalized Kullback-Leibler and Jensen-Shannon divergences, the latter allowing us to define a natural distance measure between complex networks. First, we show that by minimizing the Kullback-Leibler divergence between an observed network and a parametric network model, inference of model parameter(s) by means of maximum-likelihood estimation can be achieved and model selection can be performed with appropriate information criteria. Second, we show that the information-theoretic metric quantifies the distance between pairs of networks and we can use it, for instance, to cluster the layers of a multilayer system. By applying this framework to networks corresponding to sites of the human microbiome, we perform hierarchical cluster analysis and recover with high accuracy existing community-based associations. Our results imply that spectral-based statistical inference in complex networks results in demonstrably superior performance as well as a conceptual backbone, filling a gap towards a network information theory.
Clustering approaches to feature change detection

NASA Astrophysics Data System (ADS)

G-Michael, Tesfaye; Gunzburger, Max; Peterson, Janet

2018-05-01

The automated detection of changes occurring between multi-temporal images is of significant importance in a wide range of medical, environmental, safety, as well as many other settings. The usage of k-means clustering is explored as a means for detecting objects added to a scene. The silhouette score for the clustering is used to define the optimal number of clusters that should be used. For simple images having a limited number of colors, new objects can be detected by examining the change between the optimal number of clusters for the original and modified images. For more complex images, new objects may need to be identified by examining the relative areas covered by corresponding clusters in the original and modified images. Which method is preferable depends on the composition and range of colors present in the images. In addition to describing the clustering and change detection methodology of our proposed approach, we provide some simple illustrations of its application.
The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

NASA Astrophysics Data System (ADS)

Di, Nur Faraidah Muhammad; Satari, Siti Zanariah

2017-05-01

Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model.
Automatic detection of erythemato-squamous diseases using k-means clustering.

PubMed

Ubeyli, Elif Derya; Doğdu, Erdoğan

2010-04-01

A new approach based on the implementation of k-means clustering is presented for automated detection of erythemato-squamous diseases. The purpose of clustering techniques is to find a structure for the given data by finding similarities between data according to data characteristics. The studied domain contained records of patients with known diagnosis. The k-means clustering algorithm's task was to classify the data points, in this case the patients with attribute data, to one of the five clusters. The algorithm was used to detect the five erythemato-squamous diseases when 33 features defining five disease indications were used. The purpose is to determine an optimum classification scheme for this problem. The present research demonstrated that the features well represent the erythemato-squamous diseases and the k-means clustering algorithm's task achieved high classification accuracies for only five erythemato-squamous diseases.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Chongqi; Harbich, Wolfgang; Sementa, Luca

Ligand-protected Au clusters are non-bleaching fluorescence markers in bio- and medical applications. We show that their fluorescence is an intrinsic property of the Au cluster itself. We find a very intense and sharp fluorescence peak located at λ =739.2 nm (1.68 eV) for Au20 clusters in a Ne matrix held at 6 K. The fluorescence reflects the HOMO-LUMO diabatic bandgap of the cluster. The cluster shows a very rich absorption fine structure reminiscent of well defined molecule-like quantum levels. These levels are resolved since Au20 has only one stable isomer (tetrahedral), therefore our sample is mono-disperse in cluster size andmore » conformation. Density-functional theory (DFT) and time-dependent DFT calculations clarify the nature of optical absorptionand predict both main absorption peaks and intrinsic fluorescence in good agreement with experiment.« less
Genetic Diversity and Differentiation of Colletotrichum spp. Isolates Associated with Leguminosae Using Multigene Loci, RAPD and ISSR

PubMed Central

Mahmodi, Farshid; Kadir, J. B.; Puteh, A.; Pourdad, S. S.; Nasehi, A.; Soleimani, N.

2014-01-01

Genetic diversity and differentiation of 50 Colletotrichum spp. isolates from legume crops studied through multigene loci, RAPD and ISSR analysis. DNA sequence comparisons by six genes (ITS, ACT, Tub2, CHS-1, GAPDH, and HIS3) verified species identity of C. truncatum, C. dematium and C. gloeosporiodes and identity C. capsici as a synonym of C. truncatum. Based on the matrix distance analysis of multigene sequences, the Colletotrichum species showed diverse degrees of intera and interspecific divergence (0.0 to 1.4%) and (15.5–19.9), respectively. A multilocus molecular phylogenetic analysis clustered Colletotrichum spp. isolates into 3 well-defined clades, representing three distinct species; C. truncatum, C. dematium and C. gloeosporioides. The ISSR and RAPD and cluster analysis exhibited a high degree of variability among different isolates and permitted the grouping of isolates of Colletotrichum spp. into three distinct clusters. Distinct populations of Colletotrichum spp. isolates were genetically in accordance with host specificity and inconsistent with geographical origins. The large population of C. truncatum showed greater amounts of genetic diversity than smaller populations of C. dematium and C. gloeosporioides species. Results of ISSR and RAPD markers were congruent, but the effective maker ratio and the number of private alleles were greater in ISSR markers. PMID:25288981
Scientific Cluster Deployment and Recovery - Using puppet to simplify cluster management

NASA Astrophysics Data System (ADS)

Hendrix, Val; Benjamin, Doug; Yao, Yushu

2012-12-01

Deployment, maintenance and recovery of a scientific cluster, which has complex, specialized services, can be a time consuming task requiring the assistance of Linux system administrators, network engineers as well as domain experts. Universities and small institutions that have a part-time FTE with limited time for and knowledge of the administration of such clusters can be strained by such maintenance tasks. This current work is the result of an effort to maintain a data analysis cluster (DAC) with minimal effort by a local system administrator. The realized benefit is the scientist, who is the local system administrator, is able to focus on the data analysis instead of the intricacies of managing a cluster. Our work provides a cluster deployment and recovery process (CDRP) based on the puppet configuration engine allowing a part-time FTE to easily deploy and recover entire clusters with minimal effort. Puppet is a configuration management system (CMS) used widely in computing centers for the automatic management of resources. Domain experts use Puppet's declarative language to define reusable modules for service configuration and deployment. Our CDRP has three actors: domain experts, a cluster designer and a cluster manager. The domain experts first write the puppet modules for the cluster services. A cluster designer would then define a cluster. This includes the creation of cluster roles, mapping the services to those roles and determining the relationships between the services. Finally, a cluster manager would acquire the resources (machines, networking), enter the cluster input parameters (hostnames, IP addresses) and automatically generate deployment scripts used by puppet to configure it to act as a designated role. In the event of a machine failure, the originally generated deployment scripts along with puppet can be used to easily reconfigure a new machine. The cluster definition produced in our CDRP is an integral part of automating cluster deployment in a cloud environment. Our future cloud efforts will further build on this work.
Genetic characterisation of Taenia multiceps cysts from ruminants in Greece.

PubMed

Al-Riyami, Shumoos; Ioannidou, Evi; Koehler, Anson V; Hussain, Muhammad H; Al-Rawahi, Abdulmajeed H; Giadinis, Nektarios D; Lafi, Shawkat Q; Papadopoulos, Elias; Jabbar, Abdul

2016-03-01

This study was designed to genetically characterise the larval stage (coenurus) of Taenia multiceps from ruminants in Greece, utilising DNA regions within the cytochrome c oxidase subunit 1 (partial cox1) and NADH dehydrogenase 1 (pnad1) mitochondrial (mt) genes, respectively. A molecular-phylogenetic approach was used to analyse the pcox1 and pnad1 amplicons derived from genomic DNA samples from individual cysts (n=105) from cattle (n=3), goats (n=5) and sheep (n=97). Results revealed five and six distinct electrophoretic profiles for pcox1 and pnad1, respectively, using single-strand conformation polymorphism. Direct sequencing of selected amplicons representing each of these profiles defined five haplotypes each for pcox1 and pnad1, among all 105 isolates. Phylogenetic analysis of individual sequence data for each locus, including a range of well-defined reference sequences, inferred that all isolates of T. multiceps cysts from ruminants in Greece clustered with previously published sequences from different continents. The present study provides a foundation for future large-scale studies on the epidemiology of T. multiceps in ruminants as well as dogs in Greece. Copyright © 2015 Elsevier B.V. All rights reserved.
Understanding ligand effects in gold clusters using mass spectrometry

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

Johnson, Grant E.; Laskin, Julia

This review summarizes recent research on the influence of phosphine ligands on the size, stability, and reactivity of gold clusters synthesized in solution. Sub-nanometer clusters exhibit size- and composition-dependent properties that are unique from those of larger nanoparticles. The highly tunable properties of clusters and their high surface-to-volume ratio make them promising candidates for a variety of technological applications. However, because “each-atom-counts” toward defining cluster properties it is critically important to develop robust synthesis methods to efficiently prepare clusters of predetermined size. For decades phosphines have been known to direct the size-selected synthesis of gold clusters. Despite the preparation ofmore » numerous species it is still not understood how different functional groups at phosphine centers affect the size and properties of gold clusters. Using electrospray ionization mass spectrometry (ESI-MS) it is possible to characterize the effect of ligand substitution on the distribution of clusters formed in solution at defined reaction conditions. In addition, ligand exchange reactions on preformed clusters may be monitored using ESI-MS. Collision induced dissociation (CID) may also be employed to obtain qualitative insight into the fragmentation of mixed ligand clusters and the relative binding energies of differently substituted phosphines. Quantitative ligand binding energies and cluster stability may be determined employing surface induced dissociation (SID) in a custom-built Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR-MS). Rice-Ramsperger-Kassel-Marcus (RRKM) based modeling of the SID data allows dissociation energies and entropy values to be extracted that may be compared with the results of high-level theoretical calculations. The charge reduction and reactivity of atomically precise gold clusters, including partially ligated species generated in the gas-phase by in source CID, on well-defined surfaces may be explored using ion soft landing (SL) in a custom-built instrument combined with in situ time of flight secondary ion mass spectrometry (TOF-SIMS). Jointly, this multipronged experimental approach allows characterization of the full spectrum of relevant phenomena including cluster synthesis, ligand exchange, thermochemistry, surface immobilization, and reactivity. The fundamental insights obtained from this work will facilitate the directed synthesis of gold clusters with predetermined size and properties for specific applications.« less

The kinematics of dense clusters of galaxies. II - The distribution of velocity dispersions

NASA Technical Reports Server (NTRS)

Zabludoff, Ann I.; Geller, Margaret J.; Huchra, John P.; Ramella, Massimo

1993-01-01

From the survey of 31 Abell R above 1 cluster fields within z of 0.02-0.05, we extract 25 dense clusters with velocity dispersions omicron above 300 km/s and with number densities exceeding the mean for the Great Wall of galaxies by one deviation. From the CfA Redshift Survey (in preparation), we obtain an approximately volume-limited catalog of 31 groups with velocity dispersions above 100 km/s and with the same number density limit. We combine these well-defined samples to obtain the distribution of cluster velocity dispersions. The group sample enables us to correct for incompleteness in the Abell catalog at low velocity dispersions. The clusters from the Abell cluster fields populate the high dispersion tail. For systems with velocity dispersions above 700 km/s, approximately the median for R = 1 clusters, the group and cluster abundances are consistent. The combined distribution is consistent with cluster X-ray temperature functions.
Multiscale visual quality assessment for cluster analysis with self-organizing maps

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

PubMed Central

Jabson, Jennifer M.; Bowen, Deborah; Weinberg, Janice; Kroenke, Candyce; Luo, Juhua; Messina, Catherine; Shumaker, Sally; Tindle, Hilary A.

2016-01-01

BACKGROUND Strategies for identifying the most relevant psychosocial predictors in studies of racial/ethnic minority women’s health are limited because they largely exclude cultural influences and they assume that psychosocial predictors are independent. This paper proposes and tests an empirical solution. METHODS Hierarchical cluster analysis, conducted with data from 140,652 Women’s Health Initiative participants, identified clusters among individual psychosocial predictors. Multivariable analyses tested associations between clusters and health outcomes. RESULTS A Social Cluster and a Stress Cluster were identified. The Social Cluster was positively associated with well-being and inversely associated with chronic disease index, and the Stress Cluster was inversely associated with well-being and positively associated with chronic disease index. As hypothesized, the magnitude of association between clusters and outcomes differed by race/ethnicity. CONCLUSIONS By identifying psychosocial clusters and their associations with health, we have taken an important step toward understanding how individual psychosocial predictors interrelate and how empirically formed Stress and Social clusters relate to health outcomes. This study has also demonstrated important insight about differences in associations between these psychosocial clusters and health among racial/ethnic minorities. These differences could signal the best pathways for intervention modification and tailoring. PMID:27279761
Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing

PubMed Central

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

2017-01-01

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

PubMed

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.
A new fast method for inferring multiple consensus trees using k-medoids.

PubMed

Tahiri, Nadia; Willems, Matthieu; Makarenkov, Vladimir

2018-04-05

Gene trees carry important information about specific evolutionary patterns which characterize the evolution of the corresponding gene families. However, a reliable species consensus tree cannot be inferred from a multiple sequence alignment of a single gene family or from the concatenation of alignments corresponding to gene families having different evolutionary histories. These evolutionary histories can be quite different due to horizontal transfer events or to ancient gene duplications which cause the emergence of paralogs within a genome. Many methods have been proposed to infer a single consensus tree from a collection of gene trees. Still, the application of these tree merging methods can lead to the loss of specific evolutionary patterns which characterize some gene families or some groups of gene families. Thus, the problem of inferring multiple consensus trees from a given set of gene trees becomes relevant. We describe a new fast method for inferring multiple consensus trees from a given set of phylogenetic trees (i.e. additive trees or X-trees) defined on the same set of species (i.e. objects or taxa). The traditional consensus approach yields a single consensus tree. We use the popular k-medoids partitioning algorithm to divide a given set of trees into several clusters of trees. We propose novel versions of the well-known Silhouette and Caliński-Harabasz cluster validity indices that are adapted for tree clustering with k-medoids. The efficiency of the new method was assessed using both synthetic and real data, such as a well-known phylogenetic dataset consisting of 47 gene trees inferred for 14 archaeal organisms. The method described here allows inference of multiple consensus trees from a given set of gene trees. It can be used to identify groups of gene trees having similar intragroup and different intergroup evolutionary histories. The main advantage of our method is that it is much faster than the existing tree clustering approaches, while providing similar or better clustering results in most cases. This makes it particularly well suited for the analysis of large genomic and phylogenetic datasets.
A cluster bootstrap for two-loop MHV amplitudes

DOE PAGES

Golden, John; Spradlin, Marcus

2015-02-02

We apply a bootstrap procedure to two-loop MHV amplitudes in planar N=4 super-Yang-Mills theory. We argue that the mathematically most complicated part (the Λ 2 B 2 coproduct component) of the n-particle amplitude is uniquely determined by a simple cluster algebra property together with a few physical constraints (dihedral symmetry, analytic structure, supersymmetry, and well-defined collinear limits). Finally, we present a concise, closed-form expression which manifests these properties for all n.
Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.
Genome-wide identification of novel expression signatures reveal distinct patterns and prevalence of binding motifs for p53, nuclear factor-κB and other signal transcription factors in head and neck squamous cell carcinoma

PubMed Central

Yan, Bin; Yang, Xinping; Lee, Tin-Lap; Friedman, Jay; Tang, Jun; Van Waes, Carter; Chen, Zhong

2007-01-01

Background Differentially expressed gene profiles have previously been observed among pathologically defined cancers by microarray technologies, including head and neck squamous cell carcinomas (HNSCCs). However, the molecular expression signatures and transcriptional regulatory controls that underlie the heterogeneity in HNSCCs are not well defined. Results Genome-wide cDNA microarray profiling of ten HNSCC cell lines revealed novel gene expression signatures that distinguished cancer cell subsets associated with p53 status. Three major clusters of over-expressed genes (A to C) were defined through hierarchical clustering, Gene Ontology, and statistical modeling. The promoters of genes in these clusters exhibited different patterns and prevalence of transcription factor binding sites for p53, nuclear factor-κB (NF-κB), activator protein (AP)-1, signal transducer and activator of transcription (STAT)3 and early growth response (EGR)1, as compared with the frequency in vertebrate promoters. Cluster A genes involved in chromatin structure and function exhibited enrichment for p53 and decreased AP-1 binding sites, whereas clusters B and C, containing cytokine and antiapoptotic genes, exhibited a significant increase in prevalence of NF-κB binding sites. An increase in STAT3 and EGR1 binding sites was distributed among the over-expressed clusters. Novel regulatory modules containing p53 or NF-κB concomitant with other transcription factor binding motifs were identified, and experimental data supported the predicted transcriptional regulation and binding activity. Conclusion The transcription factors p53, NF-κB, and AP-1 may be important determinants of the heterogeneous pattern of gene expression, whereas STAT3 and EGR1 may broadly enhance gene expression in HNSCCs. Defining these novel gene signatures and regulatory mechanisms will be important for establishing new molecular classifications and subtyping, which in turn will promote development of targeted therapeutics for HNSCC. PMID:17498291
An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks.

PubMed

Hosen, A S M Sanwar; Cho, Gi Hwan

2018-05-11

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head's role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks' information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime.
An Energy Centric Cluster-Based Routing Protocol for Wireless Sensor Networks

PubMed Central

Hosen, A. S. M. Sanwar; Cho, Gi Hwan

2018-01-01

Clustering is an effective way to prolong the lifetime of a wireless sensor network (WSN). The common approach is to elect cluster heads to take routing and controlling duty, and to periodically rotate each cluster head’s role to distribute energy consumption among nodes. However, a significant amount of energy dissipates due to control messages overhead, which results in a shorter network lifetime. This paper proposes an energy-centric cluster-based routing mechanism in WSNs. To begin with, cluster heads are elected based on the higher ranks of the nodes. The rank is defined by residual energy and average distance from the member nodes. With the role of data aggregation and data forwarding, a cluster head acts as a caretaker for cluster-head election in the next round, where the ranks’ information are piggybacked along with the local data sending during intra-cluster communication. This reduces the number of control messages for the cluster-head election as well as the cluster formation in detail. Simulation results show that our proposed protocol saves the energy consumption among nodes and achieves a significant improvement in the network lifetime. PMID:29751663
Characterization of a Large Cluster of Influenza A(H1N1)pdm09 Viruses Cross-Resistant to Oseltamivir and Peramivir during the 2013-2014 Influenza Season in Japan

PubMed Central

Takashita, Emi; Kiso, Maki; Fujisaki, Seiichiro; Yokoyama, Masaru; Nakamura, Kazuya; Shirakura, Masayuki; Sato, Hironori; Odagiri, Takato; Kawaoka, Yoshihiro

2015-01-01

Between September 2013 and July 2014, 2,482 influenza 2009 pandemic A(H1N1) [A(H1N1)pdm09] viruses were screened in Japan for the H275Y substitution in their neuraminidase (NA) protein, which confers cross-resistance to oseltamivir and peramivir. We found that a large cluster of the H275Y mutant virus was present prior to the main influenza season in Sapporo/Hokkaido, with the detection rate for this mutant virus reaching 29% in this area. Phylogenetic analysis suggested the clonal expansion of a single mutant virus in Sapporo/Hokkaido. To understand the reason for this large cluster, we examined the in vitro and in vivo properties of the mutant virus. We found that it grew well in cell culture, with growth comparable to that of the wild-type virus. The cluster virus also replicated well in the upper respiratory tract of ferrets and was transmitted efficiently between ferrets by way of respiratory droplets. Almost all recently circulating A(H1N1)pdm09 viruses, including the cluster virus, possessed two substitutions in NA, V241I and N369K, which are known to increase replication and transmission fitness. A structural analysis of NA predicted that a third substitution (N386K) in the NA of the cluster virus destabilized the mutant NA structure in the presence of the V241I and N369K substitutions. Our results suggest that the cluster virus retained viral fitness to spread among humans and, accordingly, caused the large cluster in Sapporo/Hokkaido. However, the mutant NA structure was less stable than that of the wild-type virus. Therefore, once the wild-type virus began to circulate in the community, the mutant virus could not compete and faded out. PMID:25691635
Emotional disorders: cluster 4 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Goldberg, D P; Krueger, R F; Andrews, G; Hobbs, M J

2009-12-01

The extant major psychiatric classifications DSM-IV, and ICD-10, are atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis would be greatly enhanced by an understanding of risk factors and clinical manifestations. In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. This paper considers the validity of the fourth cluster, emotional disorders, within that proposal. We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force, as applied to the cluster of emotional disorders. An emotional cluster of disorders identified using the 11 validators is feasible. Negative affectivity is the defining feature of the emotional cluster. Although there are differences between disorders in the remaining validating criteria, there are similarities that support the feasibility of an emotional cluster. Strong intra-cluster co-morbidity may reflect the action of common risk factors and also shared higher-order symptom dimensions in these emotional disorders. Emotional disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.
Cortical atrophy patterns in early Parkinson's disease patients using hierarchical cluster analysis.

PubMed

Uribe, Carme; Segura, Barbara; Baggio, Hugo Cesar; Abos, Alexandra; Garcia-Diaz, Anna Isabel; Campabadal, Anna; Marti, Maria Jose; Valldeoriola, Francesc; Compta, Yaroslau; Tolosa, Eduard; Junque, Carme

2018-05-01

Cortical brain atrophy detectable with MRI in non-demented advanced Parkinson's disease (PD) is well characterized, but its presence in early disease stages is still under debate. We aimed to investigate cortical atrophy patterns in a large sample of early untreated PD patients using a hypothesis-free data-driven approach. Seventy-seven de novo PD patients and 50 controls from the Parkinson's Progression Marker Initiative database with T1-weighted images in a 3-tesla Siemens scanner were included in this study. Mean cortical thickness was extracted from 360 cortical areas defined by the Human Connectome Project Multi-Modal Parcellation version 1.0, and a hierarchical cluster analysis was performed using Ward's linkage method. A general linear model with cortical thickness data was then used to compare clustering groups using FreeSurfer software. We identified two patterns of cortical atrophy. Compared with controls, patients grouped in pattern 1 (n = 33) were characterized by cortical thinning in bilateral orbitofrontal, anterior cingulate, and lateral and medial anterior temporal gyri. Patients in pattern 2 (n = 44) showed cortical thinning in bilateral occipital gyrus, cuneus, superior parietal gyrus, and left postcentral gyrus, and they showed neuropsychological impairment in memory and other cognitive domains. Even in the early stages of PD, there is evidence of cortical brain atrophy. Neuroimaging clustering analysis is able to detect two subgroups of cortical thinning, one with mainly anterior atrophy, and the other with posterior predominance and worse cognitive performance. Copyright © 2018 Elsevier Ltd. All rights reserved.
Galaxy clusters in simulations of the local Universe: a matter of constraints

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.; Tempel, Elmo

2018-06-01

To study the full formation and evolution history of galaxy clusters and their population, high-resolution simulations of the latter are flourishing. However, comparing observed clusters to the simulated ones on a one-to-one basis to refine the models and theories down to the details is non-trivial. The large variety of clusters limits the comparisons between observed and numerical clusters. Simulations resembling the local Universe down to the cluster scales permit pushing the limit. Simulated and observed clusters can be matched on a one-to-one basis for direct comparisons provided that clusters are well reproduced besides being in the proper large-scale environment. Comparing random and local Universe-like simulations obtained with differently grouped observational catalogues of peculiar velocities, this paper shows that the grouping scheme used to remove non-linear motions in the catalogues that constrain the simulations affects the quality of the numerical clusters. With a less aggressive grouping scheme - galaxies still falling on to clusters are preserved - combined with a bias minimization scheme, the mass of the dark matter haloes, simulacra for five local clusters - Virgo, Centaurus, Coma, Hydra, and Perseus - is increased by 39 per cent closing the gap with observational mass estimates. Simulacra are found on average in 89 per cent of the simulations, an increase of 5 per cent with respect to the previous grouping scheme. The only exception is Perseus. Since the Perseus-Pisces region is not well covered by the used peculiar velocity catalogue, the latest release lets us foresee a better simulacrum for Perseus in a near future.
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.
Task shifting of frontline community health workers for cardiovascular risk reduction: design and rationale of a cluster randomised controlled trial (DISHA study) in India.

PubMed

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

2016-03-15

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

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

Odenkirchen, Michael; Grebel, Eva K.; Rockosi, Constance M.

2000-12-01

We report the discovery of two well-defined tidal tails emerging from the sparse remote globular cluster Palomar 5. These tails stretch out symmetrically to both sides of the cluster in the direction of constant Galactic latitude and subtend an angle of 2.6{sup o} on the sky. The tails have been detected in commissioning data of the Sloan Digital Sky Survey (SDSS), providing deep five-color photometry in a 2.5{sup o}-wide band along the equator. The stars in the tails make up a substantial part ({approx} 1/3) of the current total population of cluster stars in the magnitude interval 19.5 {le} i*more » {le} 22.0. This reveals that the cluster is subject to heavy mass loss. The orientation of the tails provides an important key for the determination of the cluster's Galactic orbit.« less
Catalysis by clusters with precise numbers of atoms

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

Tyo, Eric C.; Vajda, Stefan

2015-07-03

Clusters that contain only a small number of atoms can exhibit unique and often unexpected properties. The clusters are of particular interest in catalysis because they can act as individual active sites, and minor changes in size and composition – such as the addition or removal of a single atom – can have a substantial influence on the activity and selectivity of a reaction. Here we review recent progress in the synthesis, characterization and catalysis of well-defined sub-nanometre clusters. We examine work on size-selected supported clusters in ultra-high vacuum environments and under realistic reaction conditions, and explore the use ofmore » computational methods to provide a mechanistic understanding of their catalytic properties. We also highlight the potential of size-selected clusters to provide insights into important catalytic processes and their use in the development of novel catalytic systems.« less
The geometry of chaotic dynamics — a complex network perspective

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

A cluster-based strategy for assessing the overlap between large chemical libraries and its application to a recent acquisition.

PubMed

Engels, Michael F M; Gibbs, Alan C; Jaeger, Edward P; Verbinnen, Danny; Lobanov, Victor S; Agrafiotis, Dimitris K

2006-01-01

We report on the structural comparison of the corporate collections of Johnson & Johnson Pharmaceutical Research & Development (JNJPRD) and 3-Dimensional Pharmaceuticals (3DP), performed in the context of the recent acquisition of 3DP by JNJPRD. The main objective of the study was to assess the druglikeness of the 3DP library and the extent to which it enriched the chemical diversity of the JNJPRD corporate collection. The two databases, at the time of acquisition, collectively contained more than 1.1 million compounds with a clearly defined structural description. The analysis was based on a clustering approach and aimed at providing an intuitive quantitative estimate and visual representation of this enrichment. A novel hierarchical clustering algorithm called divisive k-means was employed in combination with Kelley's cluster-level selection method to partition the combined data set into clusters, and the diversity contribution of each library was evaluated as a function of the relative occupancy of these clusters. Typical 3DP chemotypes enriching the diversity of the JNJPRD collection were catalogued and visualized using a modified maximum common substructure algorithm. The joint collection of JNJPRD and 3DP compounds was also compared to other databases of known medicinally active or druglike compounds. The potential of the methodology for the analysis of very large chemical databases is discussed.
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.
Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005-2010 data from ten French slaughterhouses.

PubMed

Dupuy, Céline; Morignat, Eric; Maugey, Xavier; Vinard, Jean-Luc; Hendrikx, Pascal; Ducrot, Christian; Calavas, Didier; Gay, Emilie

2013-04-30

The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging.The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data. Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer's lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues. The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases.
Formation of large-scale structure from cosmic-string loops and cold dark matter

NASA Technical Reports Server (NTRS)

Melott, Adrian L.; Scherrer, Robert J.

1987-01-01

Some results from a numerical simulation of the formation of large-scale structure from cosmic-string loops are presented. It is found that even though G x mu is required to be lower than 2 x 10 to the -6th (where mu is the mass per unit length of the string) to give a low enough autocorrelation amplitude, there is excessive power on smaller scales, so that galaxies would be more dense than observed. The large-scale structure does not include a filamentary or connected appearance and shares with more conventional models based on Gaussian perturbations the lack of cluster-cluster correlation at the mean cluster separation scale as well as excessively small bulk velocities at these scales.
Strong influence of variable treatment on the performance of numerically defined ecological regions.

PubMed

Snelder, Ton; Lehmann, Anthony; Lamouroux, Nicolas; Leathwick, John; Allenbach, Karin

2009-10-01

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale "sub-domains" defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.
Reduction Potentials of [FeFe]-Hydrogenase Accessory Iron-Sulfur Clusters Provide Insights into the Energetics of Proton Reduction Catalysis.

PubMed

Artz, Jacob H; Mulder, David W; Ratzloff, Michael W; Lubner, Carolyn E; Zadvornyy, Oleg A; LeVan, Axl X; Williams, S Garrett; Adams, Michael W W; Jones, Anne K; King, Paul W; Peters, John W

2017-07-19

An [FeFe]-hydrogenase from Clostridium pasteurianum, CpI, is a model system for biological H 2 activation. In addition to the catalytic H-cluster, CpI contains four accessory iron-sulfur [FeS] clusters in a branched series that transfer electrons to and from the active site. In this work, potentiometric titrations have been employed in combination with electron paramagnetic resonance (EPR) spectroscopy at defined electrochemical potentials to gain insights into the role of the accessory clusters in catalysis. EPR spectra collected over a range of potentials were deconvoluted into individual components attributable to the accessory [FeS] clusters and the active site H-cluster, and reduction potentials for each cluster were determined. The data suggest a large degree of magnetic coupling between the clusters. The distal [4Fe-4S] cluster is shown to have a lower reduction potential (∼ < -450 mV) than the other clusters, and molecular docking experiments indicate that the physiological electron donor, ferredoxin (Fd), most favorably interacts with this cluster. The low reduction potential of the distal [4Fe-4S] cluster thermodynamically restricts the Fd ox /Fd red ratio at which CpI can operate, consistent with the role of CpI in recycling Fd red that accumulates during fermentation. Subsequent electron transfer through the additional accessory [FeS] clusters to the H-cluster is thermodynamically favorable.
A meteor ablation-cluster ion atmospheric sodium theory

NASA Technical Reports Server (NTRS)

Richter, E. S.; Sechrist, C. F., Jr.

1979-01-01

Neutral and ionic forms of sodium form narrow, well-defined layers which peak in the 90-95 km altitude region at midlatitudes. A new theory for the sodium layer is presented, which is found to be in good agreement with existing atmospheric observations as well as available laboratory measurements of rate constants. The layer is believed to result naturally from a meteor ablation source over a chemical sink with vertical transport of Na(+) playing an important role in the layer shape and variation. While the neutral chemistry is believed to consist of chemical equilibrium between Na and NaO, the ion chemistry departs from earlier studies and considers a cluster ion scheme. It is possible that higher-order cluster ions of sodium play a role in the formation of aerosols, through attachment or ion-induced nucleation processes.
Atomically precise (catalytic) particles synthesized by a novel cluster deposition instrument

DOE PAGES

Yin, C.; Tyo, E.; Kuchta, K.; ...

2014-05-06

Here, we report a new high vacuum instrument which is dedicated to the preparation of well-defined clusters supported on model and technologically relevant supports for catalytic and materials investigations. The instrument is based on deposition of size selected metallic cluster ions that are produced by a high flux magnetron cluster source. Furthermore, we maximize the throughput of the apparatus by collecting and focusing ions utilizing a conical octupole ion guide and a linear ion guide. The size selection is achieved by a quadrupole mass filter. The new design of the sample holder provides for the preparation of multiple samples onmore » supports of various sizes and shapes in one session. After cluster deposition onto the support of interest, samples will be taken out of the chamber for a variety of testing and characterization.« less
Selective Nanoscale Mass Transport across Atomically Thin Single Crystalline Graphene Membranes.

PubMed

Kidambi, Piran R; Boutilier, Michael S H; Wang, Luda; Jang, Doojoon; Kim, Jeehwan; Karnik, Rohit

2017-05-01

Atomically thin single crystals, without grain boundaries and associated defect clusters, represent ideal systems to study and understand intrinsic defects in materials, but probing them collectively over large area remains nontrivial. In this study, the authors probe nanoscale mass transport across large-area (≈0.2 cm 2 ) single-crystalline graphene membranes. A novel, polymer-free picture frame assisted technique, coupled with a stress-inducing nickel layer is used to transfer single crystalline graphene grown on silicon carbide substrates to flexible polycarbonate track etched supports with well-defined cylindrical ≈200 nm pores. Diffusion-driven flow shows selective transport of ≈0.66 nm hydrated K + and Cl - ions over ≈1 nm sized small molecules, indicating the presence of selective sub-nanometer to nanometer sized defects. This work presents a framework to test the barrier properties and intrinsic quality of atomically thin materials at the sub-nanometer to nanometer scale over technologically relevant large areas, and suggests the potential use of intrinsic defects in atomically thin materials for molecular separations or desalting. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The replication domain model: regulating replicon firing in the context of large-scale chromosome architecture.

PubMed

Pope, Benjamin D; Gilbert, David M

2013-11-29

The "Replicon Theory" of Jacob, Brenner, and Cuzin has reliably served as the paradigm for regulating the sites where individual replicons initiate replication. Concurrent with the replicon model was Taylor's demonstration that plant and animal chromosomes replicate segmentally in a defined temporal sequence, via cytologically defined units too large to be accounted for by a single replicon. Instead, there seemed to be a program to choreograph when chromosome units replicate during S phase, executed by initiation at clusters of individual replicons within each segment. Here, we summarize recent molecular evidence for the existence of such units, now known as "replication domains", and discuss how the organization of large chromosomes into structural units has added additional layers of regulation to the original replicon model. Copyright © 2012 Elsevier Ltd. All rights reserved.
UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring

PubMed Central

Ammad Uddin, Mohammad; Mansour, Ali; Le Jeune, Denis; Ayaz, Mohammad; Aggoune, el-Hadi M.

2018-01-01

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use. PMID:29439496
UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring.

PubMed

Uddin, Mohammad Ammad; Mansour, Ali; Jeune, Denis Le; Ayaz, Mohammad; Aggoune, El-Hadi M

2018-02-11

In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters. Neither of these options is suitable in our scenario due to the factors like dynamic data collection, the strict targeted area required to be scanned, unavailability of a large number of nodes, dynamic path of the UAV, and most importantly, none of these are known in advance. The contribution of this paper is the formation of dynamic runtime clusters of field sensors by considering the above mentioned factors. Furthermore a mechanism (Bayesian classifier) is defined to select best node as cluster head. The proposed system is validated through simulation results, lab and infield experiments using concept devices. The obtained results are encouraging, especially in terms of deployment time, energy, efficiency, throughput and ease of use.
The Next Generation Virgo Cluster Survey (NGVS). XXV. Fiducial Panchromatic Colors of Virgo Core Globular Clusters and Their Comparison to Model Predictions

NASA Astrophysics Data System (ADS)

Powalka, Mathieu; Lançon, Ariane; Puzia, Thomas H.; Peng, Eric W.; Liu, Chengze; Muñoz, Roberto P.; Blakeslee, John P.; Côté, Patrick; Ferrarese, Laura; Roediger, Joel; Sánchez-Janssen, Rúben; Zhang, Hongxin; Durrell, Patrick R.; Cuillandre, Jean-Charles; Duc, Pierre-Alain; Guhathakurta, Puragra; Gwyn, S. D. J.; Hudelot, Patrick; Mei, Simona; Toloba, Elisa

2016-11-01

The central region of the Virgo Cluster of galaxies contains thousands of globular clusters (GCs), an order of magnitude more than the number of clusters found in the Local Group. Relics of early star formation epochs in the universe, these GCs also provide ideal targets to test our understanding of the spectral energy distributions (SEDs) of old stellar populations. Based on photometric data from the Next Generation Virgo Cluster Survey (NGVS) and its near-infrared counterpart NGVS-IR, we select a robust sample of ≈ 2000 GCs with excellent photometry and tha span the full range of colors present in the Virgo core. The selection exploits the well-defined locus of GCs in the uiK diagram and the fact that the GCs are marginally resolved in the images. We show that the GCs define a narrow sequence in five-dimensional color space, with limited but real dispersion around the mean sequence. The comparison of these SEDs with the predictions of 11 widely used population synthesis models highlights differences between the models and also shows that no single model adequately matches the data in all colors. We discuss possible causes for some of these discrepancies. Forthcoming papers of this series will examine how best to estimate photometric metallicities in this context, and compare the Virgo GC colors with those in other environments.
Conceptual clusters in figurative language production.

PubMed

Corts, Daniel P; Meyers, Kristina

2002-07-01

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

NASA Astrophysics Data System (ADS)

Wang, Hongbo; Zhao, Laijun

2018-02-01

China's Beijing-Tianjin-Hebei (BTH) region suffers from the country's worst air pollution. The problem has caused widespread concern both at home and abroad. Based on long-term and massive data mining of PM2.5 and PM10 concentration, we found that these pollutants showed similar variations in four seasons, but the most severe pollution was in winter. Through cluster analysis of the winter daily average concentration (DAC) of the two pollutants, we defined regions with similar variations in pollutant concentrations in winter. For the most polluted cities in BTH, the relationship between correlation coefficients for winter DAC and the distance between cities revealed that PM2.5 has regional, large-scale characteristics, with concentrated outbreaks, whereas PM10 has local, small-scale characteristics, with outbreaks at multiple locations. By selecting the key cities with the strongest linear relationship between the pollutant's DAC of each city and the daily individual air quality index values of the BTH region and through cluster analysis on the correlations between the pollutant DACs of the key cities, we defined regional divisions suitable for Joint Prevention and Control of Atmospheric Pollution (JPCAP) program to control PM2.5 and PM10. Comprehensively considering the degree of influence of regional atmospheric pollution control (RAPC) on air quality in BTH, as well as the elasticity and urgency of RAPC, we defined the control grades of the JPCAP regions. We found both the regions and corresponding control grades were consistent for PM2.5 and PM10. The thinking and methods of atmospheric pollution control we proposed will have broad significance for implementation of RAPC in other regions around the world.
Large longitudinal spin alignment generated in inelastic nuclear reactions

NASA Astrophysics Data System (ADS)

Hoff, D. E. M.; Potel, G.; Brown, K. W.; Charity, R. J.; Pruitt, C. D.; Sobotka, L. G.; Webb, T. B.; Roeder, B.; Saastamoinen, A.

2018-05-01

Large longitudinal spin alignment of E /A =24 MeV 7Li projectiles inelastically excited by Be, C, and Al targets was observed when the latter remain in their ground state. This alignment is a consequence of an angular-momentum-excitation-energy mismatch, which is well described by a DWBA cluster-model (α +t ). The longitudinal alignment of several other systems is also well described by DWBA calculations, including one where a cluster model is inappropriate, demonstrating that the alignment mechanism is a more general phenomenon. Predictions are made for inelastic excitation of 12C for beam energies above and below the mismatch threshold.
Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2018-03-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2}). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3}) and the level sets of the Gaussian free field ({d≥ 3}). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.
Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2017-12-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2} ). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3} ) and the level sets of the Gaussian free field ({d≥ 3} ). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.
An evaluation of edge effects in nutritional accessibility and availability measures: a simulation study

PubMed Central

2010-01-01

Background This paper addresses the statistical use of accessibility and availability indices and the effect of study boundaries on these measures. The measures are evaluated via an extensive simulation based on cluster models for local outlet density. We define outlet to mean either food retail store (convenience store, supermarket, gas station) or restaurant (limited service or full service restaurants). We designed a simulation whereby a cluster outlet model is assumed in a large study window and an internal subset of that window is constructed. We performed simulations on various criteria including one scenario representing an urban area with 2000 outlets as well as a non-urban area simulated with only 300 outlets. A comparison is made between estimates obtained with the full study area and estimates using only the subset area. This allows the study of the effect of edge censoring on accessibility measures. Results The results suggest that considerable bias is found at the edges of study regions in particular for accessibility measures. Edge effects are smaller for availability measures (when not smoothed) and also for short range accessibility Conclusions It is recommended that any study utilizing these measures should correct for edge effects. The use of edge correction via guard areas is recommended and the avoidance of large range distance-based accessibility measures is also proposed. PMID:20663199
Multiple object redshift determinations in clusters of galaxies using OCTOPUS

NASA Astrophysics Data System (ADS)

Mazure, A.; Proust, D.; Sodre, L.; Capelato, H. V.; Lund, G.

1988-04-01

The ESO multiobject facility, Octopus, was used to observe a sample of galaxy clusters such as SC2008-565 in an attempt to collect a large set of individual radial velocities. A dispersion of 114 A/mm was used, providing spectral coverage from 3800 to 5180 A. Octopus was found to be a well-adapted instrument for the rapid and simultaneous determination of redshifts in cataloged galaxy clusters.

Multiple object redshift determinations in clusters of galaxies using OCTOPUS

NASA Astrophysics Data System (ADS)

Mazure, A.; Proust, D.; Sodre, L.; Lund, G.; Capelato, H.

1987-03-01

The ESO multiobject facility, Octopus, was used to observe a sample of galaxy clusters such as SC2008-565 in an attempt to collect a large set of individual radial velocities. A dispersion of 114 A/mm was used, providing spectral coverage from 3800 to 5180 A. Octopus was found to be a well-adapted instrument for the rapid and simultaneous determination of redshifts in cataloged galaxy clusters.
Electric-field-induced association of colloidal particles

NASA Astrophysics Data System (ADS)

Fraden, Seth; Hurd, Alan J.; Meyer, Robert B.

1989-11-01

Dilute suspensions of micron diameter dielectric spheres confined to two dimensions are induced to aggregate linearly by application of an electric field. The growth of the average cluster size agrees well with the Smoluchowski equation, but the evolution of the measured cluster size distribution exhibits significant departures from theory at large times due to the formation of long linear clusters which effectively partition space into isolated one-dimensional strips.
Striking Phenotypic Variation yet Low Genetic Differentiation in Sympatric Lake Trout (Salvelinus namaycush)

PubMed Central

Coon, Andrew; Carson, Robert; Debes, Paul V.

2016-01-01

The study of population differentiation in the context of ecological speciation is commonly assessed using populations with obvious discreteness. Fewer studies have examined diversifying populations with occasional adaptive variation and minor reproductive isolation, so factors impeding or facilitating the progress of early stage differentiation are less understood. We detected non-random genetic structuring in lake trout (Salvelinus namaycush) inhabiting a large, pristine, postglacial lake (Mistassini Lake, Canada), with up to five discernible genetic clusters having distinctions in body shape, size, colouration and head shape. However, genetic differentiation was low (FST = 0.017) and genetic clustering was largely incongruent between several population- and individual-based clustering approaches. Genotype- and phenotype-environment associations with spatial habitat, depth and fish community structure (competitors and prey) were either inconsistent or weak. Striking morphological variation was often more continuous within than among defined genetic clusters. Low genetic differentiation was a consequence of relatively high contemporary gene flow despite large effective population sizes, not migration-drift disequilibrium. Our results suggest a highly plastic propensity for occupying multiple habitat niches in lake trout and a low cost of morphological plasticity, which may constrain the speed and extent of adaptive divergence. We discuss how factors relating to niche conservatism in this species may also influence how plasticity affects adaptive divergence, even where ample ecological opportunity apparently exists. PMID:27680019
On Identifying Clusters Within the C-type Asteroids of the Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Poole, Renae; Ziffer, J.; Harvell, T.

2012-10-01

We applied AutoClass, a data mining technique based upon Bayesian Classification, to C-group asteroid colors in the Sloan Digital Sky Survey (SDSS). Previous taxonomic studies relied mostly on Principal Component Analysis (PCA) to differentiate asteroids within the C-group (e.g. B, G, F, Ch, Cg and Cb). AutoClass's advantage is that it calculates the most probable classification for us, removing the human factor from this part of the analysis. In our results, AutoClass divided the C-groups into two large classes and six smaller classes. The two large classes (n=4974 and 2033, respectively) display distinct regions with some overlap in color-vs-color plots. Each cluster's average spectrum is compared to 'typical' spectra of the C-group subtypes as defined by Tholen (1989) and each cluster's members are evaluated for consistency with previous taxonomies. Of the 117 asteroids classified as B-type in previous taxonomies, only 12 were found with SDSS colors that matched our criteria of having less than 0.1 magnitude error in u and 0.05 magnitude error in g, r, i, and z colors. Although this is a relatively small group, 11 of the 12 B-types were placed by AutoClass in the same cluster. By determining the C-group sub-classifications in the large SDSS database, this research furthers our understanding of the stratigraphy and composition of the main-belt.
Coarsening of protein clusters on subcellular drops exhibits strong and sudden size selectivity

NASA Astrophysics Data System (ADS)

Brown, Aidan; Rutenberg, Andrew

2015-03-01

Autophagy is an important process for the degradation of cellular components, with receptor proteins targeting substrates to downstream autophagy machinery. An important question is how receptor protein interactions lead to their selective accumulation on autophagy substrates. Receptor proteins have recently been observed in clusters, raising the possibility that clustering could affect autophagy selectivity. We investigate the clustering dynamics of the autophagy receptor protein NBR1. In addition to standard receptor protein domains, NBR1 has a ``J'' domain that anchors it to membranes, and a coiled-coil domain that enhances self-interaction. We model coarsening clusters of NBR1 on the surfaces of a polydisperse collection of drops, representing organelles. Despite the disconnected nature of the drop surfaces, we recover dynamical scaling of cluster sizes. Significantly, we find that at a well-defined time after coarsening begins, clusters evaporate from smaller drops and grow on larger drops. Thus, coarsening-driven size selection will localize protein clusters to larger substrates, leaving smaller substrates without clusters. This provides a possible physical mechanism for autophagy selectivity, and can explain reports of size selection during peroxisome degradation.
Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.
Strong collective attraction in colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2009-01-01

It is shown that in a cluster of many colloids, trapped at a liquid-air interface, the well-known vertical-force-induced pairwise logarithmic attraction changes to a strongly enhanced power-law attraction. In large two-dimensional clusters, the attraction energy scales as the inverse square of the distance between colloids. The enhancement is given by the ratio eta = (square of the capillary length) / (interface surface area per colloid) and can be as large as 10;{5} . This explains why a very small vertical force on colloids, which is too weak to bring two of them together, can stabilize many-body structures on a liquid-air interface. The profile of a cluster is shown to consist of a large slow collective envelope modulated by a fast low-amplitude perturbation due to individual colloids. A closed equation for the slow envelope, which incorporates an arbitrary power-law repulsion between colloids, is derived. For example, this equation is solved for a large circular cluster with the hard-core colloid repulsion. It is suggested that the predicted effect is responsible for mysterious stabilization of colloidal structures observed in experiments on a surface of isotropic liquid and nematic liquid crystal.
MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

PubMed

The, Matthew; Käll, Lukas

2016-03-04

Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).
New VVV Survey Globular Cluster Candidates in the Milky Way Bulge

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

Minniti, Dante; Gómez, Matías; Geisler, Douglas

It is likely that a number of Galactic globular clusters remain to be discovered, especially toward the Galactic bulge. High stellar density combined with high and differential interstellar reddening are the two major problems for finding globular clusters located toward the bulge. We use the deep near-IR photometry of the VISTA Variables in the Vía Láctea (VVV) Survey to search for globular clusters projected toward the Galactic bulge, and hereby report the discovery of 22 new candidate globular clusters. These objects, detected as high density regions in our maps of bulge red giants, are confirmed as globular cluster candidates bymore » their color–magnitude diagrams. We provide their coordinates as well as their near-IR color–magnitude diagrams, from which some basic parameters are derived, such as reddenings and heliocentric distances. The color–magnitude diagrams reveal well defined red giant branches in all cases, often including a prominent red clump. The new globular cluster candidates exhibit a variety of extinctions (0.06 < A {sub Ks} < 2.77) and distances (5.3 < D < 9.5 kpc). We also classify the globular cluster candidates into 10 metal-poor and 12 metal-rich clusters, based on the comparison of their color–magnitude diagrams with those of known globular clusters also observed by the VVV Survey. Finally, we argue that the census for Galactic globular clusters still remains incomplete, and that many more candidate globular clusters (particularly the low luminosity ones) await to be found and studied in detail in the central regions of the Milky Way.« less
Evaluating tests of virialization and substructure using galaxy clusters in the ORELSE survey

NASA Astrophysics Data System (ADS)

Rumbaugh, N.; Lemaux, B. C.; Tomczak, A. R.; Shen, L.; Pelliccia, D.; Lubin, L. M.; Kocevski, D. D.; Wu, P.-F.; Gal, R. R.; Mei, S.; Fassnacht, C. D.; Squires, G. K.

2018-07-01

We evaluated the effectiveness of different indicators of cluster virialization using 12 large-scale structures in the Observations of Redshift Evolution in Large-Scale Environments survey spanning from 0.7
Grain Cluster Microstructure and Grain Boundary Character Distribution in Alloy 690

NASA Astrophysics Data System (ADS)

Xia, Shuang; Zhou, Bangxin; Chen, Wenjue

2009-12-01

The effects of thermal-mechanical processing (TMP) on microstructure evolution during recrystallization and grain boundary character distribution (GBCD) in aged Alloy 690 were investigated by the electron backscatter diffraction (EBSD) technique and optical microscopy. The original grain boundaries of the deformed microstructure did not play an important role in the manipulation of the proportion of the Σ3 n ( n = 1, 2, 3…) type boundaries. Instead, the grain cluster formed by multiple twinning starting from a single nucleus during recrystallization was the key microstructural feature affecting the GBCD. All of the grains in this kind of cluster had Σ3 n mutual misorientations regardless of whether they were adjacent. A large grain cluster containing 91 grains was found in the sample after a small-strain (5 pct) and a high-temperature (1100 °C) recrystallization anneal, and twin relationships up to the ninth generation (Σ39) were found in this cluster. The ratio of cluster size over grain size (including all types of boundaries as defining individual grains) dictated the proportion of Σ3 n boundaries.
Genetic approaches of the Fe-S cluster biogenesis process in bacteria: Historical account, methodological aspects and future challenges.

PubMed

Py, Béatrice; Barras, Frédéric

2015-06-01

Since their discovery in the 50's, Fe-S cluster proteins have attracted much attention from chemists, biophysicists and biochemists. However, in the 80's they were joined by geneticists who helped to realize that in vivo maturation of Fe-S cluster bound proteins required assistance of a large number of factors defining complex multi-step pathways. The question of how clusters are formed and distributed in vivo has since been the focus of much effort. Here we review how genetics in discovering genes and investigating processes as they unfold in vivo has provoked seminal advances toward our understanding of Fe-S cluster biogenesis. The power and limitations of genetic approaches are discussed. As a final comment, we argue how the marriage of classic strategies and new high-throughput technologies should allow genetics of Fe-S cluster biology to be even more insightful in the future. This article is part of a Special Issue entitled: Fe/S proteins: Analysis, structure, function, biogenesis and diseases. Copyright © 2015 Elsevier B.V. All rights reserved.
Numerical determination of the interfacial energy and nucleation barrier of curved solid-liquid interfaces in binary systems

NASA Astrophysics Data System (ADS)

Kundin, Julia; Choudhary, Muhammad Ajmal

2016-07-01

The phase-field crystal (PFC) technique is a widely used approach for modeling crystal growth phenomena with atomistic resolution on mesoscopic time scales. We use a two-dimensional PFC model for a binary system based on the work of Elder et al. [Phys. Rev. B 75, 064107 (2007), 10.1103/PhysRevB.75.064107] to study the effect of the curved, diffuse solid-liquid interface on the interfacial energy as well as the nucleation barrier. The calculation of the interfacial energy and the nucleation barrier certainly depends on the proper definition of the solid-liquid dividing surface and the corresponding nucleus size. We define the position of the sharp interface at which the interfacial energy is to be evaluated by using the concept of equimolar dividing surface (re) and the minimization of the interfacial energy (rs). The comparison of the results based on both radii shows that the difference re-rs is always positive and has a limit for large cluster sizes which is comparable to the Tolman length. Furthermore, we found the real nucleation barrier for small cluster sizes, which is defined as a function of the radius rs, and compared it with the classical nucleation theory. The simulation results also show that the extracted interfacial energy as function of both radii is independent of system size, and this dependence can be reasonably described by the nonclassical Tolman formula with a positive Tolman length.
The HST Large Programme on ω Centauri. II. Internal Kinematics

NASA Astrophysics Data System (ADS)

Bellini, Andrea; Libralato, Mattia; Bedin, Luigi R.; Milone, Antonino P.; van der Marel, Roeland P.; Anderson, Jay; Apai, Dániel; Burgasser, Adam J.; Marino, Anna F.; Rees, Jon M.

2018-01-01

In this second installment of the series, we look at the internal kinematics of the multiple stellar populations of the globular cluster ω Centauri in one of the parallel Hubble Space Telescope (HST) fields, located at about 3.5 half-light radii from the center of the cluster. Thanks to the over 15 yr long baseline and the exquisite astrometric precision of the HST cameras, well-measured stars in our proper-motion catalog have errors as low as ∼10 μas yr‑1, and the catalog itself extends to near the hydrogen-burning limit of the cluster. We show that second-generation (2G) stars are significantly more radially anisotropic than first-generation (1G) stars. The latter are instead consistent with an isotropic velocity distribution. In addition, 1G stars have excess systemic rotation in the plane of the sky with respect to 2G stars. We show that the six populations below the main-sequence (MS) knee identified in our first paper are associated with the five main population groups recently isolated on the upper MS in the core of cluster. Furthermore, we find both 1G and 2G stars in the field to be far from being in energy equipartition, with {η }1{{G}}=-0.007+/- 0.026 for the former and {η }2{{G}}=0.074+/- 0.029 for the latter, where η is defined so that the velocity dispersion {σ }μ scales with stellar mass as {σ }μ \\propto {m}-η . The kinematical differences reported here can help constrain the formation mechanisms for the multiple stellar populations in ω Centauri and other globular clusters. We make our astro-photometric catalog publicly available.
Users matter : multi-agent systems model of high performance computing cluster users.

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

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less
Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings.

PubMed

Eyler, Lauren; Hubbard, Alan; Juillard, Catherine

2016-10-01

Low and middle-income countries (LMICs) and the world's poor bear a disproportionate share of the global burden of injury. Data regarding disparities in injury are vital to inform injury prevention and trauma systems strengthening interventions targeted towards vulnerable populations, but are limited in LMICs. We aim to facilitate injury disparities research by generating a standardized methodology for assessing economic status in resource-limited country trauma registries where complex metrics such as income, expenditures, and wealth index are infeasible to assess. To address this need, we developed a cluster analysis-based algorithm for generating simple population-specific metrics of economic status using nationally representative Demographic and Health Surveys (DHS) household assets data. For a limited number of variables, g, our algorithm performs weighted k-medoids clustering of the population using all combinations of g asset variables and selects the combination of variables and number of clusters that maximize average silhouette width (ASW). In simulated datasets containing both randomly distributed variables and "true" population clusters defined by correlated categorical variables, the algorithm selected the correct variable combination and appropriate cluster numbers unless variable correlation was very weak. When used with 2011 Cameroonian DHS data, our algorithm identified twenty economic clusters with ASW 0.80, indicating well-defined population clusters. This economic model for assessing health disparities will be used in the new Cameroonian six-hospital centralized trauma registry. By describing our standardized methodology and algorithm for generating economic clustering models, we aim to facilitate measurement of health disparities in other trauma registries in resource-limited countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
How do obligate parasites evolve? A multi-gene phylogenetic analysis of downy mildews.

PubMed

Göker, Markus; Voglmayr, Hermann; Riethmüller, Alexandra; Oberwinkler, Franz

2007-02-01

Plant parasitism has independently evolved as a nutrition strategy in both true fungi and Oomycetes (stramenopiles). A large number of species within phytopathogenic Oomycetes, the so-called downy mildews, are defined as obligate biotrophs since they have not, to date, been cultured on any artificial medium. Other genera like Phytophthora and Pythium can in general be cultured on standard or non-standard agar media. Within all three groups there are many important plant pathogens responsible for severe economic losses as well as damage to natural ecosystems. Although they are important model systems to elucidate the evolution of obligate parasites, the phylogenetic relationships between these genera have not been clearly resolved. Based on the most comprehensive sampling of downy mildew genera to date and a representative sample of Phytophthora subgroups, we inferred the phylogenetic relationships from a multi-gene dataset containing both coding and non-coding nuclear and mitochondrial loci. Phylogenetic analyses were conducted under several optimality criteria and the results were largely consistent between all the methods applied. Strong support is achieved for monophyly of a clade comprising both the genus Phytophthora and the obligate biotrophic species. The facultatively parasitic genus Phytophthora is shown to be at least partly paraphyletic. Monophyly of a cluster nested within Phytophthora containing all obligate parasites is strongly supported. Within the obligate biotrophic downy mildews, four morphologically or ecologically well-defined subgroups receive statistical support: (1) A cluster containing all species with brownish-violet conidiosporangia, i.e., the genera Peronospora and Pseudoperonospora; (2) a clade comprising the genera with vesicular to pyriform haustoria (Basidiophora, Benua, Bremia, Paraperonospora, Plasmopara, Plasmoverna, Protobremia); (3) a group containing species included in Hyaloperonospora and Perofascia which almost exclusively infect Brassicaceae; (4) a clade including the grass parasites Viennotia oplismeni and Graminivora graminicola. Phylogenetic relationships between these four clades are not clearly resolved, and neither is the position of Sclerospora graminicola within the downy mildews. Character analysis indicates an evolutionary scenario of gradually increasing adaptation to plant parasitism in Peronosporales and that at least the most important of these adaptive steps occurred only once, including major host shifts within downy mildews.
A Multivariate Model and Analysis of Competitive Strategy in the U.S. Hardwood Lumber Industry

Treesearch

Robert J. Bush; Steven A. Sinclair

1991-01-01

Business-level competitive strategy in the hardwood lumber industry was modeled through the identification of strategic groups among large U.S. hardwood lumber producers. Strategy was operationalized using a measure based on the variables developed by Dess and Davis (1984). Factor and cluster analyses were used to define strategic groups along the dimensions of cost...
Defining the transcriptome assembly and its use for genome dynamics and transcriptome profiling studies in pigeonpea (Cajanus cajan L.)

USDA-ARS?s Scientific Manuscript database

This study reports generation of large-scale genomic resources for pigeonpea, a so-called ‘orphan crop species’ of the semi-arid tropic regions. Roche FLX/454 sequencing was carried out on a normalized cDNA pool prepared from 31 tissues produced 494,353 short transcript reads (STRs). Cluster analysi...
An algorithm for deciding the number of clusters and validating using simulated data with application to exploring crop population structure

USDA-ARS?s Scientific Manuscript database

A first step in exploring population structure in crop plants and other organisms is to define the number of subpopulations that exist for a given data set. The genetic marker data sets being generated have become increasingly large over time and commonly are the high-dimension, low sample size (HDL...

Random variability explains apparent global clustering of large earthquakes

USGS Publications Warehouse

Michael, A.J.

2011-01-01

The occurrence of 5 Mw ≥ 8.5 earthquakes since 2004 has created a debate over whether or not we are in a global cluster of large earthquakes, temporarily raising risks above long-term levels. I use three classes of statistical tests to determine if the record of M ≥ 7 earthquakes since 1900 can reject a null hypothesis of independent random events with a constant rate plus localized aftershock sequences. The data cannot reject this null hypothesis. Thus, the temporal distribution of large global earthquakes is well-described by a random process, plus localized aftershocks, and apparent clustering is due to random variability. Therefore the risk of future events has not increased, except within ongoing aftershock sequences, and should be estimated from the longest possible record of events.
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
A fully nonparametric estimator of the marginal survival function based on case–control clustered age-at-onset data

PubMed Central

Gorfine, Malka; Bordo, Nadia; Hsu, Li

2017-01-01

Summary Consider a popular case–control family study where individuals with a disease under study (case probands) and individuals who do not have the disease (control probands) are randomly sampled from a well-defined population. Possibly right-censored age at onset and disease status are observed for both probands and their relatives. For example, case probands are men diagnosed with prostate cancer, control probands are men free of prostate cancer, and the prostate cancer history of the fathers of the probands is also collected. Inherited genetic susceptibility, shared environment, and common behavior lead to correlation among the outcomes within a family. In this article, a novel nonparametric estimator of the marginal survival function is provided. The estimator is defined in the presence of intra-cluster dependence, and is based on consistent smoothed kernel estimators of conditional survival functions. By simulation, it is shown that the proposed estimator performs very well in terms of bias. The utility of the estimator is illustrated by the analysis of case–control family data of early onset prostate cancer. To our knowledge, this is the first article that provides a fully nonparametric marginal survival estimator based on case–control clustered age-at-onset data. PMID:27436674
DOE Office of Scientific and Technical Information (OSTI.GOV)

de Gasperin, F.; Ogrean, G. A.; van Weeren, R. J.

We report that extended steep-spectrum radio emission in a galaxy cluster is usually associated with a recent merger. However, given the complex scenario of galaxy cluster mergers, many of the discovered sources hardly fit into the strict boundaries of a precise taxonomy. This is especially true for radio phoenixes that do not have very well defined observational criteria. Radio phoenixes are aged radio galaxy lobes whose emission is reactivated by compression or other mechanisms. Here in this paper, we present the detection of a radio phoenix close to the moment of its formation. The source is located in Abell 1033,more » a peculiar galaxy cluster which underwent a recent merger. To support our claim, we present unpublished Westerbork Synthesis Radio Telescope and Chandra observations together with archival data from the Very Large Array and the Sloan Digital Sky Survey. We discover the presence of two subclusters displaced along the N–S direction. The two subclusters probably underwent a recent merger which is the cause of a moderately perturbed X-ray brightness distribution. A steep-spectrum extended radio source very close to an active galactic nucleus (AGN) is proposed to be a newly born radio phoenix: the AGN lobes have been displaced/compressed by shocks formed during the merger event. This scenario explains the source location, morphology, spectral index, and brightness. Finally, we show evidence of a density discontinuity close to the radio phoenix and discuss the consequences of its presence.« less
A Giant Warm Baryonic Halo for the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Max; Lieu, Richard; Joy, Marshall K.; Six, N. Frank (Technical Monitor)

2002-01-01

Several deep PSPC observations of the Coma cluster unveil a very large-scale halo of soft X-ray emission, substantially in excess of the well know radiation from the hot intra-cluster medium. The excess emission, previously reported in the central cluster regions through lower-sensitivity EUVE and ROSAT data, is now evident out to a radius of 2.5 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The spectrum at these large radii cannot be modeled non-thermally, but is consistent with the original scenario of thermal emission at warm temperatures. The mass of this plasma is at least on par with that of the hot X-ray emitting plasma, and significantly more massive if the plasma resides in low-density filamentary structures. Thus the data lend vital support to current theories of cosmic evolution, which predict greater than 50 percent by mass of today's baryons reside in warm-hot filaments converging at clusters of galaxies.
Mechanical gate control for atom-by-atom cluster assembly with scanning probe microscopy.

PubMed

Sugimoto, Yoshiaki; Yurtsever, Ayhan; Hirayama, Naoki; Abe, Masayuki; Morita, Seizo

2014-07-11

Nanoclusters supported on substrates are of great importance in physics and chemistry as well as in technical applications, such as single-electron transistors and nanocatalysts. The properties of nanoclusters differ significantly from those of either the constituent atoms or the bulk solid, and are highly sensitive to size and chemical composition. Here we propose a novel atom gating technique to assemble various atom clusters composed of a defined number of atoms at room temperature. The present gating operation is based on the transfer of single diffusing atoms among nanospaces governed by gates, which can be opened in response to the chemical interaction force with a scanning probe microscope tip. This method provides an alternative way to create pre-designed atom clusters with different chemical compositions and to evaluate their chemical stabilities, thus enabling investigation into the influence that a single dopant atom incorporated into the host clusters has on a given cluster stability.
Monoatomic and cluster beam effect on ToF-SIMS spectra of self-assembled monolayers on gold

NASA Astrophysics Data System (ADS)

Tuccitto, N.; Torrisi, V.; Delfanti, I.; Licciardello, A.

2008-12-01

Self-assembled monolayers represent well-defined systems that is a good model surface to study the effect of primary ion beams used in secondary ion mass spectrometry. The effect of polyatomic primary beams on both aliphatic and aromatic self-assembled monolayers has been studied. In particular, we analysed the variation of the relative secondary ion yield of both substrate metal-cluster (Au n-) in comparison with the molecular ions (M -) and clusters (M xAu y-) by using Bi +, Bi 3+, Bi 5+ beams. Moreover, the differences in the secondary ion generation efficiency are discussed. The main effect of the cluster beams is related to an increased formation of low-mass fragments and to the enhancement of the substrate related gold-clusters. The results show that, at variance of many other cases, the static SIMS of self-assembled monolayers does not benefit of the use of polyatomic primary ions.
Algebraic approach to small-world network models

NASA Astrophysics Data System (ADS)

Rudolph-Lilith, Michelle; Muller, Lyle E.

2014-01-01

We introduce an analytic model for directed Watts-Strogatz small-world graphs and deduce an algebraic expression of its defining adjacency matrix. The latter is then used to calculate the small-world digraph's asymmetry index and clustering coefficient in an analytically exact fashion, valid nonasymptotically for all graph sizes. The proposed approach is general and can be applied to all algebraically well-defined graph-theoretical measures, thus allowing for an analytical investigation of finite-size small-world graphs.
Diversity in the stellar velocity dispersion profiles of a large sample of brightest cluster galaxies z ≤ 0.3

NASA Astrophysics Data System (ADS)

Loubser, S. I.; Hoekstra, H.; Babul, A.; O'Sullivan, E.

2018-06-01

We analyse spatially resolved deep optical spectroscopy of brightestcluster galaxies (BCGs) located in 32 massive clusters with redshifts of 0.05 ≤ z ≤ 0.30 to investigate their velocity dispersion profiles. We compare these measurements to those of other massive early-type galaxies, as well as central group galaxies, where relevant. This unique, large sample extends to the most extreme of massive galaxies, spanning MK between -25.7 and -27.8 mag, and host cluster halo mass M500 up to 1.7 × 1015 M⊙. To compare the kinematic properties between brightest group and cluster members, we analyse similar spatially resolved long-slit spectroscopy for 23 nearby brightest group galaxies (BGGs) from the Complete Local-Volume Groups Sample. We find a surprisingly large variety in velocity dispersion slopes for BCGs, with a significantly larger fraction of positive slopes, unique compared to other (non-central) early-type galaxies as well as the majority of the brightest members of the groups. We find that the velocity dispersion slopes of the BCGs and BGGs correlate with the luminosity of the galaxies, and we quantify this correlation. It is not clear whether the full diversity in velocity dispersion slopes that we see is reproduced in simulations.
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.
[A New Distance Metric between Different Stellar Spectra: the Residual Distribution Distance].

PubMed

Liu, Jie; Pan, Jing-chang; Luo, A-li; Wei, Peng; Liu, Meng

2015-12-01

Distance metric is an important issue for the spectroscopic survey data processing, which defines a calculation method of the distance between two different spectra. Based on this, the classification, clustering, parameter measurement and outlier data mining of spectral data can be carried out. Therefore, the distance measurement method has some effect on the performance of the classification, clustering, parameter measurement and outlier data mining. With the development of large-scale stellar spectral sky surveys, how to define more efficient distance metric on stellar spectra has become a very important issue in the spectral data processing. Based on this problem and fully considering of the characteristics and data features of the stellar spectra, a new distance measurement method of stellar spectra named Residual Distribution Distance is proposed. While using this method to measure the distance, the two spectra are firstly scaled and then the standard deviation of the residual is used the distance. Different from the traditional distance metric calculation methods of stellar spectra, when used to calculate the distance between stellar spectra, this method normalize the two spectra to the same scale, and then calculate the residual corresponding to the same wavelength, and the standard error of the residual spectrum is used as the distance measure. The distance measurement method can be used for stellar classification, clustering and stellar atmospheric physical parameters measurement and so on. This paper takes stellar subcategory classification as an example to test the distance measure method. The results show that the distance defined by the proposed method is more effective to describe the gap between different types of spectra in the classification than other methods, which can be well applied in other related applications. At the same time, this paper also studies the effect of the signal to noise ratio (SNR) on the performance of the proposed method. The result show that the distance is affected by the SNR. The smaller the signal-to-noise ratio is, the greater impact is on the distance; While SNR is larger than 10, the signal-to-noise ratio has little effect on the performance for the classification.
Mothers of young children cluster into 4 groups based on psychographic food decision influencers.

PubMed

Byrd-Bredbenner, Carol; Abbot, Jaclyn Maurer; Cussler, Ellen

2008-08-01

This study explored how mothers grouped into clusters according to multiple psychographic food decision influencers and how the clusters differed in nutrient intake and nutrient content of their household food supply. Mothers (n = 201) completed a survey assessing basic demographic characteristics, food shopping and meal preparation activities, self and spouse employment, exposure to formal food or nutrition education, education level and occupation, weight status, nutrition and food preparation knowledge and skill, family member health and nutrition status, food decision influencer constructs, and dietary intake. In addition, an in-home inventory of 100 participants' household food supplies was conducted. Four distinct clusters presented when 26 psychographic food choice influencers were evaluated. These clusters appear to be valid and robust classifications of mothers in that they discriminated well on the psychographic variables used to construct the clusters as well as numerous other variables not used in the cluster analysis. In addition, the clusters appear to transcend demographic variables that often segment audiences (eg, race, mother's age, socioeconomic status), thereby adding a new dimension to the way in which this audience can be characterized. Furthermore, psychographically defined clusters predicted dietary quality. This study demonstrates that mothers are not a homogenous group and need to have their unique characteristics taken into consideration when designing strategies to promote health. These results can help health practitioners better understand factors affecting food decisions and tailor interventions to better meet the needs of mothers.
Exposing the Binary Heart of ETA Carinae

NASA Technical Reports Server (NTRS)

Forman, WIlliam; Mushotzky, Richard (Technical Monitor)

2005-01-01

Continued progress was made last year on A1367. As noted before, A1367 is a puzzling cluster with a large elongation, suggesting a major merger but with an anti-correlation between the luminosity and temperature of the two components of the cluster (NE and SW). The less luminous subconcentration appears hotter and the more luminous portion of the cluster appears cooler in contradiction to the well-established positive correlation of temperature and luminosity for clusters and groups. With the XMM-Newton observation we have developed a merger model to explain this apparent contradiction.
Reduction Potentials of [FeFe]-Hydrogenase Accessory Iron–Sulfur Clusters Provide Insights into the Energetics of Proton Reduction Catalysis

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

Artz, Jacob H.; Mulder, David W.; Ratzloff, Michael W.

An [FeFe]-hydrogenase from Clostridium pasteurianum, CpI, is a model system for biological H 2 activation. In addition to the catalytic H-cluster, CpI contains four accessory iron-sulfur [FeS] clusters in a branched series that transfer electrons to and from the active site. In this work, potentiometric titrations have been employed in combination with electron paramagnetic resonance (EPR) spectroscopy at defined electrochemical potentials to gain insights into the role of the accessory clusters in catalysis. EPR spectra collected over a range of potentials were deconvoluted into individual components attributable to the accessory [FeS] clusters and the active site H-cluster, and reduction potentialsmore » for each cluster were determined. The data suggest a large degree of magnetic coupling between the clusters. The distal [4Fe-4S] cluster is shown to have a lower reduction potential (~ < -450 mV) than the other clusters, and molecular docking experiments indicate that the physiological electron donor, ferredoxin (Fd), most favorably interacts with this cluster. The low reduction potential of the distal [4Fe-4S] cluster thermodynamically restricts the Fd ox/Fd red ratio at which CpI can operate, consistent with the role of CpI in recycling Fd redthat accumulates during fermentation. In conclusion, subsequent electron transfer through the additional accessory [FeS] clusters to the H-cluster is thermodynamically favorable.« less
Reduction Potentials of [FeFe]-Hydrogenase Accessory Iron–Sulfur Clusters Provide Insights into the Energetics of Proton Reduction Catalysis

DOE PAGES

Artz, Jacob H.; Mulder, David W.; Ratzloff, Michael W.; ...

2017-06-21

An [FeFe]-hydrogenase from Clostridium pasteurianum, CpI, is a model system for biological H 2 activation. In addition to the catalytic H-cluster, CpI contains four accessory iron-sulfur [FeS] clusters in a branched series that transfer electrons to and from the active site. In this work, potentiometric titrations have been employed in combination with electron paramagnetic resonance (EPR) spectroscopy at defined electrochemical potentials to gain insights into the role of the accessory clusters in catalysis. EPR spectra collected over a range of potentials were deconvoluted into individual components attributable to the accessory [FeS] clusters and the active site H-cluster, and reduction potentialsmore » for each cluster were determined. The data suggest a large degree of magnetic coupling between the clusters. The distal [4Fe-4S] cluster is shown to have a lower reduction potential (~ < -450 mV) than the other clusters, and molecular docking experiments indicate that the physiological electron donor, ferredoxin (Fd), most favorably interacts with this cluster. The low reduction potential of the distal [4Fe-4S] cluster thermodynamically restricts the Fd ox/Fd red ratio at which CpI can operate, consistent with the role of CpI in recycling Fd redthat accumulates during fermentation. In conclusion, subsequent electron transfer through the additional accessory [FeS] clusters to the H-cluster is thermodynamically favorable.« less
Structures in the Great Attractor region

NASA Astrophysics Data System (ADS)

Radburn-Smith, D. J.; Lucey, J. R.; Woudt, P. A.; Kraan-Korteweg, R. C.; Watson, F. G.

2006-07-01

To further our understanding of the Great Attractor (GA), we have undertaken a redshift survey using the 2-degree Field (2dF) instrument on the Anglo-Australian Telescope (AAT). Clusters and filaments in the GA region were targeted with 25 separate pointings resulting in approximately 2600 new redshifts. Targets included poorly studied X-ray clusters from the Clusters in the Zone of Avoidance (CIZA) Catalogue as well as the Cen-Crux and PKS 1343-601 clusters, both of which lie close to the classic GA centre. For nine clusters in the region, we report velocity distributions as well as virial and projected mass estimates. The virial mass of CIZA J1324.7-5736, now identified as a separate structure from the Cen-Crux cluster, is found to be ˜3 × 1014-M⊙, in good agreement with the X-ray inferred mass. In the PKS 1343-601 field, five redshifts are measured of which four are new. An analysis of redshifts from this survey, in combination with those from the literature, reveals the dominant structure in the GA region to be a large filament, which appears to extend from Abell S0639 (l= 281°, b=+11°) to (l˜ 5°, b˜-50°), encompassing the Cen-Crux, CIZA J1324.7-5736, Norma and Pavo II clusters. Behind the Norma cluster at cz˜ 15-000-km-s-1, the masses of four rich clusters are calculated. These clusters (Triangulum Australis, Ara, CIZA J1514.6-4558 and CIZA J1410.4-4246) may contribute to a continued large-scale flow beyond the GA. The results of these observations will be incorporated into a subsequent analysis of the GA flow.
Clustering analysis of line indices for LAMOST spectra with AstroStat

NASA Astrophysics Data System (ADS)

Chen, Shu-Xin; Sun, Wei-Min; Yan, Qi

2018-06-01

The application of data mining in astronomical surveys, such as the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey, provides an effective approach to automatically analyze a large amount of complex survey data. Unsupervised clustering could help astronomers find the associations and outliers in a big data set. In this paper, we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software AstroStat. Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra, which can represent the main spectral characteristics of stars. A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars. For intra distance, we use the definition of Mahalanobis distance to explore the degree of clustering for each class, while for outlier detection, we define a local outlier factor for each spectrum. AstroStat furnishes a set of visualization tools for illustrating the analysis results. Checking the spectra detected as outliers, we find that most of them are problematic data and only a few correspond to rare astronomical objects. We show two examples of these outliers, a spectrum with abnormal continuumand a spectrum with emission lines. Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.
The impact of transmission clusters on primary drug resistance in newly diagnosed HIV-1 infection.

PubMed

Yerly, Sabine; Junier, Thomas; Gayet-Ageron, Angèle; Amari, Emmanuelle Boffi El; von Wyl, Viktor; Günthard, Huldrych F; Hirschel, Bernard; Zdobnov, Evgeny; Kaiser, Laurent

2009-07-17

To monitor HIV-1 transmitted drug resistance (TDR) in a well defined urban area with large access to antiretroviral therapy and to assess the potential source of infection of newly diagnosed HIV individuals. All individuals resident in Geneva, Switzerland, with a newly diagnosed HIV infection between 2000 and 2008 were screened for HIV resistance. An infection was considered as recent when the positive test followed a negative screening test within less than 1 year. Phylogenetic analyses were performed by using the maximum likelihood method on pol sequences including 1058 individuals with chronic infection living in Geneva. Of 637 individuals with newly diagnosed HIV infection, 20% had a recent infection. Mutations associated with resistance to at least one drug class were detected in 8.5% [nucleoside reverse transcriptase inhibitors (NRTIs), 6.3%; non-nucleoside reverse transcriptase inhibitors (NNRTIs), 3.5%; protease inhibitors, 1.9%]. TDR (P-trend = 0.015) and, in particular, NNRTI resistance (P = 0.002) increased from 2000 to 2008. Phylogenetic analyses revealed that 34.9% of newly diagnosed individuals, and 52.7% of those with recent infection were linked to transmission clusters. Clusters were more frequent in individuals with TDR than in those with sensitive strains (59.3 vs. 32.6%, respectively; P < 0.0001). Moreover, 84% of newly diagnosed individuals with TDR were part of clusters composed of only newly diagnosed individuals. Reconstruction of the HIV transmission networks using phylogenetic analysis shows that newly diagnosed HIV infections are a significant source of onward transmission, particularly of resistant strains, thus suggesting an important self-fueling mechanism for TDR.
Surrogate Reservoir Model

NASA Astrophysics Data System (ADS)

Mohaghegh, Shahab

2010-05-01

Surrogate Reservoir Model (SRM) is new solution for fast track, comprehensive reservoir analysis (solving both direct and inverse problems) using existing reservoir simulation models. SRM is defined as a replica of the full field reservoir simulation model that runs and provides accurate results in real-time (one simulation run takes only a fraction of a second). SRM mimics the capabilities of a full field model with high accuracy. Reservoir simulation is the industry standard for reservoir management. It is used in all phases of field development in the oil and gas industry. The routine of simulation studies calls for integration of static and dynamic measurements into the reservoir model. Full field reservoir simulation models have become the major source of information for analysis, prediction and decision making. Large prolific fields usually go through several versions (updates) of their model. Each new version usually is a major improvement over the previous version. The updated model includes the latest available information incorporated along with adjustments that usually are the result of single-well or multi-well history matching. As the number of reservoir layers (thickness of the formations) increases, the number of cells representing the model approaches several millions. As the reservoir models grow in size, so does the time that is required for each run. Schemes such as grid computing and parallel processing helps to a certain degree but do not provide the required speed for tasks such as: field development strategies using comprehensive reservoir analysis, solving the inverse problem for injection/production optimization, quantifying uncertainties associated with the geological model and real-time optimization and decision making. These types of analyses require hundreds or thousands of runs. Furthermore, with the new push for smart fields in the oil/gas industry that is a natural growth of smart completion and smart wells, the need for real time reservoir modeling becomes more pronounced. SRM is developed using the state of the art in neural computing and fuzzy pattern recognition to address the ever growing need in the oil and gas industry to perform accurate, but high speed simulation and modeling. Unlike conventional geo-statistical approaches (response surfaces, proxy models …) that require hundreds of simulation runs for development, SRM is developed only with a few (from 10 to 30 runs) simulation runs. SRM can be developed regularly (as new versions of the full field model become available) off-line and can be put online for real-time processing to guide important decisions. SRM has proven its value in the field. An SRM was developed for a giant oil field in the Middle East. The model included about one million grid blocks with more than 165 horizontal wells and took ten hours for a single run on 12 parallel CPUs. Using only 10 simulation runs, an SRM was developed that was able to accurately mimic the behavior of the reservoir simulation model. Performing a comprehensive reservoir analysis that included making millions of SRM runs, wells in the field were divided into five clusters. It was predicted that wells in cluster one & two are best candidates for rate relaxation with minimal, long term water production while wells in clusters four and five are susceptive to high water cuts. Two and a half years and 20 wells later, rate relaxation results from the field proved that all the predictions made by the SRM analysis were correct. While incremental oil production increased in all wells (wells in clusters 1 produced the most followed by wells in cluster 2, 3 …) the percent change in average monthly water cut for wells in each cluster clearly demonstrated the analytic power of SRM. As it was correctly predicted, wells in clusters 1 and 2 actually experience a reduction in water cut while a substantial increase in water cut was observed in wells classified into clusters 4 and 5. Performing these analyses would have been impossible using the original full field simulation model.
Nanorings of self-assembled fullerene C(70) as templating nanoreactors.

PubMed

Iyer, K Swaminathan; Saunders, Martin; Becker, Thomas; Evans, Cameron W; Raston, Colin L

2009-11-18

Micelles, polyelectrolytes, peptides, and plasmid DNA with well-defined growth cavities can function as templates for the synthesis of metal nanocrystals. In a similar way, carbon-based toroidal 'nanoreactors' composed of clustered fullerenes could be used to synthesize nanohybrids by forming metal nanocrystals within the confines of the ring.

Yeast Mitoribosome Large Subunit Assembly Proceeds by Hierarchical Incorporation of Protein Clusters and Modules on the Inner Membrane.

PubMed

Zeng, Rui; Smith, Erin; Barrientos, Antoni

2018-03-06

Mitoribosomes are specialized for the synthesis of hydrophobic membrane proteins encoded by mtDNA, all essential for oxidative phosphorylation. Despite their linkage to human mitochondrial diseases and the recent cryoelectron microscopy reconstruction of yeast and mammalian mitoribosomes, how they are assembled remains obscure. Here, we dissected the yeast mitoribosome large subunit (mtLSU) assembly process by systematic genomic deletion of 44 mtLSU proteins (MRPs). Analysis of the strain collection unveiled 37 proteins essential for functional mtLSU assembly, three of which are critical for mtLSU 21S rRNA stability. Hierarchical cluster analysis of mtLSU subassemblies accumulated in mutant strains revealed co-operative assembly of protein sets forming structural clusters and preassembled modules. It also indicated crucial roles for mitochondrion-specific membrane-binding MRPs in anchoring newly transcribed 21S rRNA to the inner membrane, where assembly proceeds. Our results define the yeast mtLSU assembly landscape in vivo and provide a foundation for studies of mitoribosome assembly across evolution. Copyright © 2018 Elsevier Inc. All rights reserved.
VizieR Online Data Catalog: 2nd and 3d parameters of HB of globular clusters (Gratton+, 2010)

NASA Astrophysics Data System (ADS)

Gratton, R. G.; Carretta, E.; Bragaglia, A.; Lucatello, S.; S'orazii, V.

2010-05-01

The second parameter (the first being metallicity) defining the distribution of stars on the horizontal branch (HB) of globular clusters (GCs) has long been one of the major open issues in our understanding of the evolution of normal stars. Large photometric and spectroscopic databases are now available: they include large and homogeneous sets of colour-magnitude diagrams, cluster ages, and homogeneous data about chemical compositions from our FLAMES survey. We use these databases to re-examine this issue. Methods. We use the photometric data to derive median and extreme (i.e., the values including 90% of the distribution) colours and magnitudes of stars along the HB for about a hundred GCs. We transform these into median and extreme masses of stars on the HB, using the models developed by the Pisa group, and taking into account evolutionary effects. We compare these masses with those expected at the tip of the red giant branch (RGB) to derive the total mass lost by the stars. (11 data files).
Weak Lensing Results of the Merging Cluster A1758

NASA Technical Reports Server (NTRS)

Markevitch, M.; Gonzalez, A. H.; Bradac, M.

2011-01-01

Here we present the weak lensing results of A1758, which is known to have four cluster members undergoing two separate mergers, A1758N and A1758S. Weak lensing results of A1758N agree with previous weak lensing results of clusters lE0657-558 (Bullet cluster) and MACS J0025.4-1222, whose X-ray gas components were found to be largely separated from their clusters' gravitational potentials. A1758N has a geometry that is different from previously published mergers in that one of its X-ray peaks overlays the corresponding gravitational potential and the other X-ray peak is well separated from its cluster's gravitational potential.
Framework for behavioral analytics in anomaly identification

NASA Astrophysics Data System (ADS)

Touma, Maroun; Bertino, Elisa; Rivera, Brian; Verma, Dinesh; Calo, Seraphin

2017-05-01

Behavioral Analytics (BA) relies on digital breadcrumbs to build user profiles and create clusters of entities that exhibit a large degree of similarity. The prevailing assumption is that an entity will assimilate the group behavior of the cluster it belongs to. Our understanding of BA and its application in different domains continues to evolve and is a direct result of the growing interest in Machine Learning research. When trying to detect security threats, we use BA techniques to identify anomalies, defined in this paper as deviation from the group behavior. Early research papers in this field reveal a high number of false positives where a security alert is triggered based on deviation from the cluster learned behavior but still within the norm of what the system defines as an acceptable behavior. Further, domain specific security policies tend to be narrow and inadequately represent what an entity can do. Hence, they: a) limit the amount of useful data during the learning phase; and, b) lead to violation of policy during the execution phase. In this paper, we propose a framework for future research on the role of policies and behavior security in a coalition setting with emphasis on anomaly detection and individual's deviation from group activities.
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.
Corrected Integral Shape Averaging Applied to Obstructive Sleep Apnea Detection from the Electrocardiogram

NASA Astrophysics Data System (ADS)

Boudaoud, S.; Rix, H.; Meste, O.; Heneghan, C.; O'Brien, C.

2007-12-01

We present a technique called corrected integral shape averaging (CISA) for quantifying shape and shape differences in a set of signals. CISA can be used to account for signal differences which are purely due to affine time warping (jitter and dilation/compression), and hence provide access to intrinsic shape fluctuations. CISA can also be used to define a distance between shapes which has useful mathematical properties; a mean shape signal for a set of signals can be defined, which minimizes the sum of squared shape distances of the set from the mean. The CISA procedure also allows joint estimation of the affine time parameters. Numerical simulations are presented to support the algorithm for obtaining the CISA mean and parameters. Since CISA provides a well-defined shape distance, it can be used in shape clustering applications based on distance measures such as[InlineEquation not available: see fulltext.]-means. We present an application in which CISA shape clustering is applied to P-waves extracted from the electrocardiogram of subjects suffering from sleep apnea. The resulting shape clustering distinguishes ECG segments recorded during apnea from those recorded during normal breathing with a sensitivity of[InlineEquation not available: see fulltext.] and specificity of[InlineEquation not available: see fulltext.].
New VVV Survey Globular Cluster Candidates in the Milky Way Bulge

NASA Astrophysics Data System (ADS)

Minniti, Dante; Geisler, Douglas; Alonso-García, Javier; Palma, Tali; Beamín, Juan Carlos; Borissova, Jura; Catelan, Marcio; Clariá, Juan J.; Cohen, Roger E.; Contreras Ramos, Rodrigo; Dias, Bruno; Fernández-Trincado, Jose G.; Gómez, Matías; Hempel, Maren; Ivanov, Valentin D.; Kurtev, Radostin; Lucas, Phillip W.; Moni-Bidin, Christian; Pullen, Joyce; Ramírez Alegría, Sebastian; Saito, Roberto K.; Valenti, Elena

2017-11-01

It is likely that a number of Galactic globular clusters remain to be discovered, especially toward the Galactic bulge. High stellar density combined with high and differential interstellar reddening are the two major problems for finding globular clusters located toward the bulge. We use the deep near-IR photometry of the VISTA Variables in the Vía Láctea (VVV) Survey to search for globular clusters projected toward the Galactic bulge, and hereby report the discovery of 22 new candidate globular clusters. These objects, detected as high density regions in our maps of bulge red giants, are confirmed as globular cluster candidates by their color-magnitude diagrams. We provide their coordinates as well as their near-IR color-magnitude diagrams, from which some basic parameters are derived, such as reddenings and heliocentric distances. The color-magnitude diagrams reveal well defined red giant branches in all cases, often including a prominent red clump. The new globular cluster candidates exhibit a variety of extinctions (0.06 < A Ks < 2.77) and distances (5.3 < D < 9.5 kpc). We also classify the globular cluster candidates into 10 metal-poor and 12 metal-rich clusters, based on the comparison of their color-magnitude diagrams with those of known globular clusters also observed by the VVV Survey. Finally, we argue that the census for Galactic globular clusters still remains incomplete, and that many more candidate globular clusters (particularly the low luminosity ones) await to be found and studied in detail in the central regions of the Milky Way. Based on observations taken within the ESO programs 179.B-2002 and 298.D-5048.
Validating clustering of molecular dynamics simulations using polymer models.

PubMed

Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

2011-11-14

Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.
Validating clustering of molecular dynamics simulations using polymer models

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers. PMID:22082218
Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005–2010 data from ten French slaughterhouses

PubMed Central

2013-01-01

Background The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging. The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data. Results Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer’s lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues. Conclusion The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases. PMID:23628140
Discovery of a loose star cluster in the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.

2016-06-01

We present results for an up-to-date uncatalogued star cluster projected towards the Eastern side of the Large Magellanic Cloud (LMC) outer disc. The new object was discovered from a search of loose star cluster in the Magellanic Clouds' (MCs) outskirts using kernel density estimators on Washington CT1 deep images. Contrarily to what would be commonly expected, the star cluster resulted to be a young object (log(t yr-1) = 8.45) with a slightly subsolar metal content (Z = 0.013) and a total mass of 650 M⊙. Its core, half-mass and tidal radii also are within the frequent values of LMC star clusters. However, the new star cluster is placed at the Small Magellanic Cloud distance and at 11.3 kpc from the LMC centre. We speculate with the possibility that it was born in the inner body of the LMC and soon after expelled into the intergalactic space during the recent Milky Way/MCs interaction. Nevertheless, radial velocity and chemical abundance measurements are needed to further understand its origin, as well as extensive search for loose star clusters in order to constrain the effectiveness of star cluster scattering during galaxy interactions.
ALE OF TWO CLUSTERS YIELDS SECRETS OF STAR BIRTH IN THE EARLY UNIVERSE

NASA Technical Reports Server (NTRS)

2002-01-01

This NASA Hubble Space Telescope (HST) image shows rich detail, previously only seen in neighboring star birth regions, in a pair of star clusters 166,000 light-years away in the Large Magellanic Cloud (LMC), in the southern constellation Doradus. The field of view is 130 light-years across and was taken with the Wide Field Planetary Camera 2. HST's unique capabilities -- ultraviolet sensitivity, ability to see faint stars, and high resolution -- have been utilized fully to identify three separate populations in this concentration of nearly 10,000 stars down to the 25th magnitude (more that twice as many as can be seen over the entire sky with the naked eye on a clear night on Earth). The field of view is only 130 light-years across. Previous observations with ground-based telescopes resolve less than 1,000 stars in the same region. About 60 percent of the stars belong to the dominant yellow cluster called NGC 1850, which is estimated to be 50 million years old. A scattering of white stars in the image are massive stars that are only about 4 million years old and represent about 20 percent of the stars in the image. (The remainder are field stars in the LMC.) Besides being much younger, the white stars are much more loosely distributed than the yellow cluster. The significant difference between the two cluster ages suggests these are two separate star groups that lie along the same line of sight. The younger, more open cluster probably lies 200 light-years beyond the older cluster. If it were in the foreground, then dust contained in the white cluster would obscure stars in the older yellow cluster. To observe two well-defined star populations separated by such a small gap of space is unusual. This juxtaposition suggests that supernova explosions in the older cluster might have triggered the birth of the younger cluster. This color composite image is assembled from exposures taken in ultraviolet, visible, and near-infrared light. Yellow stars correspond to Main Sequence stars (like our Sun) with average surface temperatures of 6000 Kelvin; red stars are cool giants and supergiants (3500 K); white stars are hot young stars (25,000 K or more) that are bright in ultraviolet. Credit: R. Gilmozzi, Space Telescope Science Institute/European Space Agency; Shawn Ewald, JPL; and NASA
Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.
Molecular simulation of flow-enhanced nucleation in n-eicosane melts under steady shear and uniaxial extension.

PubMed

Nicholson, David A; Rutledge, Gregory C

2016-12-28

Non-equilibrium molecular dynamics is used to study crystal nucleation of n-eicosane under planar shear and, for the first time, uniaxial extension. A method of analysis based on the mean first-passage time is applied to the simulation results in order to determine the effect of the applied flow field type and strain rate on the steady-state nucleation rate and a characteristic growth rate, as well as the effects on kinetic parameters associated with nucleation: the free energy barrier, critical nucleus size, and monomer attachment pre-factor. The onset of flow-enhanced nucleation (FEN) occurs at a smaller critical strain rate in extension as compared to shear. For strain rates larger than the critical rate, a rapid increase in the nucleation rate is accompanied by decreases in the free energy barrier and critical nucleus size, as well as an increase in chain extension. These observations accord with a mechanism in which FEN is caused by an increase in the driving force for crystallization due to flow-induced entropy reduction. At high applied strain rates, the free energy barrier, critical nucleus size, and degree of stretching saturate, while the monomer attachment pre-factor and degree of orientational order increase steadily. This trend is indicative of a significant diffusive contribution to the nucleation rate under intense flows that is correlated with the degree of global orientational order in a nucleating system. Both flow fields give similar results for all kinetic quantities with respect to the reduced strain rate, which we define as the ratio of the applied strain rate to the critical rate. The characteristic growth rate increases with increasing strain rate, and shows a correspondence with the nucleation rate that does not depend on the type of flow field applied. Additionally, a structural analysis of the crystalline clusters indicates that the flow field suppresses the compaction and crystalline ordering of clusters, leading to the formation of large articulated clusters under strong flow fields, and compact well-ordered clusters under weak flow fields.
REGARDING THE LINE-OF-SIGHT BARYONIC ACOUSTIC FEATURE IN THE SLOAN DIGITAL SKY SURVEY AND BARYON OSCILLATION SPECTROSCOPIC SURVEY LUMINOUS RED GALAXY SAMPLES

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

Kazin, Eyal A.; Blanton, Michael R.; Scoccimarro, Roman

2010-08-20

We analyze the line-of-sight baryonic acoustic feature in the two-point correlation function {xi} of the Sloan Digital Sky Survey luminous red galaxy (LRG) sample (0.16 < z < 0.47). By defining a narrow line-of-sight region, r{sub p} < 5.5 h {sup -1} Mpc, where r{sub p} is the transverse separation component, we measure a strong excess of clustering at {approx}110 h {sup -1} Mpc, as previously reported in the literature. We also test these results in an alternative coordinate system, by defining the line of sight as {theta} < 3{sup 0}, where {theta} is the opening angle. This clustering excessmore » appears much stronger than the feature in the better-measured monopole. A fiducial {Lambda}CDM nonlinear model in redshift space predicts a much weaker signature. We use realistic mock catalogs to model the expected signal and noise. We find that the line-of-sight measurements can be explained well by our mocks as well as by a featureless {xi} = 0. We conclude that there is no convincing evidence that the strong clustering measurement is the line-of-sight baryonic acoustic feature. We also evaluate how detectable such a signal would be in the upcoming Baryon Oscillation Spectroscopic Survey (BOSS) LRG volume. Mock LRG catalogs (z < 0.6) suggest that (1) the narrow line-of-sight cylinder and cone defined above probably will not reveal a detectable acoustic feature in BOSS; (2) a clustering measurement as high as that in the current sample can be ruled out (or confirmed) at a high confidence level using a BOSS-sized data set; (3) an analysis with wider angular cuts, which provide better signal-to-noise ratios, can nevertheless be used to compare line-of-sight and transverse distances, and thereby constrain the expansion rate H(z) and diameter distance D{sub A}(z).« less
Small vs. Large Convective Cloud Objects from CERES Aqua Observations: Where are the Intraseasonal Variation Signals?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2016-01-01

During inactive phases of Madden-Julian oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep cloud clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large cloud clusters during the MJO life cycle. We analyze the cloud object data from Aqua CERES observations for tropical deep convective (DC) and cirrostratus (CS) cloud object types according to the real-time multivariate MJO index. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The size distributions, defined as the footprint numbers as a function of cloud object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large cloud-object diameters due to the reduced/increased numbers of cloud objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all cloud objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of cloud objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and cloud physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS types. These results suggest that the intreseasonal variation signals reside at the large cloud clusters while the small cloud clusters represent the background noises resulting from various types of the tropical waves with different wavenumbers and propagation directions/speeds.
Cluster analysis of autoantibodies in 852 patients with systemic lupus erythematosus from a single center.

PubMed

Artim-Esen, Bahar; Çene, Erhan; Şahinkaya, Yasemin; Ertan, Semra; Pehlivan, Özlem; Kamali, Sevil; Gül, Ahmet; Öcal, Lale; Aral, Orhan; Inanç, Murat

2014-07-01

Associations between autoantibodies and clinical features have been described in systemic lupus erythematosus (SLE). Herein, we aimed to define autoantibody clusters and their clinical correlations in a large cohort of patients with SLE. We analyzed 852 patients with SLE who attended our clinic. Seven autoantibodies were selected for cluster analysis: anti-DNA, anti-Sm, anti-RNP, anticardiolipin (aCL) immunoglobulin (Ig)G or IgM, lupus anticoagulant (LAC), anti-Ro, and anti-La. Two-step clustering and Kaplan-Meier survival analyses were used. Five clusters were identified. A cluster consisted of patients with only anti-dsDNA antibodies, a cluster of anti-Sm and anti-RNP, a cluster of aCL IgG/M and LAC, and a cluster of anti-Ro and anti-La antibodies. Analysis revealed 1 more cluster that consisted of patients who did not belong to any of the clusters formed by antibodies chosen for cluster analysis. Sm/RNP cluster had significantly higher incidence of pulmonary hypertension and Raynaud phenomenon. DsDNA cluster had the highest incidence of renal involvement. In the aCL/LAC cluster, there were significantly more patients with neuropsychiatric involvement, antiphospholipid syndrome, autoimmune hemolytic anemia, and thrombocytopenia. According to the Systemic Lupus International Collaborating Clinics damage index, the highest frequency of damage was in the aCL/LAC cluster. Comparison of 10 and 20 years survival showed reduced survival in the aCL/LAC cluster. This study supports the existence of autoantibody clusters with distinct clinical features in SLE and shows that forming clinical subsets according to autoantibody clusters may be useful in predicting the outcome of the disease. Autoantibody clusters in SLE may exhibit differences according to the clinical setting or population.
Large Scale Structure Studies: Final Results from a Rich Cluster Redshift Survey

NASA Astrophysics Data System (ADS)

Slinglend, K.; Batuski, D.; Haase, S.; Hill, J.

1995-12-01

The results from the COBE satellite show the existence of structure on scales on the order of 10% or more of the horizon scale of the universe. Rich clusters of galaxies from the Abell-ACO catalogs show evidence of structure on scales of 100 Mpc and hold the promise of confirming structure on the scale of the COBE result. Unfortunately, until now, redshift information has been unavailable for a large percentage of these clusters, so present knowledge of their three dimensional distribution has quite large uncertainties. Our approach in this effort has been to use the MX multifiber spectrometer on the Steward 2.3m to measure redshifts of at least ten galaxies in each of 88 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8 (estimated z<= 0.12) and zero or one measured redshifts. This work has resulted in a deeper, 95% complete and more reliable sample of 3-D positions of rich clusters. The primary intent of this survey has been to constrain theoretical models for the formation of the structure we see in the universe today through 2-pt. spatial correlation function and other analyses of the large scale structures traced by these clusters. In addition, we have obtained enough redshifts per cluster to greatly improve the quality and size of the sample of reliable cluster velocity dispersions available for use in other studies of cluster properties. This new data has also allowed the construction of an updated and more reliable supercluster candidate catalog. Our efforts have resulted in effectively doubling the volume traced by these clusters. Presented here is the resulting 2-pt. spatial correlation function, as well as density plots and several other figures quantifying the large scale structure from this much deeper and complete sample. Also, with 10 or more redshifts in most of our cluster fields, we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.
Self-assembled clusters of spheres related to spherical codes.

PubMed

Phillips, Carolyn L; Jankowski, Eric; Marval, Michelle; Glotzer, Sharon C

2012-10-01

We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well-defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter. We show that the arrangements of outer spheres at finite temperatures are related to spherical codes, an ideal mathematical sequence of points corresponding to the densest possible sphere packings. We demonstrate that temperature and the ratio of the diameters of the inner and outer spheres dictate cluster morphology. We present a surprising result for the equilibrium structure of a 5-cluster, for which the square pyramid arrangement is preferred over a more symmetric structure. We show this result using Brownian dynamics, a Monte Carlo simulation, and a free energy approximation. Our results suggest a promising way to assemble anisotropic building blocks from constituent colloidal spheres.
Tisettanta case study: the interoperation of furniture production companies

NASA Astrophysics Data System (ADS)

Amarilli, Fabrizio; Spreafico, Alberto

This chapter presents the Tisettanta case study, focusing on the definition of the possible innovations that ICT technologies can bring to the Italian wood-furniture industry. This sector is characterized by industrial clusters composed mainly of a few large companies with international brand reputations and a large base of SMEs that manufacture finished products or are specialized in the production of single components/processes (such as the Brianza cluster, where Tisettanta operates). In this particular business ecosystem, ICT technologies can bring relevant support and improvements to the supply chain process, where collaborations between enterprises are put into action through the exchange of business documents such as orders, order confirmation, bills of lading, invoices, etc. The analysis methodology adopted in the Tisettanta case study refers to the TEKNE Methodology of Change (see Chapter 2), which defines a framework for supporting firms in the adoption of the Internetworked Enterprise organizational paradigm.

Galaxy masses in large surveys: Connecting luminous and dark matter with weak lensing and kinematics

NASA Astrophysics Data System (ADS)

Reyes, Reinabelle

2011-01-01

Galaxy masses are difficult to determine because light traces stars and gas in a non-trivial way, and does not trace dark matter, which extends well beyond the luminous regions of galaxies. In this thesis, I use the most direct probes of dark matter available---weak gravitational lensing and galaxy kinematics---to trace the total mass in galaxies (and galaxy clusters) in large surveys. In particular, I use the large, homogeneous dataset from the Sloan Digital Sky Survey (SDSS), which provides spectroscopic redshifts for a large sample of galaxies at z ≲ 0.2 and imaging data to a depth of r < 22. By combining complementary probes, I am able to obtain robust observational constraints that cannot be obtained from any single technique alone. First, I use weak lensing of galaxy clusters to derive an optimal optical tracer of cluster mass, which was found to be a combination of cluster richness and the luminosity of the brightest cluster galaxy. Next, I combine weak lensing of luminous red galaxies with redshift distortions and clustering measurements to derive a robust probe of gravity on cosmological scales. Finally, I combine weak lensing with the kinematics of disk galaxies to constrain the total mass profile over several orders of magnitude. I derive a minimal-scatter relation between disk velocity and stellar mass (also known as the Tully-Fisher relation) that can be used, by construction, on a similarly-selected lens sample. Then, I combine this relation with halo mass measurements from weak lensing to place constraints on the ratio of the optical to virial velocities, as well as the ratio of halo to stellar masses, both as a function of stellar mass. These results will serve as inputs to and constraints on disk galaxy formation models, which will be explored in future work.
Flow over gravel beds with clusters

NASA Astrophysics Data System (ADS)

Little, M.; Venditti, J. G.

2014-12-01

The structure of a gravel bed has been shown to alter the entrainment threshold. Structures such as clusters, reticulate stone cells and other discrete structures lock grains together, making it more difficult for them to be mobilized. These structures also generate form drag, reducing the shear stress available for mobilization. Form drag over gravel beds is often assumed to be negligible, but this assumption is not well supported. Here, we explore how cluster density and arrangement affect flow resistance and the flow structure over a fixed gravel bed in a flume experiment. Cluster density was varied from 6 to 68.3 clusters per square meter which corresponds to areal bed coverages of 2 to 17%. We used regular, irregular and random arrangements of the clusters. Our results show that flow resistance over a planar gravel bed initially declines, then increases with flow depth. The addition of clusters increases flow resistance, but the effect is dependent on cluster density, flow depth and arrangement. At the highest density, clusters can increase flow resistance as by as much as 8 times when compared to flat planar bed with no grain-related form drag. Spatially resolved observations of flow over the clusters indicate that a well-defined wake forms in the lee of each cluster. At low cluster density, the wakes are isolated and weak. As cluster density increases, the wakes become stronger. At the highest density, the wakes interact and the within cluster flow field detaches from the overlying flow. This generates a distinct shear layer at the height of the clusters. In spite of this change in the flow field at high density, our results suggest that flow resistance simply increases with cluster density. Our results suggest that the form drag associated with a gravel bed can be substantial and that it depends on the arrangement of the grains on the bed.
Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

PubMed

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

2016-11-23

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

NASA Astrophysics Data System (ADS)

Santra, Mantu; Chakrabarty, Suman; Bagchi, Biman

2008-12-01

We study the nucleation of liquid phase from a supersaturated vapor in two dimensions, where the particles interact through Lennard-Jones (LJ) pairwise potential. Using different Monte Carlo simulation methods, we calculate the free energy barrier for nucleation, the line tension, and bulk densities of equilibrium liquid and vapor phases, and also investigate the size and shape of the critical nucleus. The study is carried out at an intermediate level of supersaturation (away from the spinodal limit). In two dimensions, a surprisingly large cutoff (rc≥7.0σ, σ is the diameter of LJ particles) in the truncation of the LJ potential is required to obtain converged results. A lower cutoff [typically 2.5σ which is generally sufficient in three dimensional (3D) studies] leads to a substantial error in the values of the line tension, nucleation barrier, and characteristics of the critical cluster. It is found that in two dimensions, the classical nucleation theory (CNT) fails to provide a reliable estimate of the free energy barrier. It underestimates the barrier by as much as 50% at the saturation ratio S =1.1 (defined as S =P/PC, where PC is the coexistence pressure) and at the reduced temperature T∗=0.427 (defined as T∗=kBT/ɛ, where ɛ is the depth of the potential well). Interestingly, CNT has been found to overestimate the nucleation free energy barrier in 3D systems near the triple point. In fact, the agreement of the calculated nucleation rate with CNT is much worse in two dimensions than in three dimensions. The reason for the inadequacy of the CNT can be attributed to the noncircular nature of the critical clusters. Although the shape becomes increasingly circular and the clusters become more compact with increase in cutoff radius, an appreciable noncircular nature remains even without any cutoff to make the simple CNT inaccurate.
Forming clusters within clusters: how 30 Doradus recollapsed and gave birth again

NASA Astrophysics Data System (ADS)

Rahner, Daniel; Pellegrini, Eric W.; Glover, Simon C. O.; Klessen, Ralf S.

2018-01-01

The 30 Doradus nebula in the Large Magellanic Cloud (LMC) contains the massive starburst cluster NGC 2070 with a massive and probably younger stellar sub clump at its centre: R136. It is not clear how such a massive inner cluster could form several million years after the older stars in NGC 2070, given that stellar feedback is usually thought to expel gas and inhibit further star formation. Using the recently developed 1D feedback scheme WARPFIELD to scan a large range of cloud and cluster properties, we show that an age offset of several million years between the stellar populations is in fact to be expected given the interplay between feedback and gravity in a giant molecular cloud with a density ≳500 cm-3 due to re-accretion of gas on to the older stellar population. Neither capture of field stars nor gas retention inside the cluster have to be invoked in order to explain the observed age offset in NGC 2070 as well as the structure of the interstellar medium around it.
Reproducible Earth observation analytics: challenges, ideas, and a study case on containerized land use change detection

NASA Astrophysics Data System (ADS)

Appel, Marius; Nüst, Daniel; Pebesma, Edzer

2017-04-01

Geoscientific analyses of Earth observation data typically involve a long path from data acquisition to scientific results and conclusions. Before starting the actual processing, scenes must be downloaded from the providers' platforms and the computing infrastructure needs to be prepared. The computing environment often requires specialized software, which in turn might have lots of dependencies. The software is often highly customized and provided without commercial support, which leads to rather ad-hoc systems and irreproducible results. To let other scientists reproduce the analyses, the full workspace including data, code, the computing environment, and documentation must be bundled and shared. Technologies such as virtualization or containerization allow for the creation of identical computing environments with relatively little effort. Challenges, however, arise when the volume of the data is too large, when computations are done in a cluster environment, or when complex software components such as databases are used. We discuss these challenges for the example of scalable Land use change detection on Landsat imagery. We present a reproducible implementation that runs R and the scalable data management and analytical system SciDB within a Docker container. Thanks to an explicit container recipe (the Dockerfile), this enables the all-in-one reproduction including the installation of software components, the ingestion of the data, and the execution of the analysis in a well-defined environment. We furthermore discuss possibilities how the implementation could be transferred to multi-container environments in order to support reproducibility on large cluster environments.
Ensemble Clustering Classification compete SVM and One-Class classifiers applied on plant microRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbedAllah, Loai

2016-12-22

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that ECkNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.
Ensemble Clustering Classification Applied to Competing SVM and One-Class Classifiers Exemplified by Plant MicroRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbdAllah, Loai

2016-12-01

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that EC-kNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.
Microseismic Monitoring of Stimulating Shale Gas Reservoir in SW China: 2. Spatial Clustering Controlled by the Preexisting Faults and Fractures

NASA Astrophysics Data System (ADS)

Chen, Haichao; Meng, Xiaobo; Niu, Fenglin; Tang, Youcai; Yin, Chen; Wu, Furong

2018-02-01

Microseismic monitoring is crucial to improving stimulation efficiency of hydraulic fracturing treatment, as well as to mitigating potential induced seismic hazard. We applied an improved matching and locating technique to the downhole microseismic data set during one treatment stage along a horizontal well within the Weiyuan shale gas play inside Sichuan Basin in SW China, resulting in 3,052 well-located microseismic events. We employed this expanded catalog to investigate the spatiotemporal evolution of the microseismicity in order to constrain migration of the injected fluids and the associated dynamic processes. The microseismicity is generally characterized by two distinctly different clusters, both of which are highly correlated with the injection activity spatially and temporarily. The distant and well-confined cluster (cluster A) is featured by relatively large-magnitude events, with 40 events of M -1 or greater, whereas the cluster in the immediate vicinity of the wellbore (cluster B) includes two apparent lineations of seismicity with a NE-SW trending, consistent with the predominant orientation of natural fractures. We calculated the b-value and D-value, an index of fracture complexity, and found significant differences between the two seismicity clusters. Particularly, the distant cluster showed an extremely low b-value ( 0.47) and D-value ( 1.35). We speculate that the distant cluster is triggered by reactivation of a preexisting critically stressed fault, whereas the two lineations are induced by shear failures of optimally oriented natural fractures associated with fluid diffusion. In both cases, the spatially clustered microseismicity related to hydraulic stimulation is strongly controlled by the preexisting faults and fractures.
Probing cluster surface morphology by cryo spectroscopy of N2 on cationic nickel clusters

NASA Astrophysics Data System (ADS)

Dillinger, Sebastian; Mohrbach, Jennifer; Niedner-Schatteburg, Gereon

2017-11-01

We present the cryogenic (26 K) IR spectra of selected [Nin(N2)m]+ (n = 5-20, m = 1 - mmax), which strongly reveal n- and m-dependent features in the N2 stretching region, in conjunction with density functional theory modeling of some of these findings. The observed spectral features allow us to refine the kinetic classification [cf. J. Mohrbach, S. Dillinger, and G. Niedner-Schatteburg, J. Chem. Phys. 147, 184304 (2017)] and to define four classes of structure related surface adsorption behavior: Class (1) of Ni6+, Ni13+, and Ni19+ are highly symmetrical clusters with all smooth surfaces of equally coordinated Ni atoms that entertain stepwise N2 adsorption up to stoichiometric N2:Nisurface saturation. Class (2) of Ni12+ and Ni18+ are highly symmetrical clusters minus one. Their relaxed smooth surfaces reorganize by enhanced N2 uptake toward some low coordinated Ni surface atoms with double N2 occupation. Class (3) of Ni5+ and Ni7+ through Ni11+ are small clusters of rough surfaces with low coordinated Ni surface atoms, and some reveal semi-internal Ni atoms of high next-neighbor coordination. Surface reorganization upon N2 uptake turns rough into rough surface by Ni atom migration and turns octahedral based structures into pentagonal bipyramidal structures. Class (4) of Ni14+ through Ni17+ and Ni20+ are large clusters with rough and smooth surface areas. They possess smooth icosahedral surfaces with some proximate capping atom(s) on one hemisphere of the icosahedron with the other one largely unaffected.
2-Way k-Means as a Model for Microbiome Samples.

PubMed

Jackson, Weston J; Agarwal, Ipsita; Pe'er, Itsik

2017-01-01

Motivation . Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k -means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.
2-Way k-Means as a Model for Microbiome Samples

PubMed Central

2017-01-01

Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project. PMID:29177026
Breaking through the false coincidence barrier in electron–ion coincidence experiments

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

Osborn, David L.; Hayden, Carl C.; Hemberger, Patrick

Photoelectron Photoion Coincidence (PEPICO) spectroscopy holds the promise of a universal, isomer-selective, and sensitive analytical technique for time-resolved quantitative analysis of bimolecular chemical reactions. Unfortunately, its low dynamic range of ~10 3 has largely precluded its use for this purpose, where a dynamic range of at least 10 5 is generally required. This limitation is due to the false coincidence background common to all coincidence experiments, especially at high count rates. Electron/ion pairs emanating from separate ionization events but arriving within the ion time of flight (TOF) range of interest constitute the false coincidence background. Although this background has uniformmore » intensity at every m/z value, the Poisson scatter in the false coincidence background obscures small signals. In this paper, temporal ion deflection coupled with a position-sensitive ion detector enables suppression of the false coincidence background, increasing the dynamic range in the PEPICO TOF mass spectrum by 2–3 orders of magnitude. The ions experience a time-dependent electric deflection field at a well-defined fraction of their time of flight. This deflection defines an m/z- and ionization-time dependent ion impact position for true coincidences, whereas false coincidences appear randomly outside this region and can be efficiently suppressed. When cold argon clusters are ionized, false coincidence suppression allows us to observe species up to Ar 9 +, whereas Ar 4 + is the largest observable cluster under traditional operation. As a result, this advance provides mass-selected photoelectron spectra for fast, high sensitivity quantitative analysis of reacting systems.« less
A hexanuclear gold carbonyl cluster† †Dedicated to Prof. Dr Pablo Espinet on the occasion of his 65th birthday. Abbreviations are defined prior to the Acknowledgements section. As defined in ref. 1, “clusters are molecular units which may contain small or large numbers of similar atoms where there are several short internuclear distances between atom pairs.” This definition is fully compatible with that originally given by F. A. Cotton (ref. 2). ‡ ‡Electronic supplementary information (ESI) available: Experimental procedures, comments on the X-ray structure determinations and 3D Hirschfeld surfaces for the ions constituting the crystal of 4. CCDC 1049919–1049921. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c5sc01578b Click here for additional data file. Click here for additional data file.

PubMed Central

Martínez-Salvador, Sonia; Falvello, Larry R.; Martín, Antonio

2015-01-01

The hexanuclear gold carbonyl cluster [PPh4]2[Au6(CF3)6Br2(CO)2] (4) has been obtained by spontaneous self-assembly of the following independent units: CF3AuCO (1) and [PPh4][Br(AuCF3)2] (3). The cyclo-Au6 aggregate 4, in which the components are held together by unassisted, fairly strong aurophilic interactions (Au···Au ∼310 pm), exhibits a cyclohexane-like arrangement with chair conformation. These aurophilic interactions also result in significant ν(CO) lowering: from 2194 cm–1 in the separate component 1 to 2171 cm–1 in the mixed aggregate 4. Procedures to prepare the single-bridged dinuclear component 3 as well as the mononuclear derivative [PPh4][CF3AuBr] (2) are also reported. PMID:28717445
Breaking through the false coincidence barrier in electron–ion coincidence experiments

DOE PAGES

Osborn, David L.; Hayden, Carl C.; Hemberger, Patrick; ...

2016-10-31

Photoelectron Photoion Coincidence (PEPICO) spectroscopy holds the promise of a universal, isomer-selective, and sensitive analytical technique for time-resolved quantitative analysis of bimolecular chemical reactions. Unfortunately, its low dynamic range of ~10 3 has largely precluded its use for this purpose, where a dynamic range of at least 10 5 is generally required. This limitation is due to the false coincidence background common to all coincidence experiments, especially at high count rates. Electron/ion pairs emanating from separate ionization events but arriving within the ion time of flight (TOF) range of interest constitute the false coincidence background. Although this background has uniformmore » intensity at every m/z value, the Poisson scatter in the false coincidence background obscures small signals. In this paper, temporal ion deflection coupled with a position-sensitive ion detector enables suppression of the false coincidence background, increasing the dynamic range in the PEPICO TOF mass spectrum by 2–3 orders of magnitude. The ions experience a time-dependent electric deflection field at a well-defined fraction of their time of flight. This deflection defines an m/z- and ionization-time dependent ion impact position for true coincidences, whereas false coincidences appear randomly outside this region and can be efficiently suppressed. When cold argon clusters are ionized, false coincidence suppression allows us to observe species up to Ar 9 +, whereas Ar 4 + is the largest observable cluster under traditional operation. As a result, this advance provides mass-selected photoelectron spectra for fast, high sensitivity quantitative analysis of reacting systems.« less
Early Transition Metal Oxides as Catalysts: Crossing Scales from Clusters to Single Crystals to Functioning Materials

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

Lai-Sheng Wang

2009-07-07

The overall goal of this program is to investigate the electronic structure and chemical bonding of early transition metal oxide clusters and use them as well-defined molecular models to obtain insight into properties and mechanisms of oxide catalysts, as well as to provide accurate spectroscopic and molecular information to verify theoretical methods used to predict materials properties. A laser vaporization cluster source is used to produce metal oxide clusters with different sizes, structures, and compositions. Well-defined inorganic polyoxometalate clusters in solution are transported in the gas phase using electrospray. Two state-of-the-art photoelectron spectroscopy apparatuses are used to interrogate the oxidemore » clusters and polyoxometalate anions in the gas phase to obtain spectroscopic and electronic structure information. The experimental effort is assisted by theoretical calculations to understanding the structures, chemical bonding, and catalytical properties of the transition metal oxide clusters. The research approach combines novel and flexible experimental techniques and advanced theoretical/computational methodologies and seeks molecular-level information to aiding the design of new catalysts, as well as mechanistic understanding. We have focused on the investigation of tungsten oxide clusters containing three W atoms: W{sub 3}O{sub x}{sup -} (x = 7-11). A number of interesting findings have been made. We observed that the oxygen-poor W{sub 3}O8 cluster contains a localized W{sup 4+} center, which can be used as a molecular model for O-deficient defect sites. A chemisorption energy was obtained through density functional calculations for W{sub 3}O8 + O{sub 2} {yields} W{sub 3}O{sub 10} as -78 kcal/mol. We further found that the neutral stoichiometric W{sub 2}O{sub 6} and W{sub 3}O{sub 9} clusters do not react with O{sub 2} and they only form physi-sorbed complexes, W{sub 2}O{sub 6}(O{sub 2}) and W{sub 3}O{sub 9}(O{sub 2}). However, the negatively charged W{sub 2}O{sub 6}{sup -} and W{sub 3}O{sub 9}{sup -} clusters are found to form chemisorbed complexes due to the presence of the extra electron. Thus, the W{sub 2}O{sub 6}{sup -} and W{sub 3}O{sub 9}{sup -} negative clusters can be viewed as models for O{sub 2} interaction with a reduced W site (W{sup 5+}) on the oxide surface. These studies also led to the surprising observation of the first d-orbital aromatic clusters in W{sub 3}O{sub 9}{sup 2-} and Mo{sub 3}O{sub 9}{sup 2-}, which each contains a completely delocalized three-center two-electron bond made entirely made of the metal d orbitals. This last result was highlighted in both Chem & Eng. News and Nature. We further studied a series of small metalate anions using electrospray, including the hydroxo and methoxo oxometalate MO{sub 3}(OH){sup -} and MO{sub 3}(OCH{sub 3}){sup -}, and the dimetalates: M{sub 2}O{sub 7}{sup 2-}, MM{prime}O{sub 7}{sup 2-}, and M{sub 2}O{sub 7}{sup -} (M, M{prime} = Cr, Mo, and W).« less
Efficient similarity-based data clustering by optimal object to cluster reallocation.

PubMed

Rossignol, Mathias; Lagrange, Mathieu; Cont, Arshia

2018-01-01

We present an iterative flat hard clustering algorithm designed to operate on arbitrary similarity matrices, with the only constraint that these matrices be symmetrical. Although functionally very close to kernel k-means, our proposal performs a maximization of average intra-class similarity, instead of a squared distance minimization, in order to remain closer to the semantics of similarities. We show that this approach permits the relaxing of some conditions on usable affinity matrices like semi-positiveness, as well as opening possibilities for computational optimization required for large datasets. Systematic evaluation on a variety of data sets shows that compared with kernel k-means and the spectral clustering methods, the proposed approach gives equivalent or better performance, while running much faster. Most notably, it significantly reduces memory access, which makes it a good choice for large data collections. Material enabling the reproducibility of the results is made available online.
Ontology-based topic clustering for online discussion data

NASA Astrophysics Data System (ADS)

Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

2013-03-01

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

PubMed

Gavish, Avishai; Barkai, Naama

2016-06-01

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities ('noise') inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ∼800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ∼10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this 'noisy' environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ∼10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations ('noise') in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.
Cluster Dynamical Mass from Magellan Multi-Object Spectroscopy for SGAS Clusters

NASA Astrophysics Data System (ADS)

Murray, Katherine; Sharon, Keren; Johnson, Traci; Gifford, Daniel; Gladders, Michael; Bayliss, Matthew; Florian, Michael; Rigby, Jane R.; Miller, Christopher J.

2016-01-01

Galaxy clusters are giant structures in space consisting of hundreds or thousands of galaxies, interstellar matter, and dark matter, all bound together by gravity. We analyze the spectra of the cluster members of several strong lensing clusters from a large program, the Sloan Giant Arcs Survey, to determine the total mass of the lensing clusters. From spectra obtained with the LDSS3 and IMACS cameras on the Magellan 6.5m telescopes, we measure the spectroscopic redshifts of about 50 galaxies in each cluster, and calculate the velocity distributions within the galaxy clusters, as well as their projected cluster-centric radii. From these two pieces of information, we measure the size and total dynamical mass of each cluster. We can combine this calculation with other measurements of mass of the same galaxy clusters (like measurements from strong lensing or X-ray) to determine the spatial distribution of luminous and dark matter out to the virial radius of the cluster.

Genome-based exploration of the specialized metabolic capacities of the genus Rhodococcus.

PubMed

Ceniceros, Ana; Dijkhuizen, Lubbert; Petrusma, Mirjan; Medema, Marnix H

2017-08-09

Bacteria of the genus Rhodococcus are well known for their ability to degrade a large range of organic compounds. Some rhodococci are free-living, saprophytic bacteria; others are animal and plant pathogens. Recently, several studies have shown that their genomes encode putative pathways for the synthesis of a large number of specialized metabolites that are likely to be involved in microbe-microbe and host-microbe interactions. To systematically explore the specialized metabolic potential of this genus, we here performed a comprehensive analysis of the biosynthetic coding capacity across publicly available rhododoccal genomes, and compared these with those of several Mycobacterium strains as well as that of their mutual close relative Amycolicicoccus subflavus. Comparative genomic analysis shows that most predicted biosynthetic gene cluster families in these strains are clade-specific and lack any homology with gene clusters encoding the production of known natural products. Interestingly, many of these clusters appear to encode the biosynthesis of lipopeptides, which may play key roles in the diverse environments were rhodococci thrive, by acting as biosurfactants, pathogenicity factors or antimicrobials. We also identified several gene cluster families that are universally shared among all three genera, which therefore may have a more 'primary' role in their physiology. Inactivation of these clusters by mutagenesis might help to generate weaker strains that can be used as live vaccines. The genus Rhodococcus thus provides an interesting target for natural product discovery, in view of its large and mostly uncharacterized biosynthetic repertoire, its relatively fast growth and the availability of effective genetic tools for its genomic modification.
Cluster-assembled metallic glasses

PubMed Central

2013-01-01

A bottom-up approach to nanofabricate metallic glasses from metal clusters as building blocks is presented. Considering metallic glasses as a subclass of cluster-assembled materials, the relation between the two lively fields of metal clusters and metallic glasses is pointed out. Deposition of selected clusters or collections of them, generated by state-of-the-art cluster beam sources, could lead to the production of a well-defined amorphous material. In contrast to rapidly quenched glasses where only the composition of the glass can be controlled, in cluster-assembled glasses, one can precisely control the structural building blocks. Comparing properties of glasses with similar compositions but differing in building blocks and therefore different in structure will facilitate the study of structure–property correlation in metallic glasses. This bottom-up method provides a novel alternative path to the synthesis of glassy alloys and will contribute to improving fundamental understanding in the field of metallic glasses. It may even permit the production of glassy materials for alloys that cannot be quenched rapidly enough to circumvent crystallization. Additionally, gaining deeper insight into the parameters governing the structure–property relation in metallic glasses can have a great impact on understanding and design of other cluster-assembled materials. PMID:23899019
Supra-galactic colour patterns in globular cluster systems

NASA Astrophysics Data System (ADS)

Forte, Juan C.

2017-07-01

An analysis of globular cluster systems associated with galaxies included in the Virgo and Fornax Hubble Space Telescope-Advanced Camera Surveys reveals distinct (g - z) colour modulation patterns. These features appear on composite samples of globular clusters and, most evidently, in galaxies with absolute magnitudes Mg in the range from -20.2 to -19.2. These colour modulations are also detectable on some samples of globular clusters in the central galaxies NGC 1399 and NGC 4486 (and confirmed on data sets obtained with different instruments and photometric systems), as well as in other bright galaxies in these clusters. After discarding field contamination, photometric errors and statistical effects, we conclude that these supra-galactic colour patterns are real and reflect some previously unknown characteristic. These features suggest that the globular cluster formation process was not entirely stochastic but included a fraction of clusters that formed in a rather synchronized fashion over large spatial scales, and in a tentative time lapse of about 1.5 Gy at redshifts z between 2 and 4. We speculate that the putative mechanism leading to that synchronism may be associated with large scale feedback effects connected with violent star-forming events and/or with supermassive black holes.
UPDATED MASS SCALING RELATIONS FOR NUCLEAR STAR CLUSTERS AND A COMPARISON TO SUPERMASSIVE BLACK HOLES

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

Scott, Nicholas; Graham, Alister W.

2013-02-15

We investigate whether or not nuclear star clusters and supermassive black holes (SMBHs) follow a common set of mass scaling relations with their host galaxy's properties, and hence can be considered to form a single class of central massive object (CMO). We have compiled a large sample of galaxies with measured nuclear star cluster masses and host galaxy properties from the literature and fit log-linear scaling relations. We find that nuclear star cluster mass, M {sub NC}, correlates most tightly with the host galaxy's velocity dispersion: log M {sub NC} = (2.11 {+-} 0.31)log ({sigma}/54) + (6.63 {+-} 0.09), butmore » has a slope dramatically shallower than the relation defined by SMBHs. We find that the nuclear star cluster mass relations involving host galaxy (and spheroid) luminosity and stellar and dynamical mass, intercept with but are in general shallower than the corresponding black hole scaling relations. In particular, M {sub NC}{proportional_to}M {sup 0.55{+-}0.15} {sub Gal,dyn}; the nuclear cluster mass is not a constant fraction of its host galaxy or spheroid mass. We conclude that nuclear stellar clusters and SMBHs do not form a single family of CMOs.« less
LEM-CF Premixed Tool Kit

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

2015-01-19

The purpose of LEM-CF Premixed Tool Kit is to process premixed flame simulation data from the LEM-CF solver (https://fileshare.craft-tech.com/clusters/view/lem-cf) into a large-eddy simulation (LES) subgrid model database. These databases may be used with a user-defined-function (UDF) that is included in the Tool Kit. The subgrid model UDF may be used with the ANSYS FLUENT flow solver or other commercial flow solvers.
Forest-fire model with natural fire resistance.

PubMed

Yoder, Mark R; Turcotte, Donald L; Rundle, John B

2011-04-01

Observations suggest that contemporary wildfire suppression practices in the United States have contributed to conditions that facilitate large, destructive fires. We introduce a forest-fire model with natural fire resistance that supports this theory. Fire resistance is defined with respect to the size and shape of clusters; the model yields power-law frequency-size distributions of model fires that are consistent with field observations in the United States, Canada, and Australia.
Benchmark CCSD(T) and DFT study of binding energies in Be7 - 12: in search of reliable DFT functional for beryllium clusters

NASA Astrophysics Data System (ADS)

Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel

2018-05-01

We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.
Continental Scale Vegetation Structure Mapping Using Field Calibrated Landsat, ALOS Palsar And GLAS ICESat

NASA Astrophysics Data System (ADS)

Scarth, P.; Phinn, S. R.; Armston, J.; Lucas, R.

2015-12-01

Vertical plant profiles are important descriptors of canopy structure and are used to inform models of biomass, biodiversity and fire risk. In Australia, an approach has been developed to produce large area maps of vertical plant profiles by extrapolating waveform lidar estimates of vertical plant profiles from ICESat/GLAS using large area segmentation of ALOS PALSAR and Landsat satellite image products. The main assumption of this approach is that the vegetation height profiles are consistent across the segments defined from ALOS PALSAR and Landsat image products. More than 1500 field sites were used to develop an index of fractional cover using Landsat data. A time series of the green fraction was used to calculate the persistent green fraction continuously across the landscape. This was fused with ALOS PALSAR L-band Fine Beam Dual polarisation 25m data and used to segment the Australian landscapes. K-means clustering then grouped the segments with similar cover and backscatter into approximately 1000 clusters. Where GLAS-ICESat footprints intersected these clusters, canopy profiles were extracted and aggregated to produce a mean vertical vegetation profile for each cluster that was used to derive mean canopy and understorey height, depth and density. Due to the large number of returns, these retrievals are near continuous across the landscape, enabling them to be used for inventory and modelling applications. To validate this product, a radiative transfer model was adapted to map directional gap probability from airborne waveform lidar datasets to retrieve vertical plant profiles Comparison over several test sites show excellent agreement and work is underway to extend the analysis to improve national biomass mapping. The integration of the three datasets provide options for future operational monitoring of structure and AGB across large areas for quantifying carbon dynamics, structural change and biodiversity.
Effectiveness and cost-effectiveness of telehealthcare for chronic obstructive pulmonary disease: study protocol for a cluster randomized controlled trial.

PubMed

Udsen, Flemming Witt; Lilholt, Pernille Heyckendorff; Hejlesen, Ole; Ehlers, Lars Holger

2014-05-21

Several feasibility studies show promising results of telehealthcare on health outcomes and health-related quality of life for patients suffering from chronic obstructive pulmonary disease, and some of these studies show that telehealthcare may even lower healthcare costs. However, the only large-scale trial we have so far - the Whole System Demonstrator Project in England - has raised doubts about these results since it conclude that telehealthcare as a supplement to usual care is not likely to be cost-effective compared with usual care alone. The present study is known as 'TeleCare North' in Denmark. It seeks to address these doubts by implementing a large-scale, pragmatic, cluster-randomized trial with nested economic evaluation. The purpose of the study is to assess the effectiveness and the cost-effectiveness of a telehealth solution for patients suffering from chronic obstructive pulmonary disease compared to usual practice. General practitioners will be responsible for recruiting eligible participants (1,200 participants are expected) for the trial in the geographical area of the North Denmark Region. Twenty-six municipality districts in the region define the randomization clusters. The primary outcomes are changes in health-related quality of life, and the incremental cost-effectiveness ratio measured from baseline to follow-up at 12 months. Secondary outcomes are changes in mortality and physiological indicators (diastolic and systolic blood pressure, pulse, oxygen saturation, and weight). There has been a call for large-scale clinical trials with rigorous cost-effectiveness assessments in telehealthcare research. This study is meant to improve the international evidence base for the effectiveness and cost-effectiveness of telehealthcare to patients suffering from chronic obstructive pulmonary disease by implementing a large-scale pragmatic cluster-randomized clinical trial. Clinicaltrials.gov, http://NCT01984840, November 14, 2013.
Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

PubMed

Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

2014-04-02

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.
In situ solid-state electrochemistry of mass-selected ions at well-defined electrode–electrolyte interfaces

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

Prabhakaran, Venkateshkumar; Johnson, Grant E.; Wang, Bingbing

2016-11-07

Molecular-level understanding of electrochemical processes occurring at electrode-electrolyte interfaces (EEI) is key to the rational development of high-performance and sustainable electrochemical technologies. This article reports the development and first application of solid-state in situ electrochemical probes to study redox and catalytic processes occurring at well-defined EEI generated using soft-landing of mass- and charge-selected cluster ions (SL). In situ electrochemical probes with excellent mass transfer properties are fabricated using carefully-designed nanoporous ionic liquid membranes. SL enables deposition of pure active species that are not obtainable with other techniques onto electrode surfaces with precise control over charge state, composition, and kinetic energy.more » SL is, therefore, a unique tool for studying fundamental processes occurring at EEI. For the first time using an aprotic electrochemical probe, the effect of charge state (PMo12O403-/2-) and the contribution of building blocks of Keggin polyoxometalate (POM) clusters to redox processes are characterized by populating EEI with novel POM anions generated by electrospray ionization and gas phase dissociation. Additionally, a proton conducting electrochemical probe has been developed to characterize the reactive electrochemistry (oxygen reduction activity) of bare Pt clusters (Pt40 ~1 nm diameter), thus demonstrating the capability of the probe for studying reactions in controlled gaseous environments. The newly developed in situ electrochemical probes combined with ion SL provide a versatile method to characterize the EEI in solid-state redox systems and reactive electrochemistry at precisely-defined conditions. This capability will advance molecular-level understanding of processes occurring at EEI that are critical to many energy-related technologies.« less
Towards a realistic population of simulated galaxy groups and clusters

NASA Astrophysics Data System (ADS)

Le Brun, Amandine M. C.; McCarthy, Ian G.; Schaye, Joop; Ponman, Trevor J.

2014-06-01

We present a new suite of large-volume cosmological hydrodynamical simulations called cosmo-OWLS. They form an extension to the OverWhelmingly Large Simulations (OWLS) project, and have been designed to help improve our understanding of cluster astrophysics and non-linear structure formation, which are now the limiting systematic errors when using clusters as cosmological probes. Starting from identical initial conditions in either the Planck or WMAP7 cosmologies, we systematically vary the most important `sub-grid' physics, including feedback from supernovae and active galactic nuclei (AGN). We compare the properties of the simulated galaxy groups and clusters to a wide range of observational data, such as X-ray luminosity and temperature, gas mass fractions, entropy and density profiles, Sunyaev-Zel'dovich flux, I-band mass-to-light ratio, dominance of the brightest cluster galaxy and central massive black hole (BH) masses, by producing synthetic observations and mimicking observational analysis techniques. These comparisons demonstrate that some AGN feedback models can produce a realistic population of galaxy groups and clusters, broadly reproducing both the median trend and, for the first time, the scatter in physical properties over approximately two decades in mass (1013 M⊙ ≲ M500 ≲ 1015 M⊙) and 1.5 decades in radius (0.05 ≲ r/r500 ≲ 1.5). However, in other models, the AGN feedback is too violent (even though they reproduce the observed BH scaling relations), implying that calibration of the models is required. The production of realistic populations of simulated groups and clusters, as well as models that bracket the observations, opens the door to the creation of synthetic surveys for assisting the astrophysical and cosmological interpretation of cluster surveys, as well as quantifying the impact of selection effects.
Extended phenotype and clinical subgroups in unilateral Meniere disease: A cross-sectional study with cluster analysis.

PubMed

Frejo, L; Martin-Sanz, E; Teggi, R; Trinidad, G; Soto-Varela, A; Santos-Perez, S; Manrique, R; Perez, N; Aran, I; Almeida-Branco, M S; Batuecas-Caletrio, A; Fraile, J; Espinosa-Sanchez, J M; Perez-Guillen, V; Perez-Garrigues, H; Oliva-Dominguez, M; Aleman, O; Benitez, J; Perez, P; Lopez-Escamez, J A

2017-12-01

To define clinical subgroups by cluster analysis in patients with unilateral Meniere disease (MD) and to compare them with the clinical subgroups found in bilateral MD. A cross-sectional study with a two-step cluster analysis. A tertiary referral multicenter study. Nine hundred and eighty-eight adult patients with unilateral MD. best predictors to define clinical subgroups with potential different aetiologies. We established five clusters in unilateral MD. Group 1 is the most frequently found, includes 53% of patients, and it is defined as the sporadic, classic MD without migraine and without autoimmune disorder (AD). Group 2 is found in 8% of patients, and it is defined by hearing loss, which antedates the vertigo episodes by months or years (delayed MD), without migraine or AD in most of cases. Group 3 involves 13% of patients, and it is considered familial MD, while group 4, which includes 15% of patients, is linked to the presence of migraine in all cases. Group 5 is found in 11% of patients and is defined by a comorbid AD. We found significant differences in the distribution of AD in clusters 3, 4 and 5 between patients with uni- and bilateral MD. Cluster analysis defines clinical subgroups in MD, and it extends the phenotype beyond audiovestibular symptoms. This classification will help to improve the phenotyping in MD and facilitate the selection of patients for randomised clinical trials. © 2017 John Wiley & Sons Ltd.
Subnanometer to nanometer transition metal CO oxidation catalysts

DOEpatents

Vajda, Stefan; Fortunelli, Alessandro; Yasumatsu, Hisato

2017-12-26

The present invention provides a catalyst defined in part by a conductive substrate; a film overlaying a surface of the substrate; and a plurality of metal clusters supported by the layer, wherein each cluster comprises between 8 and 11 atoms. Further provided is a catalyst defined in part by a conductive substrate; a layer overlaying a surface of the substrate; and a plurality of metal clusters supported by the layer, wherein each cluster comprises at least two metals.
Growth of Pd Nanoclusters on Single-Layer Graphene on Cu(111)

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

Soy, Esin; Guisinger, Nathan P.; Trenary, Michael

We report scanning tunneling microscopy results on the nucleation and growth of Pd nanoclusters on a single layer of graphene on the Cu(111) surface. The shape, organization, and structural evolution of the Pd nanoclusters were investigated using two different growth methods, continuous and stepwise. The size and shape of the formed nanoclusters were found to greatly depend on the growth technique used. The size and density of spherical Pd nanoclusters increased with increasing coverage during stepwise deposition as a result of coarsening of existing clusters and continued nucleation of new clusters. In contrast, continuous deposition gave rise to well-defined triangularmore » Pd clusters as a result of anisotropic growth on the graphene surface. Exposure to ethylene caused a decrease in the size of the Pd clusters. As a result, this is attributed to the exothermic formation of ethylidyne on the cluster surfaces and an accompanying weakening of the Pd–Pd bonding.« less
Growth of Pd Nanoclusters on Single-Layer Graphene on Cu(111)

DOE PAGES

Soy, Esin; Guisinger, Nathan P.; Trenary, Michael

2017-07-05

We report scanning tunneling microscopy results on the nucleation and growth of Pd nanoclusters on a single layer of graphene on the Cu(111) surface. The shape, organization, and structural evolution of the Pd nanoclusters were investigated using two different growth methods, continuous and stepwise. The size and shape of the formed nanoclusters were found to greatly depend on the growth technique used. The size and density of spherical Pd nanoclusters increased with increasing coverage during stepwise deposition as a result of coarsening of existing clusters and continued nucleation of new clusters. In contrast, continuous deposition gave rise to well-defined triangularmore » Pd clusters as a result of anisotropic growth on the graphene surface. Exposure to ethylene caused a decrease in the size of the Pd clusters. As a result, this is attributed to the exothermic formation of ethylidyne on the cluster surfaces and an accompanying weakening of the Pd–Pd bonding.« less
Spatiotemporal earthquake clusters along the North Anatolian fault zone offshore Istanbul

USGS Publications Warehouse

Bulut, Fatih; Ellsworth, William L.; Bohnhoff, Marco; Aktar, Mustafa; Dresen, Georg

2011-01-01

We investigate earthquakes with similar waveforms in order to characterize spatiotemporal microseismicity clusters within the North Anatolian fault zone (NAFZ) in northwest Turkey along the transition between the 1999 ??zmit rupture zone and the Marmara Sea seismic gap. Earthquakes within distinct activity clusters are relocated with cross-correlation derived relative travel times using the double difference method. The spatiotemporal distribution of micro earthquakes within individual clusters is resolved with relative location accuracy comparable to or better than the source size. High-precision relative hypocenters define the geometry of individual fault patches, permitting a better understanding of fault kinematics and their role in local-scale seismotectonics along the region of interest. Temporal seismic sequences observed in the eastern Sea of Marmara region suggest progressive failure of mostly nonoverlapping areas on adjacent fault patches and systematic migration of microearthquakes within clusters during the progressive failure of neighboring fault patches. The temporal distributions of magnitudes as well as the number of events follow swarmlike behavior rather than a mainshock/aftershock pattern.
bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.
Biclustering of gene expression data using reactive greedy randomized adaptive search procedure.

PubMed

Dharan, Smitha; Nair, Achuthsankar S

2009-01-30

Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix and can be a very useful analysis tool when some genes have multiple functions and experimental conditions are diverse. Cheng and Church have introduced a measure called mean squared residue score to evaluate the quality of a bicluster and has become one of the most popular measures to search for biclusters. In this paper, we review basic concepts of the metaheuristics Greedy Randomized Adaptive Search Procedure (GRASP)-construction and local search phases and propose a new method which is a variant of GRASP called Reactive Greedy Randomized Adaptive Search Procedure (Reactive GRASP) to detect significant biclusters from large microarray datasets. The method has two major steps. First, high quality bicluster seeds are generated by means of k-means clustering. In the second step, these seeds are grown using the Reactive GRASP, in which the basic parameter that defines the restrictiveness of the candidate list is self-adjusted, depending on the quality of the solutions found previously. We performed statistical and biological validations of the biclusters obtained and evaluated the method against the results of basic GRASP and as well as with the classic work of Cheng and Church. The experimental results indicate that the Reactive GRASP approach outperforms the basic GRASP algorithm and Cheng and Church approach. The Reactive GRASP approach for the detection of significant biclusters is robust and does not require calibration efforts.
Abell 1033: birth of a radio phoenix

DOE PAGES

de Gasperin, F.; Ogrean, G. A.; van Weeren, R. J.; ...

2015-02-26

We report that extended steep-spectrum radio emission in a galaxy cluster is usually associated with a recent merger. However, given the complex scenario of galaxy cluster mergers, many of the discovered sources hardly fit into the strict boundaries of a precise taxonomy. This is especially true for radio phoenixes that do not have very well defined observational criteria. Radio phoenixes are aged radio galaxy lobes whose emission is reactivated by compression or other mechanisms. Here in this paper, we present the detection of a radio phoenix close to the moment of its formation. The source is located in Abell 1033,more » a peculiar galaxy cluster which underwent a recent merger. To support our claim, we present unpublished Westerbork Synthesis Radio Telescope and Chandra observations together with archival data from the Very Large Array and the Sloan Digital Sky Survey. We discover the presence of two subclusters displaced along the N–S direction. The two subclusters probably underwent a recent merger which is the cause of a moderately perturbed X-ray brightness distribution. A steep-spectrum extended radio source very close to an active galactic nucleus (AGN) is proposed to be a newly born radio phoenix: the AGN lobes have been displaced/compressed by shocks formed during the merger event. This scenario explains the source location, morphology, spectral index, and brightness. Finally, we show evidence of a density discontinuity close to the radio phoenix and discuss the consequences of its presence.« less

Constructivism in Practice: an Exploratory Study of Teaching Patterns and Student Motivation in Physics Classrooms in Finland, Germany and Switzerland

NASA Astrophysics Data System (ADS)

Beerenwinkel, Anne; von Arx, Matthias

2017-04-01

For the last three decades, moderate constructivism has become an increasingly prominent perspective in science education. Researchers have defined characteristics of constructivist-oriented science classrooms, but the implementation of such science teaching in daily classroom practice seems difficult. Against this background, we conducted a sub-study within the tri-national research project Quality of Instruction in Physics (QuIP) analysing 60 videotaped physics classes involving a large sample of students ( N = 1192) from Finland, Germany and Switzerland in order to investigate the kinds of constructivist components and teaching patterns that can be found in regular classrooms without any intervention. We applied a newly developed coding scheme to capture constructivist facets of science teaching and conducted principal component and cluster analyses to explore which components and patterns were most prominent in the classes observed. Two underlying components were found, resulting in two scales—Structured Knowledge Acquisition and Fostering Autonomy—which describe key aspects of constructivist teaching. Only the first scale was rather well established in the lessons investigated. Classes were clustered based on these scales. The analysis of the different clusters suggested that teaching physics in a structured way combined with fostering students' autonomy contributes to students' motivation. However, our regression models indicated that content knowledge is a more important predictor for students' motivation, and there was no homogeneous pattern for all gender- and country-specific subgroups investigated. The results are discussed in light of recent discussions on the feasibility of constructivism in practice.
A survey of scientific literacy to provide a foundation for designing science communication in Japan.

PubMed

Kawamoto, Shishin; Nakayama, Minoru; Saijo, Miki

2013-08-01

There are various definitions and survey methods for scientific literacy. Taking into consideration the contemporary significance of scientific literacy, we have defined it with an emphasis on its social aspects. To acquire the insights needed to design a form of science communication that will enhance the scientific literacy of each individual, we conducted a large-scale random survey within Japan of individuals older than 18 years, using a printed questionnaire. The data thus acquired were analyzed using factor analysis and cluster analysis to create a 3-factor/4-cluster model of people's interest and attitude toward science, technology and society and their resulting tendencies. Differences were found among the four clusters in terms of the three factors: scientific factor, social factor, and science-appreciating factor. We propose a plan for designing a form of science communication that is appropriate to this current status of scientific literacy in Japan.
Cosmology with void-galaxy correlations.

PubMed

Hamaus, Nico; Wandelt, Benjamin D; Sutter, P M; Lavaux, Guilhem; Warren, Michael S

2014-01-31

Galaxy bias, the unknown relationship between the clustering of galaxies and the underlying dark matter density field is a major hurdle for cosmological inference from large-scale structure. While traditional analyses focus on the absolute clustering amplitude of high-density regions mapped out by galaxy surveys, we propose a relative measurement that compares those to the underdense regions, cosmic voids. On the basis of realistic mock catalogs we demonstrate that cross correlating galaxies and voids opens up the possibility to calibrate galaxy bias and to define a static ruler thanks to the observable geometric nature of voids. We illustrate how the clustering of voids is related to mass compensation and show that volume-exclusion significantly reduces the degree of stochasticity in their spatial distribution. Extracting the spherically averaged distribution of galaxies inside voids from their cross correlations reveals a remarkable concordance with the mass-density profile of voids.
Urban retail location: Insights from percolation theory and spatial interaction modeling

PubMed Central

Molinero, Carlos; Wilson, Alan

2017-01-01

Characterising road networks has been the focus of a large body of research due to it being the main driver of activities in an urban ecosystem and the structuring factor in the dynamics of the city. One of these activities, and one with the largest economical impact in a city, is retail dynamics and its evolution. Therefore, the mathematical modeling of the location of retail activities and of the emergence of clustering in retail centers has as well generated a large number of works. Despite these two interwoven components strongly depending on one another and their fundamental importance in understanding cities, little work has been done in order to compare their local and global properties. Here we compare the road network’s hierarchical structure, unveiled through a percolation analysis of the network, with the retail location distribution defined by exploiting a gravity-based retail model. We interpret the great agreement in the city’s organizations as it emerges from both methodologies as new evidence of the interdependence of these two crucial dimensions of a city’s life. PMID:28977032
Urban retail location: Insights from percolation theory and spatial interaction modeling.

PubMed

Piovani, Duccio; Molinero, Carlos; Wilson, Alan

2017-01-01

Characterising road networks has been the focus of a large body of research due to it being the main driver of activities in an urban ecosystem and the structuring factor in the dynamics of the city. One of these activities, and one with the largest economical impact in a city, is retail dynamics and its evolution. Therefore, the mathematical modeling of the location of retail activities and of the emergence of clustering in retail centers has as well generated a large number of works. Despite these two interwoven components strongly depending on one another and their fundamental importance in understanding cities, little work has been done in order to compare their local and global properties. Here we compare the road network's hierarchical structure, unveiled through a percolation analysis of the network, with the retail location distribution defined by exploiting a gravity-based retail model. We interpret the great agreement in the city's organizations as it emerges from both methodologies as new evidence of the interdependence of these two crucial dimensions of a city's life.
Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

2003-01-01

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292
Sample size determination for GEE analyses of stepped wedge cluster randomized trials.

PubMed

Li, Fan; Turner, Elizabeth L; Preisser, John S

2018-06-19

In stepped wedge cluster randomized trials, intact clusters of individuals switch from control to intervention from a randomly assigned period onwards. Such trials are becoming increasingly popular in health services research. When a closed cohort is recruited from each cluster for longitudinal follow-up, proper sample size calculation should account for three distinct types of intraclass correlations: the within-period, the inter-period, and the within-individual correlations. Setting the latter two correlation parameters to be equal accommodates cross-sectional designs. We propose sample size procedures for continuous and binary responses within the framework of generalized estimating equations that employ a block exchangeable within-cluster correlation structure defined from the distinct correlation types. For continuous responses, we show that the intraclass correlations affect power only through two eigenvalues of the correlation matrix. We demonstrate that analytical power agrees well with simulated power for as few as eight clusters, when data are analyzed using bias-corrected estimating equations for the correlation parameters concurrently with a bias-corrected sandwich variance estimator. © 2018, The International Biometric Society.
Molecular Typing of Mycobacterium Tuberculosis Complex by 24-Locus Based MIRU-VNTR Typing in Conjunction with Spoligotyping to Assess Genetic Diversity of Strains Circulating in Morocco

PubMed Central

Bouklata, Nada; Supply, Philip; Jaouhari, Sanae; Charof, Reda; Seghrouchni, Fouad; Sadki, Khalid; El Achhab, Youness; Nejjari, Chakib; Filali-Maltouf, Abdelkarim

2015-01-01

Background Standard 24-locus Mycobacterial Interspersed Repetitive Unit Variable Number Tandem Repeat (MIRU-VNTR) typing allows to get an improved resolution power for tracing TB transmission and predicting different strain (sub) lineages in a community. Methodology During 2010–2012, a total of 168 Mycobacterium tuberculosis Complex (MTBC) isolates were collected by cluster sampling from 10 different Moroccan cities, and centralized by the National Reference Laboratory of Tuberculosis over the study period. All isolates were genotyped using spoligotyping, and a subset of 75 was genotyped using 24-locus based MIRU-VNTR typing, followed by first line drug susceptibility testing. Corresponding strain lineages were predicted using MIRU-VNTRplus database. Principal Findings Spoligotyping resulted in 137 isolates in 18 clusters (2–50 isolates per cluster: clustering rate of 81.54%) corresponding to a SIT number in the SITVIT database, while 31(18.45%) patterns were unique of which 10 were labelled as “unknown” according to the same database. The most prevalent spoligotype family was LAM; (n = 81 or 48.24% of isolates, dominated by SIT42, n = 49), followed by Haarlem (23.80%), T superfamily (15.47%), >Beijing (2.97%), > U clade (2.38%) and S clade (1.19%). Subsequent 24-Locus MIRU-VNTR typing identified 64 unique types and 11 isolates in 5 clusters (2 to 3isolates per cluster), substantially reducing clusters defined by spoligotyping only. The single cluster of three isolates corresponded to two previously treated MDR-TB cases and one new MDR-TB case known to be contact a same index case and belonging to a same family, albeit residing in 3 different administrative regions. MIRU-VNTR loci 4052, 802, 2996, 2163b, 3690, 1955, 424, 2531, 2401 and 960 were highly discriminative in our setting (HGDI >0.6). Conclusions 24-locus MIRU-VNTR typing can substantially improve the resolution of large clusters initially defined by spoligotyping alone and predominating in Morocco, and could therefore be used to better study tuberculosis transmission in a population-based, multi-year sample context. PMID:26285026
Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

NASA Astrophysics Data System (ADS)

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2017-07-01

The reconstruction of the signal from hadrons and jets emerging from the proton-proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.
Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1.

PubMed

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von Radziewski, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Milosavljevic, M Vranjes; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, T; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Wasicki, C; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Wessels, M; Wetter, J; Whalen, K; Wharton, A M; White, A; White, M J; White, R; White, S; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, A; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winter, B T; Wittgen, M; Wittkowski, J; Wollstadt, S J; Wolter, M W; Wolters, H; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamada, M; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yurkewicz, A; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Nedden, M Zur; Zurzolo, G; Zwalinski, L

2017-01-01

The reconstruction of the signal from hadrons and jets emerging from the proton-proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.
Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

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

Aad, G.; Abbott, B.; Abdallah, J.

The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections dependingmore » on the nature of the cluster. Lastly, topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.« less
Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2017-07-24

The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections dependingmore » on the nature of the cluster. Lastly, topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.« less
Final Report for "Non-Accelerator Physics – Research in High Energy Physics: Dark Energy Research on DES"

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

Ritz, Steve; Jeltema, Tesla

One of the greatest mysteries in modern cosmology is the fact that the expansion of the universe is observed to be accelerating. This acceleration may stem from dark energy, an additional energy component of the universe, or may indicate that the theory of general relativity is incomplete on cosmological scales. The growth rate of large-scale structure in the universe and particularly the largest collapsed structures, clusters of galaxies, is highly sensitive to the underlying cosmology. Clusters will provide one of the single most precise methods of constraining dark energy with the ongoing Dark Energy Survey (DES). The accuracy of themore » cosmological constraints derived from DES clusters necessarily depends on having an optimized and well-calibrated algorithm for selecting clusters as well as an optical richness estimator whose mean relation and scatter compared to cluster mass are precisely known. Calibrating the galaxy cluster richness-mass relation and its scatter was the focus of the funded work. Specifically, we employ X-ray observations and optical spectroscopy with the Keck telescopes of optically-selected clusters to calibrate the relationship between optical richness (the number of galaxies in a cluster) and underlying mass. This work also probes aspects of cluster selection like the accuracy of cluster centering which are critical to weak lensing cluster studies.« less
Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping.

PubMed

Frickenhaus, Stephan; Kannan, Srinivasaraghavan; Zacharias, Martin

2009-02-01

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.
Assessing the performance of dispersionless and dispersion-accounting methods: helium interaction with cluster models of the TiO2(110) surface.

PubMed

de Lara-Castells, María Pilar; Stoll, Hermann; Mitrushchenkov, Alexander O

2014-08-21

As a prototypical dispersion-dominated physisorption problem, we analyze here the performance of dispersionless and dispersion-accounting methodologies on the helium interaction with cluster models of the TiO2(110) surface. A special focus has been given to the dispersionless density functional dlDF and the dlDF+Das construction for the total interaction energy (K. Pernal, R. Podeswa, K. Patkowski, and K. Szalewicz, Phys. Rev. Lett. 2009, 109, 263201), where Das is an effective interatomic pairwise functional form for the dispersion. Likewise, the performance of symmetry-adapted perturbation theory (SAPT) method is evaluated, where the interacting monomers are described by density functional theory (DFT) with the dlDF, PBE, and PBE0 functionals. Our benchmarks include CCSD(T)-F12b calculations and comparative analysis on the nuclear bound states supported by the He-cluster potentials. Moreover, intra- and intermonomer correlation contributions to the physisorption interaction are analyzed through the method of increments (H. Stoll, J. Chem. Phys. 1992, 97, 8449) at the CCSD(T) level of theory. This method is further applied in conjunction with a partitioning of the Hartree-Fock interaction energy to estimate individual interaction energy components, comparing them with those obtained using the different SAPT(DFT) approaches. The cluster size evolution of dispersionless and dispersion-accounting energy components is then discussed, revealing the reduced role of the dispersionless interaction and intramonomer correlation when the extended nature of the surface is better accounted for. On the contrary, both post-Hartree-Fock and SAPT(DFT) results clearly demonstrate the high-transferability character of the effective pairwise dispersion interaction whatever the cluster model is. Our contribution also illustrates how the method of increments can be used as a valuable tool not only to achieve the accuracy of CCSD(T) calculations using large cluster models but also to evaluate the performance of SAPT(DFT) methods for the physically well-defined contributions to the total interaction energy. Overall, our work indicates the excellent performance of a dlDF+Das approach in which the parameters are optimized using the smallest cluster model of the target surface to treat van der Waals adsorbate-surface interactions.
Determinación de miembros, binaridad y metalicidad de gigantes rojas en el cúmulo abierto de edad intermedia NGC 2354

NASA Astrophysics Data System (ADS)

Clariá, J. J.; Mermilliod, J. C.; Piatti, A. E.

We present new Coravel radial-velocity observations and photoelectric photometry in the UBV, DDO and Washington systems for a sample of red giant candidates in the field of the intermediate-age open cluster NGC 2354. Photometric membership probabilities show very good agrement with those obtained from Coravel radial velocities. The analysis of the photometric and kinematical data allow us to confirm cluster membership for 9 red giants, one of them being a spectroscopic binary, while 4 confirmed spectroscopic binaries appear to be probable members. We have also discovered 4 spectroscopic binaries not belonging to the cluster. A mean radial velocity of (33.40±0.27)km s-1 and a mean reddening E(B-V)= 0.13±0.03 were derived for the cluster giants. NGC 2354 has a mean ultraviolet excess <δ(U-B)>=-0.03±0.01, relative to the field K giants, and a mean new cyanogen anomaly ΔCN=-0.035±0.007, both implying [Fe/H]≈-0.3. The moderately metal-poor character of NGC 2354 is confirmed using five different metal abundance indicators of the Washington system. The cluster giant branch is formed by a well defined clump of 7 stars and 4 stars with high membership probabilities seem to define an ascending giant branch. The whole red giant locus cannot be reproduced by any theoretical track. This paper will appear in Astron. & Astrophys. Suppl. (1999).
Improving the distinguishable cluster results: spin-component scaling

NASA Astrophysics Data System (ADS)

Kats, Daniel

2018-06-01

The spin-component scaling is employed in the energy evaluation to improve the distinguishable cluster approach. SCS-DCSD reaction energies reproduce reference values with a root-mean-squared deviation well below 1 kcal/mol, the interaction energies are three to five times more accurate than DCSD, and molecular systems with a large amount of static electron correlation are still described reasonably well. SCS-DCSD represents a pragmatic approach to achieve chemical accuracy with a simple method without triples, which can also be applied to multi-configurational molecular systems.
Analysis of group B streptococcal isolates from infants and pregnant women in Portugal revealing two lineages with enhanced invasiveness.

PubMed

Martins, E R; Pessanha, M A; Ramirez, M; Melo-Cristino, J

2007-10-01

The populations of group B streptococcus (GBS) associated with vaginal carriage in pregnant women and invasive neonatal infections in Portugal were compared. GBS isolates were characterized by serotyping, pulsed-field gel electrophoresis (PFGE) profiling, and multilocus sequence typing (MLST). Serotypes III and V accounted for 44% of all colonization isolates (n = 269), whereas serotypes III and Ia amounted to 69% of all invasive isolates (n = 64). Whereas serotype Ia was associated with early-onset disease (EOD), serotype III was associated with late-onset disease (LOD). Characterization by PFGE and MLST identified very diverse populations in carriage and invasive disease. Serotype Ia was represented mainly by a single PFGE cluster defined by sequence type 23 (ST23) and the infrequent ST24. In contrast, serotype III was found in a large number of PFGE clusters and STs, but a single PFGE cluster defined by ST17 was found to be associated with invasive disease. Although serotype III was associated only with LOD, ST17 showed an enhanced capacity to cause both EOD and LOD. Our data reinforce the evidence for enhanced invasiveness of ST17 and identify a lineage expressing serotype Ia capsule and represented by ST23 and ST24 as having enhanced potential to cause EOD.
The neuropeptide PDF acts directly on evening pacemaker neurons to regulate multiple features of circadian behavior.

PubMed

Lear, Bridget C; Zhang, Luoying; Allada, Ravi

2009-07-01

Discrete clusters of circadian clock neurons temporally organize daily behaviors such as sleep and wake. In Drosophila, a network of just 150 neurons drives two peaks of timed activity in the morning and evening. A subset of these neurons expresses the neuropeptide pigment dispersing factor (PDF), which is important for promoting morning behavior as well as maintaining robust free-running rhythmicity in constant conditions. Yet, how PDF acts on downstream circuits to mediate rhythmic behavior is unknown. Using circuit-directed rescue of PDF receptor mutants, we show that PDF targeting of just approximately 30 non-PDF evening circadian neurons is sufficient to drive morning behavior. This function is not accompanied by large changes in core molecular oscillators in light-dark, indicating that PDF RECEPTOR likely regulates the output of these cells under these conditions. We find that PDF also acts on this focused set of non-PDF neurons to regulate both evening activity phase and period length, consistent with modest resetting effects on core oscillators. PDF likely acts on more distributed pacemaker neuron targets, including the PDF neurons themselves, to regulate rhythmic strength. Here we reveal defining features of the circuit-diagram for PDF peptide function in circadian behavior, revealing the direct neuronal targets of PDF as well as its behavioral functions at those sites. These studies define a key direct output circuit sufficient for multiple PDF dependent behaviors.
High-Volume Repeaters of Self-Harm.

PubMed

Ness, Jennifer; Hawton, Keith; Bergen, Helen; Waters, Keith; Kapur, Navneet; Cooper, Jayne; Steeg, Sarah; Clarke, Martin

2016-11-01

Repetition of self-harm is common and is strongly associated with suicide. Despite this, there is limited research on high-volume repetition. To investigate individuals with high-volume repeat self-harm attendances to the emergency department (ED), including their patterns of attendance and mortality. Data from the Multicentre Study of Self-Harm in England were used. High-volume repetition was defined as ⩾15 attendances within 4 years. An attendance timeline was constructed for each high-volume repeater (HVR) and the different patterns of attendance were explored using an executive sorting task and hierarchical cluster analysis. A small proportion of self-harm patients are HVRs (0.6%) but they account for a large percentage of self-harm attendances (10%). In this study, the new methodological approach resulted in three types of attendance patterns. All of the HVRs had clusters of attendance and a greater proportion died from external causes compared with non-HVRs. The approach used in this study offers a new method for investigating this problem that could have both clinical and research benefits. The need for early intervention is highlighted by the large number of self-harm episodes per patient, the clustered nature of attendances, and the higher prevalence of death from external causes.

Large hydrogen-bonded pre-nucleation (HSO4-)(H2SO4)m(H2O)k and (HSO4-)(NH3)(H2SO4)m(H2O)k clusters in the earth's atmosphere.

PubMed

Herb, Jason; Xu, Yisheng; Yu, Fangqun; Nadykto, A B

2013-01-10

The importance of pre-nucleation cluster stability as the key parameter controlling nucleation of atmospheric airborne ions is well-established. In this Article, large ternary ionic (HSO(4)(-))(H(2)SO(4))(m)(NH(3))(H(2)O)(n) clusters have been studied using Density Functional Theory (DFT) and composite ab initio methods. Twenty classes of clusters have been investigated, and thermochemical properties of common atmospheric (HSO(4)(-))(H(2)SO(4))(m)(NH(3))(0)(H(2)O)(k) and (HSO(4)(-))(H(2)SO(4))(m)(NH(3))(1)(H(2)O)(n) clusters (with m, k, and n up to 3) have been obtained. A large amount of new themochemical and structural data ready-to-use for constraining kinetic nucleation models has been reported. We have performed a comprehensive thermochemical analysis of the obtained data and have investigated the impacts of ammonia and negatively charged bisulfate ion on stability of binary clusters in some detail. The comparison of theoretical predictions and experiments shows that the PW91PW91/6-311++G(3df,3pd) results are in very good agreement with both experimental data and high level ab initio CCSD(T)/CBS values and suggest that the PW91PW91/6-311++G(3df,3pd) method is a viable alternative to higher level ab initio methods in studying large pre-nucleation clusters, for which the higher level computations are prohibitively expensive. The uncertainties in both theory and experiments have been investigated, and possible ways of their reduction have been proposed.
Dispersed metal cluster catalysts by design. Synthesis, characterization, structure, and performance

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

Arslan, Ilke; Dixon, David A.; Gates, Bruce C.

2015-09-30

To understand the class of metal cluster catalysts better and to lay a foundation for the prediction of properties leading to improved catalysts, we have synthesized metal catalysts with well-defined structures and varied the cluster structures and compositions systematically—including the ligands bonded to the metals. These ligands include supports and bulky organics that are being tuned to control both the electron transfer to or from the metal and the accessibility of reactants to influence catalytic properties. We have developed novel syntheses to prepare these well-defined catalysts with atomic-scale control the environment by choice and placement of ligands and applied state-of-themore » art spectroscopic, microscopic, and computational methods to determine their structures, reactivities, and catalytic properties. The ligands range from nearly flat MgO surfaces to enveloping zeolites to bulky calixarenes to provide controlled coverages of the metal clusters, while also enforcing unprecedented degrees of coordinative unsaturation at the metal site—thereby facilitating bonding and catalysis events at exposed metal atoms. With this wide range of ligand properties and our arsenal of characterization tools, we worked to achieve a deep, fundamental understanding of how to synthesize robust supported and ligand-modified metal clusters with controlled catalytic properties, thereby bridging the gap between active site structure and function in unsupported and supported metal catalysts. We used methods of organometallic and inorganic chemistry combined with surface chemistry for the precise synthesis of metal clusters and nanoparticles, characterizing them at various stages of preparation and under various conditions (including catalytic reaction conditions) and determining their structures and reactivities and how their catalytic properties depend on their compositions and structures. Key characterization methods included IR, NMR, and EXAFS spectroscopies to identify ligands on the metals and their reactions; EXAFS spectroscopy and high-resolution STEM to determine cluster framework structures and changes resulting from reactant treatment and locations of metal atoms on support surfaces; X-ray diffraction crystallography to determine full structures of cluster-ligand combinations in the absence of a support, and TEM with tomographic methods to observe individual metal atoms and determine three-dimensional structures of catalysts. Electronic structure calculations were used to verify and interpret spectra and extend the understanding of reactivity beyond what is measurable experimentally.« less
Homogenous Population Genetic Structure of the Non-Native Raccoon Dog (Nyctereutes procyonoides) in Europe as a Result of Rapid Population Expansion

PubMed Central

Drygala, Frank; Korablev, Nikolay; Ansorge, Hermann; Fickel, Joerns; Isomursu, Marja; Elmeros, Morten; Kowalczyk, Rafał; Baltrunaite, Laima; Balciauskas, Linas; Saarma, Urmas; Schulze, Christoph; Borkenhagen, Peter; Frantz, Alain C.

2016-01-01

The extent of gene flow during the range expansion of non-native species influences the amount of genetic diversity retained in expanding populations. Here, we analyse the population genetic structure of the raccoon dog (Nyctereutes procyonoides) in north-eastern and central Europe. This invasive species is of management concern because it is highly susceptible to fox rabies and an important secondary host of the virus. We hypothesized that the large number of introduced animals and the species’ dispersal capabilities led to high population connectivity and maintenance of genetic diversity throughout the invaded range. We genotyped 332 tissue samples from seven European countries using 16 microsatellite loci. Different algorithms identified three genetic clusters corresponding to Finland, Denmark and a large ‘central’ population that reached from introduction areas in western Russia to northern Germany. Cluster assignments provided evidence of long-distance dispersal. The results of an Approximate Bayesian Computation analysis supported a scenario of equal effective population sizes among different pre-defined populations in the large central cluster. Our results are in line with strong gene flow and secondary admixture between neighbouring demes leading to reduced genetic structuring, probably a result of its fairly rapid population expansion after introduction. The results presented here are remarkable in the sense that we identified a homogenous genetic cluster inhabiting an area stretching over more than 1500km. They are also relevant for disease management, as in the event of a significant rabies outbreak, there is a great risk of a rapid virus spread among raccoon dog populations. PMID:27064784
Acute chest syndrome is associated with single nucleotide polymorphism-defined beta globin cluster haplotype in children with sickle cell anaemia

PubMed Central

Bean, Christopher J.; Boulet, Sheree L.; Yang, Genyan; Payne, Amanda B.; Ghaji, Nafisa; Pyle, Meredith E.; Hooper, W. Craig; Bhatnagar, Pallav; Keefer, Jeffrey; Barron-Casella, Emily A.; Casella, James F.; DeBaun, Michael R.

2013-01-01

Summary Genetic diversity at the human β-globin locus has been implicated as a modifier of sickle cell anaemia (SCA) severity. However, haplotypes defined by restriction fragment length polymorphism sites across the β-globin locus have not been consistently associated with clinical phenotypes. To define the genetic structure at the β-globin locus more thoroughly, we performed high-density single nucleotide polymorphism (SNP) mapping in 820 children who were homozygous for the sickle cell mutation (HbSS). Genotyping results revealed very high linkage disequilibrium across a large region spanning the locus control region and the HBB (β-globin gene) cluster. We identified three predominant haplotypes accounting for 96% of the βS-carrying chromosomes in this population that could be distinguished using a minimal set of common SNPs. Consistent with previous studies, fetal haemoglobin level was significantly associated with βS-haplotypes. After controlling for covariates, an association was detected between haplotype and rate of hospitalization for acute chest syndrome (ACS) (incidence rate ratio 0.51, 95% confidence interval 0.29–0.89) but not incidence rate of vaso-occlusive pain or presence of silent cerebral infarct (SCI). Our results suggest that these SNP-defined βS-haplotypes may be associated with ACS, but not pain or SCI in a study population of children with SCA. PMID:23952145
m-BIRCH: an online clustering approach for computer vision applications

NASA Astrophysics Data System (ADS)

Madan, Siddharth K.; Dana, Kristin J.

2015-03-01

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

PubMed Central

Ek, Stina; Rizzuto, Debora; Fratiglioni, Laura; Johnell, Kristina; Xu, Weili

2018-01-01

Abstract Background Although falls in older adults are related to multiple risk factors, these factors have commonly been studied individually. We aimed to identify risk profiles for injurious falls in older adults by detecting clusters of established risk factors and quantifying their impact on fall risk. Methods Participants were 2,566 people, aged 60 years and older, from the population-based Swedish National Study on Aging and Care in Kungsholmen. Injurious falls was defined as hospitalization for or receipt of outpatient care because a fall. Cluster analysis was used to identify aggregation of possible risk factors including chronic diseases, fall-risk increasing drugs (FRIDs), physical and cognitive impairments, and lifestyle-related factors. Associations between the clusters and injurious falls over 3, 5, and 10 years were estimated using flexible parametric survival models. Results Five clusters were identified including: a “healthy”, a “well-functioning with multimorbidity”, a “well-functioning, with multimorbidity and high FRID consumption”, a “physically and cognitively impaired”, and a “disabled” cluster. The risk of injurious falls for all groups was significantly higher than for the first cluster of healthy individuals in the reference category. Hazard ratios (95% confidence intervals) ranged from 1.71 (1.02–2.66) for the second cluster to 12.67 (7.38–21.75) for the last cluster over 3 years of follow-up. The highest risk was observed in the last two clusters with high burden of physical and cognitive impairments. Conclusion Risk factors for injurious fall tend to aggregate, representing different levels of risk for falls. Our findings can be useful to tailor and prioritize clinical and public health interventions. PMID:28605455
Sand sources and transport pathways for the San Francisco Bay coastal system, based on X-ray diffraction mineralogy

USGS Publications Warehouse

Hein, James R.; Mizell, Kira; Barnard, Patrick L.; Barnard, P.L.; Jaffee, B.E.; Schoellhamer, D.H.

2013-01-01

The mineralogical compositions of 119 samples collected from throughout the San Francisco Bay coastal system, including bayfloor and seafloor, area beaches, cliff outcrops, and major drainages, were determined using X-ray diffraction (XRD). Comparison of the mineral concentrations and application of statistical cluster analysis of XRD spectra allowed for the determination of provenances and transport pathways. The use of XRD mineral identifications provides semi-quantitative compositions needed for comparisons of beach and offshore sands with potential cliff and river sources, but the innovative cluster analysis of XRD diffraction spectra provides a unique visualization of how groups of samples within the San Francisco Bay coastal system are related so that sand-sized sediment transport pathways can be inferred. The main vector for sediment transport as defined by the XRD analysis is from San Francisco Bay to the outer coast, where the sand then accumulates on the ebb tidal delta and also moves alongshore. This mineralogical link defines a critical pathway because large volumes of sediment have been removed from the Bay over the last century via channel dredging, aggregate mining, and borrow pit mining, with comparable volumes of erosion from the ebb tidal delta over the same period, in addition to high rates of shoreline retreat along the adjacent, open-coast beaches. Therefore, while previously only a temporal relationship was established, the transport pathway defined by mineralogical and geochemical tracers support the link between anthropogenic activities in the Bay and widespread erosion outside the Bay. The XRD results also establish the regional and local importance of sediment derived from cliff erosion, as well as both proximal and distal fluvial sources. This research is an important contribution to a broader provenance study aimed at identifying the driving forces for widespread geomorphic change in a heavily urbanized coastal-estuarine system.
REVIEWS OF TOPICAL PROBLEMS: Large-scale star formation in galaxies

NASA Astrophysics Data System (ADS)

Efremov, Yurii N.; Chernin, Artur D.

2003-01-01

A brief review is given of the history of modern ideas on the ongoing star formation process in the gaseous disks of galaxies. Recent studies demonstrate the key role of the interplay between the gas self-gravitation and its turbulent motions. The large scale supersonic gas flows create structures of enhanced density which then give rise to the gravitational condensation of gas into stars and star clusters. Formation of star clusters, associations and complexes is considered, as well as the possibility of isolated star formation. Special emphasis is placed on star formation under the action of ram pressure.
Iron-carbide cluster thermal dynamics for catalyzed carbon nanotube growth

NASA Astrophysics Data System (ADS)

Ding, Feng; Bolton, Kim; Rosén, Arne

2004-07-01

Molecular dynamics simulations have been used to study the thermal behavior of FeN-mCm clusters where N, the total number of atoms, extends up to 2400. Comparison of the computed results with experimental data shows that the simulations yield the correct trends for the liquid-solid region of the iron-carbide phase diagram as well as the correct dependence of cluster melting point as a function of cluster size. The calculation indicates that, when carbon nanotubes (CNTs) are grown on large (>3-4 nm) catalyst particles at low temperatures (<1200 K), the catalyst particles are not completely molten. It is argued that the mechanism of CNT growth under these conditions may be governed by the surface melting of the cluster. .
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.
Social network-based recruitment successfully reveals HIV-1 transmission networks among high-risk individuals in El Salvador.

PubMed

Dennis, Ann M; Murillo, Wendy; de Maria Hernandez, Flor; Guardado, Maria Elena; Nieto, Ana Isabel; Lorenzana de Rivera, Ivette; Eron, Joseph J; Paz-Bailey, Gabriela

2013-05-01

HIV in Central America is concentrated among certain groups such as men who have sex with men (MSM) and female sex workers (FSWs). We compared social recruitment chains and HIV transmission clusters from 699 MSM and 787 FSWs to better understand factors contributing to ongoing HIV transmission in El Salvador. Phylogenies were reconstructed using pol sequences from 119 HIV-positive individuals recruited by respondent-driven sampling (RDS) and compared with RDS chains in 3 cities in El Salvador. Transmission clusters with a mean pairwise genetic distance ≤ 0.015 and Bayesian posterior probabilities =1 were identified. Factors associated with cluster membership were evaluated among MSM. Sequences from 34 (43%) MSM and 4 (10%) FSW grouped in 14 transmission clusters. Clusters were defined by risk group (12 MSM clusters) and geographic residence (only 1 spanned separate cities). In 4 MSM clusters (all n = 2), individuals were also members of the same RDS chain, but only 2 had members directly linked through recruitment. All large clusters (n ≥ 3) spanned >1 RDS chain. Among MSM, factors independently associated with cluster membership included recent infection by BED assay (P = 0.02), sex with stable male partners (P = 0.02), and sex with ≥ 3 male partners in the past year (P = 0.04). We found few HIV transmissions corresponding directly with the social recruitment. However, we identified clustering in nearly one-half of MSM suggesting that RDS recruitment was indirectly but successfully uncovering transmission networks, particularly among recent infections. Interrogating RDS chains with phylogenetic analyses may help refine methods for identifying transmission clusters.
Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

NASA Technical Reports Server (NTRS)

Thompson, David R.; Mandrake, Lukas; Green, Robert O.

2013-01-01

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.
Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

PubMed Central

Villandre, Luc; Günthard, Huldrych F.; Kouyos, Roger; Stadler, Tanja

2016-01-01

Background Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. Methods The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index. Results and Conclusion Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs. PMID:26863322
A 10-year population based study of 'opt-out' HIV testing of tuberculosis patients in Alberta, Canada: national implications.

PubMed

Long, Richard; Niruban, Selvanayagam; Heffernan, Courtney; Cooper, Ryan; Fisher, Dina; Ahmed, Rabia; Egedahl, Mary Lou; Fur, Rhonda

2014-01-01

Compliance with the recommendation that all tuberculosis (TB) patients be tested for human immunodeficiency virus (HIV) has not yet been achieved in Canada or globally. The experience of "opt-out" HIV testing of TB patients in the Province of Alberta, Canada is described over a 10-year period, 2003-2012. Testing rates are reported before and after the introduction of the "opt-out" approach. Risk factors for HIV seropositivity are described and demographic, clinical and laboratory characteristics of TB patients who were newly diagnosed versus previously diagnosed with HIV are compared. Genotypic clusters, defined as groups of two or more cases whose isolates of Mycobacterium tuberculosis had identical DNA fingerprints over the 10-year period or within 2 years of one another, were analyzed for their ability to predict HIV co-infection. HIV testing rates were 26% before and 90% after the introduction of "opt-out" testing. During the "opt-out" testing years those <15 or >64 years of age at diagnosis were less likely to have been tested. In those tested the prevalence of HIV was 5.6%. In the age group 15-64 years, risk factors for HIV were: age (35-64 years), Canadian-born Aboriginal or foreign-born sub-Saharan African origin, and combined respiratory and non-respiratory disease. Compared to TB patients previously known to be HIV positive, TB patients newly discovered to be HIV positive had more advanced HIV disease (lower CD4 counts; higher viral loads) at diagnosis. Large cluster size was associated with Aboriginal ancestry. Cluster size predicted HIV co-infection in Aboriginal peoples when clusters included all cases reported over 10 years but not when clusters included cases reported within 2 years of one another. "Opt-out" HIV testing of TB patients is effective and well received. Universal HIV testing of TB patients (>80% of patients tested) has immediate (patients) and longer-term (TB/HIV program planning) benefits.
Improving Prediction of Large-scale Regime Transitions

NASA Astrophysics Data System (ADS)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these synoptic classes, both in the observations and the CFSv2, are investigated. At a future point in the project, the results from these multiscale investigations will be integrated in the form of a prediction tool for important variables (temperatures, precipitation and their extremes) for the 1-4 week timeframe.
Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL.

PubMed

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

2017-01-09

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

PubMed

Frank, Stefan; Roberts, Daniel E; Rikvold, Per Arne

2005-02-08

The influence of nearest-neighbor diffusion on the decay of a metastable low-coverage phase (monolayer adsorption) in a square lattice-gas model of electrochemical metal deposition is investigated by kinetic Monte Carlo simulations. The phase-transformation dynamics are compared to the well-established Kolmogorov-Johnson-Mehl-Avrami theory. The phase transformation is accelerated by diffusion, but remains in accord with the theory for continuous nucleation up to moderate diffusion rates. At very high diffusion rates the phase-transformation kinetic shows a crossover to instantaneous nucleation. Then, the probability of medium-sized clusters is reduced in favor of large clusters. Upon reversal of the supersaturation, the adsorbate desorbs, but large clusters still tend to grow during the initial stages of desorption. Calculation of the free energy of subcritical clusters by enumeration of lattice animals yields a quasiequilibrium distribution which is in reasonable agreement with the simulation results. This is an improvement relative to classical droplet theory, which fails to describe the distributions, since the macroscopic surface tension is a bad approximation for small clusters.
Cluster Analysis of Rat Olfactory Bulb Responses to Diverse Odorants

PubMed Central

Falasconi, Matteo; Leon, Michael; Johnson, Brett A.; Marco, Santiago

2012-01-01

In an effort to deepen our understanding of mammalian olfactory coding, we have used an objective method to analyze a large set of odorant-evoked activity maps collected systematically across the rat olfactory bulb to determine whether such an approach could identify specific glomerular regions that are activated by related odorants. To that end, we combined fuzzy c-means clustering methods with a novel validity approach based on cluster stability to evaluate the significance of the fuzzy partitions on a data set of glomerular layer responses to a large diverse group of odorants. Our results confirm the existence of glomerular response clusters to similar odorants. They further indicate a partial hierarchical chemotopic organization wherein larger glomerular regions can be subdivided into smaller areas that are rather specific in their responses to particular functional groups of odorants. These clusters bear many similarities to, as well as some differences from, response domains previously proposed for the glomerular layer of the bulb. These data also provide additional support for the concept of an identity code in the mammalian olfactory system. PMID:22459165
A Massive Warm Baryonic Halo in the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall K.; Lieu, Richard

2003-01-01

Several deep PSPC observations of the Coma Cluster reveal a very large scale halo of soft X-ray emission, substantially in excess of the well-known radiation from the hot intracluster medium. The excess emission, previously reported in the central region of the cluster using lower sensitivity Extreme Ultraviolet Explorer (EUVE) and ROSAT data, is now evident out to a radius of 2.6 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The X-ray spectrum at these large radii cannot be modeled nonthermally but is consistent with the original scenario of thermal emission from warm gas at approx. 10(exp 6) K. The mass of the warm gas is on par with that of the hot X-ray-emitting plasma and significantly more massive if the warm gas resides in low-density filamentary structures. Thus, the data lend vital support to current theories of cosmic evolution, which predict that at low redshift approx. 30%-40% of the baryons reside in warm filaments converging at clusters of galaxies.
Modulation of Subseasonal Tropical Cyclone Genesis In The Western North Pacific By Wave Activities

NASA Astrophysics Data System (ADS)

Gao, Jianyun; Cheung, Kevin K. W.

2017-04-01

Tropical cyclone (TC) activity is well known to possess variability on multiple timescales, ranging from inter-decadal to intraseasonal. In this study, the subseasonal variability of TC genesis in the western North Pacific (WNP) is examined during summer (May-October) for the period of 1979-2015. In particular, clustering of TC activity within subseasonal timescale is the focus. First, three phases (active, normal and inactive phases) of TC clustering are defined based on the statistics of genesis frequency. Then the modes of subseasonal modulation of these three phases by intraseasonal (30-60-day) oscillation (ISO), biweekly (10-20-day) oscillation (BWO), and the convectively coupled equatorial waves (CCEW), including Rossby, Kelvin, and mixed Rossby-gravity and tropical depression-type waves are considered. It is found that the embedding large-scale circulation is significantly different between the inactive phase and the other phases. Further, the intensities and propagation phases of the ISO, BWO and CCEW play different roles to modulate TC genesis frequency during the active and normal phase. Considering the lag correlation of these subseasonal modulation modes and TC genesis, it is possible to construct a statistical model for the purpose of extended-range forecasting of subseasonal variability of TC occurrence over the WNP.

RNF17 blocks promiscuous activity of PIWI proteins in mouse testes.

PubMed

Wasik, Kaja A; Tam, Oliver H; Knott, Simon R; Falciatori, Ilaria; Hammell, Molly; Vagin, Vasily V; Hannon, Gregory J

2015-07-01

PIWI proteins and their associated piRNAs protect germ cells from the activity of mobile genetic elements. Two classes of piRNAs—primary and secondary—are defined by their mechanisms of biogenesis. Primary piRNAs are processed directly from transcripts of piRNA cluster loci, whereas secondary piRNAs are generated in an adaptive amplification loop, termed the ping-pong cycle. In mammals, piRNA populations are dynamic, shifting as male germ cells develop. Embryonic piRNAs consist of both primary and secondary species and are mainly directed toward transposons. In meiotic cells, the piRNA population is transposon-poor and largely restricted to primary piRNAs derived from pachytene piRNA clusters. The transition from the embryonic to the adult piRNA pathway is not well understood. Here we show that RNF17 shapes adult meiotic piRNA content by suppressing the production of secondary piRNAs. In the absence of RNF17, ping-pong occurs inappropriately in meiotic cells. Ping-pong initiates piRNA responses against not only transposons but also protein-coding genes and long noncoding RNAs, including genes essential for germ cell development. Thus, the sterility of Rnf17 mutants may be a manifestation of a small RNA-based autoimmune reaction. © 2015 Wasik et al.; Published by Cold Spring Harbor Laboratory Press.
RNF17 blocks promiscuous activity of PIWI proteins in mouse testes

PubMed Central

Wasik, Kaja A.; Tam, Oliver H.; Knott, Simon R.; Falciatori, Ilaria; Hammell, Molly; Vagin, Vasily V.; Hannon, Gregory J.

2015-01-01

PIWI proteins and their associated piRNAs protect germ cells from the activity of mobile genetic elements. Two classes of piRNAs—primary and secondary—are defined by their mechanisms of biogenesis. Primary piRNAs are processed directly from transcripts of piRNA cluster loci, whereas secondary piRNAs are generated in an adaptive amplification loop, termed the ping-pong cycle. In mammals, piRNA populations are dynamic, shifting as male germ cells develop. Embryonic piRNAs consist of both primary and secondary species and are mainly directed toward transposons. In meiotic cells, the piRNA population is transposon-poor and largely restricted to primary piRNAs derived from pachytene piRNA clusters. The transition from the embryonic to the adult piRNA pathway is not well understood. Here we show that RNF17 shapes adult meiotic piRNA content by suppressing the production of secondary piRNAs. In the absence of RNF17, ping-pong occurs inappropriately in meiotic cells. Ping-pong initiates piRNA responses against not only transposons but also protein-coding genes and long noncoding RNAs, including genes essential for germ cell development. Thus, the sterility of Rnf17 mutants may be a manifestation of a small RNA-based autoimmune reaction. PMID:26115953
Highlighting Astyanax Species Diversity through DNA Barcoding

PubMed Central

Oliveira, Carlos Alexandre Miranda; de Melo, Filipe Augusto Gonçalves; Bertaco, Vinicius de Araújo; de Astarloa, Juan M. Díaz; Rosso, Juan J.; Foresti, Fausto; Oliveira, Claudio

2016-01-01

DNA barcoding has been used extensively to solve taxonomic questions and identify new species. Neotropical fishes are found in a wide variety of shapes and sizes, with a large number of species yet to be described, many of which are very difficult to identify. Characidae is the most species-rich family of the Characiformes, and many of its genera are affected by taxonomic uncertainties, including the widely-distributed, species-rich genus Astyanax. In this study, we present an extensive analysis of Astyanax covering almost its entire area of occurrence, based on DNA barcoding. The use of different approaches (ABGD, GMYC and BIN) to the clustering of the sequences revealed ample consistency in the results obtained by the initial cutoff value of 2% divergence for putative species in the Neighbor-Joining analysis using the Kimura-2-parameter model. The results indicate the existence of five Astyanax lineages. Some groups, such as that composed by the trans-Andean forms, are mostly composed of well-defined species, and in others a number of nominal species are clustered together, hampering the delimitation of species, which in many cases proved impossible. The results confirm the extreme complexity of the systematics of the genus Astyanax and show that DNA barcoding can be an useful tool to address these complexes questions. PMID:27992537
Design of partially supervised classifiers for multispectral image data

NASA Technical Reports Server (NTRS)

Jeon, Byeungwoo; Landgrebe, David

1993-01-01

A partially supervised classification problem is addressed, especially when the class definition and corresponding training samples are provided a priori only for just one particular class. In practical applications of pattern classification techniques, a frequently observed characteristic is the heavy, often nearly impossible requirements on representative prior statistical class characteristics of all classes in a given data set. Considering the effort in both time and man-power required to have a well-defined, exhaustive list of classes with a corresponding representative set of training samples, this 'partially' supervised capability would be very desirable, assuming adequate classifier performance can be obtained. Two different classification algorithms are developed to achieve simplicity in classifier design by reducing the requirement of prior statistical information without sacrificing significant classifying capability. The first one is based on optimal significance testing, where the optimal acceptance probability is estimated directly from the data set. In the second approach, the partially supervised classification is considered as a problem of unsupervised clustering with initially one known cluster or class. A weighted unsupervised clustering procedure is developed to automatically define other classes and estimate their class statistics. The operational simplicity thus realized should make these partially supervised classification schemes very viable tools in pattern classification.
Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.

PubMed

Jadhav, Rohit R; Ye, Zhenqing; Huang, Rui-Lan; Liu, Joseph; Hsu, Pei-Yin; Huang, Yi-Wen; Rangel, Leticia B; Lai, Hung-Cheng; Roa, Juan Carlos; Kirma, Nameer B; Huang, Tim Hui-Ming; Jin, Victor X

2015-01-01

Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines. Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα-) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17β-estradiol (E2) and demethylating agent 5-aza-2'-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer. Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.
Mass Modeling of Frontier Fields Cluster MACS J1149.5+2223 Using Strong and Weak Lensing

NASA Astrophysics Data System (ADS)

Finney, Emily Quinn; Bradač, Maruša; Huang, Kuang-Han; Hoag, Austin; Morishita, Takahiro; Schrabback, Tim; Treu, Tommaso; Borello Schmidt, Kasper; Lemaux, Brian C.; Wang, Xin; Mason, Charlotte

2018-05-01

We present a gravitational-lensing model of MACS J1149.5+2223 using ultra-deep Hubble Frontier Fields imaging data and spectroscopic redshifts from HST grism and Very Large Telescope (VLT)/MUSE spectroscopic data. We create total mass maps using 38 multiple images (13 sources) and 608 weak-lensing galaxies, as well as 100 multiple images of 31 star-forming regions in the galaxy that hosts supernova Refsdal. We find good agreement with a range of recent models within the HST field of view. We present a map of the ratio of projected stellar mass to total mass (f ⋆) and find that the stellar mass fraction for this cluster peaks on the primary BCG. Averaging within a radius of 0.3 Mpc, we obtain a value of < {f}\\star > ={0.012}-0.003+0.004, consistent with other recent results for this ratio in cluster environments, though with a large global error (up to δf ⋆ = 0.005) primarily due to the choice of IMF. We compare values of f ⋆ and measures of star formation efficiency for this cluster to other Hubble Frontier Fields clusters studied in the literature, finding that MACS1149 has a higher stellar mass fraction than these other clusters but a star formation efficiency typical of massive clusters.
Prospects for Determining the Mass Distributions of Galaxy Clusters on Large Scales Using Weak Gravitational Lensing

NASA Astrophysics Data System (ADS)

Fong, M.; Bowyer, R.; Whitehead, A.; Lee, B.; King, L.; Applegate, D.; McCarthy, I.

2018-05-01

For more than two decades, the Navarro, Frenk, and White (NFW) model has stood the test of time; it has been used to describe the distribution of mass in galaxy clusters out to their outskirts. Stacked weak lensing measurements of clusters are now revealing the distribution of mass out to and beyond their virial radii, where the NFW model is no longer applicable. In this study we assess how well the parameterised Diemer & Kravstov (DK) density profile describes the characteristic mass distribution of galaxy clusters extracted from cosmological simulations. This is determined from stacked synthetic lensing measurements of the 50 most massive clusters extracted from the Cosmo-OWLS simulations, using the Dark Matter Only run and also the run that most closely matches observations. The characteristics of the data reflect the Weighing the Giants survey and data from the future Large Synoptic Survey Telescope (LSST). In comparison with the NFW model, the DK model favored by the stacked data, in particular for the future LSST data, where the number density of background galaxies is higher. The DK profile depends on the accretion history of clusters which is specified in the current study. Eventually however subsamples of galaxy clusters with qualities indicative of disparate accretion histories could be studied.
Clustering impact regime with shocks in freely evolving granular gas

NASA Astrophysics Data System (ADS)

Isobe, Masaharu

2017-06-01

A freely cooling granular gas without any external force evolves from the initial homogeneous state to the inhomogeneous clustering state, at which the energy decay deviates from the Haff's law. The asymptotic behavior of energy in the inelastic hard sphere model have been predicted by several theories, which are based on the mode coupling theory or extension of inelastic hard rods gas. In this study, we revisited the clustering regime of freely evolving granular gas via large-scale molecular dynamics simulation with up to 16.7 million inelastic hard disks. We found novel regime regarding on collisions between "clusters" spontaneously appearing after clustering regime, which can only be identified more than a few million particles system. The volumetric dilatation pattern of semicircular shape originated from density shock propagation are well characterized on the appearing of "cluster impact" during the aggregation process of clusters.
Description of Eurystomatella sinica n. gen., n. sp., with establishment of a new family Eurystomatellidae n. fam. (Protista, Ciliophora, Scuticociliatia) and analyses of its phylogeny inferred from sequences of the small-subunit rRNA gene.

PubMed

Miao, Miao; Wang, Yangang; Song, Weibo; Clamp, John C; Al-Rasheid, Khaled A S

2010-02-01

Recently, an undescribed marine ciliate was isolated from China. Investigation of its morphology and infraciliature revealed it as an undescribed species representing a new genus, Eurystomatella n. gen., the type of the new family Eurystomatellidae n. fam. The new family is defined by close-set, apically positioned oral membranelles and a dominant buccal field that is surrounded by an almost completely circular paroral membrane. The new genus is defined by having a small oral membranelle 1 (M1), bipartite M2 and well-developed M3, a body surface faintly sculptured with a silverline system in a quadrangular, reticulate pattern and a cytostome located at the anterior third of a large buccal field. The type species of the new genus, Eurystomatella sinica n. sp., is a morphologically unique form that is defined mainly by the combination of a conspicuously flattened body, several caudal cilia, extremely long cilia associated with the buccal apparatus and a contractile vacuole located subcaudally. According to phylogenetic analyses of small-subunit (SSU) rRNA gene sequences, Eurystomatella clusters with the genus Cyclidium, as a sister group to the family Pleuronematidae. The great divergence in both buccal and somatic ciliature between Eurystomatella and all other known scuticociliates supports the establishment of a new family for Eurystomatella.
Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres.

PubMed

Banerjee, Arindam; Ghosh, Joydeep

2004-05-01

Competitive learning mechanisms for clustering, in general, suffer from poor performance for very high-dimensional (>1000) data because of "curse of dimensionality" effects. In applications such as document clustering, it is customary to normalize the high-dimensional input vectors to unit length, and it is sometimes also desirable to obtain balanced clusters, i.e., clusters of comparable sizes. The spherical kmeans (spkmeans) algorithm, which normalizes the cluster centers as well as the inputs, has been successfully used to cluster normalized text documents in 2000+ dimensional space. Unfortunately, like regular kmeans and its soft expectation-maximization-based version, spkmeans tends to generate extremely imbalanced clusters in high-dimensional spaces when the desired number of clusters is large (tens or more). This paper first shows that the spkmeans algorithm can be derived from a certain maximum likelihood formulation using a mixture of von Mises-Fisher distributions as the generative model, and in fact, it can be considered as a batch-mode version of (normalized) competitive learning. The proposed generative model is then adapted in a principled way to yield three frequency-sensitive competitive learning variants that are applicable to static data and produced high-quality and well-balanced clusters for high-dimensional data. Like kmeans, each iteration is linear in the number of data points and in the number of clusters for all the three algorithms. A frequency-sensitive algorithm to cluster streaming data is also proposed. Experimental results on clustering of high-dimensional text data sets are provided to show the effectiveness and applicability of the proposed techniques. Index Terms-Balanced clustering, expectation maximization (EM), frequency-sensitive competitive learning (FSCL), high-dimensional clustering, kmeans, normalized data, scalable clustering, streaming data, text clustering.
Efficient data management in a large-scale epidemiology research project.

PubMed

Meyer, Jens; Ostrzinski, Stefan; Fredrich, Daniel; Havemann, Christoph; Krafczyk, Janina; Hoffmann, Wolfgang

2012-09-01

This article describes the concept of a "Central Data Management" (CDM) and its implementation within the large-scale population-based medical research project "Personalized Medicine". The CDM can be summarized as a conjunction of data capturing, data integration, data storage, data refinement, and data transfer. A wide spectrum of reliable "Extract Transform Load" (ETL) software for automatic integration of data as well as "electronic Case Report Forms" (eCRFs) was developed, in order to integrate decentralized and heterogeneously captured data. Due to the high sensitivity of the captured data, high system resource availability, data privacy, data security and quality assurance are of utmost importance. A complex data model was developed and implemented using an Oracle database in high availability cluster mode in order to integrate different types of participant-related data. Intelligent data capturing and storage mechanisms are improving the quality of data. Data privacy is ensured by a multi-layered role/right system for access control and de-identification of identifying data. A well defined backup process prevents data loss. Over the period of one and a half year, the CDM has captured a wide variety of data in the magnitude of approximately 5terabytes without experiencing any critical incidents of system breakdown or loss of data. The aim of this article is to demonstrate one possible way of establishing a Central Data Management in large-scale medical and epidemiological studies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Tri-Laboratory Linux Capacity Cluster 2007 SOW

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

Seager, M

2007-03-22

The Advanced Simulation and Computing (ASC) Program (formerly know as Accelerated Strategic Computing Initiative, ASCI) has led the world in capability computing for the last ten years. Capability computing is defined as a world-class platform (in the Top10 of the Top500.org list) with scientific simulations running at scale on the platform. Example systems are ASCI Red, Blue-Pacific, Blue-Mountain, White, Q, RedStorm, and Purple. ASC applications have scaled to multiple thousands of CPUs and accomplished a long list of mission milestones on these ASC capability platforms. However, the computing demands of the ASC and Stockpile Stewardship programs also include a vastmore » number of smaller scale runs for day-to-day simulations. Indeed, every 'hero' capability run requires many hundreds to thousands of much smaller runs in preparation and post processing activities. In addition, there are many aspects of the Stockpile Stewardship Program (SSP) that can be directly accomplished with these so-called 'capacity' calculations. The need for capacity is now so great within the program that it is increasingly difficult to allocate the computer resources required by the larger capability runs. To rectify the current 'capacity' computing resource shortfall, the ASC program has allocated a large portion of the overall ASC platforms budget to 'capacity' systems. In addition, within the next five to ten years the Life Extension Programs (LEPs) for major nuclear weapons systems must be accomplished. These LEPs and other SSP programmatic elements will further drive the need for capacity calculations and hence 'capacity' systems as well as future ASC capability calculations on 'capability' systems. To respond to this new workload analysis, the ASC program will be making a large sustained strategic investment in these capacity systems over the next ten years, starting with the United States Government Fiscal Year 2007 (GFY07). However, given the growing need for 'capability' systems as well, the budget demands are extreme and new, more cost effective ways of fielding these systems must be developed. This Tri-Laboratory Linux Capacity Cluster (TLCC) procurement represents the ASC first investment vehicle in these capacity systems. It also represents a new strategy for quickly building, fielding and integrating many Linux clusters of various sizes into classified and unclassified production service through a concept of Scalable Units (SU). The programmatic objective is to dramatically reduce the overall Total Cost of Ownership (TCO) of these 'capacity' systems relative to the best practices in Linux Cluster deployments today. This objective only makes sense in the context of these systems quickly becoming very robust and useful production clusters under the crushing load that will be inflicted on them by the ASC and SSP scientific simulation capacity workload.« less
Mechanism of unconfined dust explosions: Turbulent clustering and radiation-induced ignition.

PubMed

Liberman, Michael; Kleeorin, Nathan; Rogachevskii, Igor; Haugen, Nils Erland L

2017-05-01

It is known that unconfined dust explosions typically start off with a relatively weak primary flame followed by a severe secondary explosion. We show that clustering of dust particles in a temperature stratified turbulent flow ahead of the primary flame may give rise to a significant increase in the radiation penetration length. These particle clusters, even far ahead of the flame, are sufficiently exposed and heated by the radiation from the flame to become ignition kernels capable to ignite a large volume of fuel-air mixtures. This efficiently increases the total flame surface area and the effective combustion speed, defined as the rate of reactant consumption of a given volume. We show that this mechanism explains the high rate of combustion and overpressures required to account for the observed level of damage in unconfined dust explosions, e.g., at the 2005 Buncefield vapor-cloud explosion. The effect of the strong increase of radiation transparency due to turbulent clustering of particles goes beyond the state of the art of the application to dust explosions and has many implications in atmospheric physics and astrophysics.
Web service module for access to g-Lite

NASA Astrophysics Data System (ADS)

Goranova, R.; Goranov, G.

2012-10-01

G-Lite is a lightweight grid middleware for grid computing installed on all clusters of the European Grid Infrastructure (EGI). The middleware is partially service-oriented and does not provide well-defined Web services for job management. The existing Web services in the environment cannot be directly used by grid users for building service compositions in the EGI. In this article we present a module of well-defined Web services for job management in the EGI. We describe the architecture of the module and the design of the developed Web services. The presented Web services are composable and can participate in service compositions (workflows). An example of usage of the module with tools for service compositions in g-Lite is shown.
Mod-2 wind turbine system cluster research test program. Volume 1: Initial plan E-1290

NASA Technical Reports Server (NTRS)

Gordon, L. H.

1982-01-01

Upon completion of the design and development of three Mod-2 wind turbines, a series of research experiments are planned to gather data on and evaluate the performance, environmental effects, and operation of a cluster as well as a single, large multimegawatt wind turbine. Information on the program objectives, a Mod-2 system description, a planned schedule, organizational roles, and responsibilities, is included.
Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

PubMed

Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

2016-07-14

In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.
[Scleroderma cluster among type-setters].

PubMed

Magnavita, N

2007-01-01

The etiology of systemic sclerosis, probably multifactorial, is not yet well defined. Among the many endogenous and exogenous factors probably involved, occupational elements may play an essential role. Here we report a cluster of local scleroderma and systemic sclerosis, which occurred in a small group of typography workers exposed to polyvinyl-acetate glues, containing up to 1% of vinyl-acetate. Vinyl acetate exposure has been associated with acidification of the intracellular environment, which is thought to produce cytotoxic and/or mitogenic responses that are the sentinel pharmacodynamic steps toward cancer. Autoantibody production in systemic sclerosis depends upon intracellular acidification. More studies are needed to clarify the relationship between vinyl acetate exposure and scleroderma.
Binding branched and linear DNA structures: From isolated clusters to fully bonded gels

NASA Astrophysics Data System (ADS)

Fernandez-Castanon, J.; Bomboi, F.; Sciortino, F.

2018-01-01

The proper design of DNA sequences allows for the formation of well-defined supramolecular units with controlled interactions via a consecution of self-assembling processes. Here, we benefit from the controlled DNA self-assembly to experimentally realize particles with well-defined valence, namely, tetravalent nanostars (A) and bivalent chains (B). We specifically focus on the case in which A particles can only bind to B particles, via appropriately designed sticky-end sequences. Hence AA and BB bonds are not allowed. Such a binary mixture system reproduces with DNA-based particles the physics of poly-functional condensation, with an exquisite control over the bonding process, tuned by the ratio, r, between B and A units and by the temperature, T. We report dynamic light scattering experiments in a window of Ts ranging from 10 °C to 55 °C and an interval of r around the percolation transition to quantify the decay of the density correlation for the different cases. At low T, when all possible bonds are formed, the system behaves as a fully bonded network, as a percolating gel, and as a cluster fluid depending on the selected r.
Prognostic factors and outcome in anorexia nervosa: a follow-up study.

PubMed

Errichiello, Luca; Iodice, Davide; Bruzzese, Dario; Gherghi, Marco; Senatore, Ignazio

2016-03-01

Anorexia nervosa is an eating disorder characterized by food restriction, irrational fear of gaining weight and consequent weight loss. High mortality rates have been reported, mostly due to suicide and malnutrition. Good outcomes largely vary between 18 and 42%. We aimed to assess outcome and prognostic factors of a large group of patients with anorexia nervosa. Moreover we aimed to identify clusters of prognostic factors related to specific outcomes. We retrospectively reviewed data of 100 patients diagnosed with anorexia nervosa previously hospitalized in a tertiary level structure. Then we performed follow-up structured telephone interviews. We identified four dead patients, while 34% were clinically recovered. In univariate analysis, short duration of inpatient treatment (p = 0.003), short duration of disorder (p = 0.001), early age at first inpatient treatment (p = 0.025) and preserved insight (p = 0.029) were significantly associated with clinical recovery at follow-up. In multiple logistic regression analysis, duration of first inpatient treatment, duration of disorder and preserved insight maintained their association with outcome. Moreover multiple correspondence analysis and cluster analysis allowed to identify different typologies of patients with specific features. Notably, group 1 was characterized by two or more inpatient treatments, BMI ≤ 14, absence of insight, history of long-term inpatient treatments, first inpatient treatment ≥30 days. While group 4 was characterized by preserved insight, BMI ≥ 16, first inpatient treatment ≤14 days, no more than one inpatient treatment, no psychotropic drugs intake, duration of illness ≤4 years. We confirmed the association between short duration of inpatient treatment, short duration of disorder, early age at first inpatient treatment, preserved insight and clinical recovery. We also differentiated patients with anorexia nervosa in well-defined outcome groups according to specific clusters of prognostic factors. Our study might help clinicians to evaluate prognosis of patients with anorexia nervosa.
Electron exchange between r-keggin tungstoaluminates and a well-defined cluster-anion probe for studies in electron transfer

Treesearch

Yurii V. Geletii; Craig L. Hill; Alan J. Bailey; Kenneth I. Hardcastle; Rajai H. Atalla; Ira A. Weinstock

2005-01-01

Fully oxidized [alpha]-AlIIIW12O405-(1ox), and one-electron-reduced [alpha]-AlIIIW12O406-(1red), are well-behaved (stable and free of ion pairing) over a wide range of pH and ionic-strength values at room temperature in water. Having established this, 27Al NMR spectroscopy is used to measure rates of electron exchange between 1ox (27Al NMR: 72.2 ppm relative to Al(H2O)...

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

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

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

2017-07-24

Metal-organic frameworks (MOFs), with their well-ordered pore networks and tunable surface chemistries, offer a versatile platform for preparing well-defined nanostructures wherein functionality such as catalysis can be incorporated. We resolved the atomic structure of Ni-oxo species deposited in the MOF NU-1000 through atomic layer deposition using local and long-range structure probes, including X-ray absorption spectroscopy, pair distribution function analysis and difference envelope density analysis, with electron microscopy imaging and computational modeling.
A diagnostic for determining the quality of single-reference electron correlation methods

NASA Technical Reports Server (NTRS)

Lee, Timothy J.; Taylor, Peter R.

1989-01-01

It was recently proposed that the Euclidian norm of the t(sub 1) vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appopriate. This diagnostic, T(sub 1) is defined for use with self-consistent-field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T(sub 1) is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of non-dynamical electron correlation and is far superior to C(sub 0) from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T(sub 1) (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
A diagnostic for determining the quality of single-reference electron correlation methods

NASA Technical Reports Server (NTRS)

Lee, Timothy J.; Taylor, Peter R.

1989-01-01

It was recently proposed that the Euclidian norm of the t sub 1 vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appropriate. This diagnostic, T sub 1, is defined for use with self consistent field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T sub 1 is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of nondynamical electron correlation and is far superior to C sub 0 from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T sub 1 (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
Puma (Puma concolor) epididymal sperm morphometry

PubMed Central

Cucho, Hernán; Alarcón, Virgilio; Ordóñez, César; Ampuero, Enrique; Meza, Aydee; Soler, Carles

2016-01-01

The Andean puma (Puma concolor) has not been widely studied, particularly in reference to its semen characteristics. The aim of the present study was to define the morphometry of puma sperm heads and classify their subpopulations by cluster analysis. Samples were recovered postmortem from two epididymides from one animal and prepared for morphological observation after staining with the Hemacolor kit. Morphometric data were obtained from 581 spermatozoa using a CASA-Morph system, rendering 13 morphometric parameters. The principal component (PC) analysis was performed followed by cluster analysis for the establishment of subpopulations. Two PC components were obtained, the first related to size and the second to shape. Three subpopulations were observed, corresponding to elongated and intermediate-size sperm heads and acrosomes, to large heads with large acrosomes, and to small heads with short acrosomes. In conclusion, puma spermatozoa showed no uniform sperm morphology but three clear subpopulations. These results should be used for future work in the establishment of an adequate germplasm bank of this species. PMID:27678466
Puma (Puma concolor) epididymal sperm morphometry.

PubMed

Cucho, Hernán; Alarcón, Virgilio; Ordóñez, César; Ampuero, Enrique; Meza, Aydee; Soler, Carles

2016-01-01

The Andean puma (Puma concolor) has not been widely studied, particularly in reference to its semen characteristics. The aim of the present study was to define the morphometry of puma sperm heads and classify their subpopulations by cluster analysis. Samples were recovered postmortem from two epididymides from one animal and prepared for morphological observation after staining with the Hemacolor kit. Morphometric data were obtained from 581 spermatozoa using a CASA-Morph system, rendering 13 morphometric parameters. The principal component (PC) analysis was performed followed by cluster analysis for the establishment of subpopulations. Two PC components were obtained, the first related to size and the second to shape. Three subpopulations were observed, corresponding to elongated and intermediate-size sperm heads and acrosomes, to large heads with large acrosomes, and to small heads with short acrosomes. In conclusion, puma spermatozoa showed no uniform sperm morphology but three clear subpopulations. These results should be used for future work in the establishment of an adequate germplasm bank of this species.
A comprehensive study of the rich open star cluster NGC 2099 based on deep BVI CCD observations

NASA Astrophysics Data System (ADS)

Nilakshi,; Sagar, R.

2002-01-01

The CCD observations of the rich open star cluster NGC 2099 and its surrounding field region have been carried out up to a limiting magnitude of V ~ 22 mag in B, V and I passbands for the first time. A total of ~ 12 000 stars have been observed in the area of about 24arcmin x 34arcmin in the cluster region, as well as ~ 2180 stars in the ~ 12arcmin x 12arcmin area of the field region located ~ 45arcmin away from the cluster center. The cluster parameters determined by fitting the convective core overshoot isochrones in the V, (B-V) and V, (V-I) diagrams are E(B-V) = 0.30+/-0.04 mag, distance = 1360+/- 100 pc, age = 400 Myr and metallicity Z = 0.008. A well-defined cluster main sequence spread over about 8 mag in range is observed for the first time. Its intrinsic spread amounting to ~ 0.06 mag in colour is almost the same over the entire brightness and can be understood in terms of the presence of physical/optical binaries. The core and cluster radii determined from the radial stellar density profiles are 185 arcsec and 1000 arcsec respectively. Only about 22% of cluster members are present in the core region. The effects of mass segregation, most probably due to dynamical evolution, have been observed in the cluster. The mass function slope of the entire cluster is ~ -0.67+/-0.12. It becomes closer to the Salpeter value of -1.35, if flattening in the cluster mass function due to presence of both binaries and a much more extended corona is considered. Full Table 4 is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/381/65
Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town

PubMed Central

2011-01-01

Background The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated. Results A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented. Conclusions The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters. PMID:21513556
Hierarchical Cluster Formation in Concentrated Monoclonal Antibody Formulations

NASA Astrophysics Data System (ADS)

Godfrin, P. Douglas; Zarzar, Jonathan; Zarraga, Isidro Dan; Porcar, Lionel; Falus, Peter; Wagner, Norman; Liu, Yun

Reversible cluster formation has been identified as an underlying cause of large solution viscosities observed in some concentrated monoclonal antibody (mAb) formulations. As high solution viscosity prevents the use of subcutaneous injection as a delivery method for some mAbs, a fundamental understanding of the interactions responsible for high viscosities in concentrated mAb solutions is of significant relevance to mAb applications in human health care as well as of intellectual interest. Here, we present a detailed investigation of a well-studied IgG1 based mAb to relate the short time dynamics and microstructure to significant viscosity changes over a range of pharmaceutically relevant physiochemical conditions. Using a combination of experimental techniques, it is found that upon adding Na2SO4, these antibodies dimerize in solution. Proteins form strongly bounded reversible dimers at dilute concentrations that, when concentrated, interact with each other to form loosely bounded, large, transient clusters. The combined effect of forming strongly bounded dimers and a large transient network is a significant increase in the solution viscosity. Strongly bounded, reversible dimers may exist in many IgG1 based mAb systems such that these results contribute to a more comprehensive understanding of the physical mechanisms producing high viscosities in concentrated protein solutions.
Merger driven star-formation activity in Cl J1449+0856 at z=1.99 as seen by ALMA and JVLA

NASA Astrophysics Data System (ADS)

Coogan, R. T.; Daddi, E.; Sargent, M. T.; Strazzullo, V.; Valentino, F.; Gobat, R.; Magdis, G.; Bethermin, M.; Pannella, M.; Onodera, M.; Liu, D.; Cimatti, A.; Dannerbauer, H.; Carollo, M.; Renzini, A.; Tremou, E.

2018-06-01

We use ALMA and JVLA observations of the galaxy cluster Cl J1449+0856 at z=1.99, in order to study how dust-obscured star-formation, ISM content and AGN activity are linked to environment and galaxy interactions during the crucial phase of high-z cluster assembly. We present detections of multiple transitions of 12CO, as well as dust continuum emission detections from 11 galaxies in the core of Cl J1449+0856. We measure the gas excitation properties, star-formation rates, gas consumption timescales and gas-to-stellar mass ratios for the galaxies. We find evidence for a large fraction of galaxies with highly-excited molecular gas, contributing >50% to the total SFR in the cluster core. We compare these results with expectations for field galaxies, and conclude that environmental influences have strongly enhanced the fraction of excited galaxies in this cluster. We find a dearth of molecular gas in the galaxies' gas reservoirs, implying a high star-formation efficiency (SFE) in the cluster core, and find short gas depletion timescales τdep<0.1-0.4 Gyrs for all galaxies. Interestingly, we do not see evidence for increased specific star-formation rates (sSFRs) in the cluster galaxies, despite their high SFEs and gas excitations. We find evidence for a large number of mergers in the cluster core, contributing a large fraction of the core's total star-formation compared with expectations in the field. We conclude that the environmental impact on the galaxy excitations is linked to the high rate of galaxy mergers, interactions and active galactic nuclei in the cluster core.
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.
Cooperativity of halogen, chalcogen, and pnictogen bonds in infinite molecular chains by electronic structure theory.

PubMed

George, Janine; Deringer, Volker L; Dronskowski, Richard

2014-05-01

Halogen bonds (XBs) are intriguing noncovalent interactions that are frequently being exploited for crystal engineering. Recently, similar bonding mechanisms have been proposed for adjacent main-group elements, and noncovalent "chalcogen bonds" and "pnictogen bonds" have been identified in crystal structures. A fundamental question, largely unresolved thus far, is how XBs and related contacts interact with each other in crystals; similar to hydrogen bonding, one might expect "cooperativity" (bonds amplifying each other), but evidence has been sparse. Here, we explore the crucial step from gas-phase oligomers to truly infinite chains by means of quantum chemical computations. A periodic density functional theory (DFT) framework allows us to address polymeric chains of molecules avoiding the dreaded "cluster effects" as well as the arbitrariness of defining a "large enough" cluster. We focus on three types of molecular chains that we cut from crystal structures; furthermore, we explore reasonable substitutional variants in silico. We find evidence of cooperativity in chains of halogen cyanides and also in similar chalcogen- and pnictogen-bonded systems; the bonds, in the most extreme cases, are amplified through cooperative effects by 79% (I···N), 90% (Te···N), and 103% (Sb···N). Two experimentally known organic crystals, albeit with similar atomic connectivity and XB characteristics, show signs of cooperativity in one case but not in another. Finally, no cooperativity is observed in alternating halogen/acetone and halogen/1,4-dioxane chains; in fact, these XBs weaken each other by up to 26% compared to the respective gas-phase dimers.
Recent advances in spin-free state-specific and state-universal multi-reference coupled cluster formalisms: A unitary group adapted approach

NASA Astrophysics Data System (ADS)

Maitra, Rahul; Sinha, Debalina; Sen, Sangita; Shee, Avijit; Mukherjee, Debashis

2012-06-01

We present here the formulations and implementations of Mukherjee's State-Specific and State-Universal Multi-reference Coupled Cluster theories, which are explicitly spin free being obtained via the Unitary Group Adapted (UGA) approach, and thus, do not suffer from spin-contamination. We refer to them as UGA-SSMRCC and UGASUMRCC respectively. We propose a new multi-exponential cluster Ansatz analogous to but different from the one suggested by Jeziorski and Monkhorst (JM). Unlike the JM Ansatz, our choice involves spin-free unitary generators for the cluster operators and we replace the traditional exponential structure for the wave-operator by a suitable normal ordered exponential. We sketch the consequences of choosing our Ansatz, which leads to fully spin-free finite power series structure of the direct term of the MRCC equations. The UGA-SUMRCC follows from a suitable hierarchical generation of the cluster amplitudes of increasing rank, while the UGA-SSMRCC requires suitable sufficiency conditions to arrive at a well-defined set of equations for the cluster amplitudes. We discuss two distinct and inequivalent sufficiency conditions and their pros and cons. We also discuss a variant of the UGA-SSMRCC, where the number of cluster amplitudes can be drastically reduced by internal contraction of the two-body inactive cluster amplitudes. These are the most numerous, and thus a spin-free internally contracted description will lead to a high speed-up factor. We refer to this as ICID-UGA-SSMRCC. Essentially the same mathematical manipulations provide us with the UGA-SUMRCC theory as well. Pilot numerical results are presented to indicate the promise and the efficacy of all the three methods.
Star Count Density Profiles and Structural Parameters of 26 Galactic Globular Clusters

NASA Astrophysics Data System (ADS)

Miocchi, P.; Lanzoni, B.; Ferraro, F. R.; Dalessandro, E.; Vesperini, E.; Pasquato, M.; Beccari, G.; Pallanca, C.; Sanna, N.

2013-09-01

We used an appropriate combination of high-resolution Hubble Space Telescope observations and wide-field, ground-based data to derive the radial stellar density profiles of 26 Galactic globular clusters from resolved star counts (which can be all freely downloaded on-line). With respect to surface brightness (SB) profiles (which can be biased by the presence of sparse, bright stars), star counts are considered to be the most robust and reliable tool to derive cluster structural parameters. For each system, a detailed comparison with both King and Wilson models has been performed and the most relevant best-fit parameters have been obtained. This collection of data represents the largest homogeneous catalog collected so far of star count profiles and structural parameters derived therefrom. The analysis of the data of our catalog has shown that (1) the presence of the central cusps previously detected in the SB profiles of NGC 1851, M13, and M62 is not confirmed; (2) the majority of clusters in our sample are fit equally well by the King and the Wilson models; (3) we confirm the known relationship between cluster size (as measured by the effective radius) and galactocentric distance; (4) the ratio between the core and the effective radii shows a bimodal distribution, with a peak at ~0.3 for about 80% of the clusters and a secondary peak at ~0.6 for the remaining 20%. Interestingly, the main peak turns out to be in agreement with that expected from simulations of cluster dynamical evolution and the ratio between these two radii correlates well with an empirical dynamical-age indicator recently defined from the observed shape of blue straggler star radial distribution, thus suggesting that no exotic mechanisms of energy generation are needed in the cores of the analyzed clusters.
Dynamic triggering of low magnitude earthquakes in the Middle American Subduction Zone

NASA Astrophysics Data System (ADS)

Escudero, C. R.; Velasco, A. A.

2010-12-01

We analyze global and Middle American Subduction Zone (MASZ) seismicity from 1998 to 2008 to quantify the transient stresses effects at teleseismic distances. We use the Bulletin of the International Seismological Centre Catalog (ISCCD) published by the Incorporated Research Institutions for Seismology (IRIS). To identify MASZ seismicity changes due to distant, large (Mw >7) earthquakes, we first identify local earthquakes that occurred before and after the mainshocks. We then group the local earthquakes within a cluster radius between 75 to 200 km. We obtain statistics based on characteristics of both mainshocks and local earthquakes clusters, such as local cluster-mainshock azimuth, mainshock focal mechanism, and local earthquakes clusters within the MASZ. Due to lateral variations of the dip along the subducted oceanic plate, we divide the Mexican subduction zone in four segments. We then apply the Paired Samples Statistical Test (PSST) to the sorted data to identify increment, decrement or either in the local seismicity associated with distant large earthquakes. We identify dynamic triggering for all MASZ segments produced by large earthquakes emerging from specific azimuths, as well as, a decrease for some cases. We find no depend of seismicity changes due to focal mainshock mechanism.
Minimal spanning tree algorithm for γ-ray source detection in sparse photon images: cluster parameters and selection strategies

DOE PAGES

Campana, R.; Bernieri, E.; Massaro, E.; ...

2013-05-22

We present that the minimal spanning tree (MST) algorithm is a graph-theoretical cluster-finding method. We previously applied it to γ-ray bidimensional images, showing that it is quite sensitive in finding faint sources. Possible sources are associated with the regions where the photon arrival directions clusterize. MST selects clusters starting from a particular “tree” connecting all the point of the image and performing a cut based on the angular distance between photons, with a number of events higher than a given threshold. In this paper, we show how a further filtering, based on some parameters linked to the cluster properties, canmore » be applied to reduce spurious detections. We find that the most efficient parameter for this secondary selection is the magnitudeM of a cluster, defined as the product of its number of events by its clustering degree. We test the sensitivity of the method by means of simulated and real Fermi-Large Area Telescope (LAT) fields. Our results show that √M is strongly correlated with other statistical significance parameters, derived from a wavelet based algorithm and maximum likelihood (ML) analysis, and that it can be used as a good estimator of statistical significance of MST detections. Finally, we apply the method to a 2-year LAT image at energies higher than 3 GeV, and we show the presence of new clusters, likely associated with BL Lac objects.« less
Cluster Analysis of Clinical Data Identifies Fibromyalgia Subgroups

PubMed Central

Docampo, Elisa; Collado, Antonio; Escaramís, Geòrgia; Carbonell, Jordi; Rivera, Javier; Vidal, Javier; Alegre, José

2013-01-01

Introduction Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. Material and Methods 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Results Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. Conclusions We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment. PMID:24098674
Gas-liquid nucleation at large metastability: unusual features and a new formalism

NASA Astrophysics Data System (ADS)

Santra, Mantu; Singh, Rakesh S.; Bagchi, Biman

2011-03-01

Nucleation at large metastability is still largely an unsolved problem, even though it is a problem of tremendous current interest, with wide-ranging practical value, from atmospheric research to materials science. It is now well accepted that the classical nucleation theory (CNT) fails to provide a qualitative picture and gives incorrect quantitative values for such quantities as activation-free energy barrier and supersaturation dependence of nucleation rate, especially at large metastability. In this paper, we present an alternative formalism to treat nucleation at large supersaturation by introducing an extended set of order parameters in terms of the kth largest liquid-like clusters, where k = 1 is the largest cluster in the system, k = 2 is the second largest cluster and so on. At low supersaturation, the size of the largest liquid-like cluster acts as a suitable order parameter. At large supersaturation, the free energy barrier for the largest liquid-like cluster disappears. We identify this supersaturation as the one at the onset of kinetic spinodal. The kinetic spinodal is system-size-dependent. Beyond kinetic spinodal many clusters grow simultaneously and competitively and hence the nucleation and growth become collective. In order to describe collective growth, we need to consider the full set of order parameters. We derive an analytic expression for the free energy of formation of the kth largest cluster. The expression predicts that, at large metastability (beyond kinetic spinodal), the barrier of growth for several largest liquid-like clusters disappears, and all these clusters grow simultaneously. The approach to the critical size occurs by barrierless diffusion in the cluster size space. The expression for the rate of barrier crossing predicts weaker supersaturation dependence than what is predicted by CNT at large metastability. Such a crossover behavior has indeed been observed in recent experiments (but eluded an explanation till now). In order to understand the large numerical discrepancy between simulation predictions and experimental results, we carried out a study of the dependence on the range of intermolecular interactions of both the surface tension of an equilibrium planar gas-liquid interface and the free energy barrier of nucleation. Both are found to depend significantly on the range of interaction for the Lennard-Jones potential, both in two and three dimensions. The value of surface tension and also the free energy difference between the gas and the liquid phase increase significantly and converge only when the range of interaction is extended beyond 6-7 molecular diameters. We find, with the full range of interaction potential, that the surface tension shows only a weak dependence on supersaturation, so the reason for the breakdown of CNT (with simulated values of surface tension and free energy gap) cannot be attributed to the supersaturation dependence of surface tension. This remains an unsettled issue at present because of the use of the value of surface tension obtained at coexistence.
Galaxy Evolution Viewed as Functions of Environment and Mass

NASA Astrophysics Data System (ADS)

Kodama, Tadayuki; Tanaka, Masayuki; Tanaka, Ichi; Kajisawa, Masaru

We present two large surveys of distant clusters currently being carried out with Subaru, making use of its great capability of wide-field study both in the optical and in the near-infrared. The optical surveys, called PISCES, have mapped out large scale structures in and around 8 distant clusters at 0.4 < z <1.3, composed of multiple filaments and clumps extended over 15-30 Mpc scale. From the photometric and spectroscopic properties of galaxies over a wide range in environment, we find that the truncation of galaxies is seen in the outskirts of clusters rather than in the cluster cores.We also see a clear environmental dependence of the down-sizing (progressively later quenching of star formation in smaller galaxies). The near-infrared surveys are being conducted with a new wide-field instrument targeting proto-clusters around high-zradio-loud galaxies up to z ~4. Most of these field are known to show a large number of Lyαand/or Hαemitters at the same redshifts of the radio galaxies. We see a clear excess of near-infrared selected galaxies (JHK s -selected galaxies as well as DRG) in these fields, and they are indeed proto-clusters with not only young emitters but also evolved populations. Spatial distribution of such NIR selected galaxies is filamentary and track similar structures traced by the emitters. There is an hint that the bright-end of the red sequence first appeared between z= 3 and 2.
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.
On the problem of earthquake correlation in space and time over large distances

NASA Astrophysics Data System (ADS)

Georgoulas, G.; Konstantaras, A.; Maravelakis, E.; Katsifarakis, E.; Stylios, C. D.

2012-04-01

A quick examination of geographical maps with the epicenters of earthquakes marked on them reveals a strong tendency of these points to form compact clusters of irregular shapes and various sizes often traversing with other clusters. According to [Saleur et al. 1996] "earthquakes are correlated in space and time over large distances". This implies that seismic sequences are not formatted randomly but they follow a spatial pattern with consequent triggering of events. Seismic cluster formation is believed to be due to underlying geological natural hazards, which: a) act as the energy storage elements of the phenomenon, and b) tend to form a complex network of numerous interacting faults [Vallianatos and Tzanis, 1998]. Therefore it is imperative to "isolate" meaningful structures (clusters) in order to mine information regarding the underlying mechanism and at a second stage to test the causality effect implied by what is known as the Domino theory [Burgman, 2009]. Ongoing work by Konstantaras et al. 2011 and Katsifarakis et al. 2011 on clustering seismic sequences in the area of the Southern Hellenic Arc and progressively throughout the Greek vicinity and the entire Mediterranean region based on an explicit segmentation of the data based both on their temporal and spatial stamp, following modelling assumptions proposed by Dobrovolsky et al. 1989 and Drakatos et al. 2001, managed to identify geologically validated seismic clusters. These results suggest that that the time component should be included as a dimension during the clustering process as seismic cluster formation is dynamic and the emerging clusters propagate in time. Another issue that has not been investigated yet explicitly is the role of the magnitude of each seismic event. In other words the major seismic event should be treated differently compared to pre or post seismic sequences. Moreover the sometimes irregular and elongated shapes that appear on geophysical maps means that clustering algorithms such as the well known k-means that tend to form "well-shaped" clusters may not suffice for the problem at hand and other families of unsupervised pattern recognition methods might be a better choice. One such algorithm is the DBSCAN algorithm which is based on the notion of density. In this proposed version the density is not estimated solely on the number of seismic events occurring at a specific spatio-temporal area, but also takes into account the size of the seismic event. A second method proposes the use of a modified measure of proximity that will also account for the size of the earthquake along with traditional clustering schemes such as k-means and agglomerative clustering (k-means is seeded with a quite large number for k and the results are fed to the hierarchical algorithm in order to alleviate the memory requirements on one hand and also allow for irregular shapes on the other hand). Preliminary results of seismic cluster formation using these algorithms appear promising as they are in agreement with geophysical observations on distinct seismic regions, such as those of the neighbouring regions in the Ionian sea and that of the southern Hellenic seismic arc; as well as by the location and orientation of the mapped network of underlying natural hazards beneath each clusters vicinity.

Radio active galactic nuclei in galaxy clusters: Feedback, merger signatures, and cluster tracers

NASA Astrophysics Data System (ADS)

Paterno-Mahler, Rachel Beth

Galaxy clusters, the largest gravitationally-bound structures in the universe, are composed of 50-1000s of galaxies, hot X-ray emitting gas, and dark matter. They grow in size over time through cluster and group mergers. The merger history of a cluster can be imprinted on the hot gas, known as the intracluster medium (ICM). Merger signatures include shocks, cold fronts, and sloshing of the ICM, which can form spiral structures. Some clusters host double-lobed radio sources driven by active galactic nuclei (AGN). First, I will present a study of the galaxy cluster Abell 2029, which is very relaxed on large scales and has one of the largest continuous sloshing spirals yet observed in the X-ray, extending outward approximately 400 kpc. The sloshing gas interacts with the southern lobe of the radio galaxy, causing it to bend. Energy injection from the AGN is insufficient to offset cooling. The sloshing spiral may be an important additional mechanism in preventing large amounts of gas from cooling to very low temperatures. Next, I will present a study of Abell 98, a triple system currently undergoing a merger. I will discuss the merger history, and show that it is causing a shock. The central subcluster hosts a double-lobed AGN, which is evacuating a cavity in the ICM. Understanding the physical processes that affect the ICM is important for determining the mass of clusters, which in turn affects our calculations of cosmological parameters. To further constrain these parameters, as well as models of galaxy evolution, it is important to use a large sample of galaxy clusters over a range of masses and redshifts. Bent, double-lobed radio sources can potentially act as tracers of galaxy clusters over wide ranges of these parameters. I examine how efficient bent radio sources are at tracing high-redshift (z>0.7) clusters. Out of 646 sources in our high-redshift Clusters Occupied by Bent Radio AGN (COBRA) sample, 282 are candidate new, distant clusters of galaxies based on measurements of excess galaxy counts surrounding the radio sources in Spitzer infrared images.
Robust clustering of languages across Wikipedia growth

NASA Astrophysics Data System (ADS)

Ban, Kristina; Perc, Matjaž; Levnajić, Zoran

2017-10-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.
Robust clustering of languages across Wikipedia growth.

PubMed

Ban, Kristina; Perc, Matjaž; Levnajić, Zoran

2017-10-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.
Robust clustering of languages across Wikipedia growth

PubMed Central

Ban, Kristina; Levnajić, Zoran

2017-01-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy. PMID:29134106
Emergence of clustering in an acquaintance model without homophily

NASA Astrophysics Data System (ADS)

Bhat, Uttam; Krapivsky, P. L.; Redner, S.

2014-11-01

We introduce an agent-based acquaintance model in which social links are created by processes in which there is no explicit homophily. In spite of the homogeneous nature of the social interactions, highly-clustered social networks can arise. The crucial feature of our model is that of variable transitive interactions. Namely, when an agent introduces two unconnected friends, the rate at which a connection actually occurs between them depends on the number of their mutual acquaintances. As this transitive interaction rate is varied, the social network undergoes a dramatic clustering transition. Close to the transition, the network consists of a collection of well-defined communities. As a function of time, the network can also undergo an incomplete gelation transition, in which the gel, or giant cluster, does not constitute the entire network, even at infinite time. Some of the clustering properties of our model also arise, but in a more gradual manner, in Facebook networks. Finally, we discuss a more realistic variant of our original model in which network realizations can be constructed that quantitatively match Facebook networks.
The SAMI Galaxy Survey: the cluster redshift survey, target selection and cluster properties

NASA Astrophysics Data System (ADS)

Owers, M. S.; Allen, J. T.; Baldry, I.; Bryant, J. J.; Cecil, G. N.; Cortese, L.; Croom, S. M.; Driver, S. P.; Fogarty, L. M. R.; Green, A. W.; Helmich, E.; de Jong, J. T. A.; Kuijken, K.; Mahajan, S.; McFarland, J.; Pracy, M. B.; Robotham, A. G. S.; Sikkema, G.; Sweet, S.; Taylor, E. N.; Verdoes Kleijn, G.; Bauer, A. E.; Bland-Hawthorn, J.; Brough, S.; Colless, M.; Couch, W. J.; Davies, R. L.; Drinkwater, M. J.; Goodwin, M.; Hopkins, A. M.; Konstantopoulos, I. S.; Foster, C.; Lawrence, J. S.; Lorente, N. P. F.; Medling, A. M.; Metcalfe, N.; Richards, S. N.; van de Sande, J.; Scott, N.; Shanks, T.; Sharp, R.; Thomas, A. D.; Tonini, C.

2017-06-01

We describe the selection of galaxies targeted in eight low-redshift clusters (APMCC0917, A168, A4038, EDCC442, A3880, A2399, A119 and A85; 0.029 < z < 0.058) as part of the Sydney-AAO Multi-Object Integral field spectrograph Galaxy Survey (SAMI-GS). We have conducted a redshift survey of these clusters using the AAOmega multi-object spectrograph on the 3.9-m Anglo-Australian Telescope. The redshift survey is used to determine cluster membership and to characterize the dynamical properties of the clusters. In combination with existing data, the survey resulted in 21 257 reliable redshift measurements and 2899 confirmed cluster member galaxies. Our redshift catalogue has a high spectroscopic completeness (˜94 per cent) for rpetro ≤ 19.4 and cluster-centric distances R < 2R200. We use the confirmed cluster member positions and redshifts to determine cluster velocity dispersion, R200, virial and caustic masses, as well as cluster structure. The clusters have virial masses 14.25 ≤ log(M200/M⊙) ≤ 15.19. The cluster sample exhibits a range of dynamical states, from relatively relaxed-appearing systems, to clusters with strong indications of merger-related substructure. Aperture- and point spread function matched photometry are derived from Sloan Digital Sky Survey and VLT Survey Telescope/ATLAS imaging and used to estimate stellar masses. These estimates, in combination with the redshifts, are used to define the input target catalogue for the cluster portion of the SAMI-GS. The primary SAMI-GS cluster targets have R
Electronic and molecular structure of carbon grains

NASA Technical Reports Server (NTRS)

Almloef, Jan; Luethi, Hans-Peter

1990-01-01

Clusters of carbon atoms have been studied with large-scale ab initio calculations. Planar, single-sheet graphite fragments with 6 to 54 atoms were investigated, as well as the spherical C(sub 60) Buckminsterfullerene molecule. Polycyclic aromatic hydrocarbons (PAHs) have also been considered. Thermodynamic differences between diamond- and graphite-like grains have been studied in particular. Saturation of the peripheral bonds with hydrogen is found to provide a smooth and uniform convergence of the properties with increasing cluster size. For the graphite-like clusters the convergence to bulk values is much slower than for the three-dimensional complexes.
Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

NASA Technical Reports Server (NTRS)

McIntosh, Dawn

2006-01-01

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search
Large stability and high catalytic activities of sub-nm metal (0) clusters: implications into the nucleation and growth theory.

PubMed

Piñeiro, Yolanda; Buceta, David; Calvo, Javier; Huseyinova, Shahana; Cuerva, Miguel; Pérez, Ángel; Domínguez, Blanca; López-Quintela, M Arturo

2015-07-01

Clusters are stable catalytic species, which are produced during the synthesis of nanoparticles (NPs). Their existence contradicts the thermodynamic principles used to explain the formation of NPs by the classical nucleation and growth theories (NGTs). Using chemical and electrochemical methods we will show that depending on the experimental conditions one can produce either Ag clusters or Ag NPs. Moreover, using already prepared Ag clusters one can observe the disappearance of the usual induction period observed for the kinetics of NP formation, indicating that clusters catalyze the formation of NPs. Taking these data together with some previous examples of cluster-catalyzed anisotropic growth, we derived a qualitative approach to include the catalytic activities of clusters into the formation of NPs, which is incorporated into the NGT. Some qualitative conclusions about the main experimental parameters, which affect the formation of clusters versus NPs, as well as the catalytic mechanism versus the non-catalytic one, are also described. Copyright © 2015 Elsevier Inc. All rights reserved.
Performance analysis of clustering techniques over microarray data: A case study

NASA Astrophysics Data System (ADS)

Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.
Modeling Species Distributions from Heterogeneous Data for the Biogeographic Regionalization of the European Bryophyte Flora

PubMed Central

Mateo, Rubén G.; Vanderpoorten, Alain; Muñoz, Jesús

2013-01-01

The definition of biogeographic regions provides a fundamental framework for a range of basic and applied questions in biogeography, evolutionary biology, systematics and conservation. Previous research suggested that environmental forcing results in highly congruent regionalization patterns across taxa, but that the size and number of regions depends on the dispersal ability of the taxa considered. We produced a biogeographic regionalization of European bryophytes and hypothesized that (1) regions defined for bryophytes would differ from those defined for other taxa due to the highly specific eco-physiology of the group and (2) their high dispersal ability would result in the resolution of few, large regions. Species distributions were recorded using 10,000 km2 MGRS pixels. Because of the lack of data across large portions of the area, species distribution models employing macroclimatic variables as predictors were used to determine the potential composition of empty pixels. K-means clustering analyses of the pixels based on their potential species composition were employed to define biogeographic regions. The optimal number of regions was determined by v-fold cross-validation and Moran’s I statistic. The spatial congruence of the regions identified from their potential bryophyte assemblages with large-scale vegetation patterns is at odds with our primary hypothesis. This reinforces the notion that post-glacial migration patterns might have been much more similar in bryophytes and vascular plants than previously thought. The substantially lower optimal number of clusters and the absence of nested patterns within the main biogeographic regions, as compared to identical analyses in vascular plants, support our second hypothesis. The modelling approach implemented here is, however, based on many assumptions that are discussed but can only be tested when additional data on species distributions become available, highlighting the substantial importance of developing integrated mapping projects for all taxa in key biogeographically areas of Europe, and the Mediterranean peninsulas in particular. PMID:23409015
Thermodynamics of the Coma Cluster Outskirts

NASA Astrophysics Data System (ADS)

Simionescu, A.; Werner, N.; Urban, O.; Allen, S. W.; Fabian, A. C.; Mantz, A.; Matsushita, K.; Nulsen, P. E. J.; Sanders, J. S.; Sasaki, T.; Sato, T.; Takei, Y.; Walker, S. A.

2013-09-01

We present results from a large mosaic of Suzaku observations of the Coma Cluster, the nearest and X-ray brightest hot (~8 keV), dynamically active, non-cool core system, focusing on the thermodynamic properties of the intracluster medium on large scales. For azimuths not aligned with an infalling subcluster toward the southwest, our measured temperature and X-ray brightness profiles exhibit broadly consistent radial trends, with the temperature decreasing from about 8.5 keV at the cluster center to about 2 keV at a radius of 2 Mpc, which is the edge of our detection limit. The southwest merger significantly boosts the surface brightness, allowing us to detect X-ray emission out to ~2.2 Mpc along this direction. Apart from the southwestern infalling subcluster, the surface brightness profiles show multiple edges around radii of 30-40 arcmin. The azimuthally averaged temperature profile, as well as the deprojected density and pressure profiles, all show a sharp drop consistent with an outwardly-propagating shock front located at 40 arcmin, corresponding to the outermost edge of the giant radio halo observed at 352 MHz with the Westerbork Synthesis Radio Telescope. The shock front may be powering this radio emission. A clear entropy excess inside of r 500 reflects the violent merging events linked with these morphological features. Beyond r 500, the entropy profiles of the Coma Cluster along the relatively relaxed directions are consistent with the power-law behavior expected from simple models of gravitational large-scale structure formation. The pressure is also in agreement at these radii with the expected values measured from Sunyaev-Zel'dovich data from the Planck satellite. However, due to the large uncertainties associated with the Coma Cluster measurements, we cannot yet exclude an entropy flattening in this system consistent with that seen in more relaxed cool core clusters.
Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

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

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less
The CCD photometry of the globular cluster Palomar 1.

NASA Astrophysics Data System (ADS)

Borissova, J.; Spassova, N.

1995-04-01

A CCD photometry of the halo cluster Palomar 1 is presented in the Thuan-Gunn photometric system. The principal sequences of the color-magnitude diagrams are delineated in different spectral bands. The color-magnitude diagrams of the cluster show a well defined red horizontal branch, a subgiant branch and a main-sequence down to about two magnitudes below the main sequence turnoff. The giant branch is absent and the brightest stars are the horizontal branch stars. The age of the cluster determined by comparison with the isochrones of Bell & Vanden Berg (1987) is consistent with an age in the interval 12-14Gyr. A distance modulus of (m-M)_g0_=15.38+/-0.15 magnitude and E(g-r)=0.16 has been derived. An estimate of the cluster structural parameters such as core radius and concentration parameter gives r_c_=1.5pc and c=1.46. A mass estimate of 1.1 10^3^Msun_ and a mass-to-light ratio of 1.79 have been obtained using King's (1966) method. The morphology of color-magnitude diagrams allows Pal 1 to be interpreted as probably a globular cluster rather than an old open one.
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases.

PubMed

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-03-08

High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank--like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL.
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases

PubMed Central

Corsi, Claudio; Ferragina, Paolo; Marangoni, Roberto

2007-01-01

Background High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective. Results The BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank – like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding. Conclusion Bpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL. PMID:17430575
Magnetic Ordering in Gold Nanoclusters

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

Agrachev, Mikhail; Antonello, Sabrina; Dainese, Tiziano

Here, several research groups have observed magnetism in monolayer-protected gold-cluster samples, but the results were often contradictory and thus a clear understanding of this phenomenon is still missing. We used Au 25(SCH 2CH 2Ph) 18 0, which is a paramagnetic cluster that can be prepared with atomic precision and whose structure is known precisely. Previous magnetometry studies only detected paramagnetism. We used samples representing a range of crystallographic orders and studied their magnetic behaviors by electron paramagnetic resonance (EPR). As a film, Au 25(SCH 2CH 2Ph) 18 0 displays paramagnetic behavior but, at low temperature, ferromagnetic interactions are detectable. Onemore » or few single crystals undergo physical reorientation with the applied field and display ferromagnetism, as detected through hysteresis experiments. A large collection of microcrystals is magnetic even at room temperature and shows distinct paramagnetic, superparamagnetic, and ferromagnetic behaviors. Simulation of the EPR spectra shows that both spin-orbit coupling and crystal distortion are important to determine the observed magnetic behaviors. DFT calculations carried out on single cluster and periodic models predict values of spin6orbit coupling and crystal6splitting effects in agreement with the EPR derived quantities. Magnetism in gold nanoclusters is thus demonstrated to be the outcome of a very delicate balance of factors. To obtain reproducible results, the samples must be (i) controlled for composition and thus be monodispersed with atomic precision, (ii) of known charge state, and (iii) well defined also in terms of crystallinity and experimental conditions. This study highlights the efficacy of EPR spectroscopy to provide a molecular understanding of these phenomena« less
Biclustering of gene expression data using reactive greedy randomized adaptive search procedure

PubMed Central

Dharan, Smitha; Nair, Achuthsankar S

2009-01-01

Background Biclustering algorithms belong to a distinct class of clustering algorithms that perform simultaneous clustering of both rows and columns of the gene expression matrix and can be a very useful analysis tool when some genes have multiple functions and experimental conditions are diverse. Cheng and Church have introduced a measure called mean squared residue score to evaluate the quality of a bicluster and has become one of the most popular measures to search for biclusters. In this paper, we review basic concepts of the metaheuristics Greedy Randomized Adaptive Search Procedure (GRASP)-construction and local search phases and propose a new method which is a variant of GRASP called Reactive Greedy Randomized Adaptive Search Procedure (Reactive GRASP) to detect significant biclusters from large microarray datasets. The method has two major steps. First, high quality bicluster seeds are generated by means of k-means clustering. In the second step, these seeds are grown using the Reactive GRASP, in which the basic parameter that defines the restrictiveness of the candidate list is self-adjusted, depending on the quality of the solutions found previously. Results We performed statistical and biological validations of the biclusters obtained and evaluated the method against the results of basic GRASP and as well as with the classic work of Cheng and Church. The experimental results indicate that the Reactive GRASP approach outperforms the basic GRASP algorithm and Cheng and Church approach. Conclusion The Reactive GRASP approach for the detection of significant biclusters is robust and does not require calibration efforts. PMID:19208127
Magnetic Ordering in Gold Nanoclusters

DOE PAGES

Agrachev, Mikhail; Antonello, Sabrina; Dainese, Tiziano; ...

2017-06-12

Here, several research groups have observed magnetism in monolayer-protected gold-cluster samples, but the results were often contradictory and thus a clear understanding of this phenomenon is still missing. We used Au 25(SCH 2CH 2Ph) 18 0, which is a paramagnetic cluster that can be prepared with atomic precision and whose structure is known precisely. Previous magnetometry studies only detected paramagnetism. We used samples representing a range of crystallographic orders and studied their magnetic behaviors by electron paramagnetic resonance (EPR). As a film, Au 25(SCH 2CH 2Ph) 18 0 displays paramagnetic behavior but, at low temperature, ferromagnetic interactions are detectable. Onemore » or few single crystals undergo physical reorientation with the applied field and display ferromagnetism, as detected through hysteresis experiments. A large collection of microcrystals is magnetic even at room temperature and shows distinct paramagnetic, superparamagnetic, and ferromagnetic behaviors. Simulation of the EPR spectra shows that both spin-orbit coupling and crystal distortion are important to determine the observed magnetic behaviors. DFT calculations carried out on single cluster and periodic models predict values of spin6orbit coupling and crystal6splitting effects in agreement with the EPR derived quantities. Magnetism in gold nanoclusters is thus demonstrated to be the outcome of a very delicate balance of factors. To obtain reproducible results, the samples must be (i) controlled for composition and thus be monodispersed with atomic precision, (ii) of known charge state, and (iii) well defined also in terms of crystallinity and experimental conditions. This study highlights the efficacy of EPR spectroscopy to provide a molecular understanding of these phenomena« less
Structure and thermodynamics of a mixture of patchy and spherical colloids: A multi-body association theory with complete reference fluid information

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

Bansal, Artee; Asthagiri, D.; Cox, Kenneth R.

A mixture of solvent particles with short-range, directional interactions and solute particles with short-range, isotropic interactions that can bond multiple times is of fundamental interest in understanding liquids and colloidal mixtures. Because of multi-body correlations, predicting the structure and thermodynamics of such systems remains a challenge. Earlier Marshall and Chapman [J. Chem. Phys. 139, 104904 (2013)] developed a theory wherein association effects due to interactions multiply the partition function for clustering of particles in a reference hard-sphere system. The multi-body effects are incorporated in the clustering process, which in their work was obtained in the absence of the bulk medium.more » The bulk solvent effects were then modeled approximately within a second order perturbation approach. However, their approach is inadequate at high densities and for large association strengths. Based on the idea that the clustering of solvent in a defined coordination volume around the solute is related to occupancy statistics in that defined coordination volume, we develop an approach to incorporate the complete information about hard-sphere clustering in a bulk solvent at the density of interest. The occupancy probabilities are obtained from enhanced sampling simulations but we also develop a concise parametric form to model these probabilities using the quasichemical theory of solutions. We show that incorporating the complete reference information results in an approach that can predict the bonding state and thermodynamics of the colloidal solute for a wide range of system conditions.« less

Coronal Mass Ejection Data Clustering and Visualization of Decision Trees

NASA Astrophysics Data System (ADS)

Ma, Ruizhe; Angryk, Rafal A.; Riley, Pete; Filali Boubrahimi, Soukaina

2018-05-01

Coronal mass ejections (CMEs) can be categorized as either “magnetic clouds” (MCs) or non-MCs. Features such as a large magnetic field, low plasma-beta, and low proton temperature suggest that a CME event is also an MC event; however, so far there is neither a definitive method nor an automatic process to distinguish the two. Human labeling is time-consuming, and results can fluctuate owing to the imprecise definition of such events. In this study, we approach the problem of MC and non-MC distinction from a time series data analysis perspective and show how clustering can shed some light on this problem. Although many algorithms exist for traditional data clustering in the Euclidean space, they are not well suited for time series data. Problems such as inadequate distance measure, inaccurate cluster center description, and lack of intuitive cluster representations need to be addressed for effective time series clustering. Our data analysis in this work is twofold: clustering and visualization. For clustering we compared the results from the popular hierarchical agglomerative clustering technique to a distance density clustering heuristic we developed previously for time series data clustering. In both cases, dynamic time warping will be used for similarity measure. For classification as well as visualization, we use decision trees to aggregate single-dimensional clustering results to form a multidimensional time series decision tree, with averaged time series to present each decision. In this study, we achieved modest accuracy and, more importantly, an intuitive interpretation of how different parameters contribute to an MC event.
Interaction force in a vertical dust chain inside a glass box.

PubMed

Kong, Jie; Qiao, Ke; Matthews, Lorin S; Hyde, Truell W

2014-07-01

Small number dust particle clusters can be used as probes for plasma diagnostics. The number of dust particles as well as cluster size and shape can be easily controlled employing a glass box placed within a Gaseous Electronics Conference (GEC) rf reference chamber to provide confinement of the dust. The plasma parameters inside this box and within the larger plasma chamber have not yet been adequately defined. Adjusting the rf power alters the plasma conditions causing structural changes of the cluster. This effect can be used to probe the relationship between the rf power and other plasma parameters. This experiment employs the sloshing and breathing modes of small cluster oscillations to examine the relationship between system rf power and the particle charge and plasma screening length inside the glass box. The experimental results provided indicate that both the screening length and dust charge decrease as rf power inside the box increases. The decrease in dust charge as power increases may indicate that ion trapping plays a significant role in the sheath.
Large-scale depositional characteristics of the Ulleung Basin and its impact on electrical resistivity and Archie-parameters for gas hydrate saturation estimates

USGS Publications Warehouse

Riedel, Michael; Collett, Timothy S.; Kim, H.-S.; Bahk, J.-J.; Kim, J.-H.; Ryu, B.-J.; Kim, G.-Y.

2013-01-01

Gas hydrate saturation estimates were obtained from an Archie-analysis of the Logging-While-Drilling (LWD) electrical resistivity logs under consideration of the regional geological framework of sediment deposition in the Ulleung Basin, East Sea, of Korea. Porosity was determined from the LWD bulk density log and core-derived values of grain density. In situ measurements of pore-fluid salinity as well as formation temperature define a background trend for pore-fluid resistivity at each drill site. The LWD data were used to define sets of empirical Archie-constants for different depth-intervals of the logged borehole at all sites drilled during the second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2). A clustering of data with distinctly different trend-lines is evident in the cross-plot of porosity and formation factor for all sites drilled during UBGH2. The reason for the clustering is related to the difference between hemipelagic sediments (mostly covering the top ∼100 mbsf) and mass-transport deposits (MTD) and/or the occurrence of biogenic opal. For sites located in the north-eastern portion of the Ulleung Basin a set of individual Archie-parameters for a shallow depth interval (hemipelagic) and a deeper MTD zone was achieved. The deeper zone shows typically higher resistivities for the same range of porosities seen in the upper zone, reflecting a shift in sediment properties. The presence of large amounts of biogenic opal (up to and often over 50% as defined by XRD data) was especially observed at Sites UBGH2-2_1 and UBGH2-2_2 (as well as UBGH1-9 from a previous drilling expedition in 2007). The boundary between these two zones can also easily be identified in gamma-ray logs, which also show unusually low readings in the opal-rich interval. Only by incorporating different Archie-parameters for the different zones a reasonable estimate of gas hydrate saturation was achieved that also matches results from other techniques such as pore-fluid freshening, velocity-based calculations, and pressure-core degassing experiments. Seismically, individual boundaries between zones were determined using a grid of regional 2D seismic data. Zoning from the Archie-analysis for sites in the south-western portion of the Ulleung Basin was also observed, but at these sites it is linked to individually stacked MTDs only and does not reflect a mineralogical occurrence of biogenic opal or hemipelagic sedimentation. The individual MTD events represent differently compacted material often associated with a strong decrease in porosity (and increase in density), warranting a separate set of empirical Archie-parameters.
Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.
The WAGGS project - I. The WiFeS Atlas of Galactic Globular cluster Spectra

NASA Astrophysics Data System (ADS)

Usher, Christopher; Pastorello, Nicola; Bellstedt, Sabine; Alabi, Adebusola; Cerulo, Pierluigi; Chevalier, Leonie; Fraser-McKelvie, Amelia; Penny, Samantha; Foster, Caroline; McDermid, Richard M.; Schiavon, Ricardo P.; Villaume, Alexa

2017-07-01

We present the WiFeS Atlas of Galactic Globular cluster Spectra, a library of integrated spectra of Milky Way and Local Group globular clusters. We used the WiFeS integral field spectrograph on the Australian National University 2.3 m telescope to observe the central regions of 64 Milky Way globular clusters and 22 globular clusters hosted by the Milky Way's low-mass satellite galaxies. The spectra have wider wavelength coverage (3300-9050 Å) and higher spectral resolution (R = 6800) than existing spectral libraries of Milky Way globular clusters. By including Large and Small Magellanic Cloud star clusters, we extend the coverage of parameter space of existing libraries towards young and intermediate ages. While testing stellar population synthesis models and analysis techniques is the main aim of this library, the observations may also further our understanding of the stellar populations of Local Group globular clusters and make possible the direct comparison of extragalactic globular cluster integrated light observations with well-understood globular clusters in the Milky Way. The integrated spectra are publicly available via the project website.
Hydration of an apolar solute in a two-dimensional waterlike lattice fluid

NASA Astrophysics Data System (ADS)

Buzano, C.; de Stefanis, E.; Pretti, M.

2005-05-01

In a previous work, we investigated a two-dimensional lattice-fluid model, displaying some waterlike thermodynamic anomalies. The model, defined on a triangular lattice, is now extended to aqueous solutions with apolar species. Water molecules are of the “Mercedes Benz” type, i.e., they possess a D3 (equilateral triangle) symmetry, with three equivalent bonding arms. Bond formation depends both on orientation and local density. The insertion of inert molecules displays typical signatures of hydrophobic hydration: large positive transfer free energy, large negative transfer entropy (at low temperature), strong temperature dependence of the transfer enthalpy and entropy, i.e., large (positive) transfer heat capacity. Model properties are derived by a generalized first order approximation on a triangle cluster.
Hydration of an apolar solute in a two-dimensional waterlike lattice fluid.

PubMed

Buzano, C; De Stefanis, E; Pretti, M

2005-05-01

In a previous work, we investigated a two-dimensional lattice-fluid model, displaying some waterlike thermodynamic anomalies. The model, defined on a triangular lattice, is now extended to aqueous solutions with apolar species. Water molecules are of the "Mercedes Benz" type, i.e., they possess a D3 (equilateral triangle) symmetry, with three equivalent bonding arms. Bond formation depends both on orientation and local density. The insertion of inert molecules displays typical signatures of hydrophobic hydration: large positive transfer free energy, large negative transfer entropy (at low temperature), strong temperature dependence of the transfer enthalpy and entropy, i.e., large (positive) transfer heat capacity. Model properties are derived by a generalized first order approximation on a triangle cluster.
THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

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

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

2016-01-15

We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% ofmore » the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections.« less
Extracting Galaxy Cluster Gas Inhomogeneity from X-Ray Surface Brightness: A Statistical Approach and Application to Abell 3667

NASA Astrophysics Data System (ADS)

Kawahara, Hajime; Reese, Erik D.; Kitayama, Tetsu; Sasaki, Shin; Suto, Yasushi

2008-11-01

Our previous analysis indicates that small-scale fluctuations in the intracluster medium (ICM) from cosmological hydrodynamic simulations follow the lognormal probability density function. In order to test the lognormal nature of the ICM directly against X-ray observations of galaxy clusters, we develop a method of extracting statistical information about the three-dimensional properties of the fluctuations from the two-dimensional X-ray surface brightness. We first create a set of synthetic clusters with lognormal fluctuations around their mean profile given by spherical isothermal β-models, later considering polytropic temperature profiles as well. Performing mock observations of these synthetic clusters, we find that the resulting X-ray surface brightness fluctuations also follow the lognormal distribution fairly well. Systematic analysis of the synthetic clusters provides an empirical relation between the three-dimensional density fluctuations and the two-dimensional X-ray surface brightness. We analyze Chandra observations of the galaxy cluster Abell 3667, and find that its X-ray surface brightness fluctuations follow the lognormal distribution. While the lognormal model was originally motivated by cosmological hydrodynamic simulations, this is the first observational confirmation of the lognormal signature in a real cluster. Finally we check the synthetic cluster results against clusters from cosmological hydrodynamic simulations. As a result of the complex structure exhibited by simulated clusters, the empirical relation between the two- and three-dimensional fluctuation properties calibrated with synthetic clusters when applied to simulated clusters shows large scatter. Nevertheless we are able to reproduce the true value of the fluctuation amplitude of simulated clusters within a factor of 2 from their two-dimensional X-ray surface brightness alone. Our current methodology combined with existing observational data is useful in describing and inferring the statistical properties of the three-dimensional inhomogeneity in galaxy clusters.
The globular cluster system of NGC 1316. IV. Nature of the star cluster complex SH2

NASA Astrophysics Data System (ADS)

Richtler, T.; Husemann, B.; Hilker, M.; Puzia, T. H.; Bresolin, F.; Gómez, M.

2017-05-01

Context. The light of the merger remnant NGC 1316 (Fornax A) is dominated by old and intermediate-age stars. The only sign of current star formation in this big galaxy is the Hii region SH2, an isolated star cluster complex with a ring-like morphology and an estimated age of 0.1 Gyr at a galactocentric distance of about 35 kpc. A nearby intermediate-age globular cluster, surrounded by weak line emission and a few more young star clusters, is kinematically associated. The origin of this complex is enigmatic. Aims: We want to investigate the nature of this star cluster complex. The nebular emission lines permit a metallicity determination which can discriminate between a dwarf galaxy or other possible precursors. Methods: We used the Integral Field Unit (IFU) of the VIMOS instrument at the Very Large Telescope of the European Southern Observatory in high dispersion mode to study the morphology, kinematics, and metallicity employing line maps, velocity maps, and line diagnostics of a few characteristic spectra. Results: The line ratios of different spectra vary, indicating highly structured Hii regions, but define a locus of uniform metallicity. The strong-line diagnostic diagrams and empirical calibrations point to a nearly solar or even super-solar oxygen abundance. The velocity dispersion of the gas is highest in the region offset from the bright clusters. Star formation may be active on a low level. There is evidence for a large-scale disk-like structure in the region of SH2, which would make the similar radial velocity of the nearby globular cluster easier to understand. Conclusions: The high metallicity does not fit to a dwarf galaxy as progenitor. We favour the scenario of a free-floating gaseous complex having its origin in the merger 2 Gyr ago. Over a long period the densities increased secularly until finally the threshold for star formation was reached. SH2 illustrates how massive star clusters can form outside starbursts and without a considerable field population. Based on observations taken at the European Southern Observatory, Cerro Paranal, Chile, under the programme 082.B-0680, 076.B-0154, 065.N-0166, 065.N-0459.
Kramers degeneracy and relaxation in vanadium, niobium and tantalum clusters

NASA Astrophysics Data System (ADS)

Diaz-Bachs, A.; Katsnelson, M. I.; Kirilyuk, A.

2018-04-01

In this work we use magnetic deflection of V, Nb, and Ta atomic clusters to measure their magnetic moments. While only a few of the clusters show weak magnetism, all odd-numbered clusters deflect due to the presence of a single unpaired electron. Surprisingly, for the majority of V and Nb clusters an atomic-like behavior is found, which is a direct indication of the absence of spin–lattice interaction. This is in agreement with Kramers degeneracy theorem for systems with a half-integer spin. This purely quantum phenomenon is surprisingly observed for large systems of more than 20 atoms, and also indicates various quantum relaxation processes, via Raman two-phonon and Orbach high-spin mechanisms. In heavier, Ta clusters, the relaxation is always present, probably due to larger masses and thus lower phonon energies, as well as increased spin–orbit coupling.
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.
Studies in the X-Ray Emission of Clusters of Galaxies and Other Topics

NASA Technical Reports Server (NTRS)

Vrtilek, Jan; Thronson, Harley (Technical Monitor)

2001-01-01

The paper discusses the following: (1) X-ray study of groups of galaxies with Chandra and XMM. (2) X-ray properties of point sources in Chandra deep fields. (3) Study of cluster substructure using wavelet techniques. (4) Combined study of galaxy clusters with X-ray and the S-Z effect. Groups of galaxies are the fundamental building blocks of large scale structure in the Universe. X-ray study of the intragroup medium offers a powerful approach to addressing some of the major questions that still remain about almost all aspects of groups: their ages, origins, importance of composition of various galaxy types, relations to clusters, and origin and enrichment of the intragroup gas. Long exposures with Chandra have opened new opportunities for the study of X-ray background. The presence of substructure within clusters of galaxies has substantial implications for our understanding of cluster evolution as well as fundamental questions in cosmology.
Constructing Flexible, Configurable, ETL Pipelines for the Analysis of "Big Data" with Apache OODT

NASA Astrophysics Data System (ADS)

Hart, A. F.; Mattmann, C. A.; Ramirez, P.; Verma, R.; Zimdars, P. A.; Park, S.; Estrada, A.; Sumarlidason, A.; Gil, Y.; Ratnakar, V.; Krum, D.; Phan, T.; Meena, A.

2013-12-01

A plethora of open source technologies for manipulating, transforming, querying, and visualizing 'big data' have blossomed and matured in the last few years, driven in large part by recognition of the tremendous value that can be derived by leveraging data mining and visualization techniques on large data sets. One facet of many of these tools is that input data must often be prepared into a particular format (e.g.: JSON, CSV), or loaded into a particular storage technology (e.g.: HDFS) before analysis can take place. This process, commonly known as Extract-Transform-Load, or ETL, often involves multiple well-defined steps that must be executed in a particular order, and the approach taken for a particular data set is generally sensitive to the quantity and quality of the input data, as well as the structure and complexity of the desired output. When working with very large, heterogeneous, unstructured or semi-structured data sets, automating the ETL process and monitoring its progress becomes increasingly important. Apache Object Oriented Data Technology (OODT) provides a suite of complementary data management components called the Process Control System (PCS) that can be connected together to form flexible ETL pipelines as well as browser-based user interfaces for monitoring and control of ongoing operations. The lightweight, metadata driven middleware layer can be wrapped around custom ETL workflow steps, which themselves can be implemented in any language. Once configured, it facilitates communication between workflow steps and supports execution of ETL pipelines across a distributed cluster of compute resources. As participants in a DARPA-funded effort to develop open source tools for large-scale data analysis, we utilized Apache OODT to rapidly construct custom ETL pipelines for a variety of very large data sets to prepare them for analysis and visualization applications. We feel that OODT, which is free and open source software available through the Apache Software Foundation, is particularly well suited to developing and managing arbitrary large-scale ETL processes both for the simplicity and flexibility of its wrapper framework, as well as the detailed provenance information it exposes throughout the process. Our experience using OODT to manage processing of large-scale data sets in domains as diverse as radio astronomy, life sciences, and social network analysis demonstrates the flexibility of the framework, and the range of potential applications to a broad array of big data ETL challenges.
Nanoclusters first: a hierarchical phase transformation in a novel Mg alloy

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

NASA Astrophysics Data System (ADS)

Rupel, Dylan

2015-03-01

The first goal of this note is to extend the well-known Feigin homomorphisms taking quantum groups to quantum polynomial algebras. More precisely, we define generalized Feigin homomorphisms from a quantum shuffle algebra to quantum polynomial algebras which extend the classical Feigin homomorphisms along the embedding of the quantum group into said quantum shuffle algebra. In a recent work of Berenstein and the author, analogous extensions of Feigin homomorphisms from the dual Hall-Ringel algebra of a valued quiver to quantum polynomial algebras were defined. To relate these constructions, we establish a homomorphism, dubbed the quantum shuffle character, from the dual Hall-Ringel algebra to the quantum shuffle algebra which relates the generalized Feigin homomorphisms. These constructions can be compactly described by a commuting tetrahedron of maps beginning with the quantum group and terminating in a quantum polynomial algebra. The second goal in this project is to better understand the dual canonical basis conjecture for skew-symmetrizable quantum cluster algebras. In the symmetrizable types it is known that dual canonical basis elements need not have positive multiplicative structure constants, while this is still suspected to hold for skew-symmetrizable quantum cluster algebras. We propose an alternate conjecture for the symmetrizable types: the cluster monomials should correspond to irreducible characters of a KLR algebra. Indeed, the main conjecture of this note would establish this ''KLR conjecture'' for acyclic skew-symmetrizable quantum cluster algebras: that is, we conjecture that the images of rigid representations under the quantum shuffle character give irreducible characters for KLR algebras. We sketch a proof in the symmetric case giving an alternative to the proof of Kimura-Qin that all non-initial cluster variables in an acyclic skew-symmetric quantum cluster algebra are contained in the dual canonical basis. With these results in mind we interpret the cluster mutations directly in terms of the representation theory of the KLR algebra.
Early Results from Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Dai, Xinyu; Griffin, Rhiannon; Nugent, Jenna; Kochanek, Christopher S.; Bregman, Joel N.

2016-04-01

The Swift AGN and Cluster Survey (SACS) uses 125 deg^2 of Swift X-ray Telescope serendipitous fields with variable depths surrounding gamma-ray bursts to provide a medium depth (4 × 10^-15 erg cm^-2 s^-1) and area survey filling the gap between deep, narrow Chandra/XMM-Newton surveys and wide, shallow ROSAT surveys. Here, we present the first two papers in a series of publications for SACS. In the first paper, we introduce our method and catalog of 22,563 point sources and 442 extended sources. SACS provides excellent constraints on the AGN and cluster number counts at the bright end with negligible uncertainties due to cosmic variance, and these constraints are consistent with previous measurements. The depth and areal coverage of SACS is well suited for galaxy cluster surveys outside the local universe, reaching z > 1 for massive clusters. In the second paper, we use SDSS DR8 data to study the 203 extended SACS sources that are located within the SDSS footprint. We search for galaxy over-densities in 3-D space using SDSS galaxies and their photometric redshifts near the Swift galaxy cluster candidates. We find 103 Swift clusters with a > 3σ over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmations as galaxy clusters. We present a series of cluster properties including the redshift, BCG magnitude, BCG-to-X-ray center offset, optical richness, X-ray luminosity and red sequences. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≤ 0.3 and 80% complete for z ≤ 0.4, consistent with the survey depth of SDSS. These analysis results suggest that our Swift cluster selection algorithm presented in our first paper has yielded a statistically well-defined cluster sample for further studying cluster evolution and cosmology. In the end, we will discuss our ongoing optical identification of z>0.5 cluster sample, using MDM, KPNO, CTIO, and Magellan data, and discuss SACS as a pilot for eROSITA deep surveys.
A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.
Suppression of vacancy cluster growth in concentrated solid solution alloys

DOE PAGES

Zhao, Shijun; Velisa, Gihan; Xue, Haizhou; ...

2016-12-13

Large vacancy clusters, such as stacking-fault tetrahedra, are detrimental vacancy-type defects in ion-irradiated structural alloys. Suppression of vacancy cluster formation and growth is highly desirable to improve the irradiation tolerance of these materials. In this paper, we demonstrate that vacancy cluster growth can be inhibited in concentrated solid solution alloys by modifying cluster migration pathways and diffusion kinetics. The alloying effects of Fe and Cr on the migration of vacancy clusters in Ni concentrated alloys are investigated by molecular dynamics simulations and ion irradiation experiment. While the diffusion coefficients of small vacancy clusters in Ni-based binary and ternary solid solutionmore » alloys are higher than in pure Ni, they become lower for large clusters. This observation suggests that large clusters can easily migrate and grow to very large sizes in pure Ni. In contrast, cluster growth is suppressed in solid solution alloys owing to the limited mobility of large vacancy clusters. Finally, the differences in cluster sizes and mobilities in Ni and in solid solution alloys are consistent with the results from ion irradiation experiments.« less
The Structural Parameters of the Globular Clusters in M31 with PAndAS

NASA Astrophysics Data System (ADS)

Woodley, Kristin; Pan-Andromeda Archaeological Survey (PAndAS)

2012-05-01

The Pan-Andromeda Archaeological Survey (PAndAS) has obtained images with the Canada France Hawaii Telescope using the instrument MegaCam, covering over 400 square degrees in the sky and extending beyond 150 kpc in radius from the center of M31. With this extensive data set, we have measured the structural parameters of all confirmed globular clusters in M31 as well as for a large fraction of the candidate globular clusters in the Revised Bologna Catalog V.4 (Galleti et al. 2004, A&A, 416, 917). In this paper, we present their parameters, including their core-, effective (half-light)-, and tidal radii, as well as their ellipticities measured in a homogeneous manner with ISHAPE (Larsen 1999, A&AS, 139, 393). We examine these parameters as functions of radial position, luminosity, color, metallicity, and age. We also use our measurements as an additional parameter to help constrain the candidacy of the unconfirmed globular clusters.

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.
A comprehensive HST BVI catalogue of star clusters in five Hickson compact groups of galaxies

NASA Astrophysics Data System (ADS)

Fedotov, K.; Gallagher, S. C.; Durrell, P. R.; Bastian, N.; Konstantopoulos, I. S.; Charlton, J.; Johnson, K. E.; Chandar, R.

2015-05-01

We present a photometric catalogue of star cluster candidates in Hickson compact groups (HCGs) 7, 31, 42, 59, and 92, based on observations with the Advanced Camera for Surveys and the Wide Field Camera 3 on the Hubble Space Telescope. The catalogue contains precise cluster positions (right ascension and declination), magnitudes, and colours in the BVI filters. The number of detected sources ranges from 2200 to 5600 per group, from which we construct the high-confidence sample by applying a number of criteria designed to reduce foreground and background contaminants. Furthermore, the high-confidence cluster candidates for each of the 16 galaxies in our sample are split into two subpopulations: one that may contain young star clusters and one that is dominated by globular older clusters. The ratio of young star cluster to globular cluster candidates varies from group to group, from equal numbers to the extreme of HCG 31 which has a ratio of 8 to 1, due to a recent starburst induced by interactions in the group. We find that the number of blue clusters with MV < -9 correlates well with the current star formation rate in an individual galaxy, while the number of globular cluster candidates with MV < -7.8 correlates well (though with large scatter) with the stellar mass. Analyses of the high-confidence sample presented in this paper show that star clusters can be successfully used to infer the gross star formation history of the host groups and therefore determine their placement in a proposed evolutionary sequence for compact galaxy groups.
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)
Preparation of Large-Diameter GaAs Crystals.

DTIC Science & Technology

1981-09-18

ionized impurity content for 40 n-type semi-insulating GaAs. Figure 17 Analysis (in wt %) of impurities in B203 after crystal growth 41 from PBN and quartz...encapsulant to the generation of defect clusters in LEC InP. (15 ) Statistics relative to the incidence of twinning for growth with dry ( ppm wt OH...and wet (> 1000 ppm wt OH) B203 are given in Fig. 5 for growths from fused-SiO 2 and PBN crucibles. A crystal is defined as having twinned if it
A link between nonlinear self-organization and dissipation in drift-wave turbulence

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

Manz, P.; Birkenmeier, G.; Stroth, U.

Structure formation and self-organization in two-dimensional drift-wave turbulence show up in many different faces. Fluctuation data from a magnetized plasma are analyzed and three mechanisms transferring kinetic energy to large-scale structures are identified. Beside the common vortex merger, clustering of vortices constituting a large-scale strain field and vortex thinning, where due to the interactions of vortices of different scales larger vortices are amplified by the smaller ones, are observed. The vortex thinning mechanism appears to be the most efficient one to generate large scale structures in drift-wave turbulence. Vortex merging as well as vortex clustering are accompanied by strong energymore » transfer to small-scale noncoherent fluctuations (dissipation) balancing the negative entropy generation due to the self-organization process.« less
Neutral hydrogen gas, past and future star formation in galaxies in and around the ‘Sausage’ merging galaxy cluster

DOE PAGES

Stroe, Andra; Oosterloo, Tom; Rottgering, Huub J. A.; ...

2015-07-25

CIZA J2242.8+5301 (z = 0.188, nicknamed ‘Sausage’) is an extremely massive (M 200 ~2.0 × 10 15 M ⊙), merging cluster with shock waves towards its outskirts, which was found to host numerous emission line galaxies. We performed extremely deep Westerbork Synthesis Radio Telescope H i observations of the ‘Sausage’ cluster to investigate the effect of the merger and the shocks on the gas reservoirs fuelling present and future star formation (SF) in cluster members. By using spectral stacking, we find that the emission line galaxies in the ‘Sausage’ cluster have, on average, as much H i gas as fieldmore » galaxies (when accounting for the fact cluster galaxies are more massive than the field galaxies), contrary to previous studies. Since the cluster galaxies are more massive than the field spirals, they may have been able to retain their gas during the cluster merger. The large H i reservoirs are expected to be consumed within ~0.75–1.0 Gyr by the vigorous SF and active galactic nuclei activity and/or driven out by the outflows we observe. We find that the star formation rate (SFR) in a large fraction of H α emission line cluster galaxies correlates well with the radio broad-band emission, tracing supernova remnant emission. This suggests that the cluster galaxies, all located in post-shock regions, may have been undergoing sustained SFR for at least 100 Myr. In conclusion, this fully supports the interpretation proposed by Stroe et al. and Sobral et al. that gas-rich cluster galaxies have been triggered to form stars by the passage of the shock.« less
Measures of large-scale structure in the CfA redshift survey slices

NASA Technical Reports Server (NTRS)

De Lapparent, Valerie; Geller, Margaret J.; Huchra, John P.

1991-01-01

Variations of the counts-in-cells with cell size are used here to define two statistical measures of large-scale clustering in three 6 deg slices of the CfA redshift survey. A percolation criterion is used to estimate the filling factor which measures the fraction of the total volume in the survey occupied by the large-scale structures. For the full 18 deg slice of the CfA redshift survey, f is about 0.25 + or - 0.05. After removing groups with more than five members from two of the slices, variations of the counts in occupied cells with cell size have a power-law behavior with a slope beta about 2.2 on scales from 1-10/h Mpc. Application of both this statistic and the percolation analysis to simulations suggests that a network of two-dimensional structures is a better description of the geometry of the clustering in the CfA slices than a network of one-dimensional structures. Counts-in-cells are also used to estimate at 0.3 galaxy h-squared/Mpc the average galaxy surface density in sheets like the Great Wall.
Clustering analysis of proteins from microbial genomes at multiple levels of resolution.

PubMed

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

2016-08-31

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

NASA Astrophysics Data System (ADS)

Quenneville, Jason; Germann, Timothy

2007-06-01

A reactive force field (ReaxFF^2) is used with molecular dynamics to probe the chemistry induced by intense heating (accelerated `cook-off') of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB). Large-system simulations are desired for TATB because of the high degree of carbon clustering expected in this material. Using small, 800-atom, simulations, we will show the reaction rate as a function of temperature and density as well as the time evolution of reaction products. A larger simulation (with 14,000 atoms) will illustrate the effect of system size on both carbon clustering and reaction rate. Insight into the mechanisms of product formation will be given, as well as the chemical structure (graphitic or diamond-like) of the carbon clusters obtained. ^2 A. C. T. Van Duin, et al, J. Phys. Chem. A, 1005, 9396 (2001).
PREFACE: Nanostructured surfaces

NASA Astrophysics Data System (ADS)

Palmer, Richard E.

2003-10-01

We can define nanostructured surfaces as well-defined surfaces which contain lateral features of size 1-100 nm. This length range lies well below the micron regime but equally above the Ångstrom regime, which corresponds to the interatomic distances on single-crystal surfaces. This special issue of Journal of Physics: Condensed Matter presents a collection of twelve papers which together address the fabrication, characterization, properties and applications of such nanostructured surfaces. Taken together they represent, in effect, a status report on the rapid progress taking place in this burgeoning area. The first four papers in this special issue have been contributed by members of the European Research Training Network ‘NanoCluster’, which is concerned with the deposition, growth and characterization of nanometre-scale clusters on solid surfaces—prototypical examples of nanoscale surface features. The paper by Vandamme is concerned with the fundamentals of the cluster-surface interaction; the papers by Gonzalo and Moisala address, respectively, the optical and catalytic properties of deposited clusters; and the paper by van Tendeloo reports the application of transmission electron microscopy (TEM) to elucidate the surface structure of spherical particles in a catalyst support. The fifth paper, by Mendes, is also the fruit of a European Research Training Network (‘Micro-Nano’) and is jointly contributed by three research groups; it reviews the creation of nanostructured surface architectures from chemically-synthesized nanoparticles. The next five papers in this special issue are all concerned with the characterization of nanostructured surfaces with scanning tunnelling microscopy (STM) and atomic force microscopy (AFM). The papers by Bolotov, Hamilton and Dunstan demonstrate that the STM can be employed for local electrical measurements as well as imaging, as illustrated by the examples of deposited clusters, model semiconductor structures and real devices, respectively, while the papers by Ledieu and Guo report the structural characterization of novel surface systems—quasicrystal surfaces and supramolecular monolayers, respectively. The final two papers, by Bennett and Smith, demonstrate the positive interplay between experimental measurements and theoretical modelling in the investigation of nanostructured surfaces. The examples discussed include, respectively, the growth of metal clusters on oxide surfaces and the deposition of fullerenes and energetic clusters from the gas phase. We note finally that the last six papers in this special issue have been contributed by members of the Committee of the newly-formed Nanoscale Physics and Technology Group of the Institute of Physics. The Group shares with this special issue the aim of promoting and disseminating exciting advances in the flourishing field of nanoscale physics.
Understanding the presence of vacancy clusters in ZnO from a kinetic perspective

NASA Astrophysics Data System (ADS)

Bang, Junhyeok; Kim, Youg-Sung; Park, C. H.; Gao, F.; Zhang, S. B.

2014-06-01

Vacancy clusters have been observed in ZnO by positron-annihilation spectroscopy (PAS), but detailed mechanisms are unclear. This is because the clustering happens in non-equilibrium conditions, for which theoretical method has not been well established. Combining first-principles calculation and kinetic Monte Carlo simulation, we determine the roles of non-equilibrium kinetics on the vacancies clustering. We find that clustering starts with the formation of Zn and O vacancy pairs (VZn - Vo), which further grow by attracting additional mono-vacancies. At this stage, vacancy diffusivity becomes crucial: due to the larger diffusivity of VZn compared to VO, more VZn-abundant clusters are formed than VO-abundant clusters. The large dissociation energy barriers, e.g., over 2.5 eV for (VZn - Vo), suggest that, once formed, it is difficult for the clusters to dissociate. By promoting mono-vacancy diffusion, thermal annealing will increase the size of the clusters. As the PAS is insensitive to VO donor defects, our results suggest an interpretation of the experimental data that could not have been made without the in-depth calculations.
Network visualization of conformational sampling during molecular dynamics simulation.

PubMed

Ahlstrom, Logan S; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T; Patel, Sunita; Vorontsov, Ivan I; Tama, Florence; Miyashita, Osamu

2013-11-01

Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. Copyright © 2013 Elsevier Inc. All rights reserved.
Understanding continental megathrust earthquake potential through geological mountain building processes: an example in Nepal Himalaya

NASA Astrophysics Data System (ADS)

Zhang, Huai; Zhang, Zhen; Wang, Liangshu; Leroy, Yves; shi, Yaolin

2017-04-01

How to reconcile continent megathrust earthquake characteristics, for instances, mapping the large-great earthquake sequences into geological mountain building process, as well as partitioning the seismic-aseismic slips, is fundamental and unclear. Here, we scope these issues by focusing a typical continental collisional belt, the great Nepal Himalaya. We first prove that refined Nepal Himalaya thrusting sequences, with accurately defining of large earthquake cycle scale, provide new geodynamical hints on long-term earthquake potential in association with, either seismic-aseismic slip partition up to the interpretation of the binary interseismic coupling pattern on the Main Himalayan Thrust (MHT), or the large-great earthquake classification via seismic cycle patterns on MHT. Subsequently, sequential limit analysis is adopted to retrieve the detailed thrusting sequences of Nepal Himalaya mountain wedge. Our model results exhibit apparent thrusting concentration phenomenon with four thrusting clusters, entitled as thrusting 'families', to facilitate the development of sub-structural regions respectively. Within the hinterland thrusting family, the total aseismic shortening and the corresponding spatio-temporal release pattern are revealed by mapping projection. Whereas, in the other three families, mapping projection delivers long-term large (M<8)-great (M>8) earthquake recurrence information, including total lifespans, frequencies and large-great earthquake alternation information by identifying rupture distances along the MHT. In addition, this partition has universality in continental-continental collisional orogenic belt with identified interseismic coupling pattern, while not applicable in continental-oceanic megathrust context.
Exploring Relations Between BCG & Cluster Properties in the SPectroscopic IDentification of eROSITA Sources Survey from 0.05 < z < 0.3

NASA Astrophysics Data System (ADS)

Furnell, Kate E.; Collins, Chris A.; Kelvin, Lee S.; Clerc, Nicolas; Baldry, Ivan K.; Finoguenov, Alexis; Erfanianfar, Ghazaleh; Comparat, Johan; Schneider, Donald P.

2018-04-01

We present a sample of 329 low to intermediate redshift (0.05 < z < 0.3) brightest cluster galaxies (BCGs) in X-ray selected clusters from the SPectroscopic IDentification of eRosita Sources (SPIDERS) survey, a spectroscopic survey within Sloan Digital Sky Survey-IV (SDSS-IV). We define our BCGs by simultaneous consideration of legacy X-ray data from ROSAT, maximum likelihood outputs from an optical cluster-finder algorithm and visual inspection. Using SDSS imaging data, we fit Sérsic profiles to our BCGs in three bands (g, r, i) with SIGMA, a GALFIT-based software wrapper. We examine the reliability of our fits by running our pipeline on ˜104 psf-convolved model profiles injected into 8 random cluster fields; we then use the results of this analysis to create a robust subsample of 198 BCGs. We outline three cluster properties of interest: overall cluster X-ray luminosity (LX), cluster richness as estimated by REDMAPPER (λ) and cluster halo mass (M200), which is estimated via velocity dispersion. In general, there are significant correlations with BCG stellar mass between all three environmental properties, but no significant trends arise with either Sérsic index or effective radius. There is no major environmental dependence on the strength of the relation between effective radius and BCG stellar mass. Stellar mass therefore arises as the most important factor governing BCG morphology. Our results indicate that our sample consists of a large number of relaxed, mature clusters containing broadly homogeneous BCGs up to z ˜ 0.3, suggesting that there is little evidence for much ongoing structural evolution for BCGs in these systems.
Multiple stellar populations in Magellanic Cloud clusters - VI. A survey of multiple sequences and Be stars in young clusters

NASA Astrophysics Data System (ADS)

Milone, A. P.; Marino, A. F.; Di Criscienzo, M.; D'Antona, F.; Bedin, L. R.; Da Costa, G.; Piotto, G.; Tailo, M.; Dotter, A.; Angeloni, R.; Anderson, J.; Jerjen, H.; Li, C.; Dupree, A.; Granata, V.; Lagioia, E. P.; Mackey, A. D.; Nardiello, D.; Vesperini, E.

2018-06-01

The split main sequences (MSs) and extended MS turnoffs (eMSTOs) detected in a few young clusters have demonstrated that these stellar systems host multiple populations differing in a number of properties such as rotation and, possibly, age. We analyse Hubble Space Telescope photometry for 13 clusters with ages between ˜40 and ˜1000 Myr and of different masses. Our goal is to investigate for the first time the occurrence of multiple populations in a large sample of young clusters. We find that all the clusters exhibit the eMSTO phenomenon and that MS stars more massive than ˜1.6 M_{⊙} define a blue and a red MS, with the latter hosting the majority of MS stars. The comparison between the observations and isochrones suggests that the blue MSs are made of slow-rotating stars, while the red MSs host stars with rotational velocities close to the breakup value. About half of the bright MS stars in the youngest clusters are H α emitters. These Be stars populate the red MS and the reddest part of the eMSTO, thus supporting the idea that the red MS is made of fast rotators. We conclude that the split MS and the eMSTO are a common feature of young clusters in both Magellanic Clouds. The phenomena of a split MS and an eMSTO occur for stars that are more massive than a specific threshold, which is independent of the host-cluster mass. As a by-product, we report the serendipitous discovery of a young Small Magellanic Cloud cluster, GALFOR 1.
Efficient electronic structure theory via hierarchical scale-adaptive coupled-cluster formalism: I. Theory and computational complexity analysis

NASA Astrophysics Data System (ADS)

Lyakh, Dmitry I.

2018-03-01

A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra. Inspired by the hierarchical techniques from the renormalisation group approach, H/H2-matrix algebra and fast multipole method, the computational scaling reduction in our formalism is achieved via coarsening of quantum many-body interactions at larger interaction scales, thus imposing a hierarchical structure on many-body tensors of coupled-cluster theory. In our approach, the interaction scale can be defined on any appropriate Euclidean domain (spatial domain, momentum-space domain, energy domain, etc.). We show that the hierarchically resolved many-body tensors can reduce the storage requirements to O(N), where N is the number of simulated quantum particles. Subsequently, we prove that any connected many-body diagram consisting of a finite number of arbitrary-order tensors, e.g. an arbitrary coupled-cluster diagram, can be evaluated in O(NlogN) floating-point operations. On top of that, we suggest an additional approximation to further reduce the computational complexity of higher order coupled-cluster equations, i.e. equations involving higher than double excitations, which otherwise would introduce a large prefactor into formal O(NlogN) scaling.
Definition of variables required for comprehensive description of drug dosage and clinical pharmacokinetics.

PubMed

Medem, Anna V; Seidling, Hanna M; Eichler, Hans-Georg; Kaltschmidt, Jens; Metzner, Michael; Hubert, Carina M; Czock, David; Haefeli, Walter E

2017-05-01

Electronic clinical decision support systems (CDSS) require drug information that can be processed by computers. The goal of this project was to determine and evaluate a compilation of variables that comprehensively capture the information contained in the summary of product characteristic (SmPC) and unequivocally describe the drug, its dosage options, and clinical pharmacokinetics. An expert panel defined and structured a set of variables and drafted a guideline to extract and enter information on dosage and clinical pharmacokinetics from textual SmPCs as published by the European Medicines Agency (EMA). The set of variables was iteratively revised and evaluated by data extraction and variable allocation of roughly 7% of all centrally approved drugs. The information contained in the SmPC was allocated to three information clusters consisting of 260 variables. The cluster "drug characterization" specifies the nature of the drug. The cluster "dosage" provides information on approved drug dosages and defines corresponding specific conditions. The cluster "clinical pharmacokinetics" includes pharmacokinetic parameters of relevance for dosing in clinical practice. A first evaluation demonstrated that, despite the complexity of the current free text SmPCs, dosage and pharmacokinetic information can be reliably extracted from the SmPCs and comprehensively described by a limited set of variables. By proposing a compilation of variables well describing drug dosage and clinical pharmacokinetics, the project represents a step forward towards the development of a comprehensive database system serving as information source for sophisticated CDSS.
Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733
Kappa statistic for clustered matched-pair data.

PubMed

Yang, Zhao; Zhou, Ming

2014-07-10

Kappa statistic is widely used to assess the agreement between two procedures in the independent matched-pair data. For matched-pair data collected in clusters, on the basis of the delta method and sampling techniques, we propose a nonparametric variance estimator for the kappa statistic without within-cluster correlation structure or distributional assumptions. The results of an extensive Monte Carlo simulation study demonstrate that the proposed kappa statistic provides consistent estimation and the proposed variance estimator behaves reasonably well for at least a moderately large number of clusters (e.g., K ≥50). Compared with the variance estimator ignoring dependence within a cluster, the proposed variance estimator performs better in maintaining the nominal coverage probability when the intra-cluster correlation is fair (ρ ≥0.3), with more pronounced improvement when ρ is further increased. To illustrate the practical application of the proposed estimator, we analyze two real data examples of clustered matched-pair data. Copyright © 2014 John Wiley & Sons, Ltd.
OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

SU-G-TeP3-14: Three-Dimensional Cluster Model in Inhomogeneous Dose Distribution

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

Wei, J; Penagaricano, J; Narayanasamy, G

2016-06-15

Purpose: We aim to investigate 3D cluster formation in inhomogeneous dose distribution to search for new models predicting radiation tissue damage and further leading to new optimization paradigm for radiotherapy planning. Methods: The aggregation of higher dose in the organ at risk (OAR) than a preset threshold was chosen as the cluster whose connectivity dictates the cluster structure. Upon the selection of the dose threshold, the fractional density defined as the fraction of voxels in the organ eligible to be part of the cluster was determined according to the dose volume histogram (DVH). A Monte Carlo method was implemented tomore » establish a case pertinent to the corresponding DVH. Ones and zeros were randomly assigned to each OAR voxel with the sampling probability equal to the fractional density. Ten thousand samples were randomly generated to ensure a sufficient number of cluster sets. A recursive cluster searching algorithm was developed to analyze the cluster with various connectivity choices like 1-, 2-, and 3-connectivity. The mean size of the largest cluster (MSLC) from the Monte Carlo samples was taken to be a function of the fractional density. Various OARs from clinical plans were included in the study. Results: Intensive Monte Carlo study demonstrates the inverse relationship between the MSLC and the cluster connectivity as anticipated and the cluster size does not change with fractional density linearly regardless of the connectivity types. An initially-slow-increase to exponential growth transition of the MSLC from low to high density was observed. The cluster sizes were found to vary within a large range and are relatively independent of the OARs. Conclusion: The Monte Carlo study revealed that the cluster size could serve as a suitable index of the tissue damage (percolation cluster) and the clinical outcome of the same DVH might be potentially different.« less
A simulation of the intracluster medium with feedback from cluster galaxies

NASA Technical Reports Server (NTRS)

Metzler, Christopher A.; Evrard, August E.

1994-01-01

We detail method and report first results from a three-dimensional hydrodynamical and N-body simulation of the formation and evolution of a Coma-sized cluster of galaxies, with the intent of studying the history of the hot, X-ray emitting intracluster medium. Cluster gas, galaxies, and dark matter are included in the model. The galaxies and dark matter fell gravitational forces; the cluster gas also undergoes hydrodynamical effects such as shock heating and PdV work. For the first time in three dimensions, we include modeling of ejection of processed gas from the simulated galaxies by winds, including heating and heavy element enrichment. For comparison, we employ a `pure infall' simulation using the same initial conditions but with no galaxies or winds. We employ an extreme ejection history for galactic feedback in order to define the boundary of likely models. As expected, feedback raises the entropy of the intracluster gas, preventing it from collapsing to densities as high as those attained in the infall model. The effect is more pronounced in subclusters formed at high redshift. The cluster with feedback is always less X-ray luminous, but experiences more rapid luminosity evolution, than the pure infall cluster. Even employing an extreme ejection model, the final gas temperature is only approximately 15% larger than in the infall model. The radial temperature profile is very nearly isothermal within 1.5 Mpc. The cluster galaxies in the feedback model have a velocity dispersion approximately 15% lower than the dark matter. This results in the true ratio of specific energies in galaxies to gas being less than one, beta(sub spec) approximately 0.7. The infall model predicts beta(sub spec) approximately 1.2. Large excursions in these values occur over time, following the complex dynamical history of the cluster. The morphology of the X-ray emission is little affected by feedback. The emission profiles of both clusters are well described by the standard beta-model with beta(sub fit) approximately equal to 0.7 - 0.9. X-ray mass estimates based on the assumptions of hydrostatic equilibrium and the applicability of the beta-model are quite accurate in both cases. A strong, radial iron abundance gradient is present, which develops as a consequence of the steepening of the galaxy density profile over time. Spectroscopic observations using nonimaging detectors with wide (approximately 45 min) fields of view dramatically smear the gradient. Observations with arcminute resolution, made available with the ASCA satellite, would readily resolve the gradient.
Spatial heterogeneity of type I error for local cluster detection tests

PubMed Central

2014-01-01

Background Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs’ type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect. Methods A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff’s spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect. Results The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated. Conclusions In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance. PMID:24885343
Orthology detection combining clustering and synteny for very large datasets.

PubMed

Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K; Prohaska, Sonja J; Stadler, Peter F

2014-01-01

The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.
Orthology Detection Combining Clustering and Synteny for Very Large Datasets

PubMed Central

Lechner, Marcus; Hernandez-Rosales, Maribel; Doerr, Daniel; Wieseke, Nicolas; Thévenin, Annelyse; Stoye, Jens; Hartmann, Roland K.; Prohaska, Sonja J.; Stadler, Peter F.

2014-01-01

The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets. PMID:25137074
Atomically precise organomimetic cluster nanomolecules assembled via perfluoroaryl-thiol SNAr chemistry

NASA Astrophysics Data System (ADS)

Qian, Elaine A.; Wixtrom, Alex I.; Axtell, Jonathan C.; Saebi, Azin; Jung, Dahee; Rehak, Pavel; Han, Yanxiao; Moully, Elamar Hakim; Mosallaei, Daniel; Chow, Sylvia; Messina, Marco S.; Wang, Jing Yang; Royappa, A. Timothy; Rheingold, Arnold L.; Maynard, Heather D.; Král, Petr; Spokoyny, Alexander M.

2017-04-01

The majority of biomolecules are intrinsically atomically precise, an important characteristic that enables rational engineering of their recognition and binding properties. However, imparting a similar precision to hybrid nanoparticles has been challenging because of the inherent limitations of existing chemical methods and building blocks. Here we report a new approach to form atomically precise and highly tunable hybrid nanomolecules with well-defined three-dimensionality. Perfunctionalization of atomically precise clusters with pentafluoroaryl-terminated linkers produces size-tunable rigid cluster nanomolecules. These species are amenable to facile modification with a variety of thiol-containing molecules and macromolecules. Assembly proceeds at room temperature within hours under mild conditions, and the resulting nanomolecules exhibit high stabilities because of their full covalency. We further demonstrate how these nanomolecules grafted with saccharides can exhibit dramatically improved binding affinity towards a protein. Ultimately, the developed strategy allows the rapid generation of precise molecular assemblies to investigate multivalent interactions.
Adamantyl- and Furanyl-Protected Nanoscale Silver Sulfide Clusters.

PubMed

Bestgen, Sebastian; Yang, Xiaoxun; Issac, Ibrahim; Fuhr, Olaf; Roesky, Peter W; Fenske, Dieter

2016-07-11

The silver salts of 1-adamantanethiol (AdSH) and furan-2-ylmethanethiol (FurCH2 SH) were successfully applied as building blocks for ligand-protected Ag2 S nanoclusters. The reaction of the silver thiolates [AgSAd]x and [AgSCH2 Fur]x with S(SiMe3 )2 and 1,5-bis(diphenylphosphino)pentane (dpppt) afforded three different clusters with 58, 94 and, 190 silver atoms. The intensely colored compounds [Ag58 S13 (SAd)32 ] (1), [Ag94 S34 (SAd)26 (dpppt)6 ] (2), and [Ag190 S58 (SCH2 Fur)74 (dpppt)8 ] (3) were structurally characterized by single-crystal X-ray diffraction and exhibit different cluster core geometries and ligand shells. The diameters of the well-defined sphere-shaped nanoclusters range from 2.2 nm to 3.5 nm. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
The applications of small-angle X-ray scattering in studying nano-scaled polyoxometalate clusters in solutions

NASA Astrophysics Data System (ADS)

Li, Mu; Zhang, Mingxin; Wang, Weiyu; Cheng, Stephen Z. D.; Yin, Panchao

2018-05-01

Nano-scaled polyoxometalates (POMs) clusters with sizes ranging from 1 to 10 nm attract tremendous attention and have been extensively studied due to POMs' fascinating structural characteristics and prospects for wide-ranging applications. As a unique class of nanoparticles with well-defined structural topologies and monodispersed masses, the structures and properties of POMs in both bulk state and solutions have been explored with several well-developed protocols. Small-angle X-ray scattering (SAXS) technique, as a powerful tool for studying polymers and nanoparticles, has been recently extended to the investigating of solution behaviors of POMs. In this mini-review, the general principle and typical experimental procedures of SAXS are illustrated first. The applications of SAXS in characterizing POMs' morphology, counterion distribution around POMs, and short-range interactions among POMs in solutions are highlighted. [Figure not available: see fulltext.
Searching for filaments and large-scale structure around DAFT/FADA clusters

NASA Astrophysics Data System (ADS)

Durret, F.; Márquez, I.; Acebrón, A.; Adami, C.; Cabrera-Lavers, A.; Capelato, H.; Martinet, N.; Sarron, F.; Ulmer, M. P.

2016-04-01

Context. Clusters of galaxies are located at the intersection of cosmic filaments and are still accreting galaxies and groups along these preferential directions. However, because of their relatively low contrast on the sky, filaments are difficult to detect (unless a large amount of spectroscopic data are available), and unambiguous detections have been limited until now to relatively low redshifts (z< ~ 0.3). Aims: This project is aimed at searching for extensions and filaments around clusters, traced by galaxies selected to be at the cluster redshift based on the red sequence. In the 0.4
Treatment effect of methylphenidate on intrinsic functional brain network in medication-naïve ADHD children: A multivariate analysis.

PubMed

Yoo, Jae Hyun; Kim, Dohyun; Choi, Jeewook; Jeong, Bumseok

2018-04-01

Methylphenidate is a first-line therapeutic option for treating attention-deficit/hyperactivity disorder (ADHD); however, elicited changes on resting-state functional networks (RSFNs) are not well understood. This study investigated the treatment effect of methylphenidate using a variety of RSFN analyses and explored the collaborative influences of treatment-relevant RSFN changes in children with ADHD. Resting-state functional magnetic resonance imaging was acquired from 20 medication-naïve ADHD children before methylphenidate treatment and twelve weeks later. Changes in large-scale functional connectivity were defined using independent component analysis with dual regression and graph theoretical analysis. The amplitude of low frequency fluctuation (ALFF) was measured to investigate local spontaneous activity alteration. Finally, significant findings were recruited to random forest regression to identify the feature subset that best explains symptom improvement. After twelve weeks of methylphenidate administration, large-scale connectivity was increased between the left fronto-parietal RSFN and the left insula cortex and the right fronto-parietal and the brainstem, while the clustering coefficient (CC) of the global network and nodes, the left fronto-parietal, cerebellum, and occipital pole-visual network, were decreased. ALFF was increased in the bilateral superior parietal cortex and decreased in the right inferior fronto-temporal area. The subset of the local and large-scale RSFN changes, including widespread ALFF changes, the CC of the global network and the cerebellum, could explain the 27.1% variance of the ADHD Rating Scale and 13.72% of the Conner's Parent Rating Scale. Our multivariate approach suggests that the neural mechanism of methylphenidate treatment could be associated with alteration of spontaneous activity in the superior parietal cortex or widespread brain regions as well as functional segregation of the large-scale intrinsic functional network.
Incidence of the muffin-tin approximation on the electronic structure of large clusters calculated by the MS-LSD method: The typical case of C{sub 60}

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

Razafinjanahary, H.; Rogemond, F.; Chermette, H.

The MS-LSD method remains a method of interest when rapidity and small computer resources are required; its main drawback is some lack of accuracy, mainly due to the muffin-tin distribution of the potential. In the case of large clusters or molecules, the use of an empty sphere to fill, in part, the large intersphere region can improve greatly the results. Calculations bearing on C{sub 60} has been undertaken to underline this trend, because, on the one hand, the fullerenes exhibit a remarkable possibility to fit a large empty sphere in the center of the cluster and, on the other hand,more » numerous accurate calculations have already been published, allowing quantitative comparison with results. The author`s calculations suggest that in case of added empty sphere the results compare well with the results of more accurate calculations. The calculated electron affinity for C{sub 60} and C{sub 60}{sup {minus}} are in reasonable agreement with experimental values, but the stability of C{sub 60}{sup 2-} in gas phase is not found. 35 refs., 3 figs., 5 tabs.« less
SACS: Spitzer Archival Cluster Survey

NASA Astrophysics Data System (ADS)

Stern, Daniel

Emerging from the cosmic web, galaxy clusters are the most massive gravitationally bound structures in the universe. Thought to have begun their assembly at z > 2, clusters provide insights into the growth of large-scale structure as well as the physics that drives galaxy evolution. Understanding how and when the most massive galaxies assemble their stellar mass, stop forming stars, and acquire their observed morphologies in these environments remain outstanding questions. The redshift range 1.3 < z < 2 is a key epoch in this respect: elliptical galaxies start to become the dominant population in cluster cores, and star formation in spiral galaxies is being quenched. Until recently, however, this redshift range was essentially unreachable with available instrumentation, with clusters at these redshifts exceedingly challenging to identify from either ground-based optical/nearinfrared imaging or from X-ray surveys. Mid-infrared (MIR) imaging with the IRAC camera on board of the Spitzer Space Telescope has changed the landscape. High-redshift clusters are easily identified in the MIR due to a combination of the unique colors of distant galaxies and a negative k-correction in the 3-5 μm range which makes such galaxies bright. Even 90-sec observations with Spitzer/IRAC, a depth which essentially all extragalactic observations in the archive achieve, is sufficient to robustly detect overdensities of L* galaxies out to z~2. Here we request funding to embark on a ambitious scientific program, the “SACS: Spitzer Archival Cluster Survey”, a comprehensive search for the most distant galaxy clusters in all Spitzer/IRAC extragalactic pointings available in the archive. With the SACS we aim to discover ~2000 of 1.3 < z < 2.5 clusters, thus provide the ultimate catalog for high-redshift MIR selected clusters: a lasting legacy for Spitzer. The study we propose will increase by more than a factor of 10 the number of high-redshift clusters discovered by all previous surveys combined, providing a high-purity, uniform sample. Matching the Spitzer/IRAC-selected clusters with data at similar and longer wavelengths available in the archive (WISE 3- 5μm, Spitzer/MIPS 24μm or Herschel/SPIRE 250μm data) we will be also able to study the dependence on the environment of star formation and AGN activity out to z~2, and to study the effect of star-forming galaxies and AGNs on cosmological results from ongoing Sunyaev-Zel'dovich (SZ) and X-ray cluster surveys. The identified clusters will be valuable for both astrophysics and cosmology. In terms of astrophysics, the redshift probed by the MIR color selection targets a key epoch in cluster development, when star formation is shutting down and the galaxies are becoming passive. Massive clusters also distort space-time around them, creating powerful gravitational telescopes that lens the distant universe. This both allows detailed studies of the lensed objects with otherwise unachievable sensitivity, as well as provides a unique probe of the mass distribution in the lensing cluster. In terms of cosmology, clusters are the most massive structures in the universe, and their space density is sensitive to basic cosmological parameters. Clusters identified by this program will become a lasting legacy of Spitzer, providing exciting targets for Chandra, Hubble, James Webb Space Telescope (JWST), Astro-H, Athena, as well as future 30-m class ground-based telescopes (e.g., GMT, ELT, TMT). The upcoming large-scale, space-based surveys of eROSITA, Euclid, and WFIRST all have distant cluster studies as key scientific goals. Our proposed survey will provide new high redshift targets for those satellites, enabling unique, exciting multi-wavelength studies of the Spitzer-selected sample, as well as a training set to identify additional high-redshift clusters outside of the Spitzer footprint.
Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases.

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

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

USGS Publications Warehouse

Bethke, R.; Taylor, Mitchell K.; Amstrup, Steven C.; Messier, François

1996-01-01

To produce reliable estimates of the size or vital rates of a given population, it is important that the boundaries of the population under study are clearly defined. This is particularly critical for large, migratory animals where levels of sustainable harvest are based on these estimates, and where small errors may have serious long-term consequences for the population. Once populations are delineated, rates of exchange between adjacent populations can be determined and accounted/corrected for when calculating abundance (e.g., based on mark-recapture data). Using satellite radio-collar locations for polar bears in the western Canadian Arctic, we illustrate one approach to delineating wildlife populations that integrates cluster analysis methods for determining group membership with home range plotting procedures to define spatial utilization. This approach is flexible with respect to the specific procedures used and provides an objective and quantitative basis for defining population boundaries.
Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds

PubMed Central

Tousseyn, Simon; Dupont, Patrick; Goffin, Karolien; Sunaert, Stefan; Van Paesschen, Wim

2014-01-01

There is currently a lack of knowledge about electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) specificity. Our aim was to define sensitivity and specificity of blood oxygen level dependent (BOLD) responses to interictal epileptic spikes during EEG-fMRI for detecting the ictal onset zone (IOZ). We studied 21 refractory focal epilepsy patients who had a well-defined IOZ after a full presurgical evaluation and interictal spikes during EEG-fMRI. Areas of spike-related BOLD changes overlapping the IOZ in patients were considered as true positives; if no overlap was found, they were treated as false-negatives. Matched healthy case-controls had undergone similar EEG-fMRI in order to determine true-negative and false-positive fractions. The spike-related regressor of the patient was used in the design matrix of the healthy case-control. Suprathreshold BOLD changes in the brain of controls were considered as false positives, absence of these changes as true negatives. Sensitivity and specificity were calculated for different statistical thresholds at the voxel level combined with different cluster size thresholds and represented in receiver operating characteristic (ROC)-curves. Additionally, we calculated the ROC-curves based on the cluster containing the maximal significant activation. We achieved a combination of 100% specificity and 62% sensitivity, using a Z-threshold in the interval 3.4–3.5 and cluster size threshold of 350 voxels. We could obtain higher sensitivity at the expense of specificity. Similar performance was found when using the cluster containing the maximal significant activation. Our data provide a guideline for different EEG-fMRI settings with their respective sensitivity and specificity for detecting the IOZ. The unique cluster containing the maximal significant BOLD activation was a sensitive and specific marker of the IOZ. PMID:25101049
The grapevine expression atlas reveals a deep transcriptome shift driving the entire plant into a maturation program.

PubMed

Fasoli, Marianna; Dal Santo, Silvia; Zenoni, Sara; Tornielli, Giovanni Battista; Farina, Lorenzo; Zamboni, Anita; Porceddu, Andrea; Venturini, Luca; Bicego, Manuele; Murino, Vittorio; Ferrarini, Alberto; Delledonne, Massimo; Pezzotti, Mario

2012-09-01

We developed a genome-wide transcriptomic atlas of grapevine (Vitis vinifera) based on 54 samples representing green and woody tissues and organs at different developmental stages as well as specialized tissues such as pollen and senescent leaves. Together, these samples expressed ∼91% of the predicted grapevine genes. Pollen and senescent leaves had unique transcriptomes reflecting their specialized functions and physiological status. However, microarray and RNA-seq analysis grouped all the other samples into two major classes based on maturity rather than organ identity, namely, the vegetative/green and mature/woody categories. This division represents a fundamental transcriptomic reprogramming during the maturation process and was highlighted by three statistical approaches identifying the transcriptional relationships among samples (correlation analysis), putative biomarkers (O2PLS-DA approach), and sets of strongly and consistently expressed genes that define groups (topics) of similar samples (biclustering analysis). Gene coexpression analysis indicated that the mature/woody developmental program results from the reiterative coactivation of pathways that are largely inactive in vegetative/green tissues, often involving the coregulation of clusters of neighboring genes and global regulation based on codon preference. This global transcriptomic reprogramming during maturation has not been observed in herbaceous annual species and may be a defining characteristic of perennial woody plants.
Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

PubMed Central

Bradshaw, Peter L.; Colville, Jonathan F.; Linder, H. Peter

2015-01-01

We used a very large dataset (>40% of all species) from the endemic-rich Cape Floristic Region (CFR) to explore the impact of different weighting techniques, coefficients to calculate similarity among the cells, and clustering approaches on biogeographical regionalisation. The results were used to revise the biogeographical subdivision of the CFR. We show that weighted data (down-weighting widespread species), similarity calculated using Kulczinsky’s second measure, and clustering using UPGMA resulted in the optimal classification. This maximized the number of endemic species, the number of centres recognized, and operational geographic units assigned to centres of endemism (CoEs). We developed a dendrogram branch order cut-off (BOC) method to locate the optimal cut-off points on the dendrogram to define candidate clusters. Kulczinsky’s second measure dendrograms were combined using consensus, identifying areas of conflict which could be due to biotic element overlap or transitional areas. Post-clustering GIS manipulation substantially enhanced the endemic composition and geographic size of candidate CoEs. Although there was broad spatial congruence with previous phytogeographic studies, our techniques allowed for the recovery of additional phytogeographic detail not previously described for the CFR. PMID:26147438
Conductive tracks of 30-MeV C60 clusters in doped and undoped tetrahedral amorphous carbon

NASA Astrophysics Data System (ADS)

Krauser, J.; Gehrke, H.-G.; Hofsäss, H.; Trautmann, C.; Weidinger, A.

2013-07-01

In insulating tetrahedral amorphous carbon (ta-C), the irradiation with 30-MeV C60 cluster ions leads to the formation of well conducting tracks. While electrical currents through individual tracks produced with monoatomic projectiles (e.g. Au or U) often exhibit rather large track to track fluctuations, C60 clusters are shown to generate highly conducting tracks with very narrow current distributions. Additionally, all recorded current-voltage curves show linear characteristics. These findings are attributed to the large specific energy loss dE/dx of the 30-MeV C60 clusters. We also investigated C60 tracks in ta-C films which were slightly doped with B, N or Fe during film growth. Doping apparently increases the ion track conductivity. However, at the same time the insulating characteristics of the pristine ta-C film can be reduced. The present C60 results are compared with data from earlier experiments with monoatomic heavy ion beams. The investigations were performed by means of atomic force microscopy including temperature dependent conductivity measurements of single ion tracks.
Relativistic coupled-cluster calculations of the 173Yb nuclear quadrupole coupling constant for the YbF molecule

NASA Astrophysics Data System (ADS)

Pašteka, L. F.; Mawhorter, R. J.; Schwerdtfeger, P.

2016-04-01

We report calculations on the q(Yb) electric field gradient (EFG) for the X2Σ+ and A2Π1/2 electronic states of the ytterbium monofluoride (YbF) molecule at the molecular mean-field Dirac-Coulomb-Gaunt as well as scalar-relativistic coupled-cluster levels of theory using large uncontracted basis sets. Vibrational contributions are included in the final results. Our estimated nuclear quadrupole coupling constants of -3386(78) MHz and -2083(153) MHz for the X2Σ+ and A2Π1/2 states of 173YbF are in stark contrast to the only available experimental results (-2050(170) MHz and -1090(160) MHz) respectively, where the only similarity is the difference between the two values. Perturbative triple contributions in the coupled cluster treatment are significant and point towards the necessity to go to higher order in the coupled-cluster treatment in future calculations. We also present density functional calculations which show rather large variations for the Yb EFG with different functionals used; the best result was obtained using the CAM-B3LYP* functional.

Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

PubMed

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.
Efficient Record Linkage Algorithms Using Complete Linkage Clustering

PubMed Central

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times. PMID:27124604
Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

PubMed Central

DeMaere, Matthew Z.

2016-01-01

Background Chromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance. Discussion Previously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development. PMID:27843713
Not-so-simple stellar populations in the intermediate-age Large Magellanic Cloud star clusters NGC 1831 and NGC 1868

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

Li, Chengyuan; De Grijs, Richard; Deng, Licai, E-mail: joshuali@pku.edu.cn, E-mail: grijs@pku.edu.cn

2014-04-01

Using a combination of high-resolution Hubble Space Telescope/Wide-Field and Planetary Camera-2 observations, we explore the physical properties of the stellar populations in two intermediate-age star clusters, NGC 1831 and NGC 1868, in the Large Magellanic Cloud based on their color-magnitude diagrams. We show that both clusters exhibit extended main-sequence turn offs. To explain the observations, we consider variations in helium abundance, binarity, age dispersions, and the fast rotation of the clusters' member stars. The observed narrow main sequence excludes significant variations in helium abundance in both clusters. We first establish the clusters' main-sequence binary fractions using the bulk of themore » clusters' main-sequence stellar populations ≳ 1 mag below their turn-offs. The extent of the turn-off regions in color-magnitude space, corrected for the effects of binarity, implies that age spreads of order 300 Myr may be inferred for both clusters if the stellar distributions in color-magnitude space were entirely due to the presence of multiple populations characterized by an age range. Invoking rapid rotation of the population of cluster members characterized by a single age also allows us to match the observed data in detail. However, when taking into account the extent of the red clump in color-magnitude space, we encounter an apparent conflict for NGC 1831 between the age dispersion derived from that based on the extent of the main-sequence turn off and that implied by the compact red clump. We therefore conclude that, for this cluster, variations in stellar rotation rate are preferred over an age dispersion. For NGC 1868, both models perform equally well.« less
The unusually large Plasmodium telomerase reverse-transcriptase localizes in a discrete compartment associated with the nucleolus

PubMed Central

Figueiredo, Luisa M.; Rocha, Eduardo P. C.; Mancio-Silva, Liliana; Prevost, Christine; Hernandez-Verdun, Danièle; Scherf, Artur

2005-01-01

Telomerase replicates chromosome ends, a function necessary for maintaining genome integrity. We have identified the gene that encodes the catalytic reverse transcriptase (RT) component of this enzyme in the malaria parasite Plasmodium falciparum (PfTERT) as well as the orthologous genes from two rodent and one simian malaria species. PfTERT is predicted to encode a basic protein that contains the major sequence motifs previously identified in known telomerase RTs (TERTs). At ∼2500 amino acids, PfTERT is three times larger than other characterized TERTs. We observed remarkable sequence diversity between TERT proteins of different Plasmodial species, with conserved domains alternating with hypervariable regions. Immunofluorescence analysis revealed that PfTERT is expressed in asexual blood stage parasites that have begun DNA synthesis. Surprisingly, rather than at telomere clusters, PfTERT typically localizes into a discrete nuclear compartment. We further demonstrate that this compartment is associated with the nucleolus, hereby defined for the first time in P.falciparum. PMID:15722485
Distinct aggregation patterns and fluid porous phase in a 2D model for colloids with competitive interactions

NASA Astrophysics Data System (ADS)

Bordin, José Rafael

2018-04-01

In this paper we explore the self-assembly patterns in a two dimensional colloidal system using extensive Langevin Dynamics simulations. The pair potential proposed to model the competitive interaction have a short range length scale between first neighbors and a second characteristic length scale between third neighbors. We investigate how the temperature and colloidal density will affect the assembled morphologies. The potential shows aggregate patterns similar to observed in previous works, as clusters, stripes and porous phase. Nevertheless, we observe at high densities and temperatures a porous mesophase with a high mobility, which we name fluid porous phase, while at lower temperatures the porous structure is rigid. triangular packing was observed for the colloids and pores in both solid and fluid porous phases. Our results show that the porous structure is well defined for a large range of temperature and density, and that the fluid porous phase is a consequence of the competitive interaction and the random forces from the Langevin Dynamics.
Quantum trilogy: discrete Toda, Y-system and chaos

NASA Astrophysics Data System (ADS)

Yamazaki, Masahito

2018-02-01

We discuss a discretization of the quantum Toda field theory associated with a semisimple finite-dimensional Lie algebra or a tamely-laced infinite-dimensional Kac-Moody algebra G, generalizing the previous construction of discrete quantum Liouville theory for the case G = A 1. The model is defined on a discrete two-dimensional lattice, whose spatial direction is of length L. In addition we also find a ‘discretized extra dimension’ whose width is given by the rank r of G, which decompactifies in the large r limit. For the case of G = A N or AN-1(1) , we find a symmetry exchanging L and N under appropriate spatial boundary conditions. The dynamical time evolution rule of the model is quantizations of the so-called Y-system, and the theory can be well described by the quantum cluster algebra. We discuss possible implications for recent discussions of quantum chaos, and comment on the relation with the quantum higher Teichmüller theory of type A N .
Estimation of pairwise sequence similarity of mammalian enhancers with word neighbourhood counts.

PubMed

Göke, Jonathan; Schulz, Marcel H; Lasserre, Julia; Vingron, Martin

2012-03-01

The identity of cells and tissues is to a large degree governed by transcriptional regulation. A major part is accomplished by the combinatorial binding of transcription factors at regulatory sequences, such as enhancers. Even though binding of transcription factors is sequence-specific, estimating the sequence similarity of two functionally similar enhancers is very difficult. However, a similarity measure for regulatory sequences is crucial to detect and understand functional similarities between two enhancers and will facilitate large-scale analyses like clustering, prediction and classification of genome-wide datasets. We present the standardized alignment-free sequence similarity measure N2, a flexible framework that is defined for word neighbourhoods. We explore the usefulness of adding reverse complement words as well as words including mismatches into the neighbourhood. On simulated enhancer sequences as well as functional enhancers in mouse development, N2 is shown to outperform previous alignment-free measures. N2 is flexible, faster than competing methods and less susceptible to single sequence noise and the occurrence of repetitive sequences. Experiments on the mouse enhancers reveal that enhancers active in different tissues can be separated by pairwise comparison using N2. N2 represents an improvement over previous alignment-free similarity measures without compromising speed, which makes it a good candidate for large-scale sequence comparison of regulatory sequences. The software is part of the open-source C++ library SeqAn (www.seqan.de) and a compiled version can be downloaded at http://www.seqan.de/projects/alf.html. Supplementary data are available at Bioinformatics online.
A Hierarchical Framework for State-Space Matrix Inference and Clustering.

PubMed

Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J; Bresnick, Emery H; Keleş, Sündüz

2016-09-01

In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC ( M atrix B ased A nalysis for S tate-space I nference and C lustering) framework. MBASIC consists of two parts: state-space mapping and state-space clustering. In state-space mapping, it maps observations onto a finite state-space, representing the activation states of units across conditions. In state-space clustering, MBASIC incorporates a finite mixture model to cluster the units based on their inferred state-space profiles across all conditions. Both the state-space mapping and clustering can be simultaneously estimated through an Expectation-Maximization algorithm. MBASIC flexibly adapts to a large number of parametric distributions for the observed data, as well as the heterogeneity in replicate experiments. It allows for imposing structural assumptions on each cluster, and enables model selection using information criterion. In our data-driven simulation studies, MBASIC showed significant accuracy in recovering both the underlying state-space variables and clustering structures. We applied MBASIC to two genome research problems using large numbers of datasets from the ENCODE project. The first application grouped genes based on transcription factor occupancy profiles of their promoter regions in two different cell types. The second application focused on identifying groups of loci that are similar to a GATA2 binding site that is functional at its endogenous locus by utilizing transcription factor occupancy data and illustrated applicability of MBASIC in a wide variety of problems. In both studies, MBASIC showed higher levels of raw data fidelity than analyzing these data with a two-step approach using ENCODE results on transcription factor occupancy data.
The Swift AGN and Cluster Survey

NASA Astrophysics Data System (ADS)

Danae Griffin, Rhiannon; Dai, Xinyu; Kochanek, Christopher S.; Bregman, Joel N.; Nugent, Jenna

2016-01-01

The Swift active galactic nucleus (AGN) and Cluster Survey (SACS) uses 125 deg^2 of Swift X-ray Telescope serendipitous fields with variable depths surrounding X-ray bursts to provide a medium depth (4 × 10^-15 erg cm^-2 s^-1) and area survey filling the gap between deep, narrow Chandra/XMM-Newton surveys and wide, shallow ROSAT surveys. Here, we present the first two papers in a series of publications for SACS. In the first paper, we introduce our method and catalog of 22,563 point sources and 442 extended sources. We examine the number counts of the AGN and galaxy cluster populations. SACS provides excellent constraints on the AGN number counts at the bright end with negligible uncertainties due to cosmic variance, and these constraints are consistent with previous measurements. The depth and areal coverage of SACS is well suited for galaxy cluster surveys outside the local universe, reaching z ˜ 1 for massive clusters. In the second paper, we use Sloan Digital Sky Survey (SDSS) DR8 data to study the 203 extended SACS sources that are located within the SDSS footprint. We search for galaxy over-densities in 3-D space using SDSS galaxies and their photometric redshifts near the Swift galaxy cluster candidates. We find 103 Swift clusters with a > 3σ over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmations as galaxy clusters. We present a series of cluster properties including the redshift, BCG magnitude, BCG-to-X-ray center offset, optical richness, X-ray luminosity and red sequences. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≤ 0.3 and 80% complete for z ≤ 0.4, consistent with the survey depth of SDSS. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 2 and 1 matches in optical, X-ray and SZ catalogs, respectively, so the majority of these clusters are new detections. These analysis results suggest that our Swift cluster selection algorithm presented in our first paper has yielded a statistically well-defined cluster sample for further studying cluster evolution and cosmology.
Determining the Optimal Number of Clusters with the Clustergram

NASA Technical Reports Server (NTRS)

Fluegemann, Joseph K.; Davies, Misty D.; Aguirre, Nathan D.

2011-01-01

Cluster analysis aids research in many different fields, from business to biology to aerospace. It consists of using statistical techniques to group objects in large sets of data into meaningful classes. However, this process of ordering data points presents much uncertainty because it involves several steps, many of which are subject to researcher judgment as well as inconsistencies depending on the specific data type and research goals. These steps include the method used to cluster the data, the variables on which the cluster analysis will be operating, the number of resulting clusters, and parts of the interpretation process. In most cases, the number of clusters must be guessed or estimated before employing the clustering method. Many remedies have been proposed, but none is unassailable and certainly not for all data types. Thus, the aim of current research for better techniques of determining the number of clusters is generally confined to demonstrating that the new technique excels other methods in performance for several disparate data types. Our research makes use of a new cluster-number-determination technique based on the clustergram: a graph that shows how the number of objects in the cluster and the cluster mean (the ordinate) change with the number of clusters (the abscissa). We use the features of the clustergram to make the best determination of the cluster-number.
Preparation of multifunctional glyconanoparticles as a platform for potential carbohydrate-based anticancer vaccines.

PubMed

Ojeda, Rafael; de Paz, Jose Luis; Barrientos, Africa G; Martín-Lomas, Manuel; Penadés, Soledad

2007-02-26

A novel platform for anticancer vaccines has been prepared using glyconanotechnology recently developed in our laboratory. Ten different multifunctional gold glyconanoparticles incorporating sialylTn and Lewis(y) antigens, T-cell helper peptides (TT) and glucose in well defined average proportions and with differing density have been synthesised in one step and characterised using NMR and TEM. Size and nature of the linker were crucial to control kinetics of S-Au bond formation and to achieve the desired ligand ratio on the gold clusters. The technology presented here opens the way for tailoring polyvalent anticancer vaccines candidates and drug delivery carriers with defined average chemical composition.
Distributed controller clustering in software defined networks.

PubMed

Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.
Large Earthquakes Disrupt Groundwater System by Breaching Aquitards

NASA Astrophysics Data System (ADS)

Wang, C. Y.; Manga, M.; Liao, X.; Wang, L. P.

2016-12-01

Changes of groundwater system by large earthquakes are widely recognized. Some changes have been attributed to increases in the vertical permeability but basic questions remain: How do increases in the vertical permeability occur? How frequent do they occur? How fast does the vertical permeability recover after the earthquake? Is there a quantitative measure for detecting the occurrence of aquitard breaching? Here we attempt to answer these questions by examining data accumulated in the past 15 years. Analyses of increased stream discharges and their geochemistry after large earthquakes show evidence that the excess water originates from groundwater released from high elevations by large increase of the vertical permeability. Water-level data from a dense network of clustered wells in a sedimentary basin near the epicenter of the 1999 M7.6 Chi-Chi earthquake in western Taiwan show that, while most confined aquifers remained confined after the earthquake, about 10% of the clustered wells show evidence of coseismic breaching of aquitards and a great increase of the vertical permeability. Water level in wells without evidence of coseismic breaching of aquitards show similar tidal response before and after the earthquake; wells with evidence of coseismic breaching of aquitards, on the other hand, show distinctly different tidal response before and after the earthquake and that the aquifers became hydraulically connected for many months thereafter. Breaching of aquitards by large earthquakes has significant implications for a number of societal issues such as the safety of water resources, the security of underground waste repositories, and the production of oil and gas. The method demonstrated here may be used for detecting the occurrence of aquitard breaching by large earthquakes in other seismically active areas.
Deep experimental profiling of microRNA diversity, deployment, and evolution across the Drosophila genus.

PubMed

Mohammed, Jaaved; Flynt, Alex S; Panzarino, Alexandra M; Mondal, Md Mosharrof Hossein; DeCruz, Matthew; Siepel, Adam; Lai, Eric C

2018-01-01

To assess miRNA evolution across the Drosophila genus, we analyzed several billion small RNA reads across 12 fruit fly species. These data permit comprehensive curation of species- and clade-specific variation in miRNA identity, abundance, and processing. Among well-conserved miRNAs, we observed unexpected cases of clade-specific variation in 5' end precision, occasional antisense loci, and putatively noncanonical loci. We also used strict criteria to identify a large set (649) of novel, evolutionarily restricted miRNAs. Within the bulk collection of species-restricted miRNAs, two notable subpopulations are splicing-derived mirtrons and testes-restricted, recently evolved, clustered (TRC) canonical miRNAs. We quantified miRNA birth and death using our annotation and a phylogenetic model for estimating rates of miRNA turnover. We observed striking differences in birth and death rates across miRNA classes defined by biogenesis pathway, genomic clustering, and tissue restriction, and even identified flux heterogeneity among Drosophila clades. In particular, distinct molecular rationales underlie the distinct evolutionary behavior of different miRNA classes. Mirtrons are associated with high rates of 3' untemplated addition, a mechanism that impedes their biogenesis, whereas TRC miRNAs appear to evolve under positive selection. Altogether, these data reveal miRNA diversity among Drosophila species and principles underlying their emergence and evolution. © 2018 Mohammed et al.; Published by Cold Spring Harbor Laboratory Press.
First evidence of diffuse ultra-steep-spectrum radio emission surrounding the cool core of a cluster

NASA Astrophysics Data System (ADS)

Savini, F.; Bonafede, A.; Brüggen, M.; van Weeren, R.; Brunetti, G.; Intema, H.; Botteon, A.; Shimwell, T.; Wilber, A.; Rafferty, D.; Giacintucci, S.; Cassano, R.; Cuciti, V.; de Gasperin, F.; Röttgering, H.; Hoeft, M.; White, G.

2018-05-01

Diffuse synchrotron radio emission from cosmic-ray electrons is observed at the center of a number of galaxy clusters. These sources can be classified either as giant radio halos, which occur in merging clusters, or as mini halos, which are found only in cool-core clusters. In this paper, we present the first discovery of a cool-core cluster with an associated mini halo that also shows ultra-steep-spectrum emission extending well beyond the core that resembles radio halo emission. The large-scale component is discovered thanks to LOFAR observations at 144 MHz. We also analyse GMRT observations at 610 MHz to characterise the spectrum of the radio emission. An X-ray analysis reveals that the cluster is slightly disturbed, and we suggest that the steep-spectrum radio emission outside the core could be produced by a minor merger that powers electron re-acceleration without disrupting the cool core. This discovery suggests that, under particular circumstances, both a mini and giant halo could co-exist in a single cluster, opening new perspectives for particle acceleration mechanisms in galaxy clusters.
Clustering of gamma-ray burst types in the Fermi GBM catalogue: indications of photosphere and synchrotron emissions during the prompt phase

NASA Astrophysics Data System (ADS)

Acuner, Zeynep; Ryde, Felix

2018-04-01

Many different physical processes have been suggested to explain the prompt gamma-ray emission in gamma-ray bursts (GRBs). Although there are examples of both bursts with photospheric and synchrotron emission origins, these distinct spectral appearances have not been generalized to large samples of GRBs. Here, we search for signatures of the different emission mechanisms in the full Fermi Gamma-ray Space Telescope/GBM (Gamma-ray Burst Monitor) catalogue. We use Gaussian Mixture Models to cluster bursts according to their parameters from the Band function (α, β, and Epk) as well as their fluence and T90. We find five distinct clusters. We further argue that these clusters can be divided into bursts of photospheric origin (2/3 of all bursts, divided into three clusters) and bursts of synchrotron origin (1/3 of all bursts, divided into two clusters). For instance, the cluster that contains predominantly short bursts is consistent of photospheric emission origin. We discuss several reasons that can determine which cluster a burst belongs to: jet dissipation pattern and/or the jet content, or viewing angle.
Effect of charge and composition on the structural fluxionality and stability of nine atom tin-bismuth Zintl analogues.

PubMed

Gupta, Ujjwal; Reber, Arthur C; Clayborne, Penee A; Melko, Joshua J; Khanna, Shiv N; Castleman, A W

2008-12-01

Synergistic studies of bismuth doped tin clusters combining photoelectron spectra with first principles theoretical investigations establish that highly charged Zintl ions, observed in the condensed phase, can be stabilized as isolated gas phase clusters through atomic substitution that preserves the overall electron count but reduces the net charge and thereby avoids instability because of coulomb repulsion. Mass spectrometry studies reveal that Sn(8)Bi(-), Sn(7)Bi(2)(-), and Sn(6)Bi(3)(-) exhibit higher abundances than neighboring species, and photoelectron spectroscopy show that all of these heteroatomic gas phase Zintl analogues (GPZAs) have high adiabatic electron detachment energies. Sn(6)Bi(3)(-) is found to be a particularly stable cluster, having a large highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap. Theoretical calculations demonstrate that the Sn(6)Bi(3)(-) cluster is isoelectronic with the well know Sn(9)(-4) Zintl ion; however, the fluxionality reported for Sn(9)(-4) is suppressed by substituting Sn atoms with Bi atoms. Thus, while the electronic stability of the clusters is dominated by electron count, the size and position of the atoms affects the dynamics of the cluster as well. Substitution with Bi enlarges the cage compared with Sn(9)(-4) making it favorable for endohedral doping, findings which suggest that these cages may find use for building blocks of cluster assembled materials.
STAR FORMATION ACROSS THE W3 COMPLEX

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

Román-Zúñiga, Carlos G.; Ybarra, Jason E.; Tapia, Mauricio

We present a multi-wavelength analysis of the history of star formation in the W3 complex. Using deep, near-infrared ground-based images combined with images obtained with Spitzer and Chandra observatories, we identified and classified young embedded sources. We identified the principal clusters in the complex and determined their structure and extension. We constructed extinction-limited samples for five principal clusters and constructed K-band luminosity functions that we compare with those of artificial clusters with varying ages. This analysis provided mean ages and possible age spreads for the clusters. We found that IC 1795, the centermost cluster of the complex, still hosts amore » large fraction of young sources with circumstellar disks. This indicates that star formation was active in IC 1795 as recently as 2 Myr ago, simultaneous to the star-forming activity in the flanking embedded clusters, W3-Main and W3(OH). A comparison with carbon monoxide emission maps indicates strong velocity gradients in the gas clumps hosting W3-Main and W3(OH) and shows small receding clumps of gas at IC 1795, suggestive of rapid gas removal (faster than the T Tauri timescale) in the cluster-forming regions. We discuss one possible scenario for the progression of cluster formation in the W3 complex. We propose that early processes of gas collapse in the main structure of the complex could have defined the progression of cluster formation across the complex with relatively small age differences from one group to another. However, triggering effects could act as catalysts for enhanced efficiency of formation at a local level, in agreement with previous studies.« less
Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.

PubMed

Crow, Megan; Paul, Anirban; Ballouz, Sara; Huang, Z Josh; Gillis, Jesse

2018-02-28

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.

Front propagation and clustering in the stochastic nonlocal Fisher equation

NASA Astrophysics Data System (ADS)

Ganan, Yehuda A.; Kessler, David A.

2018-04-01

In this work, we study the problem of front propagation and pattern formation in the stochastic nonlocal Fisher equation. We find a crossover between two regimes: a steadily propagating regime for not too large interaction range and a stochastic punctuated spreading regime for larger ranges. We show that the former regime is well described by the heuristic approximation of the system by a deterministic system where the linear growth term is cut off below some critical density. This deterministic system is seen not only to give the right front velocity, but also predicts the onset of clustering for interaction kernels which give rise to stable uniform states, such as the Gaussian kernel, for sufficiently large cutoff. Above the critical cutoff, distinct clusters emerge behind the front. These same features are present in the stochastic model for sufficiently small carrying capacity. In the latter, punctuated spreading, regime, the population is concentrated on clusters, as in the infinite range case, which divide and separate as a result of the stochastic noise. Due to the finite interaction range, if a fragment at the edge of the population separates sufficiently far, it stabilizes as a new cluster, and the processes begins anew. The deterministic cutoff model does not have this spreading for large interaction ranges, attesting to its purely stochastic origins. We show that this mode of spreading has an exponentially small mean spreading velocity, decaying with the range of the interaction kernel.
Front propagation and clustering in the stochastic nonlocal Fisher equation.

PubMed

Ganan, Yehuda A; Kessler, David A

2018-04-01

In this work, we study the problem of front propagation and pattern formation in the stochastic nonlocal Fisher equation. We find a crossover between two regimes: a steadily propagating regime for not too large interaction range and a stochastic punctuated spreading regime for larger ranges. We show that the former regime is well described by the heuristic approximation of the system by a deterministic system where the linear growth term is cut off below some critical density. This deterministic system is seen not only to give the right front velocity, but also predicts the onset of clustering for interaction kernels which give rise to stable uniform states, such as the Gaussian kernel, for sufficiently large cutoff. Above the critical cutoff, distinct clusters emerge behind the front. These same features are present in the stochastic model for sufficiently small carrying capacity. In the latter, punctuated spreading, regime, the population is concentrated on clusters, as in the infinite range case, which divide and separate as a result of the stochastic noise. Due to the finite interaction range, if a fragment at the edge of the population separates sufficiently far, it stabilizes as a new cluster, and the processes begins anew. The deterministic cutoff model does not have this spreading for large interaction ranges, attesting to its purely stochastic origins. We show that this mode of spreading has an exponentially small mean spreading velocity, decaying with the range of the interaction kernel.
A microstrip array feed for MSAT spacecraft reflector antenna

NASA Technical Reports Server (NTRS)

Huang, John

1988-01-01

An L-band circularly polarized microstrip array antenna with relatively wide bandwidth has been developed. The array has seven subarrays which form a single cluster as part of a large overlapping cluster reflector feed array. Each of the seven subarrays consists of four uniquely arranged linearly polarized microstrip elements. A 7.5 percent impedance (VSWR less than 1.5) as well as axial ratio (less than 1 dB) bandwidths have been achieved by employing a relatively thick honeycomb substrate with special impedance matching feed probes.
Cluster formation and drag reduction-proposed mechanism of particle recirculation within the partition column of the bottom spray fluid-bed coater.

PubMed

Wang, Li Kun; Heng, Paul Wan Sia; Liew, Celine Valeria

2015-04-01

Bottom spray fluid-bed coating is a common technique for coating multiparticulates. Under the quality-by-design framework, particle recirculation within the partition column is one of the main variability sources affecting particle coating and coat uniformity. However, the occurrence and mechanism of particle recirculation within the partition column of the coater are not well understood. The purpose of this study was to visualize and define particle recirculation within the partition column. Based on different combinations of partition gap setting, air accelerator insert diameter, and particle size fraction, particle movements within the partition column were captured using a high-speed video camera. The particle recirculation probability and voidage information were mapped using a visiometric process analyzer. High-speed images showed that particles contributing to the recirculation phenomenon were behaving as clustered colonies. Fluid dynamics analysis indicated that particle recirculation within the partition column may be attributed to the combined effect of cluster formation and drag reduction. Both visiometric process analysis and particle coating experiments showed that smaller particles had greater propensity toward cluster formation than larger particles. The influence of cluster formation on coating performance and possible solutions to cluster formation were further discussed. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Bottom-up strategies for the assembling of magnetic systems using nanoclusters

NASA Astrophysics Data System (ADS)

Dupuis, V.; Hillion, A.; Robert, A.; Loiselet, O.; Khadra, G.; Capiod, P.; Albin, C.; Boisron, O.; Le Roy, D.; Bardotti, L.; Tournus, F.; Tamion, A.

2018-05-01

In the frame of the 20th Anniversary of the Journal of Nanoparticle Research (JNR), our aim is to start from the historical context 20 years ago and to give some recent results and perspectives concerning nanomagnets prepared from clusters preformed in the gas phase using the low-energy cluster beam deposition (LECBD) technique. In this paper, we focus our attention on the typical case of Co clusters embedded in various matrices to study interface magnetic anisotropy and magnetic interactions as a function of volume concentrations, and on still current and perspectives through two examples of binary metallic 3d-5d TM (namely CoPt and FeAu) cluster assemblies to illustrate size-related and nanoalloy phenomena on magnetic properties in well-defined mass-selected clusters. The structural and magnetic properties of these cluster assemblies were investigated using various experimental techniques that include high-resolution transmission electron microscopy (HRTEM), superconducting quantum interference device (SQUID) magnetometry, and synchrotron techniques such as extended X-ray absorption fine structure (EXAFS) and X-ray magnetic circular dichroism (XMCD). Depending on the chemical nature of both NPs and matrix, we observe different magnetic responses compared to their bulk counterparts. In particular, we show how finite size effects (size reduction) enhance their magnetic moment and how specific relaxation in nanoalloys can impact their magnetic anisotropy.
Superframe Duration Allocation Schemes to Improve the Throughput of Cluster-Tree Wireless Sensor Networks

PubMed Central

Leão, Erico; Montez, Carlos; Moraes, Ricardo; Portugal, Paulo; Vasques, Francisco

2017-01-01

The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks. PMID:28134822
A new method to quantify the effects of baryons on the matter power spectrum

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

Schneider, Aurel; Teyssier, Romain, E-mail: aurel@physik.uzh.ch, E-mail: teyssier@physik.uzh.ch

2015-12-01

Future large-scale galaxy surveys have the potential to become leading probes for cosmology provided the influence of baryons on the total mass distribution is understood well enough. As hydrodynamical simulations strongly depend on details in the feedback implementations, no unique and robust predictions for baryonic effects currently exist. In this paper we propose a baryonic correction model that modifies the density field of dark-matter-only N-body simulations to mimic the effects of baryons from any underlying adopted feedback recipe. The model assumes haloes to consist of 4 components: 1- hot gas in hydrostatical equilibrium, 2- ejected gas from feedback processes, 3-more » central galaxy stars, and 4- adiabatically relaxed dark matter, which all modify the initial dark-matter-only density profiles. These altered profiles allow to define a displacement field for particles in N-body simulations and to modify the total density field accordingly. The main advantage of the baryonic correction model is to connect the total matter density field to the observable distribution of gas and stars in haloes, making it possible to parametrise baryonic effects on the matter power spectrum. We show that the most crucial quantities are the mass fraction of ejected gas and its corresponding ejection radius. The former controls how strongly baryons suppress the power spectrum, while the latter provides a measure of the scale where baryonic effects become important. A comparison with X-ray and Sunyaev-Zel'dovich cluster observations suggests that baryons suppress wave modes above k∼0.5 h/Mpc with a maximum suppression of 10-25 percent around k∼ 2 h/Mpc. More detailed observations of the gas in the outskirts of groups and clusters are required to decrease the large uncertainties of these numbers.« less
Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development

PubMed Central

Alvarez, Stéphanie; Timler, Carl J.; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A.; Groot, Jeroen C. J.

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia’s Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies. PMID:29763422
Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development.

PubMed

Alvarez, Stéphanie; Timler, Carl J; Michalscheck, Mirja; Paas, Wim; Descheemaeker, Katrien; Tittonell, Pablo; Andersson, Jens A; Groot, Jeroen C J

2018-01-01

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.
COS Spectroscopy of White Dwarf Companions to Blue Stragglers

NASA Astrophysics Data System (ADS)

Gosnell, Natalie M.; Geller, Aaron M.; Knigge, Christian; Mathieu, Robert D.; Sills, Alison; Leiner, Emily; Leigh, Nathan

2017-01-01

Complete membership studies of open stellar clusters reveal that 25% of the evolved stars follow alternative pathways in stellar evolution, meaning something in the history of these stars changed their composition or mass (or both). In order to draw a complete picture of stellar evolution we must include these canonically "strange" stars in our definition of standard stellar populations. The formation mechanism of blue straggler stars, traditionally defined to be brighter and bluer than the main sequence turnoff in a star cluster, has been an outstanding question for almost six decades. Recent Hubble Space Telescope (HST) far-ultraviolet (far-UV) observations directly reveal that the blue straggler stars in the old (7 Gyr) open cluster NGC 188 are predominantly formed through mass transfer. We will present HST far-UV COS spectroscopy of white dwarf companions to blue stragglers. These white dwarfs are the remnants of the mass transfer formation process. The effective temperatures and surface gravities of the white dwarfs delineate the timeline of blue straggler formation in this cluster. The existence of these binaries in a well-studied cluster environment provides an unprecedented opportunity to observationally constrain mass transfer models and inform our understanding of many other alternative pathway stellar products.
A role for surface hydrophobicity in protein-protein recognition.

PubMed Central

Young, L.; Jernigan, R. L.; Covell, D. G.

1994-01-01

The role of hydrophobicity as a determinant of protein-protein interactions is examined. Surfaces of apo-protein targets comprising 9 classes of enzymes, 7 antibody fragments, hirudin, growth hormone, and retinol-binding protein, and their associated ligands with available X-ray structures for their complexed forms, are scanned to determine clusters of surface-accessible amino acids. Clusters of surface residues are ranked on the basis of the hydrophobicity of their constituent amino acids. The results indicate that the location of the co-crystallized ligand is commonly found to correspond with one of the strongest hydrophobic clusters on the surface of the target molecule. In 25 of 38 cases, the correspondence is exact, with the position of the most hydrophobic cluster coinciding with more than one-third of the surface buried by the bound ligand. The remaining 13 cases demonstrate this correspondence within the top 6 hydrophobic clusters. These results suggest that surface hydrophobicity can be used to identify regions of a protein's surface most likely to interact with a binding ligand. This fast and simple procedure may be useful for identifying small sets of well-defined loci for possible ligand attachment. PMID:8061602
Comparative study of cluster Ag17Cu2 by instantaneous normal mode analysis and by isothermal Brownian-type molecular dynamics simulation.

PubMed

Tang, Ping-Han; Wu, Ten-Ming; Yen, Tsung-Wen; Lai, S K; Hsu, P J

2011-09-07

We perform isothermal Brownian-type molecular dynamics simulations to obtain the velocity autocorrelation function and its time Fourier-transformed power spectral density for the metallic cluster Ag(17)Cu(2). The temperature dependences of these dynamical quantities from T = 0 to 1500 K were examined and across this temperature range the cluster melting temperature T(m), which we define to be the principal maximum position of the specific heat is determined. The instantaneous normal mode analysis is then used to dissect the cluster dynamics by calculating the vibrational instantaneous normal mode density of states and hence its frequency integrated value I(j) which is an ensemble average of all vibrational projection operators for the jth atom in the cluster. In addition to comparing the results with simulation data, we look more closely at the entities I(j) of all atoms using the point group symmetry and diagnose their temperature variations. We find that I(j) exhibit features that may be used to deduce T(m), which turns out to agree very well with those inferred from the power spectral density and specific heat. © 2011 American Institute of Physics
Dehydration, Dehydrogenation, and Condensation of Alcohols on Supported Oxide Catalysts Based on Cyclic (WO3)3 and (MoO3)3 Clusters

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

Rousseau, Roger J.; Dixon, David A.; Kay, Bruce D.

2014-01-01

Supported early transition metal oxides have important applications in numerous catalytic reactions. In this article we review preparation and activity of well-defined model WO3 and MoO3 catalysts prepared via deposition of cyclic gas-phase (WO3)3 and (MoO3)3 clusters generated by sublimation of WO3 and MoO3 powders. Conversion of small aliphatic alcohols to alkenes, aldehydes/ketons, and ethers is employed to probe the structure-activity relationships on model WO3 and MoO3 catalysts ranging from unsupported (WO3)3 and (MoO3)3 clusters embedded in alcohol matrices, to (WO3)3 clusters supported on surfaces of other oxides, and epitaxial and nanoporous WO3 films. Detailed theoretical calculations reveal the underlyingmore » reaction mechanisms and provide insight into the origin of the differences in the WO3 and MoO3 reactivity. For the range of interrogated (WO3)3 they further shed light into the role structure and binding of (WO3)3 clusters with the support play in determining their catalytic activity.« less
Defining clusters in APT reconstructions of ODS steels.

PubMed

Williams, Ceri A; Haley, Daniel; Marquis, Emmanuelle A; Smith, George D W; Moody, Michael P

2013-09-01

Oxide nanoclusters in a consolidated Fe-14Cr-2W-0.3Ti-0.3Y₂O₃ ODS steel and in the alloy powder after mechanical alloying (but before consolidation) are investigated by atom probe tomography (APT). The maximum separation method is a standard method to define and characterise clusters from within APT data, but this work shows that the extent of clustering between the two materials is sufficiently different that the nanoclusters in the mechanically alloyed powder and in the consolidated material cannot be compared directly using the same cluster selection parameters. As the cluster selection parameters influence the size and composition of the clusters significantly, a procedure to optimise the input parameters for the maximum separation method is proposed by sweeping the d(max) and N(min) parameter space. By applying this method of cluster parameter selection combined with a 'matrix correction' to account for trajectory aberrations, differences in the oxide nanoclusters can then be reliably quantified. Copyright © 2012 Elsevier B.V. All rights reserved.
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.
Evaluating Tests of Virialization and Substructure Using Galaxy Clusters in the ORELSE Survey

NASA Astrophysics Data System (ADS)

Rumbaugh, N.; Lemaux, B. C.; Tomczak, A. R.; Shen, L.; Pelliccia, D.; Lubin, L. M.; Kocevski, D. D.; Wu, P.-F.; Gal, R. R.; Mei, S.; Fassnacht, C. D.; Squires, G. K.

2018-05-01

We evaluated the effectiveness of different indicators of cluster virialization using 12 large-scale structures in the ORELSE survey spanning from 0.7 < z < 1.3. We located diffuse X-ray emission from 16 galaxy clusters using Chandra observations. We studied the properties of these clusters and their members, using Chandra data in conjunction with optical and near-IR imaging and spectroscopy. We measured X-ray luminosities and gas temperatures of each cluster, as well as velocity dispersions of their member galaxies. We compared these results to scaling relations derived from virialized clusters, finding significant offsets of up to 3-4σ for some clusters, which could indicate they are disturbed or still forming. We explored if other properties of the clusters correlated with these offsets by performing a set of tests of virialization and substructure on our sample, including Dressler-Schectman tests, power ratios, analyses of the velocity distributions of galaxy populations, and centroiding differences. For comparison to a wide range of studies, we used two sets of tests: ones that did and did not use spectral energy distribution fitting to obtain rest-frame colours, stellar masses, and photometric redshifts of galaxies. Our results indicated that the difference between the stellar mass or light mean-weighted center and the X-ray center, as well as the projected offset of the most-massive/brightest cluster galaxy from other cluster centroids had the strongest correlations with scaling relation offsets, implying they are the most robust indicators of cluster virialization and can be used for this purpose when X-ray data is insufficiently deep for reliable LX and TX measurements.
Piezometer completion report for borehole cluster sites DC-19, DC-20, and DC-22

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

Jackson, R.L.; Diediker, L.D.; Ledgerwood, R.K.

1984-07-01

This report describes the design and installation of multi-level piezometers at borehole cluster sites DC-19, DC-20 and DC-22. The network of borehole cluster sites will provide facilities for multi-level water-level monitoring across the RRL for piezometer baseline monitoring and for large-scale hydraulic stress testing. These groundwater-monitoring facilities were installed between August 1983 and March 1984. Three series of piezometer nests (A-, C- and D-series) were installed in nine hydrogeologic units (monitoring horizons) within the Columbia River Basalt Group at each borehole cluster site. In addition to the piezometer facilities, a B-series pumping well was installed at borehole cluster sites DC-20more » and DC-22. The A-series piezometer nest monitors the basal Ringold sediments and the Rattlesnake Ridge interbed. The C-series piezometer nests monitors the six deepest horizons, which are in increasing depth, the Priest Rapids interflow, Sentinel Gap flow top, Ginkgo flow top, Rocky Coulee flow top, Cohassett flow top and Umtanum flow top. The D-series piezometer monitors the Mabton interbed. The B-series pumping well was completed in the Priest Rapids interflow. 21 refs., 6 figs., 6 tabs.« less
Microseismic Event Relocation and Focal Mechanism Estimation Based on PageRank Linkage

NASA Astrophysics Data System (ADS)

Aguiar, A. C.; Myers, S. C.

2017-12-01

Microseismicity associated with enhanced geothermal systems (EGS) is key in understanding how subsurface stimulation can modify stress, fracture rock, and increase permeability. Large numbers of microseismic events are commonly associated with hydroshearing an EGS, making data mining methods useful in their analysis. We focus on PageRank, originally developed as Google's search engine, and subsequently adapted for use in seismology to detect low-frequency earthquakes by linking events directly and indirectly through cross-correlation (Aguiar and Beroza, 2014). We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes from the Newberry Volcano EGS in Central Oregon, which has been stimulated two times using high-pressure fluid injection. We create PageRank signal families from both data sets and compare these to the spatial and temporal proximity of associated earthquakes. PageRank families are relocated using differential travel times measured by waveform cross-correlation (CC) and the Bayesloc approach (Myers et al., 2007). Prior to relocation events are loosely clustered with events at a distance from the cluster. After relocation, event families are found to be tightly clustered. Indirect linkage of signals using PageRank is a reliable way to increase the number of events confidently determined to be similar, suggesting an efficient and effective grouping of earthquakes with similar physical characteristics (ie. location, focal mechanism, stress drop). We further explore the possibility of using PageRank families to identify events with similar relative phase polarities and estimate focal mechanisms following Shelly et al. (2016) method, where CC measurements are used to determine individual polarities within event clusters. Given a positive result, PageRank might be a useful tool in adaptive approaches to enhance production at well-instrumented geothermal sites. Prepared by LLNL under Contract DE-AC52-07NA27344. LLNL-ABS-722404.
Mass Cytometry Identifies Distinct Lung CD4+ T Cell Patterns in Löfgren’s Syndrome and Non-Löfgren’s Syndrome Sarcoidosis

PubMed Central

Kaiser, Ylva; Lakshmikanth, Tadepally; Chen, Yang; Mikes, Jaromir; Eklund, Anders; Brodin, Petter; Achour, Adnane; Grunewald, Johan

2017-01-01

Sarcoidosis is a granulomatous disorder of unknown etiology, characterized by accumulation of activated CD4+ T cells in the lungs. Disease phenotypes Löfgren’s syndrome (LS) and “non-LS” differ in terms of clinical manifestations, genetic background, HLA association, and prognosis, but the underlying inflammatory mechanisms largely remain unknown. Bronchoalveolar lavage fluid cells from four HLA-DRB1*03+ LS and four HLA-DRB1*03− non-LS patients were analyzed by mass cytometry, using a panel of 33 unique markers. Differentially regulated CD4+ T cell populations were identified using the Citrus algorithm, and t-stochastic neighborhood embedding was applied for dimensionality reduction and single-cell data visualization. We identified 19 individual CD4+ T cell clusters differing significantly in abundance between LS and non-LS patients. Seven clusters more frequent in LS patients were characterized by significantly higher expression of regulatory receptors CTLA-4, PD-1, and ICOS, along with low expression of adhesion marker CD44. In contrast, 12 clusters primarily found in non-LS displayed elevated expression of activation and effector markers HLA-DR, CD127, CD39, as well as CD44. Hierarchical clustering further indicated functional heterogeneity and diverse origins of T cell receptor Vα2.3/Vβ22-restricted cells in LS. Finally, a near-complete overlap of CD8 and Ki-67 expression suggested larger influence of CD8+ T cell activity on sarcoid inflammation than previously appreciated. In this study, we provide detailed characterization of pulmonary T cells and immunological parameters that define separate disease pathways in LS and non-LS. With direct association to clinical parameters, such as granuloma persistence, resolution, or chronic inflammation, these results provide a valuable foundation for further exploration and potential clinical application. PMID:28955342
Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble

NASA Astrophysics Data System (ADS)

Yongye, Austin B.; Bender, Andreas; Martínez-Mayorga, Karina

2010-08-01

Representing the 3D structures of ligands in virtual screenings via multi-conformer ensembles can be computationally intensive, especially for compounds with a large number of rotatable bonds. Thus, reducing the size of multi-conformer databases and the number of query conformers, while simultaneously reproducing the bioactive conformer with good accuracy, is of crucial interest. While clustering and RMSD filtering methods are employed in existing conformer generators, the novelty of this work is the inclusion of a clustering scheme (NMRCLUST) that does not require a user-defined cut-off value. This algorithm simultaneously optimizes the number and the average spread of the clusters. Here we describe and test four inter-dependent approaches for selecting computer-generated conformers, namely: OMEGA, NMRCLUST, RMS filtering and averaged- RMS filtering. The bioactive conformations of 65 selected ligands were extracted from the corresponding protein:ligand complexes from the Protein Data Bank, including eight ligands that adopted dissimilar bound conformations within different receptors. We show that NMRCLUST can be employed to further filter OMEGA-generated conformers while maintaining biological relevance of the ensemble. It was observed that NMRCLUST (containing on average 10 times fewer conformers per compound) performed nearly as well as OMEGA, and both outperformed RMS filtering and averaged- RMS filtering in terms of identifying the bioactive conformations with excellent and good matches (0.5 < RMSD < 1.0 Å). Furthermore, we propose thresholds for OMEGA root-mean square filtering depending on the number of rotors in a compound: 0.8, 1.0 and 1.4 for structures with low (1-4), medium (5-9) and high (10-15) numbers of rotatable bonds, respectively. The protocol employed is general and can be applied to reduce the number of conformers in multi-conformer compound collections and alleviate the complexity of downstream data processing in virtual screening experiments.

R-CMap-An open-source software for concept mapping.

PubMed

Bar, Haim; Mentch, Lucas

2017-02-01

Planning and evaluating projects often involves input from many stakeholders. Fusing and organizing many different ideas, opinions, and interpretations into a coherent and acceptable plan or project evaluation is challenging. This is especially true when seeking contributions from a large number of participants, especially when not all can participate in group discussions, or when some prefer to contribute their perspectives anonymously. One of the major breakthroughs in the area of evaluation and program planning has been the use of graphical tools to represent the brainstorming process. This provides a quantitative framework for organizing ideas and general concepts into simple-to-interpret graphs. We developed a new, open-source concept mapping software called R-CMap, which is implemented in R. This software provides a graphical user interface to guide users through the analytical process of concept mapping. The R-CMap software allows users to generate a variety of plots, including cluster maps, point rating and cluster rating maps, as well as pattern matching and go-zone plots. Additionally, R-CMap is capable of generating detailed reports that contain useful statistical summaries of the data. The plots and reports can be embedded in Microsoft Office tools such as Word and PowerPoint, where users may manually adjust various plot and table features to achieve the best visual results in their presentations and official reports. The graphical user interface of R-CMap allows users to define cluster names, change the number of clusters, select rating variables for relevant plots, and importantly, select subsets of respondents by demographic criteria. The latter is particularly useful to project managers in order to identify different patterns of preferences by subpopulations. R-CMap is user-friendly, and does not require any programming experience. However, proficient R users can add to its functionality by directly accessing built-in functions in R and sharing new features with the concept mapping community. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Groundwater level and specific conductance monitoring at Marine Corps Base, Camp Lejeune, Onslow County, North Carolina, 2007-2008

USGS Publications Warehouse

McSwain, Kristen Bukowski

2010-01-01

The U.S. Geological Survey, in cooperation with the Marine Corps Base, Camp Lejeune, monitored water-resources conditions in the surficial, Castle Hayne, Peedee, and Black Creek aquifers in Onslow County, North Carolina, from November 2007 through September 2008. To comply with North Carolina Central Coastal Plain Capacity Use Area regulations, large-volume water suppliers in Onslow County must reduce their dependency on the Black Creek aquifer as a water-supply source and have, instead, proposed using the Castle Hayne aquifer as an alternative water-supply source. The Marine Corps Base, Camp Lejeune, uses water obtained from the unregulated surficial and Castle Hayne aquifers for drinking-water supply. Water-level data were collected and field measurements of physical properties were made at 19 wells at 8 locations spanning the Marine Corps Base, Camp Lejeune. These wells were instrumented with near real-time monitoring equipment to collect hourly measurements of water level. Additionally, specific conductance and water temperature were measured hourly in 16 of the 19 wells. Graphs are presented relating altitude of groundwater level to water temperature and specific conductance measurements collected during the study, and the relative vertical gradients between aquifers are discussed. The period-of-record normal (25th to 75th percentile) monthly mean groundwater levels at two well clusters were compared to median monthly mean groundwater levels at these same well clusters for 2008 to determine groundwater-resources conditions. In 2008, water levels were below normal in the 3 wells at one of the well clusters and were normal in 4 wells at the other cluster.
Medium-induced change of the optical response of metal clusters in rare-gas matrices

NASA Astrophysics Data System (ADS)

Xuan, Fengyuan; Guet, Claude

2017-10-01

Interaction with the surrounding medium modifies the optical response of embedded metal clusters. For clusters from about ten to a few hundreds of silver atoms, embedded in rare-gas matrices, we study the environment effect within the matrix random phase approximation with exact exchange (RPAE) quantum approach, which has proved successful for free silver clusters. The polarizable surrounding medium screens the residual two-body RPAE interaction, adds a polarization term to the one-body potential, and shifts the vacuum energy of the active delocalized valence electrons. Within this model, we calculate the dipole oscillator strength distribution for Ag clusters embedded in helium droplets, neon, argon, krypton, and xenon matrices. The main contribution to the dipole surface plasmon red shift originates from the rare-gas polarization screening of the two-body interaction. The large size limit of the dipole surface plasmon agrees well with the classical prediction.
Isolation of Notl sites from chromosome 22q11

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

Ten Hoeve, J.; Groffen, J.; Heisterkamp, N.

1993-12-01

Chromosome 22q11 contains a large number of interesting loci, including genes associated with cancer and developmental defects. The region is also the site of the lambda immunoglobulin variable and constants regions and the BCR, [gamma]-glutamyl transpeptidase, and GGT-like activity multigene families. Because of the complexities associated with mapping highly related gene families, the authors have examined the utility of mapping large areas of DNA using a defined approach. A total of 21 complete NotI sites from band q11 were cloned and ordered into six noncontiguous clusters of sites using a combination of somatic cell hybrid panels, NotI jumping and linkingmore » libraries, and fluorescence in situ hybridization. The largest cluster spanned an estimated 2 Mb of NotI fragments, the smallest 115 kb. Approximately 3.5 Mb of band q11 could be examined for rearrangements in NotI restriction enzyme fragments. A number of conserved sequences, two genes, and a minimum of two families of related sequences were identified adjacent to NotI sites. 51 refs., 5 figs., 4 tabs.« less
Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data

DOE PAGES

Hsu, David

2015-09-27

Clustering methods are often used to model energy consumption for two reasons. First, clustering is often used to process data and to improve the predictive accuracy of subsequent energy models. Second, stable clusters that are reproducible with respect to non-essential changes can be used to group, target, and interpret observed subjects. However, it is well known that clustering methods are highly sensitive to the choice of algorithms and variables. This can lead to misleading assessments of predictive accuracy and mis-interpretation of clusters in policymaking. This paper therefore introduces two methods to the modeling of energy consumption in buildings: clusterwise regression,more » also known as latent class regression, which integrates clustering and regression simultaneously; and cluster validation methods to measure stability. Using a large dataset of multifamily buildings in New York City, clusterwise regression is compared to common two-stage algorithms that use K-means and model-based clustering with linear regression. Predictive accuracy is evaluated using 20-fold cross validation, and the stability of the perturbed clusters is measured using the Jaccard coefficient. These results show that there seems to be an inherent tradeoff between prediction accuracy and cluster stability. This paper concludes by discussing which clustering methods may be appropriate for different analytical purposes.« less
East Greenland and Barents Sea polar bears (Ursus maritimus): adaptive variation between two populations using skull morphometrics as an indicator of environmental and genetic differences.

PubMed

Pertoldi, Cino; Sonne, Christian; Wiig, Øystein; Baagøe, Hans J; Loeschcke, Volker; Bechshøft, Thea Østergaard

2012-06-01

A morphometric study was conducted on four skull traits of 37 male and 18 female adult East Greenland polar bears (Ursus maritimus) collected 1892-1968, and on 54 male and 44 female adult Barents Sea polar bears collected 1950-1969. The aim was to compare differences in size and shape of the bear skulls using a multivariate approach, characterizing the variation between the two populations using morphometric traits as an indicator of environmental and genetic differences. Mixture analysis testing for geographic differentiation within each population revealed three clusters for Barents Sea males and three clusters for Barents Sea females. East Greenland consisted of one female and one male cluster. A principal component analysis (PCA) conducted on the clusters defined by the mixture analysis, showed that East Greenland and Barents Sea polar bear populations overlapped to a large degree, especially with regards to females. Multivariate analyses of variance (MANOVA) showed no significant differences in morphometric means between the two populations, but differences were detected between clusters from each respective geographic locality. To estimate the importance of genetics and environment in the morphometric differences between the bears, a PCA was performed on the covariance matrix derived from the skull measurements. Skull trait size (PC1) explained approx. 80% of the morphometric variation, whereas shape (PC2) defined approx. 15%, indicating some genetic differentiation. Hence, both environmental and genetic factors seem to have contributed to the observed skull differences between the two populations. Overall, results indicate that many Barents Sea polar bears are morphometrically similar to the East Greenland ones, suggesting an exchange of individuals between the two populations. Furthermore, a subpopulation structure in the Barents Sea population was also indicated from the present analyses, which should be considered with regards to future management decisions. © 2012 The Authors.
Condensation and dissociation rates for gas phase metal clusters from molecular dynamics trajectory calculations

DOE PAGES

Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.

2018-04-24

In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-Molecular Dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients; we use this approach to examine atomic condensation onto 6-56 atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity ( v) between atom and cluster andmore » the initial impact parameter ( b). In all cases there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms, and for 14 atom and 28 atom Mg clusters, as cluster equilibration temperature increases the condensation rate coefficient drops to values below the hard sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (> 1000 m s -1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). In conclusion, the presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.« less
Condensation and dissociation rates for gas phase metal clusters from molecular dynamics trajectory calculations.

PubMed

Yang, Huan; Goudeli, Eirini; Hogan, Christopher J

2018-04-28

In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard-sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-molecular dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients. We use this approach to examine atomic condensation onto 6-56-atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity (v) between atom and cluster and the initial impact parameter (b). In all cases, there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard-sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms and for 14- and 28-atom Mg clusters, as cluster equilibration temperature increases, the condensation rate coefficient drops to values below the hard-sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (>1000 m s -1 ) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). The presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.
Condensation and dissociation rates for gas phase metal clusters from molecular dynamics trajectory calculations

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

Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.

In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-Molecular Dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients; we use this approach to examine atomic condensation onto 6-56 atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity ( v) between atom and cluster andmore » the initial impact parameter ( b). In all cases there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms, and for 14 atom and 28 atom Mg clusters, as cluster equilibration temperature increases the condensation rate coefficient drops to values below the hard sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (> 1000 m s -1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). In conclusion, the presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.« less
LoCuSS: weak-lensing mass calibration of galaxy clusters

NASA Astrophysics Data System (ADS)

Okabe, Nobuhiro; Smith, Graham P.

2016-10-01

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

NASA Astrophysics Data System (ADS)

Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.

2018-04-01

In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard-sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-molecular dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients. We use this approach to examine atomic condensation onto 6-56-atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity (v) between atom and cluster and the initial impact parameter (b). In all cases, there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard-sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms and for 14- and 28-atom Mg clusters, as cluster equilibration temperature increases, the condensation rate coefficient drops to values below the hard-sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (>1000 m s-1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). The presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.
VizieR Online Data Catalog: Coma clusters and filaments galaxies FIR survey (Fuller+, 2016)

NASA Astrophysics Data System (ADS)

Fuller, C.; Davies, J. I.; Smith, M. W. L.; Valiante, E.; Eales, S.; Bourne, N.; Dunne, L.; Dye, S.; Furlanetto, C.; Ibar, E.; Ivison, R.; Maddox, S.; Sansom, A.; Michalowski, M. J.; Davis, T.

2017-05-01

We have undertaken a Herschel FIR survey of the Coma cluster and the galaxy filament it resides within. Our survey covers an area of ~150 deg2 observed in five bands at 100, 160, 250, 350 and 500um. We have used the SDSS spectroscopic survey to define an area and redshift selected sample of 744 Coma cluster galaxies - the CCC. For comparison, we also define in a similar way a sample of 951 galaxies in the connecting filament - the CFC. (2 data files).
Globular Cluster Star Classification: Application to M13

NASA Astrophysics Data System (ADS)

Caimmi, R.

2013-06-01

Starting from recent determination of Fe, O, Na abundances on a restricted sample (N=67) of halo and thick disk stars, a natural and well motivated selection criterion is defined for the classification globular cluster stars. An application is performed to M13 using a sample (N=113) for which Fe, O, Na abundances have been recently inferred from observations. A comparison is made between the current and earlier M13 star classifications. Both O and Na empirical differential abundance distributions are determined for each class and for the whole sample (with the addition of Fe in the last case) and compared with their theoretical counterparts due to cosmic scatter obeying a Gaussian distribution whose parameters are inferred from related subsamples. The occurrence of an agreement between the empirical and theoretical distributions is interpreted as absence of significant chemical evolution and vice versa. The procedure is repeated with regard to four additional classes depending on whether oxygen and sodium abundance is above (stage CE) or below (stage AF) a selected threshold. Both O and Na empirical differential abundance distributions, related to the whole sample, exhibit a linear fit for the AF and CE stage. Within the errors, the oxygen slope for the CE stage is equal and of opposite sign with respect to the sodium slope for AF stage, while the contrary holds when dealing with the oxygen slope for the AF stage with respect to the sodium slope for the CE stage. In the light of simple models of chemical evolution applied to M13, oxygen depletion appears to be mainly turned into sodium enrichment for [O/H]≥-1.35 and [Na/H]≤-1.45, while one or more largely preferred channels occur for [O/H]<-1.35 and [Na/H]>-1.45. In addition, the primordial to the current M13 mass ratio can be inferred from the true sodium yield in units of the sodium solar abundance. Though the above results are mainly qualitative due to large (∓.5 dex) uncertainties in abundance determination, still the exhibited trend is expected to be real. The proposed classification of globular cluster stars may be extended in a twofold manner, namely to: (i) elements other than Na and Fe and (ii) globular clusters other than M13.
Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

NASA Astrophysics Data System (ADS)

Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

2017-11-01

Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.
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
Iron-sulfur cluster disassembly in the FNR protein of Escherichia coli by O2: [4Fe-4S] to [2Fe-2S] conversion with loss of biological activity

PubMed Central

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

1997-01-01

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

NASA Astrophysics Data System (ADS)

Berlind, Andreas A.; Farrar, Glennys R.

We explore what can be learned about the sources of UHECRs from their large-angular-scale clustering (referred to as their "bias" by the cosmology community). Exploiting the clustering on large scales has the advantage over small-scale correlations of being insensitive to uncertainties in source direction from magnetic smearing or measurement error. In a Cold Dark Matter cosmology, the amplitude of large-scale clustering depends on the mass of the system, with more massive systems such as galaxy clusters clustering more strongly than less massive systems such as ordinary galaxies or AGN. Therefore, studying the large-scale clustering of UHECRs can help determine a mass scale for their sources, given the assumption that their redshift depth is as expected from the GZK cutoff. We investigate the constraining power of a given UHECR sample as a function of its cutoff energy and number of events. We show that current and future samples should be able to distinguish between the cases of their sources being galaxy clusters, ordinary galaxies, or sources that are uncorrelated with the large-scale structure of the universe.
FORS2/VLT survey of Milky Way globular clusters. II. Fe and Mg abundances of 51 Milky Way globular clusters on a homogeneous scale

NASA Astrophysics Data System (ADS)

Dias, B.; Barbuy, B.; Saviane, I.; Held, E. V.; Da Costa, G. S.; Ortolani, S.; Gullieuszik, M.; Vásquez, S.

2016-05-01

Context. Globular clusters trace the formation and evolution of the Milky Way and surrounding galaxies, and outline their chemical enrichment history. To accomplish these tasks it is important to have large samples of clusters with homogeneous data and analysis to derive kinematics, chemical abundances, ages and locations. Aims: We obtain homogeneous metallicities and α-element enhancement for 51 Galactic bulge, disc, and halo globular clusters that are among the most distant and/or highly reddened in the Galaxy's globular cluster system. We also provide membership selection based on stellar radial velocities and atmospheric parameters. The implications of our results are discussed. Methods: We observed R ~ 2000 spectra in the wavelength interval 456-586 nm for over 800 red giant stars in 51 Galactic globular clusters. We applied full spectrum fitting with the code ETOILE together with libraries of observed and synthetic spectra. We compared the mean abundances of all clusters with previous work and with field stars. We used the relation between mean metallicity and horizontal branch morphology defined by all clusters to select outliers for discussion. Results: [Fe/H], [Mg/Fe], and [α/Fe] were derived in a consistent way for almost one-third of all Galactic globular clusters. We find our metallicities are comparable to those derived from high-resolution data to within σ = 0.08 dex over the interval -2.5< [Fe/H] < 0.0. Furthermore, a comparison of previous metallicity scales with our values yields σ< 0.16 dex. We also find that the distribution of [Mg/Fe] and [α/Fe] with [Fe/H] for the 51 clusters follows the general trend exhibited by field stars. It is the first time that the following clusters have been included in a large sample of homogeneous stellar spectroscopic observations and metallicity derivation: BH 176, Djorg 2, Pal 10, NGC 6426, Lynga 7, and Terzan 8. In particular, only photometric metallicities were available previously for the first three clusters, and the available metallicity for NGC 6426 was based on integrated spectroscopy and photometry. Two other clusters, HP 1 and NGC 6558, are confirmed as candidates for the oldest globular clusters in the Milky Way. Conclusions: Stellar spectroscopy in the visible at R ~ 2000 for a large sample of globular clusters is a robust and efficient way to trace the chemical evolution of the host galaxy and to detect interesting objects for follow-up at higher resolution and with forthcoming giant telescopes. The technique used here can also be applied to globular cluster systems in nearby galaxies with current instruments and to distant galaxies with the advent of ELTs. Based on observations collected at the European Southern Observatory/Paranal, Chile, under programmes 68.B-0482(A), 69.D-0455(A), 71.D-0219(A), 077.D-0775(A), and 089.D-0493(B).Full Tables 1 and A.2 with the derived average parameters for the 758 red giant stars 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/590/A9
Intrinsic alignments in redMaPPer clusters - I. Central galaxy alignments and angular segregation of satellites

NASA Astrophysics Data System (ADS)

Huang, Hung-Jin; Mandelbaum, Rachel; Freeman, Peter E.; Chen, Yen-Chi; Rozo, Eduardo; Rykoff, Eli; Baxter, Eric J.

2016-11-01

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.
Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

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

Huang, Hung -Jin; Mandelbaum, Rachel; Freeman, Peter E.

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes andmore » the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Lastly, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.« less

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