Simple, distance-dependent formulation of the Watts-Strogatz model for directed and undirected small-world networks.

PubMed

Song, H Francis; Wang, Xiao-Jing

2014-12-01

Small-world networks-complex networks characterized by a combination of high clustering and short path lengths-are widely studied using the paradigmatic model of Watts and Strogatz (WS). Although the WS model is already quite minimal and intuitive, we describe an alternative formulation of the WS model in terms of a distance-dependent probability of connection that further simplifies, both practically and theoretically, the generation of directed and undirected WS-type small-world networks. In addition to highlighting an essential feature of the WS model that has previously been overlooked, namely the equivalence to a simple distance-dependent model, this alternative formulation makes it possible to derive exact expressions for quantities such as the degree and motif distributions and global clustering coefficient for both directed and undirected networks in terms of model parameters.

Simple, distance-dependent formulation of the Watts-Strogatz model for directed and undirected small-world networks

NASA Astrophysics Data System (ADS)

Song, H. Francis; Wang, Xiao-Jing

2014-12-01

Small-world networks—complex networks characterized by a combination of high clustering and short path lengths—are widely studied using the paradigmatic model of Watts and Strogatz (WS). Although the WS model is already quite minimal and intuitive, we describe an alternative formulation of the WS model in terms of a distance-dependent probability of connection that further simplifies, both practically and theoretically, the generation of directed and undirected WS-type small-world networks. In addition to highlighting an essential feature of the WS model that has previously been overlooked, namely the equivalence to a simple distance-dependent model, this alternative formulation makes it possible to derive exact expressions for quantities such as the degree and motif distributions and global clustering coefficient for both directed and undirected networks in terms of model parameters.

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

Power and money in cluster randomized trials: when is it worth measuring a covariate?

PubMed

Moerbeek, Mirjam

2006-08-15

The power to detect a treatment effect in cluster randomized trials can be increased by increasing the number of clusters. An alternative is to include covariates into the regression model that relates treatment condition to outcome. In this paper, formulae are derived in order to evaluate both strategies on basis of their costs. It is shown that the strategy that uses covariates is more cost-efficient in detecting a treatment effect when the costs to measure these covariates are small and the correlation between the covariates and outcome is sufficiently large. The minimum required correlation depends on the cluster size, and the costs to recruit a cluster and to measure the covariate, relative to the costs to recruit a person. Measuring a covariate that varies at the person level only is recommended when cluster sizes are small and the costs to recruit and measure a cluster are large. Measuring a cluster level covariate is recommended when cluster sizes are large and the costs to recruit and measure a cluster are small. An illustrative example shows the use of the formulae in a practical setting. Copyright 2006 John Wiley & Sons, Ltd.

Computational Design of Clusters for Catalysis

NASA Astrophysics Data System (ADS)

Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

2018-04-01

When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

Coupled multipolar interactions in small-particle metallic clusters.

PubMed

Pustovit, Vitaly N; Sotelo, Juan A; Niklasson, Gunnar A

2002-03-01

We propose a new formalism for computing the optical properties of small clusters of particles. It is a generalization of the coupled dipole-dipole particle-interaction model and allows one in principle to take into account all multipolar interactions in the long-wavelength limit. The method is illustrated by computations of the optical properties of N = 6 particle clusters for different multipolar approximations. We examine the effect of separation between particles and compare the optical spectra with the discrete-dipole approximation and the generalized Mie theory.

Clustering of water molecules in ultramicroporous carbon: In-situ small-angle neutron scattering

DOE PAGES

Bahadur, Jitendra; Contescu, Cristian I.; Rai, Durgesh K.; ...

2016-10-19

The adsorption of water is central to most of the applications of microporous carbon as adsorbent material. We report early kinetics of water adsorption in the microporous carbon using in-situ small-angle neutron scattering. It is observed that adsorption of water occurs via cluster formation of molecules. Interestingly, the cluster size remains constant throughout the adsorption process whereas number density of clusters increases with time. The role of surface chemistry of microporous carbon on the early kinetics of adsorption process was also investigated. Lastly, the present study provides direct experimental evidence for cluster assisted adsorption of water molecules in microporous carbonmore » (Do-Do model).« less

Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

PubMed

Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

2017-04-01

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

ERIC Educational Resources Information Center

McNeish, Daniel M.; Stapleton, Laura M.

2016-01-01

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

Price Formation Based on Particle-Cluster Aggregation

NASA Astrophysics Data System (ADS)

Wang, Shijun; Zhang, Changshui

In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

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

PubMed

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

2016-03-01

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

Generating clustered scale-free networks using Poisson based localization of edges

NASA Astrophysics Data System (ADS)

Türker, İlker

2018-05-01

We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

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.

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.

Percolation of the site random-cluster model by Monte Carlo method

NASA Astrophysics Data System (ADS)

Wang, Songsong; Zhang, Wanzhou; Ding, Chengxiang

2015-08-01

We propose a site random-cluster model by introducing an additional cluster weight in the partition function of the traditional site percolation. To simulate the model on a square lattice, we combine the color-assignation and the Swendsen-Wang methods to design a highly efficient cluster algorithm with a small critical slowing-down phenomenon. To verify whether or not it is consistent with the bond random-cluster model, we measure several quantities, such as the wrapping probability Re, the percolating cluster density P∞, and the magnetic susceptibility per site χp, as well as two exponents, such as the thermal exponent yt and the fractal dimension yh of the percolating cluster. We find that for different exponents of cluster weight q =1.5 , 2, 2.5 , 3, 3.5 , and 4, the numerical estimation of the exponents yt and yh are consistent with the theoretical values. The universalities of the site random-cluster model and the bond random-cluster model are completely identical. For larger values of q , we find obvious signatures of the first-order percolation transition by the histograms and the hysteresis loops of percolating cluster density and the energy per site. Our results are helpful for the understanding of the percolation of traditional statistical models.

Critical exponents of the explosive percolation transition

NASA Astrophysics Data System (ADS)

da Costa, R. A.; Dorogovtsev, S. N.; Goltsev, A. V.; Mendes, J. F. F.

2014-04-01

In a new type of percolation phase transition, which was observed in a set of nonequilibrium models, each new connection between vertices is chosen from a number of possibilities by an Achlioptas-like algorithm. This causes preferential merging of small components and delays the emergence of the percolation cluster. First simulations led to a conclusion that a percolation cluster in this irreversible process is born discontinuously, by a discontinuous phase transition, which results in the term "explosive percolation transition." We have shown that this transition is actually continuous (second order) though with an anomalously small critical exponent of the percolation cluster. Here we propose an efficient numerical method enabling us to find the critical exponents and other characteristics of this second-order transition for a representative set of explosive percolation models with different number of choices. The method is based on gluing together the numerical solutions of evolution equations for the cluster size distribution and power-law asymptotics. For each of the models, with high precision, we obtain critical exponents and the critical point.

Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

PubMed

Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

2017-01-30

In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

3D Viewer Platform of Cloud Clustering Management System: Google Map 3D

NASA Astrophysics Data System (ADS)

Choi, Sung-Ja; Lee, Gang-Soo

The new management system of framework for cloud envrionemnt is needed by the platfrom of convergence according to computing environments of changes. A ISV and small business model is hard to adapt management system of platform which is offered from super business. This article suggest the clustering management system of cloud computing envirionments for ISV and a man of enterprise in small business model. It applies the 3D viewer adapt from map3D & earth of google. It is called 3DV_CCMS as expand the CCMS[1].

Individualization as Driving Force of Clustering Phenomena in Humans

PubMed Central

Mäs, Michael; Flache, Andreas; Helbing, Dirk

2010-01-01

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering. PMID:20975937

The Very Small Scale Clustering of SDSS-II and SDSS-III Galaxies

NASA Astrophysics Data System (ADS)

Piscionere, Jennifer

2015-01-01

We measure the angular clustering of galaxies from the Sloan Digital Sky Survey Data Release 7 in order to probe the spatial distribution of satellite galaxies within their dark matter halos. Specifically, we measure the angular correlation function on very small scales (7 - 320‧‧) in a range of luminosity threshold samples (absolute r-band magnitudes of -18 up to -21) that are constructed from the subset of SDSS that has been spectroscopically observed more than once (the so-called plate overlap region). We choose to measure angular clustering in this reduced survey footprint in order to minimize the effects of fiber collision incompleteness, which are otherwise substantial on these small scales. We model our clustering measurements using a fully numerical halo model that populates dark matter halos in N-body simulations to create realistic mock galaxy catalogs. The model has free parameters that specify both the number and spatial distribution of galaxies within their host halos. We adopt a flexible density profile for the spatial distribution of satellite galaxies that is similar to the dark matter Navarro-Frenk-White (NFW) profile, except that the inner slope is allowed to vary. We find that the angular clustering of our most luminous samples (Mr < -20 and -21) suggests that luminous satellite galaxies have substantially steeper inner density profiles than NFW. Lower luminosity samples are less constraining, however, and are consistent with satellite galaxies having shallow density profiles. Our results confirm the findings of Watson et al. (2012) while using different clustering measurements and modeling methodology. With the new SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS; Dawson et al., 2013), we can measure how the same class of galaxy evolves over time. The BOSS CMASS sample is of roughly constant stellar mass and number density out to z ˜ 0.6. The clustering of these samples appears to evolve very little with redshift, and each of the samples exhibit flattening of wp at roughly the same comoving distance of 100kpc.

Tantalum induced butterfly-like clusters on Si (111)-7 × 7 surface: STM/STS study at low coverage

NASA Astrophysics Data System (ADS)

Shukrynau, Pavel; Mutombo, Pingo; Švec, Martin; Hietschold, Michael; Cháb, Vladimír

2012-02-01

The adsorption of the small amounts of tantalum on Si (111)-7 × 7 reconstructed surface is investigated systematically using scanning tunneling microscopy and tunneling spectroscopy combined with first-principles density functional theory calculations. We find out that the moderate annealing of the Ta covered surface results in the formation of clusters of the butterfly-like shape. The clusters are sporadically distributed over the surface and their density is metal coverage dependent. Filled and empty state STM images of the clusters differ strongly suggesting the existence of covalent bonds within the cluster. Tunneling spectroscopy measurements reveal small energy gap, showing semiconductor-like behavior of the constituent atoms. The cluster model based on experimental images and theoretical calculations has been proposed and discussed. Presented results show that Ta joins the family of adsorbates, that are known to form magic clusters on Si (111)-7 × 7, but its magic cluster has the structural and electronic properties that are different from those reported before.

Parameters of oscillation generation regions in open star cluster models

NASA Astrophysics Data System (ADS)

Danilov, V. M.; Putkov, S. I.

2017-07-01

We determine the masses and radii of central regions of open star cluster (OCL) models with small or zero entropy production and estimate the masses of oscillation generation regions in clustermodels based on the data of the phase-space coordinates of stars. The radii of such regions are close to the core radii of the OCL models. We develop a new method for estimating the total OCL masses based on the cluster core mass, the cluster and cluster core radii, and radial distribution of stars. This method yields estimates of dynamical masses of Pleiades, Praesepe, and M67, which agree well with the estimates of the total masses of the corresponding clusters based on proper motions and spectroscopic data for cluster stars.We construct the spectra and dispersion curves of the oscillations of the field of azimuthal velocities v φ in OCL models. Weak, low-amplitude unstable oscillations of v φ develop in cluster models near the cluster core boundary, and weak damped oscillations of v φ often develop at frequencies close to the frequencies of more powerful oscillations, which may reduce the non-stationarity degree in OCL models. We determine the number and parameters of such oscillations near the cores boundaries of cluster models. Such oscillations points to the possible role that gradient instability near the core of cluster models plays in the decrease of the mass of the oscillation generation regions and production of entropy in the cores of OCL models with massive extended cores.

CHARGING AND COAGULATION OF DUST IN PROTOPLANETARY PLASMA ENVIRONMENTS

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

Matthews, L. S.; Land, V.; Hyde, T. W., E-mail: lorin_matthews@baylor.edu

2012-01-01

Combining a particle-particle, particle-cluster, and cluster-cluster agglomeration model with an aggregate charging model, the coagulation and charging of dust particles in plasma environments relevant for protoplanetary disks have been investigated, including the effect of electron depletion in high dust density environments. The results show that charged aggregates tend to grow by adding small particles and clusters to larger particles and clusters, and that cluster-cluster aggregation is significantly more effective than particle-cluster aggregation. Comparisons of the grain structure show that with increasing aggregate charge the compactness factor, {phi}{sub {sigma}}, decreases and has a narrower distribution, indicating a fluffier structure. Neutral aggregatesmore » are more compact, with larger {phi}{sub {sigma}}, and exhibit a larger variation in fluffiness. Overall, increased aggregate charge leads to larger, fluffier, and more massive aggregates.« less

M87 at 90 Centimeters: A Different Picture

DTIC Science & Technology

2000-06-15

as is envisioned in the cooling Ñow model. Subject headings : cooling Ñows È galaxies : active È galaxies : clusters : individual ( Virgo ) È galaxies...atmosphere of the Virgo Cluster (Fabricant, Lecar, & Gorenstein 1980). The X-ray atmosphere has a simple, apparently undis- turbed, morphology with a central...of a small set of amorphous central radio galaxies in other, similar, cooling-core clusters ? 4. PHYSICAL PICTURE : THE CLUSTER CORE The Virgo X-ray

Geometric Assortative Growth Model for Small-World Networks

PubMed Central

2014-01-01

It has been shown that both humanly constructed and natural networks are often characterized by small-world phenomenon and assortative mixing. In this paper, we propose a geometrically growing model for small-world networks. The model displays both tunable small-world phenomenon and tunable assortativity. We obtain analytical solutions of relevant topological properties such as order, size, degree distribution, degree correlation, clustering, transitivity, and diameter. It is also worth noting that the model can be viewed as a generalization for an iterative construction of Farey graphs. PMID:24578661

A quasichemical approach for protein-cluster free energies in dilute solution

NASA Astrophysics Data System (ADS)

Young, Teresa M.; Roberts, Christopher J.

2007-10-01

Reversible formation of protein oligomers or small clusters is a key step in processes such as protein polymerization, fibril formation, and protein phase separation from dilute solution. A straightforward, statistical mechanical approach to accurately calculate cluster free energies in solution is presented using a cell-based, quasichemical (QC) approximation for the partition function of proteins in an implicit solvent. The inputs to the model are the protein potential of mean force (PMF) and the corresponding subcell degeneracies up to relatively low particle densities. The approach is tested using simple two and three dimensional lattice models in which proteins interact with either isotropic or anisotropic nearest-neighbor attractions. Comparison with direct Monte Carlo simulation shows that cluster probabilities and free energies of oligomer formation (ΔGi0) are quantitatively predicted by the QC approach for protein volume fractions ˜10-2 (weight/volume concentration ˜10gl-1) and below. For small clusters, ΔGi0 depends weakly on the strength of short-ranged attractive interactions for most experimentally relevant values of the normalized osmotic second virial coefficient (b2*). For larger clusters (i ≫2), there is a small but non-negligible b2* dependence. The results suggest that nonspecific, hydrophobic attractions may not significantly stabilize prenuclei in processes such as non-native aggregation. Biased Monte Carlo methods are shown to accurately provide subcell degeneracies that are intractable to obtain analytically or by direct enumeration, and so offer a means to generalize the approach to mixtures and proteins with more complex PMFs.

Right-side-stretched multifractal spectra indicate small-worldness in networks

NASA Astrophysics Data System (ADS)

Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław

2018-04-01

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.

Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study.

PubMed

Barker, Daniel; D'Este, Catherine; Campbell, Michael J; McElduff, Patrick

2017-03-09

Stepped wedge cluster randomised trials frequently involve a relatively small number of clusters. The most common frameworks used to analyse data from these types of trials are generalised estimating equations and generalised linear mixed models. A topic of much research into these methods has been their application to cluster randomised trial data and, in particular, the number of clusters required to make reasonable inferences about the intervention effect. However, for stepped wedge trials, which have been claimed by many researchers to have a statistical power advantage over the parallel cluster randomised trial, the minimum number of clusters required has not been investigated. We conducted a simulation study where we considered the most commonly used methods suggested in the literature to analyse cross-sectional stepped wedge cluster randomised trial data. We compared the per cent bias, the type I error rate and power of these methods in a stepped wedge trial setting with a binary outcome, where there are few clusters available and when the appropriate adjustment for a time trend is made, which by design may be confounding the intervention effect. We found that the generalised linear mixed modelling approach is the most consistent when few clusters are available. We also found that none of the common analysis methods for stepped wedge trials were both unbiased and maintained a 5% type I error rate when there were only three clusters. Of the commonly used analysis approaches, we recommend the generalised linear mixed model for small stepped wedge trials with binary outcomes. We also suggest that in a stepped wedge design with three steps, at least two clusters be randomised at each step, to ensure that the intervention effect estimator maintains the nominal 5% significance level and is also reasonably unbiased.

The Cluster Environment of Two High-mass Protostars

NASA Astrophysics Data System (ADS)

Montes, Virginie; Hofner, Peter

2017-06-01

Characterizing the environment and stellar population in which high-mass stars form is an important step to decide between the main massive star formation theories. In the monolithic collapse model, the mass of the core will determine the final stellar mass (e.g., McKee & Tan 2003). In contrast, in the competitive accretion model (e.g., Bonnell & Bate 2006), the mass of the high-mass star is related to the properties of the cluster. As dynamical processes substantially affect the appearance of a cluster, we study early stages of high-mass star formation. These regions often show extended emission from hot dust at infrared wavelengths, which can cause difficulties to define the cluster. We use a multi-wavelength technique to study nearby high-mass star clusters, based on X-ray observations with the Chandra X-Ray Telescope, in conjunction with infrared data and VLA data. The technique relies on the fact that YSOs are particularly bright in X-ray and that contamination is relatively small. X-ray observations allow us to determine the cluster size. The cluster membership and YSOs classification is established using infrared identification of the X-ray sources, and color-color and color-magnitude diagrams.In this talk, I will present our findings on the cluster study of two high-mass star forming regions: IRAS 20126+4104 and IRAS 16562-3959. While most massive stars appear to be formed in rich a cluster environment, those two sources are candidates for the formation of massive stars in a relatively poor cluster. In contrast to what was found in previous studies (Qiu et al. 2008), the dominant B0-type protostar in IRAS 20126+4104 is associated with a small cluster of low-mass stars. I will also show our current work on IRAS 16562-3959, which contains one of the most luminous O-type protostars in the Galaxy. In the vicinity of this particularly interesting region there is a multitude of small clusters, for which I will present how their stellar population differ from the high-mass star-forming cluster IRAS 16562-3959.

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

Quantum-Size Dependence of the Energy for Vacancy Formation in Charged Small Metal Clusters. Drop Model

NASA Astrophysics Data System (ADS)

Pogosov, V. V.; Reva, V. I.

2018-04-01

Self-consistent computations of the monovacancy formation energy are performed for Na N , Mg N , and Al N (12 < N ≤ 168) spherical clusters in the drop model for stable jelly. Scenarios of the Schottky vacancy formation and "bubble vacancy blowing" are considered. It is shown that the asymptotic behavior of the size dependences of the energy for the vacancy formation by these two mechanisms is different and the difference between the characteristics of a charged and neutral cluster is entirely determined by the difference between the ionization potentials of clusters and the energies of electron attachment to them.

Shield fields: Concentrations of small volcanic edifices on Venus

NASA Technical Reports Server (NTRS)

Aubele, J. C.; Crumpler, L. S.

1992-01-01

Pre-Magellan analysis of the Venera 15/16 data indicated the existence of abundant small volcanic edifices, each less than or equal to 20 km diameter, interpreted to be predominantly shield volcanoes and occurring throughout the plains terrain, most common in equidimensional clusters. With the analysis of Magellan data, these clusters of greater than average concentration of small volcanic edifices have been called 'shield fields'. Although individual small shields can and do occur almost everywhere on the plains terrain of Venus, they most commonly occur in fields that are well-defined, predominantly equant, clusters of edifices. Major questions include why the edifices are concentrated in this way, how they relate to the source of the eruptive material, and what the possible relationship of shield fields to plains terrain is. There are three possible models for the origin of fields and small shields: (1) a field represents an 'island' of higher topography subsequently surrounded by later plains material; and (2) a field represents the area of magma reservoir.

Inference With Difference-in-Differences With a Small Number of Groups: A Review, Simulation Study, and Empirical Application Using SHARE Data.

PubMed

Rokicki, Slawa; Cohen, Jessica; Fink, Günther; Salomon, Joshua A; Landrum, Mary Beth

2018-01-01

Difference-in-differences (DID) estimation has become increasingly popular as an approach to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical methodologies have been proposed to correct for the within-group correlation of model errors resulting from the clustering of data. Little is known about how well these corrections perform with the often small number of groups observed in health research using longitudinal data. First, we review the most commonly used modeling solutions in DID estimation for panel data, including generalized estimating equations (GEE), permutation tests, clustered standard errors (CSE), wild cluster bootstrapping, and aggregation. Second, we compare the empirical coverage rates and power of these methods using a Monte Carlo simulation study in scenarios in which we vary the degree of error correlation, the group size balance, and the proportion of treated groups. Third, we provide an empirical example using the Survey of Health, Ageing, and Retirement in Europe. When the number of groups is small, CSE are systematically biased downwards in scenarios when data are unbalanced or when there is a low proportion of treated groups. This can result in over-rejection of the null even when data are composed of up to 50 groups. Aggregation, permutation tests, bias-adjusted GEE, and wild cluster bootstrap produce coverage rates close to the nominal rate for almost all scenarios, though GEE may suffer from low power. In DID estimation with a small number of groups, analysis using aggregation, permutation tests, wild cluster bootstrap, or bias-adjusted GEE is recommended.

Analysis of the electron density features of small boron clusters and the effects of doping with C, P, Al, Si, and Zn: Magic B7P and B8Si clusters

NASA Astrophysics Data System (ADS)

Saha, P.; Rahane, A. B.; Kumar, V.; Sukumar, N.

2016-05-01

Boron atomic clusters show several interesting and unusual size-dependent features due to the small covalent radius, electron deficiency, and higher coordination number of boron as compared to carbon. These include aromaticity and a diverse array of structures such as quasi-planar, ring or tubular shaped, and fullerene-like. In the present work, we have analyzed features of the computed electron density distributions of small boron clusters having up to 11 boron atoms, and investigated the effect of doping with C, P, Al, Si, and Zn atoms on their structural and physical properties, in order to understand the bonding characteristics and discern trends in bonding and stability. We find that in general there are covalent bonds as well as delocalized charge distribution in these clusters. We associate the strong stability of some of these planar/quasiplanar disc-type clusters with the electronic shell closing with effectively twelve delocalized valence electrons using a disc-shaped jellium model. {{{{B}}}9}-, B10, B7P, and B8Si, in particular, are found to be exceptional with very large gaps between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, and these are suggested to be magic clusters.

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Knyazikhin, Yuri; Larsen, Michael L.; Wiscombe, Warren J.

2005-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

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.

Phase synchronization of bursting neurons in clustered small-world networks

NASA Astrophysics Data System (ADS)

Batista, C. A. S.; Lameu, E. L.; Batista, A. M.; Lopes, S. R.; Pereira, T.; Zamora-López, G.; Kurths, J.; Viana, R. L.

2012-07-01

We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connections, the latter with a given intracluster probability. Moreover, in a given subnetwork each neuron has an intercluster probability to be connected to the other subnetworks. The local neuron dynamics has two time scales (fast and slow) and is modeled by a two-dimensional map. In such small-world network the neuron parameters are chosen to be slightly different such that, if the coupling strength is large enough, there may be synchronization of the bursting (slow) activity. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, that is, the probabilities of intracluster and intercluster connections. We find that, as the heterogeneity in the network is reduced, the network global synchronizability is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.

Local resonances in STM manipulation of chlorobenzene on Si(111)-7×7: performance of different cluster models and density functionals

NASA Astrophysics Data System (ADS)

Utecht, Manuel; Klamroth, Tillmann

2018-07-01

Hot localised charge carriers on the Si(111)-7×7 surface are modelled by small charged clusters. Such resonances induce non-local desorption, i.e. more than 10 nm away from the injection site, of chlorobenzene in scanning tunnelling microscope experiments. We used such a cluster model to characterise resonance localisation and vibrational activation for positive and negative resonances recently. In this work, we investigate to which extent the model depends on details of the used cluster or quantum chemistry methods and try to identify the smallest possible cluster suitable for a description of the neutral surface and the ion resonances. Furthermore, a detailed analysis for different chemisorption orientations is performed. While some properties, as estimates of the resonance energy or absolute values for atomic changes, show such a dependency, the main findings are very robust with respect to changes in the model and/or the chemisorption geometry.

Adsorption and diffusion of fructose in zeolite HZSM-5: selection of models and methods for computational studies.

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

Cheng, L.; Curtiss, L. A.; Assary, R. S.

The adsorption and protonation of fructose in HZSM-5 have been studied for the assessment of models for accurate reaction energy calculations and the evaluation of molecular diffusivity. The adsorption and protonation were calculated using 2T, 5T, and 46T clusters as well as a periodic model. The results indicate that the reaction thermodynamics cannot be predicted correctly using small cluster models, such as 2T or 5T, because these small cluster models fail to represent the electrostatic effect of a zeolite cage, which provides additional stabilization to the ion pair formed upon the protonation of fructose. Structural parameters optimized using the 46Tmore » cluster model agree well with those of the full periodic model; however, the calculated reaction energies are in significant error due to the poor account of dispersion effects by density functional theory. The dispersion effects contribute -30.5 kcal/mol to the binding energy of fructose in the zeolite pore based on periodic model calculations that include dispersion interactions. The protonation of the fructose ternary carbon hydroxyl group was calculated to be exothermic by 5.5 kcal/mol with a reaction barrier of 2.9 kcal/mol using the periodic model with dispersion effects. Our results suggest that the internal diffusion of fructose in HZSM-5 is very likely to be energetically limited and only occurs at high temperature due to the large size of the molecule.« less

COMPARING MID-INFRARED GLOBULAR CLUSTER COLORS WITH POPULATION SYNTHESIS MODELS

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

Barmby, P.; Jalilian, F. F.

2012-04-15

Several population synthesis models now predict integrated colors of simple stellar populations in the mid-infrared bands. To date, the models have not been extensively tested in this wavelength range. In a comparison of the predictions of several recent population synthesis models, the integrated colors are found to cover approximately the same range but to disagree in detail, for example, on the effects of metallicity. To test against observational data, globular clusters (GCs) are used as the closest objects to idealized groups of stars with a single age and single metallicity. Using recent mass estimates, we have compiled a sample ofmore » massive, old GCs in M31 which contain enough stars to guard against the stochastic effects of small-number statistics, and measured their integrated colors in the Spitzer/IRAC bands. Comparison of the cluster photometry in the IRAC bands with the model predictions shows that the models reproduce the cluster colors reasonably well, except for a small (not statistically significant) offset in [4.5] - [5.8]. In this color, models without circumstellar dust emission predict bluer values than are observed. Model predictions of colors formed from the V band and the IRAC 3.6 and 4.5 {mu}m bands are redder than the observed data at high metallicities and we discuss several possible explanations. In agreement with model predictions, V - [3.6] and V - [4.5] colors are found to have metallicity sensitivity similar to or slightly better than V - K{sub s}.« less

Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures.

PubMed

Austin, Peter C

2010-04-22

Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.

Effect of Self-Assembly of Fullerene Nano-Particles on Lipid Membrane

PubMed Central

Zhang, Saiqun; Mu, Yuguang; Zhang, John Z. H.; Xu, Weixin

2013-01-01

Carbon nanoparticles can penetrate the cell membrane and cause cytotoxicity. The diffusion feature and translocation free energy of fullerene through lipid membranes is well reported. However, the knowledge on self-assembly of fullerenes and resulting effects on lipid membrane is poorly addressed. In this work, the self-assembly of fullerene nanoparticles and the resulting influence on the dioleoylphosphtidylcholine (DOPC) model membrane were studied by using all-atom molecular dynamics simulations with explicit solvents. Our simulation results confirm that gathered small fullerene cluster can invade lipid membrane. Simulations show two pathways: 1) assembly process is completely finished before penetration; 2) assembly process coincides with penetration. Simulation results also demonstrate that in the membrane interior, fullerene clusters tend to stay at the position which is 1.0 nm away from the membrane center. In addition, the diverse microscopic stacking mode (i.e., equilateral triangle, tetrahedral pentahedral, trigonal bipyramid and octahedron) of these small fullerene clusters are well characterized. Thus our simulations provide a detailed high-resolution characterization of the microscopic structures of the small fullerene clusters. Further, we found the gathered small fullerene clusters have significant adverse disturbances to the local structure of the membrane, but no great influence on the global integrity of the lipid membrane, which suggests the prerequisite of high-content fullerene for cytotoxicity. PMID:24204827

Electronic and geometric properties of ETS-10: QM/MM studies of cluster models.

PubMed

Zimmerman, Anne Marie; Doren, Douglas J; Lobo, Raul F

2006-05-11

Hybrid DFT/MM methods have been used to investigate the electronic and geometric properties of the microporous titanosilicate ETS-10. A comparison of finite length and periodic models demonstrates that band gap energies for ETS-10 can be well represented with relatively small cluster models. Optimization of finite clusters leads to different local geometries for bulk and end sites, where the local bulk TiO6 geometry is in good agreement with recent experimental results. Geometry optimizations reveal that any asymmetry within the axial O-Ti-O chain is negligible. The band gap in the optimized model corresponds to a O(2p) --> Tibulk(3d) transition. The results suggest that the three Ti atom, single chain, symmetric, finite cluster is an effective model for the geometric and electronic properties of bulk and end TiO6 groups in ETS-10.

Synchronization as Aggregation: Cluster Kinetics of Pulse-Coupled Oscillators.

PubMed

O'Keeffe, Kevin P; Krapivsky, P L; Strogatz, Steven H

2015-08-07

We consider models of identical pulse-coupled oscillators with global interactions. Previous work showed that under certain conditions such systems always end up in sync, but did not quantify how small clusters of synchronized oscillators progressively coalesce into larger ones. Using tools from the study of aggregation phenomena, we obtain exact results for the time-dependent distribution of cluster sizes as the system evolves from disorder to synchrony.

Helium behavior in oxide dispersion strengthened (ODS) steel: Insights from ab initio modeling

NASA Astrophysics Data System (ADS)

Sun, Dan; Li, Ruihuan; Ding, Jianhua; Huang, Shaosong; Zhang, Pengbo; Lu, Zheng; Zhao, Jijun

2018-02-01

Using first-principles calculations, we systemically investigate the energetics and stability behavior of helium (He) atoms and small Hen (n = 2-4) clusters inside oxide dispersion strengthened (ODS) steel, as well as the incorporation of large amount of He atoms inside Y2O3 crystal. From the energetic point of view, He atom inside Y2O3 cluster is most stable, followed by the interstitial sites at the α-Fe/Y2O3 interface, and the tetrahedral interstitial sites inside α-Fe region. We further consider Hen (n = 2-4) clusters at the tetrahedral interstitial site surrounded by four Y atoms, which is the most stable site in the ODS steel model. The incorporation energies of all these Hen clusters are lower than that of single He atom in α-Fe, while the binding energy between two He atoms is relatively small. With insertion of 15 He atoms into 80-atom unit cell of Y2O3 crystal, the incorporation energy of He atoms is still lower than that of He4 cluster in α-Fe crystal. These theoretical results suggest that He atoms tend to aggregate inside Y2O3 clusters or at the α-Fe/Y2O3 interface, which is beneficial to prevent the He embrittlement in ODS steels.

Hydrogen bonding interaction of small acetaldehyde clusters studied with core-electron excitation spectroscopy in the oxygen K-edge region

NASA Astrophysics Data System (ADS)

Tabayashi, K.; Chohda, M.; Yamanaka, T.; Tsutsumi, Y.; Takahashi, O.; Yoshida, H.; Taniguchi, M.

2010-06-01

In order to examine inner-shell electron excitation spectra of molecular clusters with strong multipole interactions, excitation spectra and time-of-flight (TOF) fragment-mass spectra of small acetaldehyde (AA) clusters have been studied under the beam conditions. The TOF spectra at the oxygen K-edge region showed an intense growth of the protonated clusters, MnH+ (M=CH3CHO) in the cluster beams. "cluster-specific" excitation spectra could be generated by monitoring partial-ion-yields of the protonated clusters. The most intense band of O1s→π*CO was found to shift to a higher energy by 0.15 eV relative to the monomer band upon clusterization. X-ray absorption spectra (XAS) were also calculated for the representative dimer configurations using a computer modelling program based on the density functional theory. The XAS prediction for the most stable (non-planar) configuration was found to give a close comparison with the cluster-band shift observed. The band shift was interpreted as being due to the HOMO-LUMO interaction within the complex where a contribution of vibrationally blue-shifting hydrogen bonding could be identified.

A Model for Protostellar Cluster Luminosities and the Impact on the CO–H2 Conversion Factor

NASA Astrophysics Data System (ADS)

Gaches, Brandt A. L.; Offner, Stella S. R.

2018-02-01

We construct a semianalytic model to study the effect of far-ultraviolet (FUV) radiation on gas chemistry from embedded protostars. We use the protostellar luminosity function (PLF) formalism of Offner & McKee to calculate the total, FUV, and ionizing cluster luminosity for various protostellar accretion histories and cluster sizes. We2 compare the model predictions with surveys of Gould Belt star-forming regions and find that the tapered turbulent core model matches best the mean luminosities and the spread in the data. We combine the cluster model with the photodissociation region astrochemistry code, 3D-PDR, to compute the impact of the FUV luminosity from embedded protostars on the CO-to-H2 conversion factor, X CO, as a function of cluster size, gas mass, and star formation efficiency. We find that X CO has a weak dependence on the FUV radiation from embedded sources for large clusters owing to high cloud optical depths. In smaller and more efficient clusters the embedded FUV increases X CO to levels consistent with the average Milky Way values. The internal physical and chemical structures of the cloud are significantly altered, and X CO depends strongly on the protostellar cluster mass for small efficient clouds.

Mechanisms behind overshoots in mean cluster size profiles in aggregation-breakup processes.

PubMed

Sadegh-Vaziri, Ramiar; Ludwig, Kristin; Sundmacher, Kai; Babler, Matthaus U

2018-05-26

Aggregation and breakup of small particles in stirred suspensions often shows an overshoot in the time evolution of the mean cluster size: Starting from a suspension of primary particles the mean cluster size first increases before going through a maximum beyond which a slow relaxation sets in. Such behavior was observed in various systems, including polymeric latices, inorganic colloids, asphaltenes, proteins, and, as shown by independent experiments in this work, in the flocculation of microalgae. This work aims at investigating possible mechanism to explain this phenomenon using detailed population balance modeling that incorporates refined rate models for aggregation and breakup of small particles in turbulence. Four mechanisms are considered: (1) restructuring, (2) decay of aggregate strength, (3) deposition of large clusters, and (4) primary particle aggregation where only aggregation events between clusters and primary particles are permitted. We show that all four mechanisms can lead to an overshoot in the mean size profile, while in contrast, aggregation and breakup alone lead to a monotonic, "S"-shaped size evolution profile. In order to distinguish between the different mechanisms simple protocols based on variations of the shear rate during the aggregation-breakup process are proposed. Copyright © 2018 Elsevier Inc. All rights reserved.

The effect of clulstering of galaxies on the statistics of gravitational lenses

NASA Technical Reports Server (NTRS)

Anderson, N.; Alcock, C.

1986-01-01

It is examined whether clustering of galaxies can significantly alter the statistical properties of gravitational lenses? Only models of clustering that resemble the observed distribution of galaxies in the properties of the two-point correlation function are considered. Monte-Carlo simulations of the imaging process are described. It is found that the effect of clustering is too small to be significant, unless the mass of the deflectors is so large that gravitational lenses become common occurrences. A special model is described which was concocted to optimize the effect of clustering on gravitational lensing but still resemble the observed distribution of galaxies; even this simulation did not satisfactorily produce large numbers of wide-angle lenses.

Searching for Constraints on Starobinsky's Model with a Disappearing Cosmological Constant on Galaxy Cluster Scales

NASA Astrophysics Data System (ADS)

Alexeyev, S. O.; Latosh, B. N.; Echeistov, V. A.

2017-12-01

Predictions of the f( R)-gravity model with a disappearing cosmological constant (Starobinsky's model) on scales characteristic of galaxies and their clusters are considered. The absence of a difference in the mass dependence of the turnaround radius between Starobinsky's model and General Relativity accessible to observation at the current accuracy of measurements has been established. This is true both for small masses (from 109 M Sun) corresponding to an individual galaxy and for masses corresponding to large galaxy clusters (up to 1015 M Sun). The turnaround radius increases with parameter n for all masses. Despite the fact that some models give a considerably smaller turnaround radius than does General Relativity, none of the models goes beyond the bounds specified by the observational data.

Energy Characteristics of Small Metal Clusters Containing Vacancies

NASA Astrophysics Data System (ADS)

Reva, V. I.; Pogosov, V. V.

2018-02-01

Self-consistent calculations of spatial distributions of electrons, potentials, and energies of dissociation, cohesion, vacancy formation, and electron attachment, as well as the ionization potential of solid Al N , Na N clusters ( N ≥ 254), and clusters containing a vacancy ( N ≥ 12) have been performed using a model of stable jellium. The contribution of a monovacancy to the energy of the cluster, the size dependences of the characteristics, and their asymptotic forms have been considered. The calculations have been performed on the SKIT-3 cluster at the Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine (Rpeak = 7.4 Tflops).

Disease clusters, exact distributions of maxima, and P-values.

PubMed

Grimson, R C

1993-10-01

This paper presents combinatorial (exact) methods that are useful in the analysis of disease cluster data obtained from small environments, such as buildings and neighbourhoods. Maxwell-Boltzmann and Fermi-Dirac occupancy models are compared in terms of appropriateness of representation of disease incidence patterns (space and/or time) in these environments. The methods are illustrated by a statistical analysis of the incidence pattern of bone fractures in a setting wherein fracture clustering was alleged to be occurring. One of the methodological results derived in this paper is the exact distribution of the maximum cell frequency in occupancy models.

Relative dispersion of clustered drifters in a small micro-tidal estuary

NASA Astrophysics Data System (ADS)

Suara, Kabir; Chanson, Hubert; Borgas, Michael; Brown, Richard J.

2017-07-01

Small tide-dominated estuaries are affected by large scale flow structures which combine with the underlying bed generated smaller scale turbulence to significantly increase the magnitude of horizontal diffusivity. Field estimates of horizontal diffusivity and its associated scales are however rare due to limitations in instrumentation. Data from multiple deployments of low and high resolution clusters of GPS-drifters are used to examine the dynamics of a surface flow in a small micro-tidal estuary through relative dispersion analyses. During the field study, cluster diffusivity, which combines both large- and small-scale processes ranged between, 0.01 and 3.01 m2/s for spreading clusters and, -0.06 and -4.2 m2/s for contracting clusters. Pair-particle dispersion, Dp2, was scale dependent and grew as Dp2 ∼ t1.83 in streamwise and Dp2 ∼ t0.8 in cross-stream directions. At small separation scale, pair-particle (d < 0.5 m) relative diffusivity followed the Richardson's 4/3 power law and became weaker as separation scale increases. Pair-particle diffusivity was described as Kp ∼ d1.01 and Kp ∼ d0.85 in the streamwise and cross-stream directions, respectively for separation scales ranging from 0.1 to 10 m. Two methods were used to identify the mechanism responsible for dispersion within the channel. The results clearly revealed the importance of strain fields (stretching and shearing) in the spreading of particles within a small micro-tidal channel. The work provided input for modelling dispersion of passive particle in shallow micro-tidal estuaries where these were not previously experimentally studied.

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

Small-cluster renormalization group in Ising and Blume-Emery-Griffiths models with ferromagnetic, antiferromagnetic, and quenched disordered magnetic interactions

NASA Astrophysics Data System (ADS)

Antenucci, F.; Crisanti, A.; Leuzzi, L.

2014-07-01

The Ising and Blume-Emery-Griffiths (BEG) models' critical behavior is analyzed in two dimensions and three dimensions by means of a renormalization group scheme on small clusters made of a few lattice cells. Different kinds of cells are proposed for both ordered and disordered model cases. In particular, cells preserving a possible antiferromagnetic ordering under renormalization allow for the determination of the Néel critical point and its scaling indices. These also provide more reliable estimates of the Curie fixed point than those obtained using cells preserving only the ferromagnetic ordering. In all studied dimensions, the present procedure does not yield a strong-disorder critical point corresponding to the transition to the spin-glass phase. This limitation is thoroughly analyzed and motivated.

Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media

NASA Astrophysics Data System (ADS)

Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

Cluster-size entropy in the Axelrod model of social influence: small-world networks and mass media.

PubMed

Gandica, Y; Charmell, A; Villegas-Febres, J; Bonalde, I

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy S(c), which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the S(c)(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait q(c) and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

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.

Are Binary Separations related to their System Mass?

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2004-08-01

We compile most recent multiplicity fractions and binary separation distributions for different primary masses, including very low-mass and brown dwarf primaries, and compare them with dynamical decay models of small-N clusters. The model predictions are based on detailed numerical calculations of the internal cluster dynamics, as well as on Monte-Carlo methods. Both observations and models reflect the same trends: (1) The multiplicity fraction is an increasing function of the primary mass. (2) The mean binary separations are increasing with the system mass in the sense that very low-mass binaries have average separations around ≈ 4AU, while the binary separation distribution for solar-type primaries peaks at ≈ 40AU. M-type binary systems apparently preferentially populate intermediate separations. Similar specific energy at the time of cluster formation for all cluster masses can possibly explain this trend.

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Accurate Modeling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron; Scoccimarro, Roman

2015-01-01

The large-scale distribution of galaxies can be explained fairly simply by assuming (i) a cosmological model, which determines the dark matter halo distribution, and (ii) a simple connection between galaxies and the halos they inhabit. This conceptually simple framework, called the halo model, has been remarkably successful at reproducing the clustering of galaxies on all scales, as observed in various galaxy redshift surveys. However, none of these previous studies have carefully modeled the systematics and thus truly tested the halo model in a statistically rigorous sense. We present a new accurate and fully numerical halo model framework and test it against clustering measurements from two luminosity samples of galaxies drawn from the SDSS DR7. We show that the simple ΛCDM cosmology + halo model is not able to simultaneously reproduce the galaxy projected correlation function and the group multiplicity function. In particular, the more luminous sample shows significant tension with theory. We discuss the implications of our findings and how this work paves the way for constraining galaxy formation by accurate simultaneous modeling of multiple galaxy clustering statistics.

Segmentation and clustering as complementary sources of information

NASA Astrophysics Data System (ADS)

Dale, Michael B.; Allison, Lloyd; Dale, Patricia E. R.

2007-03-01

This paper examines the effects of using a segmentation method to identify change-points or edges in vegetation. It identifies coherence (spatial or temporal) in place of unconstrained clustering. The segmentation method involves change-point detection along a sequence of observations so that each cluster formed is composed of adjacent samples; this is a form of constrained clustering. The protocol identifies one or more models, one for each section identified, and the quality of each is assessed using a minimum message length criterion, which provides a rational basis for selecting an appropriate model. Although the segmentation is less efficient than clustering, it does provide other information because it incorporates textural similarity as well as homogeneity. In addition it can be useful in determining various scales of variation that may apply to the data, providing a general method of small-scale pattern analysis.

Hydrodynamic clustering of droplets in turbulence

NASA Astrophysics Data System (ADS)

Kunnen, Rudie; Yavuz, Altug; van Heijst, Gertjan; Clercx, Herman

2017-11-01

Small, inertial particles are known to cluster in turbulent flows: particles are centrifuged out of eddies and gather in the strain-dominated regions. This so-called preferential concentration is reflected in the radial distribution function (RDF; a quantitative measure of clustering). We study clustering of water droplets in a loudspeaker-driven turbulence chamber. We track the motion of droplets in 3D and calculate the RDF. At moderate scales (a few Kolmogorov lengths) we find the typical power-law scaling of preferential concentration in the RDF. However, at even smaller scales (a few droplet diameters), we encounter a hitherto unobserved additional clustering. We postulate that the additional clustering is due to hydrodynamic interactions, an effect which is typically disregarded in modeling. Using a perturbative expansion of inertial effects in a Stokes-flow description of two interacting spheres, we obtain an expression for the RDF which indeed includes the additional clustering. The additional clustering enhances the collision probability of droplets, which enhances their growth rate due to coalescence. The additional clustering is thus an essential effect in precipitation modeling.

Kinetic energy spectra in thermionic emission from small tungsten cluster anions: evidence for nonclassical electron capture.

PubMed

Concina, Bruno; Baguenard, Bruno; Calvo, Florent; Bordas, Christian

2010-03-14

The delayed electron emission from small mass-selected anionic tungsten clusters W(n)(-) has been studied for sizes in the range 9 < or = n < or = 21. Kinetic energy spectra have been measured for delays of about 100 ns after laser excitation by a velocity-map imaging spectrometer. They are analyzed in the framework of microreversible statistical theories. The low-energy behavior shows some significant deviations with respect to the classical Langevin capture model, which we interpret as possibly due to the influence of quantum dynamical effects such as tunneling through the centrifugal barrier, rather than shape effects. The cluster temperature has been extracted from both the experimental kinetic energy spectrum and the absolute decay rate. Discrepancies between the two approaches suggest that the sticking probability can be as low as a few percent for the smallest clusters.

Kinetic Monte Carlo Simulation of the Growth of Various Nanostructures through Atomic and Cluster Deposition: Application to Gold Nanostructure Growth on Graphite

NASA Astrophysics Data System (ADS)

Claassens, C. H.; Hoffman, M. J. H.; Terblans, J. J.; Swart, H. C.

2006-01-01

A Kinetic Monte Carlo (KMC) method is presented to describe the growth of metallic nanostructures through atomic and cluster deposition in the mono -and multilayer regime. The model makes provision for homo- and heteroepitaxial systems with small lattice mismatch. The accuracy of the model is tested with simulations of the growth of gold nanostructures on HOPG and comparisons are made with existing experimental data.

Formation patterns of water clusters in CMK-3 and CMK-5 mesoporous carbons: a computational recognition study.

PubMed

Peng, Xuan; Jain, Surendra Kumar; Singh, Jayant Kumar; Liu, Anqi; Jin, Qibing

2018-06-13

Grand canonical Monte Carlo simulations are performed to study the adsorption of water in realistic CMK-3 and CMK-5 models at 300 K. The adsorption isotherms are characterized by negligible uptake at lower chemical potentials and complete pore filling once the threshold chemical potential is increased. Results for the isosteric heat of adsorption, radial distribution function (O-O and O-H), hydrogen bond statistics and the cluster size distribution of water molecules are presented. The snapshots of GCMC simulations in CMK-3 and CMK-5 models show that the adsorption happens via the formation of water clusters. For the CMK-3 model, it was found that the pore filling occurred via the formation of a single water cluster and a few very small clusters. The water cluster size increased with an increase in pore size of the CMK-3 model. For the CMK-5 model, it was found that the adsorption first occurred in the inner porosity (via cluster formation). There was no adsorption of water in the outer porosity during the filling of the inner porosity. After the inner porosity was completely filled, the water begins to fill the outer porosity. Snapshots from GCMC simulations of the CMK-5 model clearly show that the water adsorption in the outer porosity occurs via the formation and growth of clusters and there was no formation of layers of water in the porosity as seen for nonpolar fluids like nitrogen.

Theoretical study of the electronic and optical properties of photochromic dithienylethene derivatives connected to small gold clusters.

PubMed

Perrier, Aurélie; Maurel, François; Aubard, Jean

2007-10-04

In the course of developing electronic devices on a molecular scale, dithienylethenes photochromic molecules constitute promising candidates for optoelectronic applications such as memories and switches. There is thus a great interest to understand and control the switching behavior of photochromic compounds deposited on metallic surfaces or nanoparticles. Within the framework of the density functional theory, we studied the effect of small gold clusters (Au3 and Au9) on the electronic structure and absorption spectrum of a model dithienylethene molecule. The molecular orbital interactions between the photochromic molecule and the gold cluster made it possible to rationalize some experimental findings (Dulic, D.; van der Molen, S. J.; Kudernac, T.; Jonkman, H. T.; de Jong, J. J. D.; Bowden, T. N.; van Esch, J.; Feringa, B. L.; van Wees, B. J. Phys. Rev. Lett. 2003, 91, 207402). For the closed-ring isomer, grafting a photochromic molecule on a small gold cluster does not change the characteristics of the electronic transition involved in the ring-opening reaction. On the opposite, the absorption spectrum of the photochromic open-ring isomer is strongly modified by the inclusion of the metallic cluster. In agreement with experimental results, our study thus showed that the cycloreversion reaction which involves the closed-ring isomer should be still possible, whereas the ring-closure reaction which involves the open-ring isomer should be inhibited. Connecting a dithienylethene molecule to a small gold cluster hence provides a qualitative comprehension of the photochromic activities of dithienylethenes connected to a gold surface.

Thermodynamics of Small Alkali Metal Halide Cluster Ions: Comparison of Classical Molecular Simulations with Experiment and Quantum Chemistry

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

Vlcek, Lukas; Uhlik, Filip; Moucka, Filip

We evaluate the ability of selected classical molecular models to describe the thermodynamic and structural aspects of gas-phase hydration of alkali halide ions and the formation of small water clusters. To understand the effect of many-body interactions (polarization) and charge penetration effects on the accuracy of a force field, we perform Monte Carlo simulations with three rigid water models using different functional forms to account for these effects: (i) point charge non-polarizable SPC/E, (ii) Drude point charge polarizable SWM4- DP, and (iii) Drude Gaussian charge polarizable BK3. Model predictions are compared with experimental Gibbs free energies and enthalpies of ionmore » hydration, and with microscopic structural properties obtained from quantum DFT calculations. We find that all three models provide comparable predictions for pure water clusters and cation hydration, but differ significantly in their description of anion hydration. None of the investigated classical force fields can consistently and quantitatively reproduce the experimental gas phase hydration thermodynamics. The outcome of this study highlights the relation between the functional form that describes the effective intermolecular interactions and the accuracy of the resulting ion hydration properties.« less

Free energy of singular sticky-sphere clusters.

PubMed

Kallus, Yoav; Holmes-Cerfon, Miranda

2017-02-01

Networks of particles connected by springs model many condensed-matter systems, from colloids interacting with a short-range potential and complex fluids near jamming, to self-assembled lattices and various metamaterials. Under small thermal fluctuations the vibrational entropy of a ground state is given by the harmonic approximation if it has no zero-frequency vibrational modes, yet such singular modes are at the epicenter of many interesting behaviors in the systems above. We consider a system of N spherical particles, and directly account for the singularities that arise in the sticky limit where the pairwise interaction is strong and short ranged. Although the contribution to the partition function from singular clusters diverges in the limit, its asymptotic value can be calculated and depends on only two parameters, characterizing the depth and range of the potential. The result holds for systems that are second-order rigid, a geometric characterization that describes all known ground-state (rigid) sticky clusters. To illustrate the applications of our theory we address the question of emergence: how does crystalline order arise in large systems when it is strongly disfavored in small ones? We calculate the partition functions of all known rigid clusters up to N≤21 and show the cluster landscape is dominated by hyperstatic clusters (those with more than 3N-6 contacts); singular and isostatic clusters are far less frequent, despite their extra vibrational and configurational entropies. Since the most hyperstatic clusters are close to fragments of a close-packed lattice, this underlies the emergence of order in sticky-sphere systems, even those as small as N=10.

Free energy of singular sticky-sphere clusters

NASA Astrophysics Data System (ADS)

Kallus, Yoav; Holmes-Cerfon, Miranda

2017-02-01

Networks of particles connected by springs model many condensed-matter systems, from colloids interacting with a short-range potential and complex fluids near jamming, to self-assembled lattices and various metamaterials. Under small thermal fluctuations the vibrational entropy of a ground state is given by the harmonic approximation if it has no zero-frequency vibrational modes, yet such singular modes are at the epicenter of many interesting behaviors in the systems above. We consider a system of N spherical particles, and directly account for the singularities that arise in the sticky limit where the pairwise interaction is strong and short ranged. Although the contribution to the partition function from singular clusters diverges in the limit, its asymptotic value can be calculated and depends on only two parameters, characterizing the depth and range of the potential. The result holds for systems that are second-order rigid, a geometric characterization that describes all known ground-state (rigid) sticky clusters. To illustrate the applications of our theory we address the question of emergence: how does crystalline order arise in large systems when it is strongly disfavored in small ones? We calculate the partition functions of all known rigid clusters up to N ≤21 and show the cluster landscape is dominated by hyperstatic clusters (those with more than 3 N -6 contacts); singular and isostatic clusters are far less frequent, despite their extra vibrational and configurational entropies. Since the most hyperstatic clusters are close to fragments of a close-packed lattice, this underlies the emergence of order in sticky-sphere systems, even those as small as N =10 .

A Simple Model for the Earthquake Cycle Combining Self-Organized Criticality with Critical Point Behavior

NASA Astrophysics Data System (ADS)

Newman, W. I.; Turcotte, D. L.

2002-12-01

We have studied a hybrid model combining the forest-fire model with the site-percolation model in order to better understand the earthquake cycle. We consider a square array of sites. At each time step, a "tree" is dropped on a randomly chosen site and is planted if the site is unoccupied. When a cluster of "trees" spans the site (a percolating cluster), all the trees in the cluster are removed ("burned") in a "fire." The removal of the cluster is analogous to a characteristic earthquake and planting "trees" is analogous to increasing the regional stress. The clusters are analogous to the metastable regions of a fault over which an earthquake rupture can propagate once triggered. We find that the frequency-area statistics of the metastable regions are power-law with a negative exponent of two (as in the forest-fire model). This is analogous to the Gutenberg-Richter distribution of seismicity. This "self-organized critical behavior" can be explained in terms of an inverse cascade of clusters. Individual trees move from small to larger clusters until they are destroyed. This inverse cascade of clusters is self-similar and the power-law distribution of cluster sizes has been shown to have an exponent of two. We have quantified the forecasting of the spanning fires using error diagrams. The assumption that "fires" (earthquakes) are quasi-periodic has moderate predictability. The density of trees gives an improved degree of predictability, while the size of the largest cluster of trees provides a substantial improvement in forecasting a "fire."

Properties of a new small-world network with spatially biased random shortcuts

NASA Astrophysics Data System (ADS)

Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

2017-11-01

This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

Corona graphs as a model of small-world networks

NASA Astrophysics Data System (ADS)

Lv, Qian; Yi, Yuhao; Zhang, Zhongzhi

2015-11-01

We introduce recursive corona graphs as a model of small-world networks. We investigate analytically the critical characteristics of the model, including order and size, degree distribution, average path length, clustering coefficient, and the number of spanning trees, as well as Kirchhoff index. Furthermore, we study the spectra for the adjacency matrix and the Laplacian matrix for the model. We obtain explicit results for all the quantities of the recursive corona graphs, which are similar to those observed in real-life networks.

Moving beyond Stylized Economic Network Models: The Hybrid World of the Indian Firm Ownership Network1

PubMed Central

Mani, Dalhia; Moody, James

2014-01-01

A central theme of economic sociology has been to highlight the complexity and diversity of real world markets, but many network models of economic social structure ignore this feature and rely instead on stylized one-dimensional characterizations. Here, the authors return to the basic insight of structural diversity in economic sociology. Using the Indian interorganizational ownership network as their case, they discover a composite—or “hybrid”—model of economic networks that combines elements of prior stylized models. The network contains a disconnected periphery conforming closely to a “transactional” model; a semiperiphery characterized by small, dense clusters with sporadic links, as predicted in “small-world” models; and finally a nested core composed of clusters connected via multiple independent paths. The authors then show how a firm’s position within the mesolevel structure is associated with demographic features such as age and industry and differences in the extent to which firms engage in multiplex and high-value exchanges. PMID:25418990

Scalar Potential Model progress

NASA Astrophysics Data System (ADS)

Hodge, John

2007-04-01

Because observations of galaxies and clusters have been found inconsistent with General Relativity (GR), the focus of effort in developing a Scalar Potential Model (SPM) has been on the examination of galaxies and clusters. The SPM has been found to be consistent with cluster cellular structure, the flow of IGM from spiral galaxies to elliptical galaxies, intergalactic redshift without an expanding universe, discrete redshift, rotation curve (RC) data without dark matter, asymmetric RCs, galaxy central mass, galaxy central velocity dispersion, and the Pioneer Anomaly. In addition, the SPM suggests a model of past expansion, past contraction, and current expansion of the universe. GR corresponds to the SPM in the limit in which a flat and static scalar potential field replaces the Sources and Sinks such as between clusters and on the solar system scale which is small relative to the distance to a Source. The papers may be viewed at http://web.infoave.net/˜scjh/ .

Clustering of arc volcanoes caused by temperature perturbations in the back-arc mantle

PubMed Central

Lee, Changyeol; Wada, Ikuko

2017-01-01

Clustering of arc volcanoes in subduction zones indicates along-arc variation in the physical condition of the underlying mantle where majority of arc magmas are generated. The sub-arc mantle is brought in from the back-arc largely by slab-driven mantle wedge flow. Dynamic processes in the back-arc, such as small-scale mantle convection, are likely to cause lateral variations in the back-arc mantle temperature. Here we use a simple three-dimensional numerical model to quantify the effects of back-arc temperature perturbations on the mantle wedge flow pattern and sub-arc mantle temperature. Our model calculations show that relatively small temperature perturbations in the back-arc result in vigorous inflow of hotter mantle and subdued inflow of colder mantle beneath the arc due to the temperature dependence of the mantle viscosity. This causes a three-dimensional mantle flow pattern that amplifies the along-arc variations in the sub-arc mantle temperature, providing a simple mechanism for volcano clustering. PMID:28660880

Clustering of arc volcanoes caused by temperature perturbations in the back-arc mantle.

PubMed

Lee, Changyeol; Wada, Ikuko

2017-06-29

Clustering of arc volcanoes in subduction zones indicates along-arc variation in the physical condition of the underlying mantle where majority of arc magmas are generated. The sub-arc mantle is brought in from the back-arc largely by slab-driven mantle wedge flow. Dynamic processes in the back-arc, such as small-scale mantle convection, are likely to cause lateral variations in the back-arc mantle temperature. Here we use a simple three-dimensional numerical model to quantify the effects of back-arc temperature perturbations on the mantle wedge flow pattern and sub-arc mantle temperature. Our model calculations show that relatively small temperature perturbations in the back-arc result in vigorous inflow of hotter mantle and subdued inflow of colder mantle beneath the arc due to the temperature dependence of the mantle viscosity. This causes a three-dimensional mantle flow pattern that amplifies the along-arc variations in the sub-arc mantle temperature, providing a simple mechanism for volcano clustering.

SBA Innovation Clusters

DTIC Science & Technology

2012-03-02

Programs and services to help you start, grow and succeed www.sba.gov U.S. Small Business Administration Your Small Business Resource 1Approved for...Public Release SBA Innovation Clusters RADM Steven G. Smith USN (Ret) Advanced Defense Technology Cluster Coordinator U.S. Small Business ...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Small Business Administration ,Advanced Defense Technology Cluster,409 3rd St, SW

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Topic modeling for cluster analysis of large biological and medical datasets

PubMed Central

2014-01-01

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

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

PubMed

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

2014-01-01

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

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Dynamical Organization of Syntaxin-1A at the Presynaptic Active Zone

PubMed Central

Ullrich, Alexander; Böhme, Mathias A.; Schöneberg, Johannes; Depner, Harald; Sigrist, Stephan J.; Noé, Frank

2015-01-01

Synaptic vesicle fusion is mediated by SNARE proteins forming in between synaptic vesicle (v-SNARE) and plasma membrane (t-SNARE), one of which is Syntaxin-1A. Although exocytosis mainly occurs at active zones, Syntaxin-1A appears to cover the entire neuronal membrane. By using STED super-resolution light microscopy and image analysis of Drosophila neuro-muscular junctions, we show that Syntaxin-1A clusters are more abundant and have an increased size at active zones. A computational particle-based model of syntaxin cluster formation and dynamics is developed. The model is parametrized to reproduce Syntaxin cluster-size distributions found by STED analysis, and successfully reproduces existing FRAP results. The model shows that the neuronal membrane is adjusted in a way to strike a balance between having most syntaxins stored in large clusters, while still keeping a mobile fraction of syntaxins free or in small clusters that can efficiently search the membrane or be traded between clusters. This balance is subtle and can be shifted toward almost no clustering and almost complete clustering by modifying the syntaxin interaction energy on the order of only 1 kBT. This capability appears to be exploited at active zones. The larger active-zone syntaxin clusters are more stable and provide regions of high docking and fusion capability, whereas the smaller clusters outside may serve as flexible reserve pool or sites of spontaneous ectopic release. PMID:26367029

Million-body star cluster simulations: comparisons between Monte Carlo and direct N-body

NASA Astrophysics Data System (ADS)

Rodriguez, Carl L.; Morscher, Meagan; Wang, Long; Chatterjee, Sourav; Rasio, Frederic A.; Spurzem, Rainer

2016-12-01

We present the first detailed comparison between million-body globular cluster simulations computed with a Hénon-type Monte Carlo code, CMC, and a direct N-body code, NBODY6++GPU. Both simulations start from an identical cluster model with 106 particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes `frozen' (no fine-tuning of any free parameters or internal algorithms of the codes) we find good agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (>1000) are retained for 12 Gyr. Thus, the very accurate direct N-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-N dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct N-body, is capable of producing an accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.

STAR CLUSTER FORMATION WITH STELLAR FEEDBACK AND LARGE-SCALE INFLOW

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

Matzner, Christopher D.; Jumper, Peter H., E-mail: matzner@astro.utoronto.ca

2015-12-10

During star cluster formation, ongoing mass accretion is resisted by stellar feedback in the form of protostellar outflows from the low-mass stars and photo-ionization and radiation pressure feedback from the massive stars. We model the evolution of cluster-forming regions during a phase in which both accretion and feedback are present and use these models to investigate how star cluster formation might terminate. Protostellar outflows are the strongest form of feedback in low-mass regions, but these cannot stop cluster formation if matter continues to flow in. In more massive clusters, radiation pressure and photo-ionization rapidly clear the cluster-forming gas when itsmore » column density is too small. We assess the rates of dynamical mass ejection and of evaporation, while accounting for the important effect of dust opacity on photo-ionization. Our models are consistent with the census of protostellar outflows in NGC 1333 and Serpens South and with the dust temperatures observed in regions of massive star formation. Comparing observations of massive cluster-forming regions against our model parameter space, and against our expectations for accretion-driven evolution, we infer that massive-star feedback is a likely cause of gas disruption in regions with velocity dispersions less than a few kilometers per second, but that more massive and more turbulent regions are too strongly bound for stellar feedback to be disruptive.« less

Emergent patterns in interacting neuronal sub-populations

NASA Astrophysics Data System (ADS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2015-05-01

We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.

Coagulation-fragmentation for a finite number of particles and application to telomere clustering in the yeast nucleus

NASA Astrophysics Data System (ADS)

Hozé, Nathanaël; Holcman, David

2012-01-01

We develop a coagulation-fragmentation model to study a system composed of a small number of stochastic objects moving in a confined domain, that can aggregate upon binding to form local clusters of arbitrary sizes. A cluster can also dissociate into two subclusters with a uniform probability. To study the statistics of clusters, we combine a Markov chain analysis with a partition number approach. Interestingly, we obtain explicit formulas for the size and the number of clusters in terms of hypergeometric functions. Finally, we apply our analysis to study the statistical physics of telomeres (ends of chromosomes) clustering in the yeast nucleus and show that the diffusion-coagulation-fragmentation process can predict the organization of telomeres.

Environmental Effects on Evolution of Cluster Galaxies in a Λ-dominated Cold Dark Matter Universe

NASA Astrophysics Data System (ADS)

Okamoto, Takashi; Nagashima, Masahiro

2003-04-01

We investigate environmental effects on evolution of bright cluster galaxies (L>L*) in a Λ-dominated cold dark matter universe using a combination of dissipationless N-body simulations and a semianalytic galaxy formation model. The N-body simulations enable us to calculate orbits of galaxies in simulated clusters. Therefore, we can incorporate stripping of cold gas from galactic disks by ram pressure (RP) from the intracluster medium into our model. In this paper we study how ram pressure stripping (RPS) and small starburst induced by a minor merger affect colors, star formation rates (SFRs), and morphologies of cluster galaxies. These processes are new ingredients in our model and have not been studied sufficiently. We find that the RPS is not important for colors and SFRs of galaxies in the cluster core if the star formation timescale is properly chosen, because the star formation is sufficiently suppressed by consumption of the cold gas in the disks. Then observed color and SFR gradients can be reproduced without the RPS. The small starburst triggered by a minor merger hardly affects the SFRs and colors of the galaxies as well. We also examine whether these two processes can resolve the known problem that the hierarchical clustering models based on the major merger-driven bulge formation scenario predict too few galaxies of intermediate bulge-to-total luminosity ratio (B/T) in clusters. When the minor burst is taken into account, the intermediate B/T population is increased, and the observed morphology gradients in clusters are successfully reproduced. Without the minor burst, the RPS cannot increase the intermediate B/T population. On the other hand, when the minor burst is considered, the RPS also plays an important role in formation of the intermediate B/T galaxies. We present redshift evolution of morphological fractions predicted by our models. The predicted number ratios of the intermediate B/T galaxies to the bulge-dominated galaxies show nearly flat or slightly increasing trends with increasing redshift. We conclude that these trends are inevitable when bulges are formed through mergers. We discuss whether our results conflict with observationally suggested NS0/NE evolution in clusters, which is a decreasing function of redshift.

Sodium dopants in helium clusters: Structure, equilibrium and submersion kinetics

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

Calvo, F.

Alkali impurities bind to helium nanodroplets very differently depending on their size and charge state, large neutral or charged dopants being wetted by the droplet whereas small neutral impurities prefer to reside aside. Using various computational modeling tools such as quantum Monte Carlo and path-integral molecular dynamics simulations, we have revisited some aspects of the physical chemistry of helium droplets interacting with sodium impurities, including the onset of snowball formation in presence of many-body polarization forces, the transition from non-wetted to wetted behavior in larger sodium clusters, and the kinetics of submersion of small dopants after sudden ionization.

Lagrangian model of copepod dynamics: Clustering by escape jumps in turbulence

NASA Astrophysics Data System (ADS)

Ardeshiri, H.; Benkeddad, I.; Schmitt, F. G.; Souissi, S.; Toschi, F.; Calzavarini, E.

2016-04-01

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behavior on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are here used to define and tune a Lagrangian copepod (LC) model. The model is further employed to simulate the behavior of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in turbulence. Second, we quantify the clustering of LC, via the fractal dimension D2. We show that D2 can be as low as ˜2.3 and that it critically depends on the shear-rate sensitivity of the proposed LC model, in particular it exhibits a minimum in a narrow range of shear-rate values. We further investigate the effect of jump intensity, jump orientation, and geometrical aspect ratio of the copepods on the small-scale spatial distribution. At last, possible ecological implications of the observed clustering on encounter rates and mating success are discussed.

The shape of galaxy dark matter halos in massive galaxy clusters: Insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-04-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and VLT/MUSE spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z=0.397, M(R < 200 kpc)=1.6×1014M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar halos are allowed, the model improves by 35%. This technique may provide a new way to investigate the processes and timescales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

The shape of galaxy dark matter haloes in massive galaxy clusters: insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-07-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and Very Large Telescope/Multi Unit Spectroscopic Explorer spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z = 0.397, M(R < 200 kpc) = 1.6 × 1014 M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar haloes are allowed, the model improves by 35 per cent. This technique may provide a new way to investigate the processes and time-scales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Modelling galaxy clustering on small scales to tighten constraints on dark energy and modified gravity

NASA Astrophysics Data System (ADS)

Wang, Yun

2017-01-01

We present a new approach to measuring cosmic expansion history and growth rate of large-scale structure using the anisotropic two-dimensional galaxy correlation function (2DCF) measured from data; it makes use of the empirical modelling of small-scale galaxy clustering derived from numerical simulations by Zheng et al. We validate this method using mock catalogues, before applying it to the analysis of the CMASS sample from the Sloan Digital Sky Survey Data Release 10 of the Baryon Oscillation Spectroscopic Survey. We find that this method enables accurate and precise measurements of cosmic expansion history and growth rate of large-scale structure. Modelling the 2DCF fully including non-linear effects and redshift space distortions in the scale range of 16-144 h-1 Mpc, we find H(0.57)rs(zd)/c = 0.0459 ± 0.0006, DA(0.57)/rs(zd) = 9.011 ± 0.073, and fg(0.57)σ8(0.57) = 0.476 ± 0.050, which correspond to precisions of 1.3 per cent, 0.8 per cent, and 10.5 per cent, respectively. We have defined rs(zd) to be the sound horizon at the drag epoch computed using a simple integral, fg(z) as the growth rate at redshift z, and σ8(z) as the matter power spectrum normalization on 8 h-1 Mpc scale at z. We find that neglecting the small-scale information significantly weakens the constraints on H(z) and DA(z), and leads to a biased estimate of fg(z). Our results indicate that we can significantly tighten constraints on dark energy and modified gravity by reliably modelling small-scale galaxy clustering.

From atoms to layers: in situ gold cluster growth kinetics during sputter deposition

NASA Astrophysics Data System (ADS)

Schwartzkopf, Matthias; Buffet, Adeline; Körstgens, Volker; Metwalli, Ezzeldin; Schlage, Kai; Benecke, Gunthard; Perlich, Jan; Rawolle, Monika; Rothkirch, André; Heidmann, Berit; Herzog, Gerd; Müller-Buschbaum, Peter; Röhlsberger, Ralf; Gehrke, Rainer; Stribeck, Norbert; Roth, Stephan V.

2013-05-01

The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources.The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources. Electronic supplementary information (ESI) available: The full GISAXS image sequence of the experiment, the model-based IsGISAXS-simulation sequence as movie files for comparison and detailed information about sample cleaning, XRR, FESEM, IsGISAXS, comparison μGIWAXS/μGISAXS, and sampling statistics. See DOI: 10.1039/c3nr34216f

On the calculation of the energies of dissociation, cohesion, vacancy formation, electron attachment, and the ionization potential of small metallic clusters containing a monovacancy

NASA Astrophysics Data System (ADS)

Pogosov, V. V.; Reva, V. I.

2017-09-01

In terms of the model of stable jellium, self-consistent calculations of spatial distributions of electrons and potentials, as well as of energies of dissociation, cohesion, vacancy formation, electron attachment, and ionization potentials of solid clusters of Mg N , Li N (with N ≤ 254 ) and of clusters containing a vacancy ( N ≥ 12) have been performed. The contribution of a monovacancy to the energy of the cluster and size dependences of its characteristics and of asymptotics have been discussed. Calculations have been performed using a SKIT-3 cluster at Glushkov Institute of Cybernetics, National Academy of Sciences, Ukraine (Rpeak = 7.4 Tflops).

SAR image segmentation using skeleton-based fuzzy clustering

NASA Astrophysics Data System (ADS)

Cao, Yun Yi; Chen, Yan Qiu

2003-06-01

SAR image segmentation can be converted to a clustering problem in which pixels or small patches are grouped together based on local feature information. In this paper, we present a novel framework for segmentation. The segmentation goal is achieved by unsupervised clustering upon characteristic descriptors extracted from local patches. The mixture model of characteristic descriptor, which combines intensity and texture feature, is investigated. The unsupervised algorithm is derived from the recently proposed Skeleton-Based Data Labeling method. Skeletons are constructed as prototypes of clusters to represent arbitrary latent structures in image data. Segmentation using Skeleton-Based Fuzzy Clustering is able to detect the types of surfaces appeared in SAR images automatically without any user input.

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

NASA Technical Reports Server (NTRS)

Putnam, Williama

2011-01-01

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Coevolving complex networks in the model of social interactions

NASA Astrophysics Data System (ADS)

Raducha, Tomasz; Gubiec, Tomasz

2017-04-01

We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions-preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to the power-law distribution of nodes' degree and high value of the clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point-an abrupt increase of the clustering coefficient, due to formation of many small complete subgraphs inside the network.

Clustering of change patterns using Fourier coefficients.

PubMed

Kim, Jaehee; Kim, Haseong

2008-01-15

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a time period because biologically related gene groups can share the same change patterns. Many clustering algorithms have been proposed to group observation data. However, because of the complexity of the underlying functions there have not been many studies on grouping data based on change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. The sample Fourier coefficients not only provide information about the underlying functions, but also reduce the dimension. In addition, as their limiting distribution is a multivariate normal, a model-based clustering method incorporating statistical properties would be appropriate. This work is aimed at discovering gene groups with similar change patterns that share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. The model-based method is advantageous over other methods in our proposed model because the sample Fourier coefficients asymptotically follow the multivariate normal distribution. Change patterns are automatically estimated with the Fourier representation in our model. Our model was tested in simulations and on real gene data sets. The simulation results showed that the model-based clustering method with the sample Fourier coefficients has a lower clustering error rate than K-means clustering. Even when the number of repeated time points was small, the same results were obtained. We also applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns. The R program is available upon the request.

ALCHEMY: a reliable method for automated SNP genotype calling for small batch sizes and highly homozygous populations

PubMed Central

Wright, Mark H.; Tung, Chih-Wei; Zhao, Keyan; Reynolds, Andy; McCouch, Susan R.; Bustamante, Carlos D.

2010-01-01

Motivation: The development of new high-throughput genotyping products requires a significant investment in testing and training samples to evaluate and optimize the product before it can be used reliably on new samples. One reason for this is current methods for automated calling of genotypes are based on clustering approaches which require a large number of samples to be analyzed simultaneously, or an extensive training dataset to seed clusters. In systems where inbred samples are of primary interest, current clustering approaches perform poorly due to the inability to clearly identify a heterozygote cluster. Results: As part of the development of two custom single nucleotide polymorphism genotyping products for Oryza sativa (domestic rice), we have developed a new genotype calling algorithm called ‘ALCHEMY’ based on statistical modeling of the raw intensity data rather than modelless clustering. A novel feature of the model is the ability to estimate and incorporate inbreeding information on a per sample basis allowing accurate genotyping of both inbred and heterozygous samples even when analyzed simultaneously. Since clustering is not used explicitly, ALCHEMY performs well on small sample sizes with accuracy exceeding 99% with as few as 18 samples. Availability: ALCHEMY is available for both commercial and academic use free of charge and distributed under the GNU General Public License at http://alchemy.sourceforge.net/ Contact: mhw6@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20926420

Dark matter self-interactions and small scale structure

NASA Astrophysics Data System (ADS)

Tulin, Sean; Yu, Hai-Bo

2018-02-01

We review theories of dark matter (DM) beyond the collisionless paradigm, known as self-interacting dark matter (SIDM), and their observable implications for astrophysical structure in the Universe. Self-interactions are motivated, in part, due to the potential to explain long-standing (and more recent) small scale structure observations that are in tension with collisionless cold DM (CDM) predictions. Simple particle physics models for SIDM can provide a universal explanation for these observations across a wide range of mass scales spanning dwarf galaxies, low and high surface brightness spiral galaxies, and clusters of galaxies. At the same time, SIDM leaves intact the success of ΛCDM cosmology on large scales. This report covers the following topics: (1) small scale structure issues, including the core-cusp problem, the diversity problem for rotation curves, the missing satellites problem, and the too-big-to-fail problem, as well as recent progress in hydrodynamical simulations of galaxy formation; (2) N-body simulations for SIDM, including implications for density profiles, halo shapes, substructure, and the interplay between baryons and self-interactions; (3) semi-analytic Jeans-based methods that provide a complementary approach for connecting particle models with observations; (4) merging systems, such as cluster mergers (e.g., the Bullet Cluster) and minor infalls, along with recent simulation results for mergers; (5) particle physics models, including light mediator models and composite DM models; and (6) complementary probes for SIDM, including indirect and direct detection experiments, particle collider searches, and cosmological observations. We provide a summary and critical look for all current constraints on DM self-interactions and an outline for future directions.

A class of spherical, truncated, anisotropic models for application to globular clusters

NASA Astrophysics Data System (ADS)

de Vita, Ruggero; Bertin, Giuseppe; Zocchi, Alice

2016-05-01

Recently, a class of non-truncated, radially anisotropic models (the so-called f(ν)-models), originally constructed in the context of violent relaxation and modelling of elliptical galaxies, has been found to possess interesting qualities in relation to observed and simulated globular clusters. In view of new applications to globular clusters, we improve this class of models along two directions. To make them more suitable for the description of small stellar systems hosted by galaxies, we introduce a "tidal" truncation by means of a procedure that guarantees full continuity of the distribution function. The new fT(ν)-models are shown to provide a better fit to the observed photometric and spectroscopic profiles for a sample of 13 globular clusters studied earlier by means of non-truncated models; interestingly, the best-fit models also perform better with respect to the radial-orbit instability. Then, we design a flexible but simple two-component family of truncated models to study the separate issues of mass segregation and multiple populations. We do not aim at a fully realistic description of globular clusters to compete with the description currently obtained by means of dedicated simulations. The goal here is to try to identify the simplest models, that is, those with the smallest number of free parameters, but still have the capacity to provide a reasonable description for clusters that are evidently beyond the reach of one-component models. With this tool, we aim at identifying the key factors that characterize mass segregation or the presence of multiple populations. To reduce the relevant parameter space, we formulate a few physical arguments based on recent observations and simulations. A first application to two well-studied globular clusters is briefly described and discussed.

Combining cluster number counts and galaxy clustering

NASA Astrophysics Data System (ADS)

Lacasa, Fabien; Rosenfeld, Rogerio

2016-08-01

The abundance of clusters and the clustering of galaxies are two of the important cosmological probes for current and future large scale surveys of galaxies, such as the Dark Energy Survey. In order to combine them one has to account for the fact that they are not independent quantities, since they probe the same density field. It is important to develop a good understanding of their correlation in order to extract parameter constraints. We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. We employ the framework of the halo model complemented by a Halo Occupation Distribution model (HOD). We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions. Indeed, we show that the non-Gaussian covariance becomes dominant at small scales, low redshifts or high cluster masses. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias. We demonstrate that the SSC obeys mathematical inequalities and positivity. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeably better constraints, with improvements of order 20% on cosmological parameters compared to the best single probe, and even greater improvement on HOD parameters, with reduction of error bars by a factor 1.4-4.8. This happens in particular because the cross-covariance introduces a synergy between the probes on small scales. We conclude that accounting for non-Gaussian effects is required for the joint analysis of these observables in galaxy surveys.

Shared and Distinct Rupture Discriminants of Small and Large Intracranial Aneurysms.

PubMed

Varble, Nicole; Tutino, Vincent M; Yu, Jihnhee; Sonig, Ashish; Siddiqui, Adnan H; Davies, Jason M; Meng, Hui

2018-04-01

Many ruptured intracranial aneurysms (IAs) are small. Clinical presentations suggest that small and large IAs could have different phenotypes. It is unknown if small and large IAs have different characteristics that discriminate rupture. We analyzed morphological, hemodynamic, and clinical parameters of 413 retrospectively collected IAs (training cohort; 102 ruptured IAs). Hierarchal cluster analysis was performed to determine a size cutoff to dichotomize the IA population into small and large IAs. We applied multivariate logistic regression to build rupture discrimination models for small IAs, large IAs, and an aggregation of all IAs. We validated the ability of these 3 models to predict rupture status in a second, independently collected cohort of 129 IAs (testing cohort; 14 ruptured IAs). Hierarchal cluster analysis in the training cohort confirmed that small and large IAs are best separated at 5 mm based on morphological and hemodynamic features (area under the curve=0.81). For small IAs (<5 mm), the resulting rupture discrimination model included undulation index, oscillatory shear index, previous subarachnoid hemorrhage, and absence of multiple IAs (area under the curve=0.84; 95% confidence interval, 0.78-0.88), whereas for large IAs (≥5 mm), the model included undulation index, low wall shear stress, previous subarachnoid hemorrhage, and IA location (area under the curve=0.87; 95% confidence interval, 0.82-0.93). The model for the aggregated training cohort retained all the parameters in the size-dichotomized models. Results in the testing cohort showed that the size-dichotomized rupture discrimination model had higher sensitivity (64% versus 29%) and accuracy (77% versus 74%), marginally higher area under the curve (0.75; 95% confidence interval, 0.61-0.88 versus 0.67; 95% confidence interval, 0.52-0.82), and similar specificity (78% versus 80%) compared with the aggregate-based model. Small (<5 mm) and large (≥5 mm) IAs have different hemodynamic and clinical, but not morphological, rupture discriminants. Size-dichotomized rupture discrimination models performed better than the aggregate model. © 2018 American Heart Association, Inc.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

PubMed

Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

2009-11-01

This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

Correlation among extinction efficiency and other parameters in an aggregate dust model

NASA Astrophysics Data System (ADS)

Dhar, Tanuj Kumar; Sekhar Das, Himadri

2017-10-01

We study the extinction properties of highly porous Ballistic Cluster-Cluster Aggregate dust aggregates in a wide range of complex refractive indices (1.4≤ n≤ 2.0, 0.001≤ k≤ 1.0) and wavelengths (0.11 {{μ }}{{m}}≤ {{λ }}≤ 3.4 {{μ }} m). An attempt has been made for the first time to investigate the correlation among extinction efficiency ({Q}{ext}), composition of dust aggregates (n,k), wavelength of radiation (λ) and size parameter of the monomers (x). If k is fixed at any value between 0.001 and 1.0, {Q}{ext} increases with increase of n from 1.4 to 2.0. {Q}{ext} and n are correlated via linear regression when the cluster size is small, whereas the correlation is quadratic at moderate and higher sizes of the cluster. This feature is observed at all wavelengths (ultraviolet to optical to infrared). We also find that the variation of {Q}{ext} with n is very small when λ is high. When n is fixed at any value between 1.4 and 2.0, it is observed that {Q}{ext} and k are correlated via a polynomial regression equation (of degree 1, 2, 3 or 4), where the degree of the equation depends on the cluster size, n and λ. The correlation is linear for small size and quadratic/cubic/quartic for moderate and higher sizes. We have also found that {Q}{ext} and x are correlated via a polynomial regression (of degree 3, 4 or 5) for all values of n. The degree of regression is found to be n and k-dependent. The set of relations obtained from our work can be used to model interstellar extinction for dust aggregates in a wide range of wavelengths and complex refractive indices.

CA II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. III. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF 14 CLUSTERS

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

Parisi, M. C.; Clariá, J. J.; Marcionni, N.

2015-05-15

We obtained spectra of red giants in 15 Small Magellanic Cloud (SMC) clusters in the region of the Ca ii lines with FORS2 on the Very Large Telescope. We determined the mean metallicity and radial velocity with mean errors of 0.05 dex and 2.6 km s{sup −1}, respectively, from a mean of 6.5 members per cluster. One cluster (B113) was too young for a reliable metallicity determination and was excluded from the sample. We combined the sample studied here with 15 clusters previously studied by us using the same technique, and with 7 clusters whose metallicities determined by other authorsmore » are on a scale similar to ours. This compilation of 36 clusters is the largest SMC cluster sample currently available with accurate and homogeneously determined metallicities. We found a high probability that the metallicity distribution is bimodal, with potential peaks at −1.1 and −0.8 dex. Our data show no strong evidence of a metallicity gradient in the SMC clusters, somewhat at odds with recent evidence from Ca ii triplet spectra of a large sample of field stars. This may be revealing possible differences in the chemical history of clusters and field stars. Our clusters show a significant dispersion of metallicities, whatever age is considered, which could be reflecting the lack of a unique age–metallicity relation in this galaxy. None of the chemical evolution models currently available in the literature satisfactorily represents the global chemical enrichment processes of SMC clusters.« less

Adsorption and Diffusion of Fructose in Zeolite HZSM-5: Selection of Models and Methods for Computational Studies

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

Cheng, Lei; Curtiss, Larry A.; Assary, Rajeev S.

The adsorption and protonation of fructose inHZSM-5 have been studied for the assessment of models for accurate reaction energy calculations and the evaluation of molecular diffusivity. The adsorption and protonation were calculated using 2T, 5T, and 46T clusters as well as a periodic model. The results indicate that the reaction thermodynamics cannot be predicted correctly using small cluster models, such as 2T or 5T, because these small cluster models fail to represent the electrostatic effect of a zeolite cage, which provides additional stabilization to the ion pair formed upon the protonation of fructose. Structural parameters optimized using the 46T clustermore » model agree well with those of the full periodic model; however, the calculated reaction energies are in significant error due to the poor account of dispersion effects by density functional theory. The dispersion effects contribute -30.5 kcal/mol to the binding energy of fructose in the zeolite pore based on periodic model calculations that include dispersion interactions. The protonation of the fructose ternary carbon hydroxyl group was calculated to be exothermic by 5.5 kcal/mol with a reaction barrier of 2.9 kcal/mol using the periodic model with dispersion effects. Our results suggest that the internal diffusion of fructose in HZSM-5 is very likely to be energetically limited and only occurs at high temperature due to the large size of the molecule.« less

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Cooperative effects in the structuring of fluoride water clusters: Ab initio hybrid quantum mechanical/molecular mechanical model incorporating polarizable fluctuating charge solvent

NASA Astrophysics Data System (ADS)

Bryce, Richard A.; Vincent, Mark A.; Malcolm, Nathaniel O. J.; Hillier, Ian H.; Burton, Neil A.

1998-08-01

A new hybrid quantum mechanical/molecular mechanical model of solvation is developed and used to describe the structure and dynamics of small fluoride/water clusters, using an ab initio wave function to model the ion and a fluctuating charge potential to model the waters. Appropriate parameters for the water-water and fluoride-water interactions are derived, with the fluoride anion being described by density functional theory and a large Gaussian basis. The role of solvent polarization in determining the structure and energetics of F(H2O)4- clusters is investigated, predicting a slightly greater stability of the interior compared to the surface structure, in agreement with ab initio studies. An extended Lagrangian treatment of the polarizable water, in which the water atomic charges fluctuate dynamically, is used to study the dynamics of F(H2O)4- cluster. A simulation using a fixed solvent charge distribution indicates principally interior, solvated states for the cluster. However, a preponderance of trisolvated configurations is observed using the polarizable model at 300 K, which involves only three direct fluoride-water hydrogen bonds. Ab initio calculations confirm this trisolvated species as a thermally accessible state at room temperature, in addition to the tetrasolvated interior and surface structures. Extension of this polarizable water model to fluoride clusters with five and six waters gave less satisfactory agreement with experimental energies and with ab initio geometries. However, our results do suggest that a quantitative model of solvent polarization is fundamental for an accurate understanding of the properties of anionic water clusters.

"Non-cold" dark matter at small scales: a general approach

NASA Astrophysics Data System (ADS)

Murgia, R.; Merle, A.; Viel, M.; Totzauer, M.; Schneider, A.

2017-11-01

Structure formation at small cosmological scales provides an important frontier for dark matter (DM) research. Scenarios with small DM particle masses, large momenta or hidden interactions tend to suppress the gravitational clustering at small scales. The details of this suppression depend on the DM particle nature, allowing for a direct link between DM models and astrophysical observations. However, most of the astrophysical constraints obtained so far refer to a very specific shape of the power suppression, corresponding to thermal warm dark matter (WDM), i.e., candidates with a Fermi-Dirac or Bose-Einstein momentum distribution. In this work we introduce a new analytical fitting formula for the power spectrum, which is simple yet flexible enough to reproduce the clustering signal of large classes of non-thermal DM models, which are not at all adequately described by the oversimplified notion of WDM . We show that the formula is able to fully cover the parameter space of sterile neutrinos (whether resonantly produced or from particle decay), mixed cold and warm models, fuzzy dark matter, as well as other models suggested by effective theory of structure formation (ETHOS). Based on this fitting formula, we perform a large suite of N-body simulations and we extract important nonlinear statistics, such as the matter power spectrum and the halo mass function. Finally, we present first preliminary astrophysical constraints, based on linear theory, from both the number of Milky Way satellites and the Lyman-α forest. This paper is a first step towards a general and comprehensive modeling of small-scale departures from the standard cold DM model.

Critical thinking in higher education: The influence of teaching styles and peer collaboration on science and math learning

NASA Astrophysics Data System (ADS)

Quitadamo, Ian Joseph

Many higher education faculty perceive a deficiency in students' ability to reason, evaluate, and make informed judgments, skills that are deemed necessary for academic and job success in science and math. These skills, often collected within a domain called critical thinking (CT), have been studied and are thought to be influenced by teaching styles (the combination of beliefs, behavior, and attitudes used when teaching) and small group collaborative learning (SGCL). However, no existing studies show teaching styles and SGCL cause changes in student CT performance. This study determined how combinations of teaching styles called clusters and peer-facilitated SGCL (a specific form of SGCL) affect changes in undergraduate student CT performance using a quasi-experimental pre-test/post-test research design and valid and reliable CT performance indicators. Quantitative analyses of three teaching style cluster models (Grasha's cluster model, a weighted cluster model, and a student-centered/teacher-centered cluster model) and peer-facilitated SGCL were performed to evaluate their ability to cause measurable changes in student CT skills. Based on results that indicated weighted teaching style clusters and peer-facilitated SGCL are associated with significant changes in student CT, we conclude that teaching styles and peer-facilitated SGCL influence the development of undergraduate CT in higher education science and math.

Modeling of the Modulation by Buffers of Ca2+ Release through Clusters of IP3 Receptors

PubMed Central

Zeller, S.; Rüdiger, S.; Engel, H.; Sneyd, J.; Warnecke, G.; Parker, I.; Falcke, M.

2009-01-01

Abstract Intracellular Ca2+ release is a versatile second messenger system. It is modeled here by reaction-diffusion equations for the free Ca2+ and Ca2+ buffers, with spatially discrete clusters of stochastic IP3 receptor channels (IP3Rs) controlling the release of Ca2+ from the endoplasmic reticulum. IP3Rs are activated by a small rise of the cytosolic Ca2+ concentration and inhibited by large concentrations. Buffering of cytosolic Ca2+ shapes global Ca2+ transients. Here we use a model to investigate the effect of buffers with slow and fast reaction rates on single release spikes. We find that, depending on their diffusion coefficient, fast buffers can either decouple clusters or delay inhibition. Slow buffers have little effect on Ca2+ release, but affect the time course of the signals from the fluorescent Ca2+ indicator mainly by competing for Ca2+. At low [IP3], fast buffers suppress fluorescence signals, slow buffers increase the contrast between bulk signals and signals at open clusters, and large concentrations of buffers, either fast or slow, decouple clusters. PMID:19686646

Angular correlation function of 1.5 million luminous red galaxies: clustering evolution and a search for baryon acoustic oscillations

NASA Astrophysics Data System (ADS)

Sawangwit, U.; Shanks, T.; Abdalla, F. B.; Cannon, R. D.; Croom, S. M.; Edge, A. C.; Ross, Nicholas P.; Wake, D. A.

2011-10-01

We present the angular correlation function measured from photometric samples comprising 1562 800 luminous red galaxies (LRGs). Three LRG samples were extracted from the Sloan Digital Sky Survey (SDSS) imaging data, based on colour-cut selections at redshifts, z≈ 0.35, 0.55 and 0.7 as calibrated by the spectroscopic surveys, SDSS-LRG, 2dF-SDSS LRG and QSO (quasi-stellar object) (2SLAQ) and the AAΩ-LRG survey. The galaxy samples cover ≈7600 deg2 of sky, probing a total cosmic volume of ≈5.5 h-3 Gpc3. The small- and intermediate-scale correlation functions generally show significant deviations from a single power-law fit with a well-detected break at ≈1 h-1 Mpc, consistent with the transition scale between the one- and two-halo terms in halo occupation models. For galaxy separations 1-20 h-1 Mpc and at fixed luminosity, we see virtually no evolution of the clustering with redshift and the data are consistent with a simple high peaks biasing model where the comoving LRG space density is constant with z. At fixed z, the LRG clustering amplitude increases with luminosity in accordance with the simple high peaks model, with a typical LRG dark matter halo mass 1013-1014 h-1 M⊙. For r < 1 h-1 Mpc, the evolution is slightly faster and the clustering decreases towards high redshift consistent with a virialized clustering model. However, assuming the halo occupation distribution (HOD) and Λ cold dark matter (ΛCDM) halo merger frameworks, ˜2-3 per cent/Gyr of the LRGs are required to merge in order to explain the small scales clustering evolution, consistent with previous results. At large scales, our result shows good agreement with the SDSS-LRG result of Eisenstein et al. but we find an apparent excess clustering signal beyond the baryon acoustic oscillations (BAO) scale. Angular power spectrum analyses of similar LRG samples also detect a similar apparent large-scale clustering excess but more data are required to check for this feature in independent galaxy data sets. Certainly, if the ΛCDM model were correct then we would have to conclude that this excess was caused by systematics at the level of Δw≈ 0.001-0.0015 in the photometric AAΩ-LRG sample.

Étude statistique et dynamique de la propagation d'épidémies dans un réseau de petit mondeStatistical and dynamical study of the epidemics propagation in a small world network

NASA Astrophysics Data System (ADS)

Zekri, Nouredine; Clerc, Jean Pierre

We study numerically in this work the statistical and dynamical properties of the clusters in a one dimensional small world model. The parameters chosen correspond to a realistic network of children of school age where a disease like measles can propagate. Extensive results on the statistical behavior of the clusters around the percolation threshold, as well as the evoltion with time, are discussed. To cite this article: N. Zekri, J.P. Clerc, C. R. Physique 3 (2002) 741-747.

Dynamic behaviour of nanometre-sized defect clusters emitted from an atomic displacement cascade in Au at 50 K

NASA Astrophysics Data System (ADS)

Ono, K.; Miyamoto, M.; Arakawa, K.; Birtcher, R. C.

2017-09-01

We demonstrate the emission of nanometre-sized defect clusters from an isolated displacement cascade formed by irradiation of high-energy self-ions and their subsequent 1-D motion in Au at 50 K, using in situ electron microscopy. The small defect clusters emitted from a displacement cascade exhibited correlated back-and-forth 1-D motion along the [-1 1 0] direction and coalescence which results in their growth and reduction of their mobility. From the analysis of the random 1-D motion, the diffusivity of the small cluster was evaluated. Correlated 1-D motion and coalescence of clusters were understood via elastic interaction between small clusters. These results provide direct experimental evidence of the migration of small defect clusters and defect cascade evolution at low temperature.

Patterns in the English language: phonological networks, percolation and assembly models

NASA Astrophysics Data System (ADS)

Stella, Massimo; Brede, Markus

2015-05-01

In this paper we provide a quantitative framework for the study of phonological networks (PNs) for the English language by carrying out principled comparisons to null models, either based on site percolation, randomization techniques, or network growth models. In contrast to previous work, we mainly focus on null models that reproduce lower order characteristics of the empirical data. We find that artificial networks matching connectivity properties of the English PN are exceedingly rare: this leads to the hypothesis that the word repertoire might have been assembled over time by preferentially introducing new words which are small modifications of old words. Our null models are able to explain the ‘power-law-like’ part of the degree distributions and generally retrieve qualitative features of the PN such as high clustering, high assortativity coefficient and small-world characteristics. However, the detailed comparison to expectations from null models also points out significant differences, suggesting the presence of additional constraints in word assembly. Key constraints we identify are the avoidance of large degrees, the avoidance of triadic closure and the avoidance of large non-percolating clusters.

Coevolutionary dynamics of opinion propagation and social balance: The key role of small-worldness

NASA Astrophysics Data System (ADS)

Chen, Yan; Chen, Lixue; Sun, Xian; Zhang, Kai; Zhang, Jie; Li, Ping

2014-03-01

The propagation of various opinions in social networks, which influences human inter-relationships and even social structure, and hence is a most important part of social life. We have incorporated social balance into opinion propagation in social networks are influenced by social balance. The edges in networks can represent both friendly or hostile relations, and change with the opinions of individual nodes. We introduce a model to characterize the coevolutionary dynamics of these two dynamical processes on Watts-Strogatz (WS) small-world network. We employ two distinct evolution rules (i) opinion renewal; and (ii) relation adjustment. By changing the rewiring probability, and thus the small-worldness of the WS network, we found that the time for the system to reach balanced states depends critically on both the average path length and clustering coefficient of the network, which is different than other networked process like epidemic spreading. In particular, the system equilibrates most quickly when the underlying network demonstrates strong small-worldness, i.e., small average path lengths and large clustering coefficient. We also find that opinion clusters emerge in the process of the network approaching the global equilibrium, and a measure of global contrariety is proposed to quantify the balanced state of a social network.

Stellar-mass black holes in young massive and open stellar clusters and their role in gravitational-wave generation - II

NASA Astrophysics Data System (ADS)

Banerjee, Sambaran

2018-01-01

The study of stellar-remnant black holes (BH) in dense stellar clusters is now in the spotlight, especially due to their intrinsic ability to form binary black holes (BBH) through dynamical encounters, which potentially coalesce via gravitational-wave (GW) radiation. In this work, which is a continuation from a recent study (Paper I), additional models of compact stellar clusters with initial masses ≲ 105 M⊙ and also those with small fractions of primordial binaries (≲ 10 per cent) are evolved for long term, applying the direct N-body approach, assuming state-of-the-art stellar-wind and remnant-formation prescriptions. That way, a substantially broader range of computed models than that in Paper I is achieved. As in Paper I, the general-relativistic BBH mergers continue to be mostly mediated by triples that are bound to the clusters rather than happen among the ejected BBHs. In fact, the number of such in situ BBH mergers, per cluster, tends to increase significantly with the introduction of a small population of primordial binaries. Despite the presence of massive primordial binaries, the merging BBHs, especially the in situ ones, are found to be exclusively dynamically assembled and hence would be spin-orbit misaligned. The BBHs typically traverse through both the LISA's and the LIGO's detection bands, being audible to both instruments. The 'dynamical heating' of the BHs keeps the electron-capture-supernova (ECS) neutron stars (NS) from effectively mass segregating and participating in exchange interactions; the dynamically active BHs would also exchange into any NS binary within ≲1 Gyr. Such young massive and open clusters have the potential to contribute to the dynamical BBH merger detection rate to a similar extent as their more massive globular-cluster counterparts.

High-throughput platform for the discovery of elicitors of silent bacterial gene clusters.

PubMed

Seyedsayamdost, Mohammad R

2014-05-20

Over the past decade, bacterial genome sequences have revealed an immense reservoir of biosynthetic gene clusters, sets of contiguous genes that have the potential to produce drugs or drug-like molecules. However, the majority of these gene clusters appear to be inactive for unknown reasons prompting terms such as "cryptic" or "silent" to describe them. Because natural products have been a major source of therapeutic molecules, methods that rationally activate these silent clusters would have a profound impact on drug discovery. Herein, a new strategy is outlined for awakening silent gene clusters using small molecule elicitors. In this method, a genetic reporter construct affords a facile read-out for activation of the silent cluster of interest, while high-throughput screening of small molecule libraries provides potential inducers. This approach was applied to two cryptic gene clusters in the pathogenic model Burkholderia thailandensis. The results not only demonstrate a prominent activation of these two clusters, but also reveal that the majority of elicitors are themselves antibiotics, most in common clinical use. Antibiotics, which kill B. thailandensis at high concentrations, act as inducers of secondary metabolism at low concentrations. One of these antibiotics, trimethoprim, served as a global activator of secondary metabolism by inducing at least five biosynthetic pathways. Further application of this strategy promises to uncover the regulatory networks that activate silent gene clusters while at the same time providing access to the vast array of cryptic molecules found in bacteria.

The velocity field of clusters of galaxies within 100 megaparsecs. II - Northern clusters

NASA Technical Reports Server (NTRS)

Mould, J. R.; Akeson, R. L.; Bothun, G. D.; Han, M.; Huchra, J. P.; Roth, J.; Schommer, R. A.

1993-01-01

Distances and peculiar velocities for galaxies in eight clusters and groups have been determined by means of the near-infrared Tully-Fisher relation. With the possible exception of a group halfway between us and the Hercules Cluster, we observe peculiar velocities of the same order as the measuring errors of about 400 km/s. The present sample is drawn from the northern Galactic hemisphere and delineates a quiet region in the Hubble flow. This contrasts with the large-scale flows seen in the Hydra-Centaurus and Perseus-Pisces regions. We compare the observed peculiar velocities with predictions based upon the gravity field inferred from the IRAS redshift survey. The differences between the observed and predicted peculiar motions are generally small, except near dense structures, where the observed motions exceed the predictions by significant amounts. Kinematic models of the velocity field are also compared with the data. We cannot distinguish between parameterized models with a great attractor or models with a bulk flow.

Efficient generation of low-energy folded states of a model protein

NASA Astrophysics Data System (ADS)

Gordon, Heather L.; Kwan, Wai Kei; Gong, Chunhang; Larrass, Stefan; Rothstein, Stuart M.

2003-01-01

A number of short simulated annealing runs are performed on a highly-frustrated 46-"residue" off-lattice model protein. We perform, in an iterative fashion, a principal component analysis of the 946 nonbonded interbead distances, followed by two varieties of cluster analyses: hierarchical and k-means clustering. We identify several distinct sets of conformations with reasonably consistent cluster membership. Nonbonded distance constraints are derived for each cluster and are employed within a distance geometry approach to generate many new conformations, previously unidentified by the simulated annealing experiments. Subsequent analyses suggest that these new conformations are members of the parent clusters from which they were generated. Furthermore, several novel, previously unobserved structures with low energy were uncovered, augmenting the ensemble of simulated annealing results, and providing a complete distribution of low-energy states. The computational cost of this approach to generating low-energy conformations is small when compared to the expense of further Monte Carlo simulated annealing runs.

Pattern selection and super-patterns in the bounded confidence model

DOE PAGES

Ben-Naim, E.; Scheel, A.

2015-10-26

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes ofmore » the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. Furthermore, the spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.« less

Pattern selection and super-patterns in the bounded confidence model

NASA Astrophysics Data System (ADS)

Ben-Naim, E.; Scheel, A.

2015-10-01

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

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.

Anomaly clustering in hyperspectral images

NASA Astrophysics Data System (ADS)

Doster, Timothy J.; Ross, David S.; Messinger, David W.; Basener, William F.

2009-05-01

The topological anomaly detection algorithm (TAD) differs from other anomaly detection algorithms in that it uses a topological/graph-theoretic model for the image background instead of modeling the image with a Gaussian normal distribution. In the construction of the model, TAD produces a hard threshold separating anomalous pixels from background in the image. We build on this feature of TAD by extending the algorithm so that it gives a measure of the number of anomalous objects, rather than the number of anomalous pixels, in a hyperspectral image. This is done by identifying, and integrating, clusters of anomalous pixels via a graph theoretical method combining spatial and spectral information. The method is applied to a cluttered HyMap image and combines small groups of pixels containing like materials, such as those corresponding to rooftops and cars, into individual clusters. This improves visualization and interpretation of objects.

The galaxy clustering crisis in abundance matching

NASA Astrophysics Data System (ADS)

Campbell, Duncan; van den Bosch, Frank C.; Padmanabhan, Nikhil; Mao, Yao-Yuan; Zentner, Andrew R.; Lange, Johannes U.; Jiang, Fangzhou; Villarreal, Antonio

2018-06-01

Galaxy clustering on small scales is significantly underpredicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, Mpeak. SHAM models based on the peak maximum circular velocity, Vpeak, have had much better success. The primary reason for Mpeak-based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on Vpeak. Despite success in predicting clustering, a simple Vpeak-based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could `save' mass-based SHAM: (1) SHAM models require a significant population of `orphan' galaxies as a result of artificial disruption/merging of sub-haloes in modern high-resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on Mpeak cannot be complete physical models as presented. Either Vpeak truly is a better predictor of stellar mass at z ˜ 0 and it remains to be seen how the correlation between stellar mass and Vpeak comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering.

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Castano, Rebecca; Mann, Tobias; Wold, Barbara

2000-01-01

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Different mechanisms of cluster explosion within a unified smooth particle hydrodynamics Thomas-Fermi approach: Optical and short-wavelength regimes compared

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

Rusek, Marian; Orlowski, Arkadiusz

2005-04-01

The dynamics of small ({<=}55 atoms) argon clusters ionized by an intense femtosecond laser pulse is studied using a time-dependent Thomas-Fermi model. The resulting Bloch-like hydrodynamic equations are solved numerically using the smooth particle hydrodynamics method without the necessity of grid simulations. As follows from recent experiments, absorption of radiation and subsequent ionization of clusters observed in the short-wavelength laser frequency regime (98 nm) differs considerably from that in the optical spectral range (800 nm). Our theoretical approach provides a unified framework for treating these very different frequency regimes and allows for a deeper understanding of the underlying cluster explosionmore » mechanisms. The results of our analysis following from extensive numerical simulations presented in this paper are compared both with experimental findings and with predictions of other theoretical models.« less

Mediator and RNA polymerase II clusters associate in transcription-dependent condensates.

PubMed

Cho, Won-Ki; Spille, Jan-Hendrik; Hecht, Micca; Lee, Choongman; Li, Charles; Grube, Valentin; Cisse, Ibrahim I

2018-06-21

Models of gene control have emerged from genetic and biochemical studies, with limited consideration of the spatial organization and dynamics of key components in living cells. Here we used live cell super-resolution and light sheet imaging to study the organization and dynamics of the Mediator coactivator and RNA polymerase II (Pol II) directly. Mediator and Pol II each form small transient and large stable clusters in living embryonic stem cells. Mediator and Pol II are colocalized in the stable clusters, which associate with chromatin, have properties of phase-separated condensates, and are sensitive to transcriptional inhibitors. We suggest that large clusters of Mediator, recruited by transcription factors at large or clustered enhancer elements, interact with large Pol II clusters in transcriptional condensates in vivo. Copyright © 2018, American Association for the Advancement of Science.

Dynamical structure factor of the J1-J2 Heisenberg model in one dimension: The variational Monte Carlo approach

NASA Astrophysics Data System (ADS)

Ferrari, Francesco; Parola, Alberto; Sorella, Sandro; Becca, Federico

2018-06-01

The dynamical spin structure factor is computed within a variational framework to study the one-dimensional J1-J2 Heisenberg model. Starting from Gutzwiller-projected fermionic wave functions, the low-energy spectrum is constructed from two-spinon excitations. The direct comparison with Lanczos calculations on small clusters demonstrates the excellent description of both gapless and gapped (dimerized) phases, including incommensurate structures for J2/J1>0.5 . Calculations on large clusters show how the intensity evolves when increasing the frustrating ratio and give an unprecedented accurate characterization of the dynamical properties of (nonintegrable) frustrated spin models.

Electronic structure, stability and magnetic properties of small M1-4(M = Fe, Co, Ni) clusters encapsulated inside a (BN)48 cage

NASA Astrophysics Data System (ADS)

Liang, Wenjuan; Jia, Jianfeng; Lv, Jin; Wu, Haishun

2015-02-01

The geometrical structure and magnetic properties of M1-4(M = Fe, Co and Ni) clusters within a (BN)48 cage were calculated at the BPW91/LanL2DZ level. The small M1-4 clusters generally prefer an off-centered position near the hexagonal rings in the (BN)48 cages. The (BN)48 cages can increase the stability of these small magnetic clusters while protecting the magnetic nature of M and M2 clusters.

Scaling and percolation in the small-world network model

NASA Astrophysics Data System (ADS)

Newman, M. E. J.; Watts, D. J.

1999-12-01

In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one nontrivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the crossover from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Padé approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model.

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.

Statistical mechanics of few-particle systems: exact results for two useful models

NASA Astrophysics Data System (ADS)

Miranda, Enrique N.

2017-11-01

The statistical mechanics of small clusters (n ˜ 10-50 elements) of harmonic oscillators and two-level systems is studied exactly, following the microcanonical, canonical and grand canonical formalisms. For clusters with several hundred particles, the results from the three formalisms coincide with those found in the thermodynamic limit. However, for clusters formed by a few tens of elements, the three ensembles yield different results. For a cluster with a few tens of harmonic oscillators, when the heat capacity per oscillator is evaluated within the canonical formalism, it reaches a limit value equal to k B , as in the thermodynamic case, while within the microcanonical formalism the limit value is k B (1-1/n). This difference could be measured experimentally. For a cluster with a few tens of two-level systems, the heat capacity evaluated within the canonical and microcanonical ensembles also presents differences that could be detected experimentally. Both the microcanonical and grand canonical formalism show that the entropy is non-additive for systems this small, while the canonical ensemble reaches the opposite conclusion. These results suggest that the microcanonical ensemble is the most appropriate for dealing with systems with tens of particles.

A detection of wobbling brightest cluster galaxies within massive galaxy clusters

NASA Astrophysics Data System (ADS)

Harvey, David; Courbin, F.; Kneib, J. P.; McCarthy, Ian G.

2017-12-01

A striking signal of dark matter beyond the standard model is the existence of cores in the centre of galaxy clusters. Recent simulations predict that a brightest cluster galaxy (BCG) inside a cored galaxy cluster will exhibit residual wobbling due to previous major mergers, long after the relaxation of the overall cluster. This phenomenon is absent with standard cold dark matter where a cuspy density profile keeps a BCG tightly bound at the centre. We test this hypothesis using cosmological simulations and deep observations of 10 galaxy clusters acting as strong gravitational lenses. Modelling the BCG wobble as a simple harmonic oscillator, we measure the wobble amplitude, Aw, in the BAHAMAS suite of cosmological hydrodynamical simulations, finding an upper limit for the cold dark matter paradigm of Aw < 2 kpc at the 95 per cent confidence limit. We carry out the same test on the data finding a non-zero amplitude of A_w=11.82^{+7.3}_{-3.0} kpc, with the observations dis-favouring Aw = 0 at the 3σ confidence level. This detection of BCG wobbling is evidence for a dark matter core at the heart of galaxy clusters. It also shows that strong lensing models of clusters cannot assume that the BCG is exactly coincident with the large-scale halo. While our small sample of galaxy clusters already indicates a non-zero Aw, with larger surveys, e.g. Euclid, we will be able to not only confirm the effect but also to use it to determine whether or not the wobbling finds its origin in new fundamental physics or astrophysical process.

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

ROSAT HRI images of Abell 85 and Abell 496: Evidence for inhomogeneities in cooling flows

NASA Technical Reports Server (NTRS)

Prestwich, Andrea H.; Guimond, Stephen J.; Luginbuhl, Christian B.; Joy, Marshall

1995-01-01

We present ROSAT high-resolution images of two clusters of galaxies with cooling flows, Abell 496 and Abell 85. In these clusters, X-ray emission on small scales above the general cluster emission is significant at the 3 sigma level. There is no evidence for optical counterparts. If real, the enhancements may be associated with clumps of gas at a lower temperature and higher density than the ambient medium, or hotter, denser gas perhaps compressed by magnetic fields. These observations can be used to test models of how thermal instabilities form and evolve in cooling flows.

ROSAT HRI images of Abell 85 and Abell 496: Evidence for inhomogeneities in cooling flows

NASA Technical Reports Server (NTRS)

Prestwich, Andrea H.; Guimond, Stephen J.; Luginbuhl, Christian; Joy, Marshall

1994-01-01

We present ROSAT HRI images of two clusters of galaxies with cooling flows, Abell 496 and Abell 85. In these clusters, x-ray emission on small scales above the general cluster emission is significant at the 3 sigma level. There is no evidence for optical counterparts. The enhancements may be associated with lumps of gas at a lower temperature and higher density than the ambient medium, or hotter, denser gas perhaps compressed by magnetic fields. These observations can be used to test models of how thermal instabilities form and evolve in cooling flows.

Kinetics of copper growth on graphene revealed by time-resolved small-angle x-ray scattering

NASA Astrophysics Data System (ADS)

Hodas, M.; Siffalovic, P.; Jergel, M.; Pelletta, M.; Halahovets, Y.; Vegso, K.; Kotlar, M.; Majkova, E.

2017-01-01

Metal growth on graphene has many applications. Transition metals are known to favor three-dimensional (3D) cluster growth on graphene. Copper is of particular interest for cost-effective surface-supported catalysis applications and as a contact material in electronics. This paper presents an in situ real-time study of Cu growth kinetics on graphene covering all stages preceding formation of a continuous film performed by laboratory-based grazing-incidence small-angle x-ray scattering (GISAXS) technique. In particular, nucleation and 3D cluster growth, coalescence, and percolation stages were identified. The cluster nucleation saturates after reaching a density of 1012c m-2 at ≈1 monolayer thickness. A Kratky plot and a paracrystal model with cumulative structural disorder were necessary to evaluate properly cluster growth and coalescence, respectively. The power law scaling constants 0.27 ±0.05 and 0.81 ±0.02 of the temporal evolution of Cu cluster size suggest the growth of isolated clusters and dynamic cluster coalescence keeping the cluster shape, respectively. Coalescence and percolation thresholds occur at Cu thicknesses of 2 ±0.4 and 8.8 ±0.7 nm , respectively. This paper demonstrates the potential of laboratory-based in situ GISAXS as a vital diagnostic tool for tailoring a large variety of Cu nanostructures on graphene based on an in situ Cu growth monitoring which is applicable in a broad range of deposition times.

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

DTIC Science & Technology

2012-08-16

threshold of 18% strain, 161 edges were removed. Watts and Strogatz [66] define the small-world network based on the clustering coefficient of the network and...NeuroImage 52: 1059–1069. 65. Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87: 198701. 66. Watts DJ, Strogatz SH

An object-based approach for detecting small brain lesions: application to Virchow-Robin spaces.

PubMed

Descombes, Xavier; Kruggel, Frithjof; Wollny, Gert; Gertz, Hermann Josef

2004-02-01

This paper is concerned with the detection of multiple small brain lesions from magnetic resonance imaging (MRI) data. A model based on the marked point process framework is designed to detect Virchow-Robin spaces (VRSs). These tubular shaped spaces are due to retraction of the brain parenchyma from its supplying arteries. VRS are described by simple geometrical objects that are introduced as small tubular structures. Their radiometric properties are embedded in a data term. A prior model includes interactions describing the clustering property of VRS. A Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC) optimizes the proposed model, obtained by multiplying the prior and the data model. Example results are shown on T1-weighted MRI datasets of elderly subjects.

Vapor condensation onto a non-volatile liquid drop

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

Inci, Levent; Bowles, Richard K., E-mail: richard.bowles@usask.ca

2013-12-07

Molecular dynamics simulations of miscible and partially miscible binary Lennard–Jones mixtures are used to study the dynamics and thermodynamics of vapor condensation onto a non-volatile liquid drop in the canonical ensemble. When the system volume is large, the driving force for condensation is low and only a submonolayer of the solvent is adsorbed onto the liquid drop. A small degree of mixing of the solvent phase into the core of the particles occurs for the miscible system. At smaller volumes, complete film formation is observed and the dynamics of film growth are dominated by cluster-cluster coalescence. Mixing into the coremore » of the droplet is also observed for partially miscible systems below an onset volume suggesting the presence of a solubility transition. We also develop a non-volatile liquid drop model, based on the capillarity approximations, that exhibits a solubility transition between small and large drops for partially miscible mixtures and has a hysteresis loop similar to the one observed in the deliquescence of small soluble salt particles. The properties of the model are compared to our simulation results and the model is used to study the formulation of classical nucleation theory for systems with low free energy barriers.« less

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

Renormalized coupled cluster approaches in the cluster-in-molecule framework: predicting vertical electron binding energies of the anionic water clusters (H2O)(n)(-).

PubMed

Xu, Peng; Gordon, Mark S

2014-09-04

Anionic water clusters are generally considered to be extremely challenging to model using fragmentation approaches due to the diffuse nature of the excess electron distribution. The local correlation coupled cluster (CC) framework cluster-in-molecule (CIM) approach combined with the completely renormalized CR-CC(2,3) method [abbreviated CIM/CR-CC(2,3)] is shown to be a viable alternative for computing the vertical electron binding energies (VEBE). CIM/CR-CC(2,3) with the threshold parameter ζ set to 0.001, as a trade-off between accuracy and computational cost, demonstrates the reliability of predicting the VEBE, with an average percentage error of ∼15% compared to the full ab initio calculation at the same level of theory. The errors are predominantly from the electron correlation energy. The CIM/CR-CC(2,3) approach provides the ease of a black-box type calculation with few threshold parameters to manipulate. The cluster sizes that can be studied by high-level ab initio methods are significantly increased in comparison with full CC calculations. Therefore, the VEBE computed by the CIM/CR-CC(2,3) method can be used as benchmarks for testing model potential approaches in small-to-intermediate-sized water clusters.

Small-scale Conformity of the Virgo Cluster Galaxies

NASA Astrophysics Data System (ADS)

Lee, Hye-Ran; Lee, Joon Hyeop; Jeong, Hyunjin; Park, Byeong-Gon

2016-06-01

We investigate the small-scale conformity in color between bright galaxies and their faint companions in the Virgo Cluster. Cluster member galaxies are spectroscopically determined using the Extended Virgo Cluster Catalog and the Sloan Digital Sky Survey Data Release 12. We find that the luminosity-weighted mean color of faint galaxies depends on the color of adjacent bright galaxy as well as on the cluster-scale environment (gravitational potential index). From this result for the entire area of the Virgo Cluster, it is not distinguishable whether the small-scale conformity is genuine or if it is artificially produced due to cluster-scale variation of galaxy color. To disentangle this degeneracy, we divide the Virgo Cluster area into three sub-areas so that the cluster-scale environmental dependence is minimized: A1 (central), A2 (intermediate), and A3 (outermost). We find conformity in color between bright galaxies and their faint companions (color-color slope significance S ˜ 2.73σ and correlation coefficient {cc}˜ 0.50) in A2, where the cluster-scale environmental dependence is almost negligible. On the other hand, the conformity is not significant or very marginal (S ˜ 1.75σ and {cc}˜ 0.27) in A1. The conformity is not significant either in A3 (S ˜ 1.59σ and {cc}˜ 0.44), but the sample size is too small in this area. These results are consistent with a scenario in which the small-scale conformity in a cluster is a vestige of infallen groups and these groups lose conformity as they come closer to the cluster center.

A Simple ab initio Model for the Hydrated Electron that Matches Experiment

PubMed Central

Kumar, Anil; Walker, Jonathan A.; Bartels, David M.; Sevilla, Michael D.

2015-01-01

Since its discovery over 50 years ago, the “structure” and properties of the hydrated electron has been a subject for wonderment and also fierce debate. In the present work we seriously explore a minimal model for the aqueous electron, consisting of a small water anion cluster embedded in a polarized continuum, using several levels of ab initio calculation and basis set. The minimum energy zero “Kelvin” structure found for any 4-water (or larger) anion cluster, at any post-Hartree-Fock theory level, is very similar to a recently reported embedded-DFT-in-classical-water-MD simulation (UMJ: Uhlig, Marsalek, and Jungwirth, Journal of Physical Chemistry Letters 2012, 3, 3071-5), with four OH bonds oriented toward the maximum charge density in a small central “void”. The minimum calculation with just four water molecules does a remarkably good job of reproducing the resonance Raman properties, the radius of gyration derived from the optical spectrum, the vertical detachment energy, and the hydration free energy. For the first time we also successfully calculate the EPR g-factor and (low temperature ice) hyperfine couplings. The simple tetrahedral anion cluster model conforms very well to experiment, suggesting it does in fact represent the dominant structural motif of the hydrated electron. PMID:26275103

Probing electronic wave functions of sodium-doped clusters: Dyson orbitals, anisotropy parameters, and ionization cross-sections

DOE PAGES

Gunina, Anastasia O.; Krylov, Anna I.

2016-11-14

We apply high-level ab initio methods to describe the electronic structure of small clusters of ammonia and dimethylether (DME) doped with sodium, which provide a model for solvated electrons. We investigate the effect of the solvent and cluster size on the electronic states. We consider both energies and properties, with a focus on the shape of the electronic wave function and the related experimental observables such as photoelectron angular distributions. The central quantity in modeling photoionization experiments is the Dyson orbital, which describes the difference between the initial N-electron and final (N-1)-electron states of a system. Dyson orbitals enter themore » expression of the photoelectron matrix element, which determines total and partial photoionization cross-sections. We compute Dyson orbitals for the Na(NH3)n and Na(DME)m clusters using correlated wave functions (obtained with equation-of-motion coupled-cluster model for electron attachment with single and double substitutions) and compare them with more approximate Hartree-Fock and Kohn-Sham orbitals. As a result, we also analyze the effect of correlation and basis sets on the shapes of Dyson orbitals and the experimental observables.« less

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate.

PubMed

Akter, Asma; Biella, Paolo; Klecka, Jan

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction.

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate

PubMed Central

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction. PMID:29136042

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

NASA Technical Reports Server (NTRS)

Thomas, James (Technical Monitor); Diskin, Boris; Harik, VasylMichael

2004-01-01

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

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.

A broad survey reveals substitution tolerance of residues ligating FeS clusters in [NiFe] hydrogenase

PubMed Central

2014-01-01

Background In order to understand the effects of FeS cluster attachment in [NiFe] hydrogenase, we undertook a study to substitute all 12 amino acid positions normally ligating the three FeS clusters in the hydrogenase small subunit. Using the hydrogenase from Alteromonas macleodii “deep ecotype” as a model, we substituted one of four amino acids (Asp, His, Asn, Gln) at each of the 12 ligating positions because these amino acids are alternative coordinating residues in otherwise conserved-cysteine positions found in a broad survey of NiFe hydrogenase sequences. We also hoped to discover an enzyme with elevated hydrogen evolution activity relative to a previously reported “G1” (H230C/P285C) improved enzyme in which the medial FeS cluster Pro and the distal FeS cluster His were each substituted for Cys. Results Among all the substitutions screened, aspartic acid substitutions were generally well-tolerated, and examination suggests that the observed deficiency in enzyme activity may be largely due to misprocessing of the small subunit of the enzyme. Alignment of hydrogenase sequences from sequence databases revealed many rare substitutions; the five substitutions present in databases that we tested all exhibited measurable hydrogen evolution activity. Select substitutions were purified and tested, supporting the results of the screening assay. Analysis of these results confirms the importance of small subunit processing. Normalizing activity to quantity of mature small subunit, indicative of total enzyme maturation, weakly suggests an improvement over the “G1” enzyme. Conclusions We have comprehensively screened 48 amino acid substitutions of the hydrogenase from A. macleodii “deep ecotype”, to understand non-canonical ligations of amino acids to FeS clusters and to improve hydrogen evolution activity of this class of hydrogenase. Our studies show that non-canonical ligations can be functional and also suggests a new limiting factor in the production of active enzyme. PMID:24934472

Methods in Computational Cosmology

NASA Astrophysics Data System (ADS)

Vakili, Mohammadjavad

State of the inhomogeneous universe and its geometry throughout cosmic history can be studied by measuring the clustering of galaxies and the gravitational lensing of distant faint galaxies. Lensing and clustering measurements from large datasets provided by modern galaxy surveys will forever shape our understanding of the how the universe expands and how the structures grow. Interpretation of these rich datasets requires careful characterization of uncertainties at different stages of data analysis: estimation of the signal, estimation of the signal uncertainties, model predictions, and connecting the model to the signal through probabilistic means. In this thesis, we attempt to address some aspects of these challenges. The first step in cosmological weak lensing analyses is accurate estimation of the distortion of the light profiles of galaxies by large scale structure. These small distortions, known as the cosmic shear signal, are dominated by extra distortions due to telescope optics and atmosphere (in the case of ground-based imaging). This effect is captured by a kernel known as the Point Spread Function (PSF) that needs to be fully estimated and corrected for. We address two challenges a head of accurate PSF modeling for weak lensing studies. The first challenge is finding the centers of point sources that are used for empirical estimation of the PSF. We show that the approximate methods for centroiding stars in wide surveys are able to optimally saturate the information content that is retrievable from astronomical images in the presence of noise. The fist step in weak lensing studies is estimating the shear signal by accurately measuring the shapes of galaxies. Galaxy shape measurement involves modeling the light profile of galaxies convolved with the light profile of the PSF. Detectors of many space-based telescopes such as the Hubble Space Telescope (HST) sample the PSF with low resolution. Reliable weak lensing analysis of galaxies observed by the HST camera requires knowledge of the PSF at a resolution higher than the pixel resolution of HST. This PSF is called the super-resolution PSF. In particular, we present a forward model of the point sources imaged through filters of the HST WFC3 IR channel. We show that this forward model can accurately estimate the super-resolution PSF. We also introduce a noise model that permits us to robustly analyze the HST WFC3 IR observations of the crowded fields. Then we try to address one of the theoretical uncertainties in modeling of galaxy clustering on small scales. Study of small scale clustering requires assuming a halo model. Clustering of halos has been shown to depend on halo properties beyond mass such as halo concentration, a phenomenon referred to as assembly bias. Standard large-scale structure studies with halo occupation distribution (HOD) assume that halo mass alone is sufficient to characterize the connection between galaxies and halos. However, assembly bias could cause the modeling of galaxy clustering to face systematic effects if the expected number of galaxies in halos is correlated with other halo properties. Using high resolution N-body simulations and the clustering measurements of Sloan Digital Sky Survey (SDSS) DR7 main galaxy sample, we show that modeling of galaxy clustering can slightly improve if we allow the HOD model to depend on halo properties beyond mass. One of the key ingredients in precise parameter inference using galaxy clustering is accurate estimation of the error covariance matrix of clustering measurements. This requires generation of many independent galaxy mock catalogs that accurately describe the statistical distribution of galaxies in a wide range of physical scales. We present a fast and accurate method based on low-resolution N-body simulations and an empirical bias model for generating mock catalogs. We use fast particle mesh gravity solvers for generation of dark matter density field and we use Markov Chain Monti Carlo (MCMC) to estimate the bias model that connects dark matter to galaxies. We show that this approach enables the fast generation of mock catalogs that recover clustering at a percent-level accuracy down to quasi-nonlinear scales. Cosmological datasets are interpreted by specifying likelihood functions that are often assumed to be multivariate Gaussian. Likelihood free approaches such as Approximate Bayesian Computation (ABC) can bypass this assumption by introducing a generative forward model of the data and a distance metric for quantifying the closeness of the data and the model. We present the first application of ABC in large scale structure for constraining the connections between galaxies and dark matter halos. We present an implementation of ABC equipped with Population Monte Carlo and a generative forward model of the data that incorporates sample variance and systematic uncertainties. (Abstract shortened by ProQuest.).

Self-organized Criticality in Hierarchical Brain Network

NASA Astrophysics Data System (ADS)

Yang, Qiu-Ying; Zhang, Ying-Yue; Chen, Tian-Lun

2008-11-01

It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

Architecture of marine food webs: To be or not be a 'small-world'.

PubMed

Marina, Tomás Ignacio; Saravia, Leonardo A; Cordone, Georgina; Salinas, Vanesa; Doyle, Santiago R; Momo, Fernando R

2018-01-01

The search for general properties in network structure has been a central issue for food web studies in recent years. One such property is the small-world topology that combines a high clustering and a small distance between nodes of the network. This property may increase food web resilience but make them more sensitive to the extinction of connected species. Food web theory has been developed principally from freshwater and terrestrial ecosystems, largely omitting marine habitats. If theory needs to be modified to accommodate observations from marine ecosystems, based on major differences in several topological characteristics is still on debate. Here we investigated if the small-world topology is a common structural pattern in marine food webs. We developed a novel, simple and statistically rigorous method to examine the largest set of complex marine food webs to date. More than half of the analyzed marine networks exhibited a similar or lower characteristic path length than the random expectation, whereas 39% of the webs presented a significantly higher clustering than its random counterpart. Our method proved that 5 out of 28 networks fulfilled both features of the small-world topology: short path length and high clustering. This work represents the first rigorous analysis of the small-world topology and its associated features in high-quality marine networks. We conclude that such topology is a structural pattern that is not maximized in marine food webs; thus it is probably not an effective model to study robustness, stability and feasibility of marine ecosystems.

Estimation of Complex Generalized Linear Mixed Models for Measurement and Growth

ERIC Educational Resources Information Center

Jeon, Minjeong

2012-01-01

Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…

Optical properties of hybrid spherical nanoclusters containing quantum emitters and metallic nanoparticles

NASA Astrophysics Data System (ADS)

Yannopapas, V.; Paspalakis, E.

2018-05-01

We study theoretically the optical response of a hybrid spherical cluster containing quantum emitters and metallic nanoparticles. The quantum emitters are modeled as two-level quantum systems whose dielectric function is obtained via a density matrix approach wherein the modified spontaneous emission decay rate at the position of each quantum emitter is calculated via the electromagnetic Green's tensor. The problem of light scattering off the hybrid cluster is solved by employing the coupled-dipole method. We find, in particular, that the presence of the quantum emitters in the cluster, even in small fractions, can significantly alter the absorption and extinction spectra of the sole cluster of the metallic nanoparticles, where the corresponding electromagnetic modes can have a weak plexcitonic character under suitable conditions.

Small area clustering of under-five children's mortality and associated factors using geo-additive Bayesian discrete-time survival model in Kersa HDSS, Ethiopia.

PubMed

Dedefo, Melkamu; Oljira, Lemessa; Assefa, Nega

2016-02-01

Child mortality reflects a country's level of socio-economic development and quality of life. In Ethiopia, limited studies were conducted on under-five mortality and almost none of them tried to identify the spatial effect on mortality. Thus, this study explored the small area clustering of under-five mortality and associated factors in Kersa HDSS, Eastern Ethiopia. The study population included all children under the age of five years during the time September, 2008-august 31, 2012 which are registered in Kersa Health and Demographic Surveillance System (Kersa HDSS). A flexible Bayesian geo-additive discrete-time survival mixed model was used. Some of the factors that are significantly associated with under-five mortality, with posterior odds ratio and 95% credible intervals, are maternal educational status 1.31(1.13,-1.49), place of delivery 1.016(1.013-1.12), no of live birth at a delivery 0.35(0.23,1.83), low household wealth index 1.26(1.10 1.43) middle level household wealth index 0.95 (0.84 1.07) pre-term duration of pregnancy 1.95(1.27,2.91), post-term duration of pregnancy 0.74(0.60,0.93) and antenatal visit 1.19(1.06, 1.35). Variation was noted in the risk of under-five mortality by the selected small administrative regions (kebeles). This study reveals geographic patterns in rates of under-five mortality in those selected small administrative regions and shows some important determinants of under-five mortality. More importantly, we observed clustering of under-five mortality, which indicates the importance of spatial effects and presentation of this clustering through maps that facilitates visuality and highlights differentials across geographical areas that would, otherwise, be overlooked in traditional data-analytic methods. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantifying substructures in Hubble Frontier Field clusters: comparison with ΛCDM simulations

DOE PAGES

Mohammed, Irshad; Saha, Prasenjit; Williams, Liliya L. R.; ...

2016-04-13

The Hubble Frontier Fields (HFF) are six clusters of galaxies, all showing indications of recent mergers, which have recently been observed for lensed images. As such they are the natural laboratories to study the merging history of galaxy clusters. In this work, we explore the 2D power spectrum of the mass distributionmore » $$P_{\\rm M}(k)$$ as a measure of substructure. We compare $$P_{\\rm M}(k)$$ of these clusters (obtained using strong gravitational lensing) to that of $$\\Lambda$$CDM simulated clusters of similar mass. In order to compute lensing $$P_{\\rm M}(k)$$, we produced free-form lensing mass reconstructions of HFF clusters, without any light traces mass (LTM) assumption. Moreover, the inferred power at small scales tends to be larger if (i)~the cluster is at lower redshift, and/or (ii)~there are deeper observations and hence more lensed images. In contrast, lens reconstructions assuming LTM show higher power at small scales even with fewer lensed images; it appears the small scale power in the LTM reconstructions is dominated by light information, rather than the lensing data. The average lensing derived $$P_{\\rm M}(k)$$ shows lower power at small scales as compared to that of simulated clusters at redshift zero, both dark-matter only and hydrodynamical. The possible reasons are: (i)~the available strong lensing data are limited in their effective spatial resolution on the mass distribution, (ii)~HFF clusters have yet to build the small scale power they would have at $$z\\sim 0$$, or (iii)~simulations are somehow overestimating the small scale power.« less

Correspondence between ion-cluster and bulk thermodynamics: on the validity of the cluster pair approximation

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

Vlcek, Lukas; Chialvo, Ariel; Simonson, J Michael

2013-01-01

Molecular models and experimental estimates based on the cluster pair approximation (CPA) provide inconsistent predictions of absolute single-ion hydration properties. To understand the origin of this discrepancy we used molecular simulations to study the transition between hydration of alkali metal and halide ions in small aqueous clusters and bulk water. The results demonstrate that the assumptions underlying the CPA are not generally valid as a result of a significant shift in the ion hydration free energies (~15 kJ/mol) and enthalpies (~47 kJ/mol) in the intermediate range of cluster sizes. When this effect is accounted for, the systematic differences between modelsmore » and experimental predictions disappear, and the value of absolute proton hydration enthalpy based on the CPA gets in closer agreement with other estimates.« less

Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks

NASA Astrophysics Data System (ADS)

Forman, Yakir; Cameron, Maria

2017-07-01

We model an isothermal aggregation process of particles/atoms interacting according to the Lennard-Jones pair potential by mapping the energy landscapes of each cluster size N onto stochastic networks, computing transition probabilities from the network for an N-particle cluster to the one for N+1, and connecting these networks into a single joint network. The attachment rate is a control parameter. The resulting network representing the aggregation of up to 14 particles contains 6427 vertices. It is not only time-irreversible but also reducible. To analyze its transient dynamics, we introduce the sequence of the expected initial and pre-attachment distributions and compute them for a wide range of attachment rates and three values of temperature. As a result, we find the configurations most likely to be observed in the process of aggregation for each cluster size. We examine the attachment process and conduct a structural analysis of the sets of local energy minima for every cluster size. We show that both processes taking place in the network, attachment and relaxation, lead to the dominance of icosahedral packing in small (up to 14 atom) clusters.

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.

Fierz Convergence Criterion: A Controlled Approach to Strongly Interacting Systems with Small Embedded Clusters.

PubMed

Ayral, Thomas; Vučičević, Jaksa; Parcollet, Olivier

2017-10-20

We present an embedded-cluster method, based on the triply irreducible local expansion formalism. It turns the Fierz ambiguity, inherent to approaches based on a bosonic decoupling of local fermionic interactions, into a convergence criterion. It is based on the approximation of the three-leg vertex by a coarse-grained vertex computed from a self-consistently determined cluster impurity model. The computed self-energies are, by construction, continuous functions of momentum. We show that, in three interaction and doping regimes of the two-dimensional Hubbard model, self-energies obtained with clusters of size four only are very close to numerically exact benchmark results. We show that the Fierz parameter, which parametrizes the freedom in the Hubbard-Stratonovich decoupling, can be used as a quality control parameter. By contrast, the GW+extended dynamical mean field theory approximation with four cluster sites is shown to yield good results only in the weak-coupling regime and for a particular decoupling. Finally, we show that the vertex has spatially nonlocal components only at low Matsubara frequencies.

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

Activity-induced clustering in model dumbbell swimmers: the role of hydrodynamic interactions.

PubMed

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

Activity-induced clustering in model dumbbell swimmers: The role of hydrodynamic interactions

NASA Astrophysics Data System (ADS)

Furukawa, Akira; Marenduzzo, Davide; Cates, Michael E.

2014-08-01

Using a fluid-particle dynamics approach, we numerically study the effects of hydrodynamic interactions on the collective dynamics of active suspensions within a simple model for bacterial motility: each microorganism is modeled as a stroke-averaged dumbbell swimmer with prescribed dipolar force pairs. Using both simulations and qualitative arguments, we show that, when the separation between swimmers is comparable to their size, the swimmers' motions are strongly affected by activity-induced hydrodynamic forces. To further understand these effects, we investigate semidilute suspensions of swimmers in the presence of thermal fluctuations. A direct comparison between simulations with and without hydrodynamic interactions shows these to enhance the dynamic clustering at a relatively small volume fraction; with our chosen model the key ingredient for this clustering behavior is hydrodynamic trapping of one swimmer by another, induced by the active forces. Furthermore, the density dependence of the motility (of both the translational and rotational motions) exhibits distinctly different behaviors with and without hydrodynamic interactions; we argue that this is linked to the clustering tendency. Our study illustrates the fact that hydrodynamic interactions not only affect kinetic pathways in active suspensions, but also cause major changes in their steady state properties.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

GPI-anchored proteins are confined in subdiffraction clusters at the apical surface of polarized epithelial cells

PubMed Central

Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe

2017-01-01

Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. PMID:29046391

Energetics of charged metal clusters containing vacancies

NASA Astrophysics Data System (ADS)

Pogosov, Valentin V.; Reva, Vitalii I.

2018-01-01

We study theoretically large metal clusters containing vacancies. We propose an approach, which combines the Kohn-Sham results for monovacancy in a bulk of metal and analytical expansions in small parameters cv (relative concentration of vacancies) and RN,v -1, RN ,v being cluster radii. We obtain expressions of the ionization potential and electron affinity in the form of corrections to electron work function, which require only the characteristics of 3D defect-free metal. The Kohn-Sham method is used to calculate the electron profiles, ionization potential, electron affinity, electrical capacitance; dissociation, cohesion, and monovacancy-formation energies of the small perfect clusters NaN, MgN, AlN (N ≤ 270) and the clusters containing a monovacancy (N ≥ 12) in the stabilized-jellium model. The quantum-sized dependences for monovacancy-formation energies are calculated for the Schottky scenario and the "bubble blowing" scenario, and their asymptotic behavior is also determined. It is shown that the asymptotical behaviors of size dependences for these two mechanisms differ from each other and weakly depend on the number of atoms in the cluster. The contribution of monovacancy to energetics of charged clusters and the size dependences of their characteristics and asymptotics are discussed. It is shown that the difference between the characteristics for the neutral and charged clusters is entirely determined by size dependences of ionization potential and electron affinity. Obtained analytical dependences may be useful for the analysis of the results of photoionization experiments and for the estimation of the size dependences of the vacancy concentration including the vicinity of the melting point.

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.

Evolution of Carbon Clusters in the Detonation Products of the Triaminotrinitrobenzene (TATB)-Based Explosive PBX 9502

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

Watkins, Erik B.; Velizhanin, Kirill A.; Dattelbaum, Dana M.

Here, the detonation of carbon-rich high explosives yields solid carbon as a major constituent of the product mixture and, depending on the thermodynamic conditions behind the shock front, a variety of carbon allotropes and morphologies may form and evolve. We applied time-resolved small angle x-ray scattering (TR-SAXS) to investigate the dynamics of carbon clustering during detonation of PBX 9502, an explosive composed of triaminotrinitrobenzene (TATB) and 5 wt% fluoropolymer binder. Solid carbon formation was probed from 0.1 to 2.0 μs behind the detonation front and revealed rapid carbon cluster growth which reached a maximum after ~200 ns. The late-time carbonmore » clusters had a radius of gyration of 3.3 nm which is consistent with 8.4 nm diameter spherical particles and matched particle sizes of recovered products. Simulations using a clustering kinetics model were found to be in good agreement with the experimental measurements of cluster growth when invoking a freeze-out temperature, and temporal shift associated with the initial precipitation of solid carbon. Product densities from reactive flow models were compared to the electron density contrast obtained from TR-SAXS and used to approximate the carbon cluster composition as a mixture of 20% highly ordered (diamond-like) and 80% disordered carbon forms, which will inform future product equation of state models for solid carbon in PBX 9502 detonation product mixtures.« less

Evolution of Carbon Clusters in the Detonation Products of the Triaminotrinitrobenzene (TATB)-Based Explosive PBX 9502

DOE PAGES

Watkins, Erik B.; Velizhanin, Kirill A.; Dattelbaum, Dana M.; ...

2017-08-15

Here, the detonation of carbon-rich high explosives yields solid carbon as a major constituent of the product mixture and, depending on the thermodynamic conditions behind the shock front, a variety of carbon allotropes and morphologies may form and evolve. We applied time-resolved small angle x-ray scattering (TR-SAXS) to investigate the dynamics of carbon clustering during detonation of PBX 9502, an explosive composed of triaminotrinitrobenzene (TATB) and 5 wt% fluoropolymer binder. Solid carbon formation was probed from 0.1 to 2.0 μs behind the detonation front and revealed rapid carbon cluster growth which reached a maximum after ~200 ns. The late-time carbonmore » clusters had a radius of gyration of 3.3 nm which is consistent with 8.4 nm diameter spherical particles and matched particle sizes of recovered products. Simulations using a clustering kinetics model were found to be in good agreement with the experimental measurements of cluster growth when invoking a freeze-out temperature, and temporal shift associated with the initial precipitation of solid carbon. Product densities from reactive flow models were compared to the electron density contrast obtained from TR-SAXS and used to approximate the carbon cluster composition as a mixture of 20% highly ordered (diamond-like) and 80% disordered carbon forms, which will inform future product equation of state models for solid carbon in PBX 9502 detonation product mixtures.« less

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

The Halo Boundary of Galaxy Clusters in the SDSS

NASA Astrophysics Data System (ADS)

Baxter, Eric; Chang, Chihway; Jain, Bhuvnesh; Adhikari, Susmita; Dalal, Neal; Kravtsov, Andrey; More, Surhud; Rozo, Eduardo; Rykoff, Eli; Sheth, Ravi K.

2017-05-01

Analytical models and simulations predict a rapid decline in the halo density profile associated with the transition from the “infalling” regime outside the halo to the “collapsed” regime within the halo. Using data from SDSS, we explore evidence for such a feature in the density profiles of galaxy clusters using several different approaches. We first estimate the steepening of the outer galaxy density profile around clusters, finding evidence for truncation of the halo profile. Next, we measure the galaxy density profile around clusters using two sets of galaxies selected on color. We find evidence of an abrupt change in galaxy colors that coincides with the location of the steepening of the density profile. Since galaxies that have completed orbits within the cluster are more likely to be quenched of star formation and thus appear redder, this abrupt change in galaxy color can be associated with the transition from single-stream to multi-stream regimes. We also use a standard model comparison approach to measure evidence for a “splashback”-like feature, but find that this approach is very sensitive to modeling assumptions. Finally, we perform measurements using an independent cluster catalog to test for potential systematic errors associated with cluster selection. We identify several avenues for future work: improved understanding of the small-scale galaxy profile, lensing measurements, identification of proxies for the halo accretion rate, and other tests. With upcoming data from the DES, KiDS, and HSC surveys, we can expect significant improvements in the study of halo boundaries.

The Clusters-in-a-Liquid Approach for Solvation: New Insights from the Conformer Specific Gas Phase Spectroscopy and Vibrational Optical Activity Spectroscopy

PubMed Central

Perera, Angelo S.; Thomas, Javix; Poopari, Mohammad R.; Xu, Yunjie

2016-01-01

Vibrational optical activity spectroscopies, namely vibrational circular dichroism (VCD) and Raman optical activity (ROA), have been emerged in the past decade as powerful spectroscopic tools for stereochemical information of a wide range of chiral compounds in solution directly. More recently, their applications in unveiling solvent effects, especially those associated with water solvent, have been explored. In this review article, we first select a few examples to demonstrate the unique sensitivity of VCD spectral signatures to both bulk solvent effects and explicit hydrogen-bonding interactions in solution. Second, we discuss the induced solvent chirality, or chiral transfer, VCD spectral features observed in the water bending band region in detail. From these chirality transfer spectral data, the related conformer specific gas phase spectroscopic studies of small chiral hydration clusters, and the associated matrix isolation VCD experiments of hydrogen-bonded complexes in cold rare gas matrices, a general picture of solvation in aqueous solution emerges. In such an aqueous solution, some small chiral hydration clusters, rather than the chiral solutes themselves, are the dominant species and are the ones that contribute mainly to the experimentally observed VCD features. We then review a series of VCD studies of amino acids and their derivatives in aqueous solution under different pHs to emphasize the importance of the inclusion of the bulk solvent effects. These experimental data and the associated theoretical analyses are the foundation for the proposed “clusters-in-a-liquid” approach to account for solvent effects effectively. We present several approaches to identify and build such representative chiral hydration clusters. Recent studies which applied molecular dynamics simulations and the subsequent snapshot averaging approach to generate the ROA, VCD, electronic CD, and optical rotatory dispersion spectra are also reviewed. Challenges associated with the molecular dynamics snapshot approach are discussed and the successes of the seemingly random “ad hoc explicit solvation” reported before are also explained. To further test and improve the “clusters-in-a-liquid” model in practice, future work in terms of conformer specific gas phase spectroscopy of sequential solvation of a chiral solute, matrix isolation VCD measurements of small chiral hydration clusters, and more sophisticated models for the bulk solvent effects would be highly valuable. PMID:26942177

Galaxy clustering dependence on the [O II] emission line luminosity in the local Universe

NASA Astrophysics Data System (ADS)

Favole, Ginevra; Rodríguez-Torres, Sergio A.; Comparat, Johan; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Montero-Dorta, Antonio D.

2017-11-01

We study the galaxy clustering dependence on the [O II] emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift z ∼ 0.1. We select volume-limited samples of galaxies with different [O II] luminosity thresholds and measure their projected, monopole and quadrupole two-point correlation functions. We model these observations using the 1 h-1 Gpc MultiDark-Planck cosmological simulation and generate light cones with the SUrvey GenerAtoR algorithm. To interpret our results, we adopt a modified (Sub)Halo Abundance Matching scheme, accounting for the stellar mass incompleteness of the emission line galaxies. The satellite fraction constitutes an extra parameter in this model and allows to optimize the clustering fit on both small and intermediate scales (i.e. rp ≲ 30 h-1 Mpc), with no need of any velocity bias correction. We find that, in the local Universe, the [O II] luminosity correlates with all the clustering statistics explored and with the galaxy bias. This latter quantity correlates more strongly with the SDSS r-band magnitude than [O II] luminosity. In conclusion, we propose a straightforward method to produce reliable clustering models, entirely built on the simulation products, which provides robust predictions of the typical ELG host halo masses and satellite fraction values. The SDSS galaxy data, MultiDark mock catalogues and clustering results are made publicly available.

The Structure of the Young Star Cluster NGC 6231. II. Structure, Formation, and Fate

NASA Astrophysics Data System (ADS)

Kuhn, Michael A.; Getman, Konstantin V.; Feigelson, Eric D.; Sills, Alison; Gromadzki, Mariusz; Medina, Nicolás; Borissova, Jordanka; Kurtev, Radostin

2017-12-01

The young cluster NGC 6231 (stellar ages ˜2-7 Myr) is observed shortly after star formation activity has ceased. Using the catalog of 2148 probable cluster members obtained from Chandra, VVV, and optical surveys (Paper I), we examine the cluster’s spatial structure and dynamical state. The spatial distribution of stars is remarkably well fit by an isothermal sphere with moderate elongation, while other commonly used models like Plummer spheres, multivariate normal distributions, or power-law models are poor fits. The cluster has a core radius of 1.2 ± 0.1 pc and a central density of ˜200 stars pc-3. The distribution of stars is mildly mass segregated. However, there is no radial stratification of the stars by age. Although most of the stars belong to a single cluster, a small subcluster of stars is found superimposed on the main cluster, and there are clumpy non-isotropic distributions of stars outside ˜4 core radii. When the size, mass, and age of NGC 6231 are compared to other young star clusters and subclusters in nearby active star-forming regions, it lies at the high-mass end of the distribution but along the same trend line. This could result from similar formation processes, possibly hierarchical cluster assembly. We argue that NGC 6231 has expanded from its initial size but that it remains gravitationally bound.

Photoabsorption spectra of small HeN+ clusters (N = 3, 4, 10). A quantum Monte Carlo modeling

NASA Astrophysics Data System (ADS)

Ćosić, Rajko; Karlický, František; Kalus, René

2018-05-01

Photoabsorption cross-sections have been calculated for HeN+ clusters of selected sizes (N = 3, 4, 10) over a broad range of photon energies (Ephot = 2 - 14 eV) and compared with available experimental data. Semiempirical electronic Hamiltonians derived from the diatomics-in-molecules approach have been used for electronic structure calculations and a quantum, path-integral Monte Carlo method has been employed to model the delocalization of helium nuclei. While a quantitative agreement has been achieved between the theory and experiment for He3+ and He4+, only qualitative correspondence is seen for He10+ .

Growth of single-layer boron nitride dome-shaped nanostructures catalysed by iron clusters.

PubMed

Torre, A La; Åhlgren, E H; Fay, M W; Ben Romdhane, F; Skowron, S T; Parmenter, C; Davies, A J; Jouhannaud, J; Pourroy, G; Khlobystov, A N; Brown, P D; Besley, E; Banhart, F

2016-08-11

We report on the growth and formation of single-layer boron nitride dome-shaped nanostructures mediated by small iron clusters located on flakes of hexagonal boron nitride. The nanostructures were synthesized in situ at high temperature inside a transmission electron microscope while the e-beam was blanked. The formation process, typically originating at defective step-edges on the boron nitride support, was investigated using a combination of transmission electron microscopy, electron energy loss spectroscopy and computational modelling. Computational modelling showed that the domes exhibit a nanotube-like structure with flat circular caps and that their stability was comparable to that of a single boron nitride layer.

Effect of sharp maximum in ion diffusivity for liquid xenon

NASA Astrophysics Data System (ADS)

Lankin, A. V.; Orekhov, M. A.

2016-11-01

Ion diffusion in a liquid usually could be treated as a movement of an ion cluster in a viscous media. For small ions this leads to a special feature: diffusion coefficient is either independent of the ion size or increases with it. We find a different behavior for small ions in liquid xenon. Calculation of the dependence of an ion diffusion coefficient in liquid xenon on the ion size is carried out. Classical molecular dynamics method is applied. Calculated dependence of the ion diffusion coefficient on its radius has sharp maximums at the ion radiuses 1.75 and 2 Å. Every maximum is placed between two regions with different stable ion cluster configurations. This leads to the instability of these configurations in a small region between them. Consequently ion with radius near 1.75 or 2 Å could jump from one configuration to another. This increases the speed of the diffusion. A simple qualitative model for this effect is suggested. The decomposition of the ion movement into continuous and jump diffusion shows that continuous part of the diffusion is the same as for the ion cluster in the stable region.

Balance functions in coalescence model

NASA Astrophysics Data System (ADS)

Bialas, A.

2004-01-01

It is shown that the quark-antiquark coalescence mechanism for pion production allows to explain the small pseudorapidity width of the balance function observed for central collisions of heavy ions, provided effects of the finite acceptance region and of the transverse flow are taken into account. In contrast, the standard hadronic cluster model is not compatible with this data.

Generic features of the primary relaxation in glass-forming materials (Review Article)

NASA Astrophysics Data System (ADS)

Kokshenev, Valery B.

2017-08-01

We discuss structural relaxation in molecular and polymeric supercooled liquids, metallic alloys and orientational glass crystals. The study stresses especially the relationships between observables raised from underlying constraints imposed on degrees of freedom of vitrification systems. A self-consistent parametrization of the α-timescale on macroscopic level results in the material-and-model independent universal equation, relating three fundamental temperatures, characteristic of the primary relaxation, that is numerically proven in all studied glass formers. During the primary relaxation, the corresponding small and large mesoscopic clusters modify their size and structure in a self-similar way, regardless of underlying microscopic realizations. We show that cluster-shape similarity, instead of cluster-size fictive divergence, gives rise to universal features observed in primary relaxation. In all glass formers with structural disorder, including orientational-glass materials (with the exception of plastic crystals), structural relaxation is shown to be driven by local random fields. Within the dynamic stochastic approach, the universal subdiffusive dynamics corresponds to random walks on small and large fractals.

What drives the formation of massive stars and clusters?

NASA Astrophysics Data System (ADS)

Ochsendorf, Bram; Meixner, Margaret; Roman-Duval, Julia; Evans, Neal J., II; Rahman, Mubdi; Zinnecker, Hans; Nayak, Omnarayani; Bally, John; Jones, Olivia C.; Indebetouw, Remy

2018-01-01

Galaxy-wide surveys allow to study star formation in unprecedented ways. In this talk, I will discuss our analysis of the Large Magellanic Cloud (LMC) and the Milky Way, and illustrate how studying both the large and small scale structure of galaxies are critical in addressing the question: what drives the formation of massive stars and clusters?I will show that ‘turbulence-regulated’ star formation models do not reproduce massive star formation properties of GMCs in the LMC and Milky Way: this suggests that theory currently does not capture the full complexity of star formation on small scales. I will also report on the discovery of a massive star forming complex in the LMC, which in many ways manifests itself as an embedded twin of 30 Doradus: this may shed light on the formation of R136 and 'Super Star Clusters' in general. Finally, I will highlight what we can expect in the next years in the field of star formation with large-scale sky surveys, ALMA, and our JWST-GTO program.

Ab Initio Study of KCl and AgCl Clusters.

NASA Astrophysics Data System (ADS)

McKeough, James; Hira, Ajit; Cathey, Tommy; Valdez, Alexandra

This paper presents a theoretical study of molecular clusters that examines the chemical and physical properties of small KnCln and AgnCln clusters (n = 2 - 24). Due to combinations of attractive and repulsive long-range forces, such clusters exhibit structural and dynamical behavior different from that of homogeneous clusters. The potentially important role of these molecular species in biochemical and medicinal processes is widely known. This work applies the hybrid ab initio methods to derive the different alkali-halide (MnHn) geometries. Of particular interest is the competition between hexagonal ring geometries and rock salt structures. Electronic energies, rotational constants, dipole moments, and vibrational frequencies for these geometries are calculated. Magic numbers for cluster stability are identified and are related to the property of cluster compactness. Mapping of the singlet, triplet, and quintet, potential energy surfaces is performed. Calculations were performed to examine the interactions of these clusters with some atoms and molecules of biological interest, including O, O2, and Fe. Potential design of new medicinal drugs is explored. We will also investigate model and material dependence of the results. AMP program of the National Science Foundation.

Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data.

PubMed

Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

2013-01-05

: A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.

A Lagrangian model of Copepod dynamics in turbulent flows

NASA Astrophysics Data System (ADS)

Ardeshiri, Hamidreza; Benkeddad, Ibtissem; Schmitt, Francois G.; Souissi, Sami; Toschi, Federico; Calzavarini, Enrico

2016-04-01

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator such as fish larave, or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behaviour on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are used to define and tune a Lagrangian Copepod (LC) model. The model is further employed to simulate the behaviour of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in turbulence. Second, we quantify the clustering of LC, via the fractal dimension D2. We show that D2 can be as low as 2.3, corresponding to local sheetlike aggregates, and that it critically depends on the shear-rate sensitivity of the proposed LC model. We further investigate the effect of jump intensity, jump orientation and geometrical aspect ratio of the copepods on the small-scale spatial distribution. Possible ecological implications of the observed clustering on encounter rates and mating success are discussed.

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

NASA Astrophysics Data System (ADS)

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

2010-11-01

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

Equilibrium stellar systems with spindle singularities

NASA Technical Reports Server (NTRS)

Shapiro, Stuart L.; Teukolsky, Saul A.

1992-01-01

Equilibrium sequences of axisymmetric Newtonian clusters that tend toward singular states are constructed. The distribution functions are chosen to be of the form f = f(E, Jz). The numerical method then determines the density and gravitational potential self-consistently to satisfy Poisson's equation. For the prolate models, spindle singularities arise from the depletion of angular momentum near the symmetry axis. While the resulting density enhancement is confined to the region near the axis, the influence of the spindle extends much further out through its tidal gravitational field. Centrally condensed prolate clusters may contain strong-field regions even though the spindle mass is small and the mean cluster eccentricity is not extreme. While the calculations performed here are entirely Newtonian, the issue of singularities is an important topic in general relativity. Equilibrium solutions for relativistic star clusters can provide a testing ground for exploring this issue. The methods used in this paper for building nonspherical clusters can be extended to relativistic systems.

Infrared Spectroscopy of Naphthalene Aggregation and Cluster Formation in Argon Matrices

NASA Technical Reports Server (NTRS)

Roser, J. E.; Allamondola, L. J.

2011-01-01

Fourier-transform mid-infrared absorption spectra of mixed argon/naphthalene matrices at 5 K are shown with ratios of argon-to-naphthalene that vary from 1000 to 0. These spectra show the changes as naphthalene clustering and aggregation occurs, with moderate spectral shifts affecting the C-H vibrational modes and relatively small or no shifts to the C-C and C-C-C vibrational modes. The possible contribution of homogeneous naphthalene clusters to the interstellar unidentified infrared bands is discussed. The contribution of polycyclic aromatic hydrocarbon (PAH) clusters to the 7.7 micron emission plateau and the blue shading of the 12.7 micron emission band are identified as promising candidates for future research. In addition, since PAH clusters are model components of Jupiter and Titan's atmospheres, the information presented here may also be applicable to the spectroscopy of these objects.

Pattern Selection and Super-Patterns in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Ben-Naim, Eli; Scheel, Arnd

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Regularity of beating of small clusters of embryonic chick ventricular heart-cells: experiment vs. stochastic single-channel population model

NASA Astrophysics Data System (ADS)

Krogh-Madsen, Trine; Kold Taylor, Louise; Skriver, Anne D.; Schaffer, Peter; Guevara, Michael R.

2017-09-01

The transmembrane potential is recorded from small isopotential clusters of 2-4 embryonic chick ventricular cells spontaneously generating action potentials. We analyze the cycle-to-cycle fluctuations in the time between successive action potentials (the interbeat interval or IBI). We also convert an existing model of electrical activity in the cluster, which is formulated as a Hodgkin-Huxley-like deterministic system of nonlinear ordinary differential equations describing five individual ionic currents, into a stochastic model consisting of a population of ˜20 000 independently and randomly gating ionic channels, with the randomness being set by a real physical stochastic process (radio static). This stochastic model, implemented using the Clay-DeFelice algorithm, reproduces the fluctuations seen experimentally: e.g., the coefficient of variation (standard deviation/mean) of IBI is 4.3% in the model vs. the 3.9% average value of the 17 clusters studied. The model also replicates all but one of several other quantitative measures of the experimental results, including the power spectrum and correlation integral of the voltage, as well as the histogram, Poincaré plot, serial correlation coefficients, power spectrum, detrended fluctuation analysis, approximate entropy, and sample entropy of IBI. The channel noise from one particular ionic current (IKs), which has channel kinetics that are relatively slow compared to that of the other currents, makes the major contribution to the fluctuations in IBI. Reproduction of the experimental coefficient of variation of IBI by adding a Gaussian white noise-current into the deterministic model necessitates using an unrealistically high noise-current amplitude. Indeed, a major implication of the modelling results is that, given the wide range of time-scales over which the various species of channels open and close, only a cell-specific stochastic model that is formulated taking into consideration the widely different ranges in the frequency content of the channel-noise produced by the opening and closing of several different types of channels will be able to reproduce precisely the various effects due to membrane noise seen in a particular electrophysiological preparation.

Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

NASA Astrophysics Data System (ADS)

Li, Xiwang

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of this thesis can be used for building cluster energy forecasting model development and model based control and operation optimization. The thesis concludes with a summary of the key outcomes of this research, as well as a list of recommendations for future work.

Sound controlled rotation of a cluster of small particles on an ultrasonically vibrating metal strip

NASA Astrophysics Data System (ADS)

Zhang, Xueyi; Zheng, Yun; Hu, Junhui

2008-01-01

We show that a vibrating metal strip, mechanically driven by an ultrasonic transducer, can rotate a cluster of small particles around a fixed point, and the diameter of the cluster of small particles can reach a stable value (steady diameter) for a given driving condition. The rotation is very stable when the vibration of the metal strip is appropriate. The revolution speed, its direction, and steady diameter of the particle cluster can be controlled by the operating frequency of the ultrasonic transducer. For shrimp eggs, a revolution speed up to 360rpm can be obtained.

Time-reversibility and particle sedimentation

NASA Technical Reports Server (NTRS)

Golubitsky, Martin; Krupa, Martin; Lim, Chjan

1991-01-01

This paper studies an ODE model, called the Stokeslet model, and describes sedimentation of small clusters of particles in a highly viscous fluid. This model has a trivial solution in which the n particles arrange themselves at the vertices of a regular n-sided polygon. When n = 3, Hocking and Caflisch et al. (1988) proved the existence of periodic motion (in the frame moving with the center of gravity in the cluster) in which the particles form an isosceles triangle. Here, the study of periodic and quasi-periodic solutions of the Stokeslet model is continued, with emphasis on the spatial and time-reversal symmetry of the model. For three particles, the existence of a second family of periodic solutions and a family of quasi-periodic solutions is proved. It is also indicated how the methods generalize to the case of n particles.

Development of Wien filter for small ion gun of surface analysis

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

Bahng, Jungbae; Busan Center, Korea Basic Science Institute, Busan 609-735; Hong, Jonggi

The gas cluster ion beam (GCIB) and liquid metal ion beam have been studied in the context of ion beam usage for analytical equipment in applications such as X-ray photoelectron spectroscopy and secondary ion mass spectroscopy (SIMS). In particular, small ion sources are used for the secondary ion generation and ion etching. To set the context to this study, the SIMS project has been launched to develop ion-gun based analytical equipment for the Korea Basic Science Institute. The objective of the first stage of the project is the generation of argon beams with a GCIB system [A. Kirkpatrick, Nucl. Instrum.more » Methods Phys. Res., Sect. B 206, 830–837 (2003)] that consists of a nozzle, skimmer, ionizer, acceleration tube, separation system, transport system, and target. The Wien filter directs the selected cluster beam to the target system by exploiting the velocity difference of the generated particles from GCIB. In this paper, we present the theoretical modeling and three-dimensional electromagnetic analysis of the Wien filter, which can separate Ar{sup +}{sub 2500} clusters from Ar{sup +}{sub 2400} to Ar{sup +}{sub 2600} clusters with a 1-mm collimator.« less

Self-Learning Off-Lattice Kinetic Monte Carlo method as applied to growth on metal surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Kara, Abdelkader; Rahman, Talat

2007-03-01

We propose a new development in the Self-Learning Kinetic Monte Carlo (SLKMC) method with the goal of improving the accuracy with which atomic mechanisms controlling diffusive processes on metal surfaces may be identified. This is important for diffusion of small clusters (2 - 20 atoms) in which atoms may occupy Off-Lattice positions. Such a procedure is also necessary for consideration of heteroepitaxial growth. The new technique combines an earlier version of SLKMC [1] with the inclusion of off-lattice occupancy. This allows us to include arbitrary positions of adatoms in the modeling and makes the simulations more realistic and reliable. We have tested this new approach for the case of the diffusion of small 2D Cu clusters diffusion on Cu(111) and found good performance and satisfactory agreement with results obtained from previous version of SLKMC. The new method also helped reveal a novel atomic mechanism contributing to cluster migration. We have also applied this method to study the diffusion of Cu clusters on Ag(111), and find that Cu atoms generally prefer to occupy off-lattice sites. [1] O. Trushin, A. Kara, A. Karim, T.S. Rahman Phys. Rev B 2005

An ``Alternating-Curvature'' Model for the Nanometer-scale Structure of the Nafion Ionomer, Based on Backbone Properties Detected by NMR

NASA Astrophysics Data System (ADS)

Schmidt-Rohr, Klaus; Chen, Q.

2006-03-01

The perfluorinated ionomer, Nafion, which consists of a (-CF2-)n backbone and charged side branches, is useful as a proton exchange membrane in H2/O2 fuel cells. A modified model of the nanometer-scale structure of hydrated Nafion will be presented. It features hydrated ionic clusters familiar from some previous models, but is based most prominently on pronounced backbone rigidity between branch points and limited orientational correlation of local chain axes. These features have been revealed by solid-state NMR measurements, which take advantage of fast rotations of the backbones around their local axes. The resulting alternating curvature of the backbones towards the hydrated clusters also better satisfies the requirement of dense space filling in solids. Simulations based on this ``alternating curvature'' model reproduce orientational correlation data from NMR, as well as scattering features such as the ionomer peak and the I(q) ˜ 1/q power law at small q values, which can be attributed to modulated cylinders resulting from the chain stiffness. The shortcomings of previous models, including Gierke's cluster model and more recent lamellar or bundle models, in matching all requirements imposed by the experimental data will be discussed.

Free Factories: Unified Infrastructure for Data Intensive Web Services

PubMed Central

Zaranek, Alexander Wait; Clegg, Tom; Vandewege, Ward; Church, George M.

2010-01-01

We introduce the Free Factory, a platform for deploying data-intensive web services using small clusters of commodity hardware and free software. Independently administered virtual machines called Freegols give application developers the flexibility of a general purpose web server, along with access to distributed batch processing, cache and storage services. Each cluster exploits idle RAM and disk space for cache, and reserves disks in each node for high bandwidth storage. The batch processing service uses a variation of the MapReduce model. Virtualization allows every CPU in the cluster to participate in batch jobs. Each 48-node cluster can achieve 4-8 gigabytes per second of disk I/O. Our intent is to use multiple clusters to process hundreds of simultaneous requests on multi-hundred terabyte data sets. Currently, our applications achieve 1 gigabyte per second of I/O with 123 disks by scheduling batch jobs on two clusters, one of which is located in a remote data center. PMID:20514356

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

Formation and Assembly of Massive Star Clusters

NASA Astrophysics Data System (ADS)

McMillan, Stephen

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

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, S. P.

1984-01-01

Small transition metal clusters were studied at a high level of approximation, including all the valence electrons in the calculation and extensive electron correlation, in order to understand the electronic structure of these small metal clusters. By comparison of dimers, trimers, and possibly higher clusters, the information obtained was used to provide insights into the electronic structure of bulk transition metals. Small metal clusters are currently of considerable experimental interest and some information is becomming available both from matrix electron spin resonance studies and from gas phase spectroscopy. Collaboration between theorists and experimentalists is thus expected to be especially profitable at this time since there is some experimental information which can serve to guide the theoretical work.

Cluster analysis applied to localized dispersion curves in East Asia: the limits of surface wave resolution

NASA Astrophysics Data System (ADS)

Witek, M.; van der Lee, S.; Kang, T. S.; Chang, S. J.; Ning, J.; Ning, S.

2017-12-01

We have measured Rayleigh wave group velocity dispersion curves from one year of station-pair cross-correlations of continuous vertical-component broadband data from 1082 seismic stations in regional networks across China, Korea, Taiwan, and Japan for the year 2011. We use the measurements to map local dispersion anomalies for periods in the range 6-40 s. We combined our ambient noise data set with the earthquake group velocity data set of Ma et al. (2014), and then applied agglomerative hierarchical clustering to the localized dispersion curves. We find that the dispersion curves naturally organize themselves into distinct tectonic regions. For our distribution of interstation distances, only 8 distinct regions need to be defined. Additional clusters reduce the overall data misfit by increasingly smaller amounts. The size and number of clusters needed to suitably predict the data may give an indication of the resolving power of the data set. The regions that emerge from the cluster analysis include Tibet, the Sea of Japan, the South China Block and the Korean peninsula, the Ordos and Yangtze cratons, and Mesozoic rift basins such as the Songliao, Bohai Bay and Ulleung basins. We also performed a traditional inversion for 3D S-velocity structure, and the resulting model fits the data as well as the 8-cluster model, while both models fit the earthquake data and ambient noise data better than the LITHO1.0 model of Pasyanos et al. (2014). Our 3D model of the crust and upper mantle confirms many of the features seen in previous studies of the region, most notably the lithospheric thinning going from west to east and low velocity zones in the crust on the Tibetan periphery. We conclude that cluster analysis is able to greatly reduce the dimensionality of surface wave dispersion data, in the sense that a data set of over half a million dispersion curves is sufficiently predicted by appropriately averaging over a relatively small set of distinct tectonic regions. The resulting clustered model objectively quantifies the more intuitive ways in which we usually tend to interpret tomographic models.

Lipid-Mediated Clusters of Guest Molecules in Model Membranes and Their Dissolving in the Presence of Lipid Rafts.

PubMed

Kardash, Maria E; Dzuba, Sergei A

2017-05-25

The clustering of molecules is an important feature of plasma membrane organization. It is challenging to develop methods for quantifying membrane heterogeneities because of their transient nature and small size. Here, we obtained evidence that transient membrane heterogeneities can be frozen at cryogenic temperatures which allows the application of solid-state experimental techniques sensitive to the nanoscale distance range. We employed the pulsed version of electron paramagnetic resonance (EPR) spectroscopy, the electron spin echo (ESE) technique, for spin-labeled molecules in multilamellar lipid bilayers. ESE decays were refined for pure contribution of spin-spin magnetic dipole-dipolar interaction between the labels; these interactions manifest themselves at a nanometer distance range. The bilayers were prepared from different types of saturated and unsaturated lipids and cholesterol (Chol); in all cases, a small amount of guest spin-labeled substances 5-doxyl-stearic-acid (5-DSA) or 3β-doxyl-5α-cholestane (DChl) was added. The local concentration found of 5-DSA and DChl molecules was remarkably higher than the mean concentration in the bilayer, evidencing the formation of lipid-mediated clusters of these molecules. To our knowledge, formation of nanoscale clusters of guest amphiphilic molecules in biological membranes is a new phenomenon suggested only recently. Two-dimensional 5-DSA molecular clusters were found, whereas flat DChl molecules were found to be clustered into stacked one-dimensional structures. These clusters disappear when the Chol content is varied between the boundaries known for lipid raft formation at room temperatures. The room temperature EPR evidenced entrapping of DChl molecules in the rafts.

Improved community model for social networks based on social mobility

NASA Astrophysics Data System (ADS)

Lu, Zhe-Ming; Wu, Zhen; Luo, Hao; Wang, Hao-Xian

2015-07-01

This paper proposes an improved community model for social networks based on social mobility. The relationship between the group distribution and the community size is investigated in terms of communication rate and turnover rate. The degree distributions, clustering coefficients, average distances and diameters of networks are analyzed. Experimental results demonstrate that the proposed model possesses the small-world property and can reproduce social networks effectively and efficiently.

Reconstruction of halo power spectrum from redshift-space galaxy distribution: cylinder-grouping method and halo exclusion effect

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Takada, Masahiro; More, Surhud; Masaki, Shogo

2017-07-01

The peculiar velocity field measured by redshift-space distortions (RSD) in galaxy surveys provides a unique probe of the growth of large-scale structure. However, systematic effects arise when including satellite galaxies in the clustering analysis. Since satellite galaxies tend to reside in massive haloes with a greater halo bias, the inclusion boosts the clustering power. In addition, virial motions of the satellite galaxies cause a significant suppression of the clustering power due to non-linear RSD effects. We develop a novel method to recover the redshift-space power spectrum of haloes from the observed galaxy distribution by minimizing the contamination of satellite galaxies. The cylinder-grouping method (CGM) we study effectively excludes satellite galaxies from a galaxy sample. However, we find that this technique produces apparent anisotropies in the reconstructed halo distribution over all the scales which mimic RSD. On small scales, the apparent anisotropic clustering is caused by exclusion of haloes within the anisotropic cylinder used by the CGM. On large scales, the misidentification of different haloes in the large-scale structures, aligned along the line of sight, into the same CGM group causes the apparent anisotropic clustering via their cross-correlation with the CGM haloes. We construct an empirical model for the CGM halo power spectrum, which includes correction terms derived using the CGM window function at small scales as well as the linear matter power spectrum multiplied by a simple anisotropic function at large scales. We apply this model to a mock galaxy catalogue at z = 0.5, designed to resemble Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies, and find that our model can predict both the monopole and quadrupole power spectra of the host haloes up to k < 0.5 {{h Mpc^{-1}}} to within 5 per cent.

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.

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Interaction of intense ultrashort pulse lasers with clusters.

NASA Astrophysics Data System (ADS)

Petrov, George

2007-11-01

The last ten years have witnessed an explosion of activity involving the interaction of clusters with intense ultrashort pulse lasers. Atomic or molecular clusters are targets with unique properties, as they are halfway between solid and gases. The intense laser radiation creates hot dense plasma, which can provide a compact source of x-rays and energetic particles. The focus of this investigation is to understand the salient features of energy absorption and Coulomb explosion by clusters. The evolution of clusters is modeled with a relativistic time-dependent 3D Molecular Dynamics (MD) model [1]. The Coulomb interaction between particles is handled by a fast tree algorithm, which allows large number of particles to be used in simulations [2]. The time histories of all particles in a cluster are followed in time and space. The model accounts for ionization-ignition effects (enhancement of the laser field in the vicinity of ions) and a variety of elementary processes for free electrons and charged ions, such as optical field and collisional ionization, outer ionization and electron recapture. The MD model was applied to study small clusters (1-20 nm) irradiated by a high-intensity (10^16-10^20 W/cm^2) sub-picosecond laser pulse. We studied fundamental cluster features such as energy absorption, x-ray emission, particle distribution, average charge per atom, and cluster explosion as a function of initial cluster radius, laser peak intensity and wavelength. Simulations of novel applications, such as table-top nuclear fusion from exploding deuterium clusters [3] and high power synchrotron radiation for biological applications and imaging [4] have been performed. The application for nuclear fusion was motivated by the efficient absorption of laser energy (˜100%) and its high conversion efficiency into ion kinetic energy (˜50%), resulting in neutron yield of 10^6 neutrons/Joule laser energy. Contributors: J. Davis and A. L. Velikovich. [1] G. M. Petrov, et al Phys. Plasmas 12 063103 (2005); 13 033106 (2006) [2] G. M. Petrov, J. Davis, European Phys. J. D 41 629 (2007) [3] G. M. Petrov, J. Davis, A. L. Velikovich, Plasma Phys. Contr. Fusion 48 1721 (2006) [4] G. M. Petrov, J. Davis, A. L. Velikovich, J. Phys. B 39 4617 (2006)

Interaction of polymer-coated silicon nanocrystals with lipid bilayers and surfactant interfaces

NASA Astrophysics Data System (ADS)

Elbaradei, Ahmed; Brown, Samuel L.; Miller, Joseph B.; May, Sylvio; Hobbie, Erik K.

2016-10-01

We use photoluminescence (PL) microscopy to measure the interaction between polyethylene-glycol-coated (PEGylated) silicon nanocrystals (SiNCs) and two model surfaces: lipid bilayers and surfactant interfaces. By characterizing the photostability, transport, and size-dependent emission of the PEGylated nanocrystal clusters, we demonstrate the retention of red PL suitable for detection and tracking with minimal blueshift after a year in an aqueous environment. The predominant interaction measured for both interfaces is short-range repulsion, consistent with the ideal behavior anticipated for PEGylated phospholipid coatings. However, we also observe unanticipated attractive behavior in a small number of scenarios for both interfaces. We attribute this anomaly to defective PEG coverage on a subset of the clusters, suggesting a possible strategy for enhancing cellular uptake by controlling the homogeneity of the PEG corona. In both scenarios, the shape of the apparent potential is modeled through the free or bound diffusion of the clusters near the confining interface.

GPI-anchored proteins are confined in subdiffraction clusters at the apical surface of polarized epithelial cells.

PubMed

Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe; Zurzolo, Chiara

2017-12-01

Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. © 2017 The Author(s).

Catalysis applications of size-selected cluster deposition

DOE PAGES

Vajda, Stefan; White, Michael G.

2015-10-23

In this Perspective, we review recent studies of size-selected cluster deposition for catalysis applications performed at the U.S. DOE National Laboratories, with emphasis on work at Argonne National Laboratory (ANL) and Brookhaven National Laboratory (BNL). The focus is on the preparation of model supported catalysts in which the number of atoms in the deposited clusters is precisely controlled using a combination of gas-phase cluster ion sources, mass spectrometry, and soft-landing techniques. This approach is particularly effective for investigations of small nanoclusters, 0.5-2 nm (<200 atoms), where the rapid evolution of the atomic and electronic structure makes it essential to havemore » precise control over cluster size. Cluster deposition allows for independent control of cluster size, coverage, and stoichiometry (e.g., the metal-to-oxygen ratio in an oxide cluster) and can be used to deposit on any substrate without constraints of nucleation and growth. Examples are presented for metal, metal oxide, and metal sulfide cluster deposition on a variety of supports (metals, oxides, carbon/diamond) where the reactivity, cluster-support electronic interactions, and cluster stability and morphology are investigated. Both UHV and in situ/operando studies are presented that also make use of surface-sensitive X-ray characterization tools from synchrotron radiation facilities. Novel applications of cluster deposition to electrochemistry and batteries are also presented. This review also highlights the application of modern ab initio electronic structure calculations (density functional theory), which can essentially model the exact experimental system used in the laboratory (i.e., cluster and support) to provide insight on atomic and electronic structure, reaction energetics, and mechanisms. As amply demonstrated in this review, the powerful combination of atomically precise cluster deposition and theory is able to address fundamental aspects of size-effects, cluster-support interactions, and reaction mechanisms of cluster materials that are central to how catalysts function. Lastly, the insight gained from such studies can be used to further the development of novel nanostructured catalysts with high activity and selectivity.« less

Lack of small-scale clustering in 21-cm intensity maps crossed with 2dF galaxy densities at z ~ 0.08

NASA Astrophysics Data System (ADS)

Anderson, Christopher; Luciw, Nicholas; Li, Yi-Chao; Kuo, Cheng-Yu; Yadav, Jaswant; Masui, Kiyoshi; Chang, Tzu-Ching; Chen, Xuelei; Oppermann, Niels; Pen, Ue-Li; Timbie, Peter T.

2017-06-01

I report results from 21-cm intensity maps acquired from the Parkes radio telescope and cross-correlated with galaxy maps from the 2dF galaxy survey. The data span the redshift range 0.057

Imprints of dynamical interactions on brown dwarf pairing statistics and kinematics

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2003-03-01

We present statistically robust predictions of brown dwarf properties arising from dynamical interactions during their early evolution in small clusters. Our conclusions are based on numerical calculations of the internal cluster dynamics as well as on Monte-Carlo models. Accounting for recent observational constraints on the sub-stellar mass function and initial properties in fragmenting star forming clumps, we derive multiplicity fractions, mass ratios, separation distributions, and velocity dispersions. We compare them with observations of brown dwarfs in the field and in young clusters. Observed brown dwarf companion fractions around 15 +/- 7% for very low-mass stars as reported recently by Close et al. (\\cite{CSFB03}) are consistent with certain dynamical decay models. A significantly smaller mean separation distribution for brown dwarf binaries than for binaries of late-type stars can be explained by similar specific energy at the time of cluster formation for all cluster masses. Due to their higher velocity dispersions, brown-dwarfs and low-mass single stars will undergo time-dependent spatial segregation from higher-mass stars and multiple systems. This will cause mass functions and binary statistics in star forming regions to vary with the age of the region and the volume sampled.

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

Collective dynamics of 'small-world' networks.

PubMed

Watts, D J; Strogatz, S H

1998-06-04

Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

The halo boundary of galaxy clusters in the SDSS

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

Baxter, Eric; Chang, Chihway; Jain, Bhuvnesh

Analytical models and simulations predict a rapid decline in the halo density profile associated with the transition from the "infalling" regime outside the halo to the "collapsed" regime within the halo. Using data from SDSS, we explore evidence for such a feature in the density profiles of galaxy clusters using several different approaches. We first estimate the steepening of the outer galaxy density profile around clusters, finding evidence for truncation of the halo profile. Next, we measure the galaxy density profile around clusters using two sets of galaxies selected on color. We find evidence of an abrupt change in galaxymore » colors that coincides with the location of the steepening of the density profile. Since galaxies that have completed orbits within the cluster are more likely to be quenched of star formation and thus appear redder, this abrupt change in galaxy color can be associated with the transition from single-stream to multi-stream regimes. We also use a standard model comparison approach to measure evidence for a "splashback"-like feature, but find that this approach is very sensitive to modeling assumptions. Finally, we perform measurements using an independent cluster catalog to test for potential systematic errors associated with cluster selection. We identify several avenues for future work: improved understanding of the small-scale galaxy profile, lensing measurements, identification of proxies for the halo accretion rate, and other tests. As a result, with upcoming data from the DES, KiDS, and HSC surveys, we can expect significant improvements in the study of halo boundaries.« less

The Halo Boundary of Galaxy Clusters in the SDSS

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

Baxter, Eric; Jain, Bhuvnesh; Sheth, Ravi K.

Analytical models and simulations predict a rapid decline in the halo density profile associated with the transition from the “infalling” regime outside the halo to the “collapsed” regime within the halo. Using data from SDSS, we explore evidence for such a feature in the density profiles of galaxy clusters using several different approaches. We first estimate the steepening of the outer galaxy density profile around clusters, finding evidence for truncation of the halo profile. Next, we measure the galaxy density profile around clusters using two sets of galaxies selected on color. We find evidence of an abrupt change in galaxymore » colors that coincides with the location of the steepening of the density profile. Since galaxies that have completed orbits within the cluster are more likely to be quenched of star formation and thus appear redder, this abrupt change in galaxy color can be associated with the transition from single-stream to multi-stream regimes. We also use a standard model comparison approach to measure evidence for a “splashback”-like feature, but find that this approach is very sensitive to modeling assumptions. Finally, we perform measurements using an independent cluster catalog to test for potential systematic errors associated with cluster selection. We identify several avenues for future work: improved understanding of the small-scale galaxy profile, lensing measurements, identification of proxies for the halo accretion rate, and other tests. With upcoming data from the DES, KiDS, and HSC surveys, we can expect significant improvements in the study of halo boundaries.« less

The halo boundary of galaxy clusters in the SDSS

DOE PAGES

Baxter, Eric; Chang, Chihway; Jain, Bhuvnesh; ...

2017-05-18

Analytical models and simulations predict a rapid decline in the halo density profile associated with the transition from the "infalling" regime outside the halo to the "collapsed" regime within the halo. Using data from SDSS, we explore evidence for such a feature in the density profiles of galaxy clusters using several different approaches. We first estimate the steepening of the outer galaxy density profile around clusters, finding evidence for truncation of the halo profile. Next, we measure the galaxy density profile around clusters using two sets of galaxies selected on color. We find evidence of an abrupt change in galaxymore » colors that coincides with the location of the steepening of the density profile. Since galaxies that have completed orbits within the cluster are more likely to be quenched of star formation and thus appear redder, this abrupt change in galaxy color can be associated with the transition from single-stream to multi-stream regimes. We also use a standard model comparison approach to measure evidence for a "splashback"-like feature, but find that this approach is very sensitive to modeling assumptions. Finally, we perform measurements using an independent cluster catalog to test for potential systematic errors associated with cluster selection. We identify several avenues for future work: improved understanding of the small-scale galaxy profile, lensing measurements, identification of proxies for the halo accretion rate, and other tests. As a result, with upcoming data from the DES, KiDS, and HSC surveys, we can expect significant improvements in the study of halo boundaries.« less

Cell cycle dynamics in a response/signalling feedback system with a gap.

PubMed

Gong, Xue; Buckalew, Richard; Young, Todd; Boczko, Erik

2014-01-01

We consider a dynamical model of cell cycles of n cells in a culture in which cells in one specific phase (S for signalling) of the cell cycle produce chemical agents that influence the growth/cell cycle progression of cells in another phase (R for responsive). In the case that the feedback is negative, it is known that subpopulations of cells tend to become clustered in the cell cycle; while for a positive feedback, all the cells tend to become synchronized. In this paper, we suppose that there is a gap between the two phases. The gap can be thought of as modelling the physical reality of a time delay in the production and action of the signalling agents. We completely analyse the dynamics of this system when the cells are arranged into two cell cycle clusters. We also consider the stability of certain important periodic solutions in which clusters of cells have a cyclic arrangement and there are just enough clusters to allow interactions between them. We find that the inclusion of a small gap does not greatly alter the global dynamics of the system; there are still large open sets of parameters for which clustered solutions are stable. Thus, we add to the evidence that clustering can be a robust phenomenon in biological systems. However, the gap does effect the system by enhancing the stability of the stable clustered solutions. We explain this phenomenon in terms of contraction rates (Floquet exponents) in various invariant subspaces of the system. We conclude that in systems for which these models are reasonable, a delay in signalling is advantageous to the emergence of clustering.

Magnetic properties of Co-doped Nb clusters

NASA Astrophysics Data System (ADS)

Diaz-Bachs, A.; Peters, L.; Logemann, R.; Chernyy, V.; Bakker, J. M.; Katsnelson, M. I.; Kirilyuk, A.

2018-04-01

Magnetic deflection experiments on isolated Co-doped Nb clusters demonstrate a strong size dependence of magnetic properties, with large magnetic moments in certain cluster sizes and fully nonmagnetic behavior of others. There are in principle two explanations for this behavior. Either the local moment at the Co site is absent or it is screened by the delocalized electrons of the cluster, i.e., the Kondo effect. In order to reveal the physical origin, first, we established the ground state geometry of the clusters by experimentally obtaining their vibrational spectra and comparing them with a density functional theory study. Then, we performed an analysis based on the Anderson impurity model. It appears that the nonmagnetic clusters are due to the absence of the local Co moment and not due to the Kondo effect. In addition, the magnetic behavior of the clusters can be understood from an inspection of their electronic structure. Here magnetism is favored when the effective hybridization around the chemical potential is small, while the absence of magnetism is signaled by a large effective hybridization around the chemical potential.

Active galactic nuclei. III - Accretion flow in an externally supplied cluster of black holes

NASA Technical Reports Server (NTRS)

Pacholczyk, A. G.; Stoeger, W. R.; Stepinski, T. F.

1989-01-01

This third paper in the series modeling QSOs and AGNs as clusters of accreting black holes studies the accretion flow within an externally supplied cluster. Significant radiation will be emitted by the cluster core, but the black holes in the outer halo, where the flow is considered spherically symmetric, will not contribute much to the overall luminosity of the source because of their large velocities relative to the infalling gas and therefore their small accretion radii. As a result, the scenario discussed in Paper I will refer to the cluster cores, rather than to entire clusters. This will steepen the high-frequency region of the spectrum unless inverse Compton scattering is effective. In many cases accretion flow in the central part of the cluster will be optically thick to electron scattering, resulting in a spectrum featuring optically thick radiative component in addition to power-law regimes. The fitting of these spectra to QSO and AGN observations is discussed, and application to 3C 273 is worked out as an example.

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

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

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, V.; Sommer, F.G.

1982-07-13

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location. 6 figs.

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, Victor; Sommer, Frank G.

1982-01-01

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location.

Hot and solid gallium clusters: too small to melt.

PubMed

Breaux, Gary A; Benirschke, Robert C; Sugai, Toshiki; Kinnear, Brian S; Jarrold, Martin F

2003-11-21

A novel multicollision induced dissociation scheme is employed to determine the energy content for mass-selected gallium cluster ions as a function of their temperature. Measurements were performed for Ga(+)(n) (n=17 39, and 40) over a 90-720 K temperature range. For Ga+39 and Ga+40 a broad maximum in the heat capacity-a signature of a melting transition for a small cluster-occurs at around 550 K. Thus small gallium clusters melt at substantially above the 302.9 K melting point of bulk gallium, in conflict with expectations that they will remain liquid to below 150 K. No melting transition is observed for Ga+17.

Evolution of Carbon Clusters in the Detonation Products of the Triaminotrinitrobenzene (TATB)-Based Explosive PBX 9502

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

Watkins, Erik B.; Velizhanin, Kirill A.; Dattelbaum, Dana M.

The detonation of carbon-rich high explosives yields solid carbon as a major constituent of the product mixture and, depending on the thermodynamic conditions behind the shock front, a variety of carbon allotropes and morphologies may form and evolve. We applied time-resolved small angle x-ray scattering (TR-SAXS) to investigate the dynamics of carbon clustering during detonation of PBX 9502, an explosive composed of triaminotrinitrobenzene (TATB) and 5 wt% fluoropolymer binder. Solid carbon formation was probed from 0.1 to 2.0 μs behind the detonation front and revealed rapid carbon cluster growth which reached a maximum after ~200 ns. The late-time carbon clustersmore » had a radius of gyration of 3.3 nm which is consistent with 8.4 nm diameter spherical particles and matched particle sizes of recovered products. Simulations using a clustering kinetics model were found to be in good agreement with the experimental measurements of cluster growth when invoking a freeze-out temperature, and temporal shift associated with the initial precipitation of solid carbon. Product densities from reactive flow models were compared to the electron density contrast obtained from TR-SAXS and used to approximate the carbon cluster composition as a mixture of 20% highly ordered (diamond-like) and 80% disordered carbon forms, which will inform future product equation of state models for solid carbon in PBX 9502 detonation product mixtures.« less

Effects of carbonyl bond, metal cluster dissociation, and evaporation rates on predictions of nanotube production in high-pressure carbon monoxide

NASA Technical Reports Server (NTRS)

Scott, Carl D.; Smalley, Richard E.

2003-01-01

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNTs) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the conformation of CO2. It is shown that the production of CO2 is significantly greater for FeCO because of its lower bond energy as compared with that of NiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Effects of Carbonyl Bond and Metal Cluster Dissociation and Evaporation Rates on Predictions of Nanotube Production in HiPco

NASA Technical Reports Server (NTRS)

Scott, Carl D.; Smalley, Richard E.

2002-01-01

The high-pressure carbon monoxide (HiPco) process for producing single-wall carbon nanotubes (SWNT) uses iron pentacarbonyl as the source of iron for catalyzing the Boudouard reaction. Attempts using nickel tetracarbonyl led to no production of SWNTs. This paper discusses simulations at a constant condition of 1300 K and 30 atm in which the chemical rate equations are solved for different reaction schemes. A lumped cluster model is developed to limit the number of species in the models, yet it includes fairly large clusters. Reaction rate coefficients in these schemes are based on bond energies of iron and nickel species and on estimates of chemical rates for formation of SWNTs. SWNT growth is measured by the co-formation of CO2. It is shown that the production of CO2 is significantly greater for FeCO due to its lower bond energy as compared with that ofNiCO. It is also shown that the dissociation and evaporation rates of atoms from small metal clusters have a significant effect on CO2 production. A high rate of evaporation leads to a smaller number of metal clusters available to catalyze the Boudouard reaction. This suggests that if CO reacts with metal clusters and removes atoms from them by forming MeCO, this has the effect of enhancing the evaporation rate and reducing SWNT production. The study also investigates some other reactions in the model that have a less dramatic influence.

Lattice animals in diffusion limited binary colloidal system

NASA Astrophysics Data System (ADS)

Shireen, Zakiya; Babu, Sujin B.

2017-08-01

In a soft matter system, controlling the structure of the amorphous materials has been a key challenge. In this work, we have modeled irreversible diffusion limited cluster aggregation of binary colloids, which serves as a model for chemical gels. Irreversible aggregation of binary colloidal particles leads to the formation of a percolating cluster of one species or both species which are also called bigels. Before the formation of the percolating cluster, the system forms a self-similar structure defined by a fractal dimension. For a one component system when the volume fraction is very small, the clusters are far apart from each other and the system has a fractal dimension of 1.8. Contrary to this, we will show that for the binary system, we observe the presence of lattice animals which has a fractal dimension of 2 irrespective of the volume fraction. When the clusters start inter-penetrating, we observe a fractal dimension of 2.5, which is the same as in the case of the one component system. We were also able to predict the formation of bigels using a simple inequality relation. We have also shown that the growth of clusters follows the kinetic equations introduced by Smoluchowski for diffusion limited cluster aggregation. We will also show that the chemical distance of a cluster in the flocculation regime will follow the same scaling law as predicted for the lattice animals. Further, we will also show that irreversible binary aggregation comes under the universality class of the percolation theory.

Structure and Binding of Ionic Clusters in Th and Zr Chloride Melts

NASA Astrophysics Data System (ADS)

Akdeniz, Z.; Tosi, M. P.

2001-11-01

We discuss microscopic ionic models for the structure and the binding of small clusters which may exist as structural units in molten ThCl4 and ZrCl4 and in their mixtures with alkali halides according to Raman scattering studies of Photiadis and Papatheodorou. The models are adjusted to the two isolated tetrahedral molecules. Appreciably higher ionicity is found for ThCl4 than for ZrCl4, and this fact underlies the strikingly different behaviour of the two systems in the dense liquid state -in particular, a molecular-type structure for molten ZrCl4 against a structure including charged oligomers in molten ThCl4.

Metal-cluster ionization energy: A profile-insensitive exact expression for the size effect

NASA Astrophysics Data System (ADS)

Seidl, Michael; Perdew, John P.; Brajczewska, Marta; Fiolhais, Carlos

1997-05-01

The ionization energy of a large spherical metal cluster of radius R is I(R)=W+(+c)/R, where W is the bulk work function and c~-0.1 is a material-dependent quantum correction to the electrostatic size effect. We present 'Koopmans' and 'displaced-profile change-in-self-consistent-field' expressions for W and c within the ordinary and stabilized-jellium models. These expressions are shown to be exact and equivalent when the exact density profile of a large neutral cluster is employed; these equivalences generalize the Budd-Vannimenus theorem. With an approximate profile obtained from a restricted variational calculation, the 'displaced-profile' expressions are the more accurate ones. This profile insensitivity is important, because it is not practical to extract c from solutions of the Kohn-Sham equations for small metal clusters.

Modeling curvature-dependent subcellular localization of a small sporulation protein in Bacillus subtilis

NASA Astrophysics Data System (ADS)

Wasnik, Vaibhav; Wingreen, Ned; Mukhopadhyay, Ranjan

2012-02-01

Recent experiments suggest that in the bacterium, B. subtilis, the cue for the localization of small sporulation protein, SpoVM, that plays a central role in spore coat formation, is curvature of the bacterial plasma membrane. This curvature-dependent localization is puzzling given the orders of magnitude difference in lengthscale of an individual protein and radius of curvature of the membrane. Here we develop a minimal model to study the relationship between curvature-dependent membrane absorption of SpoVM and clustering of membrane-associated SpoVM and compare our results with experiments.

Clustering: Working Together for Better Schools.

ERIC Educational Resources Information Center

Nachtigal, Paul; Parker, Sylvia D.

With declining enrollments and budget limitations, it becomes more and more difficult for small rural schools to offer state-approved programs (often based on the "bigger is better" model of education). For many already consolidated districts, further consolidation is not a viable solution to the problem. Cooperative arrangements are…

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

Two Point Autocorrelation Analysis of Auger Highest Energy Events Backtracked in Galactic Magnetic Field

NASA Astrophysics Data System (ADS)

Petrov, Yevgeniy

2009-10-01

Searches for sources of the highest-energy cosmic rays traditionally have included looking for clusters of event arrival directions on the sky. The smallest cluster is a pair of events falling within some angular window. In contrast to the standard two point (2-pt) autocorrelation analysis, this work takes into account influence of the galactic magnetic field (GMF). The highest energy events, those above 50EeV, collected by the surface detector of the Pierre Auger Observatory between January 1, 2004 and May 31, 2009 are used in the analysis. Having assumed protons as primaries, events are backtracked through BSS/S, BSS/A, ASS/S and ASS/A versions of Harari-Mollerach-Roulet (HMR) model of the GMF. For each version of the model, a 2-pt autocorrelation analysis is applied to the backtracked events and to 105 isotropic Monte Carlo realizations weighted by the Auger exposure. Scans in energy, separation angular window and different model parameters reveal clustering at different angular scales. Small angle clustering at 2-3 deg is particularly interesting and it is compared between different field scenarios. The strength of the autocorrelation signal at those angular scales differs between BSS and ASS versions of the HMR model. The BSS versions of the model tend to defocus protons as they arrive to Earth whereas for the ASS, in contrary, it is more likely to focus them.

Inference from the small scales of cosmic shear with current and future Dark Energy Survey data

DOE PAGES

MacCrann, N.; Aleksić, J.; Amara, A.; ...

2016-11-05

Cosmic shear is sensitive to fluctuations in the cosmological matter density field, including on small physical scales, where matter clustering is affected by baryonic physics in galaxies and galaxy clusters, such as star formation, supernovae feedback and AGN feedback. While muddying any cosmological information that is contained in small scale cosmic shear measurements, this does mean that cosmic shear has the potential to constrain baryonic physics and galaxy formation. We perform an analysis of the Dark Energy Survey (DES) Science Verification (SV) cosmic shear measurements, now extended to smaller scales, and using the Mead et al. 2015 halo model tomore » account for baryonic feedback. While the SV data has limited statistical power, we demonstrate using a simulated likelihood analysis that the final DES data will have the statistical power to differentiate among baryonic feedback scenarios. We also explore some of the difficulties in interpreting the small scales in cosmic shear measurements, presenting estimates of the size of several other systematic effects that make inference from small scales difficult, including uncertainty in the modelling of intrinsic alignment on nonlinear scales, `lensing bias', and shape measurement selection effects. For the latter two, we make use of novel image simulations. While future cosmic shear datasets have the statistical power to constrain baryonic feedback scenarios, there are several systematic effects that require improved treatments, in order to make robust conclusions about baryonic feedback.« less

Magic Numbers in Small Iron Clusters: A First-Principles Study

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

Kim, Eunja; Mohrland, Andrew B.; Weck, Philippe F.

2014-10-03

We perform ab initio spin-polarized density functional calculations of Fen aggregates with n ≤ 17 atoms to reveal the origin of the observed magic numbers, which indicate particularly high stability of clusters with 7, 13 and 15 atoms. Our results clarify the controversy regarding the ground state geometry of clusters such as Fe5and indicate that magnetism plays an important role in determining the stability and magic numbers in small iron clusters.

Report on simulation of fission gas and fission product diffusion in UO 2

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

Andersson, Anders David; Perriot, Romain Thibault; Pastore, Giovanni

2016-07-22

In UO 2 nuclear fuel, the retention and release of fission gas atoms such as xenon (Xe) are important for nuclear fuel performance by, for example, reducing the fuel thermal conductivity, causing fuel swelling that leads to mechanical interaction with the clad, increasing the plenum pressure and reducing the fuel–clad gap thermal conductivity. We use multi-­scale simulations to determine fission gas diffusion mechanisms as well as the corresponding rates in UO 2 under both intrinsic and irradiation conditions. In addition to Xe and Kr, the fission products Zr, Ru, Ce, Y, La, Sr and Ba have been investigated. Density functionalmore » theory (DFT) calculations are used to study formation, binding and migration energies of small clusters of Xe atoms and vacancies. Empirical potential calculations enable us to determine the corresponding entropies and attempt frequencies for migration as well as investigate the properties of large clusters or small fission gas bubbles. A continuum reaction-­diffusion model is developed for Xe and point defects based on the mechanisms and rates obtained from atomistic simulations. Effective fission gas diffusivities are then obtained by solving this set of equations for different chemical and irradiation conditions using the MARMOT phase field code. The predictions are compared to available experimental data. The importance of the large Xe U3O cluster (a Xe atom in a uranium + oxygen vacancy trap site with two bound uranium vacancies) is emphasized, which is a consequence of its high mobility and high binding energy. We find that the Xe U3O cluster gives Xe diffusion coefficients that are higher for intrinsic conditions than under irradiation over a wide range of temperatures. Under irradiation the fast-­moving Xe U3O cluster recombines quickly with irradiation-induced interstitial U ions, while this mechanism is less important for intrinsic conditions. The net result is higher concentration of the Xe U3O cluster for intrinsic conditions than under irradiation. We speculate that differences in the irradiation conditions and their impact on the Xe U3O cluster can explain the wide range of diffusivities reported in experimental studies. However, all vacancy-­mediated mechanisms underestimate the Xe diffusivity compared to the empirical radiation-­enhanced rate used in most fission gas release models. We investigate the possibility that diffusion of small fission gas bubbles or extended Xe-­vacancy clusters may give rise to the observed radiation-­enhanced diffusion coefficient. These studies highlight the importance of U divacancies and an octahedron coordination of uranium vacancies encompassing a Xe fission gas atom. The latter cluster can migrate via a multistep mechanism with a rather low effective barrier, which together with irradiation-induced clusters of uranium vacancies, gives rise to the irradiation-enhanced diffusion coefficient observed in experiments.« less

Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles.

PubMed

Sani-Kast, Nicole; Scheringer, Martin; Slomberg, Danielle; Labille, Jérôme; Praetorius, Antonia; Ollivier, Patrick; Hungerbühler, Konrad

2015-12-01

Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted. Copyright © 2014 Elsevier B.V. All rights reserved.

Percutaneous radiofrequency ablation of lung tumors in a large animal model.

PubMed

Ahrar, Kamran; Price, Roger E; Wallace, Michael J; Madoff, David C; Gupta, Sanjay; Morello, Frank A; Wright, Kenneth C

2003-08-01

Percutaneous radiofrequency ablation (RFA) is accepted therapy for liver tumors in the appropriate clinical setting, but its use in lung neoplasms remains investigational. We undertook this study to evaluate the feasibility and immediate effectiveness of RFA for treatment of both solitary pulmonary nodules and clusters of lung tumors in a large animal model. Percutaneous RFA of 14 lung tumors in five dogs was performed under CT guidance. Animals were euthanatized 8-48 hours after the procedure. The lungs and adjacent structures were harvested for gross and histopathologic evaluation. Five solitary pulmonary nodules (range, 17-26 mm) and three clusters of three nodules each (range, 7-17 mm per nodule) were treated with RFA. All ablations were technically successful. Perilesional ground-glass opacity and small asymptomatic pneumothoraces (n = 4) were visualized during the RFA sessions. One dog developed a large pneumothorax treated with tube thoracostomy but was euthanatized 8 hours post-RFA for persistent pneumothorax and continued breathing difficulty. Follow-up CT 48 hours post-RFA revealed opacification of the whole lung segment. Gross and histopathologic evaluation showed complete thermal coagulation necrosis of all treated lesions without evidence of any viable tumor. The region of thermal coagulation necrosis typically extended to the lung surface. Small regions of pulmonary hemorrhage and congestion often surrounded the areas of coagulation necrosis. RFA can be used to treat both solitary pulmonary nodules and clusters of tumor nodules in the canine lung tumor model. This model may be useful for development of specific RFA protocols for human lung tumors.

On the Clustering of Europa's Small Craters

NASA Technical Reports Server (NTRS)

Bierhaus, E. B.; Chapman, C. R.; Merline, W. J.

2001-01-01

We analyze the spatial distribution of Europa's small craters and find that many are too tightly clustered to result from random, primary impacts. Additional information is contained in the original extended abstract.

Abnormal response to the anorexic effect of GHS-R inhibitors and exenatide in male Snord116 deletion mouse model for Prader-Willi Syndrome

USDA-ARS?s Scientific Manuscript database

Prader-Willi syndrome (PWS) is a genetic disease characterized by persistent hunger and hyperphagia. The lack of the Snord116 small nucleolar RNA cluster has been identified as the major contributor to PWS symptoms. The Snord116 deletion (Snord116del) mouse model manifested a subset of PWS symptoms ...

Modeling small-scale variability in the composition of goshawk habitat on the Kaibab National Forest

Treesearch

Suzanne M. Joy; Robin M. Reich; Richard T. Reynolds

2000-01-01

We used field data, topographical information (elevation, slope, aspect, landform), and Landsat Thematic Mapper imagery to model forest vegetative types to a 10-m resolution on the Kaibab National Forest in northern Arizona. Forest types were identified by clustering the field data and then using a decision tree based on the spectral characteristics of a Landsat image...

Small-Scale, Local Area, and Transitional Millimeter Wave Propagation for 5G Communications

NASA Astrophysics Data System (ADS)

Rappaport, Theodore S.; MacCartney, George R.; Sun, Shu; Yan, Hangsong; Deng, Sijia

2017-12-01

This paper studies radio propagation mechanisms that impact handoffs, air interface design, beam steering, and MIMO for 5G mobile communication systems. Knife edge diffraction (KED) and a creeping wave linear model are shown to predict diffraction loss around typical building objects from 10 to 26 GHz, and human blockage measurements at 73 GHz are shown to fit a double knife-edge diffraction (DKED) model which incorporates antenna gains. Small-scale spatial fading of millimeter wave received signal voltage amplitude is generally Ricean-distributed for both omnidirectional and directional receive antenna patterns under both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions in most cases, although the log-normal distribution fits measured data better for the omnidirectional receive antenna pattern in the NLOS environment. Small-scale spatial autocorrelations of received voltage amplitudes are shown to fit sinusoidal exponential and exponential functions for LOS and NLOS environments, respectively, with small decorrelation distances of 0.27 cm to 13.6 cm (smaller than the size of a handset) that are favorable for spatial multiplexing. Local area measurements using cluster and route scenarios show how the received signal changes as the mobile moves and transitions from LOS to NLOS locations, with reasonably stationary signal levels within clusters. Wideband mmWave power levels are shown to fade from 0.4 dB/ms to 40 dB/s, depending on travel speed and surroundings.

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Propensity score matching with clustered data. An application to the estimation of the impact of caesarean section on the Apgar score.

PubMed

Arpino, Bruno; Cannas, Massimo

2016-05-30

This article focuses on the implementation of propensity score matching for clustered data. Different approaches to reduce bias due to cluster-level confounders are considered and compared using Monte Carlo simulations. We investigated methods that exploit the clustered structure of the data in two ways: in the estimation of the propensity score model (through the inclusion of fixed or random effects) or in the implementation of the matching algorithm. In addition to a pure within-cluster matching, we also assessed the performance of a new approach, 'preferential' within-cluster matching. This approach first searches for control units to be matched to treated units within the same cluster. If matching is not possible within-cluster, then the algorithm searches in other clusters. All considered approaches successfully reduced the bias due to the omission of a cluster-level confounder. The preferential within-cluster matching approach, combining the advantages of within-cluster and between-cluster matching, showed a relatively good performance both in the presence of big and small clusters, and it was often the best method. An important advantage of this approach is that it reduces the number of unmatched units as compared with a pure within-cluster matching. We applied these methods to the estimation of the effect of caesarean section on the Apgar score using birth register data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Hole pairing and ground state properties of high-Tc superconductivity within the t-t'-J-V model

NASA Astrophysics Data System (ADS)

Roy, Krishanu; Pal, Papiya; Nath, Subhadip; Ghosh, Nanda Kumar

2018-04-01

The t-t'-J-V model, one of the realistic models for studying high-Tc cuprates, has been investigated to explore the hole pairing and other ground state properties using exact diagonalization (ED) technique with 2 holes in a small 8-site cluster. The role of next-nearest-neighbor (NNN) hopping and nearest-neighbor (NN) Coulomb repulsion has been considered. It appears that qualitative behavior of the ground state energies of an 8-site and 16- or 18-site cluster is similar. Results show that a small short-ranged antiferromagnetic (AF) correlation exists in the 2 hole case which is favored by large V/t. A superconducting phase emerges at 0 ≤ V/t ≤ 4J. Hole-hole correlation calculation also suggests that the two holes of the pair are either at |i - j| = 1 or √2. Negative t'/t suppresses the possibility of pairing of holes. Though s-wave pairing susceptibility is dominant, pairing correlation length calculation indicates that the long range pairing, which is suitable for superconductivity, is in the d-wave channel. Both s- and d-wave pairing susceptibility gets suppressed by V/t while d-(s-) wave susceptibility gets favored (suppressed) by t'/t. The charge gap shows a gapped behavior while a spin-gapless region exists at small V/t for finite t'/t.

Estimating relative risks in multicenter studies with a small number of centers - which methods to use? A simulation study.

PubMed

Pedroza, Claudia; Truong, Van Thi Thanh

2017-11-02

Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.

Cascadia Seismicity Related to Seamount Subduction as detected by the Cascadia Initiative Amphibious Data

NASA Astrophysics Data System (ADS)

Morton, E.; Bilek, S. L.; Rowe, C. A.

2016-12-01

Unlike other subduction zones, the Cascadia subduction zone (CSZ) is notable for the absence of detected and located small and moderate magnitude interplate earthquakes, despite the presence of recurring episodic tremor and slip (ETS) downdip and evidence of pre-historic great earthquakes. Thermal and geodetic models indicate that the seismogenic zone exists primarily, if not entirely, offshore; therefore the perceived unusual seismic quiescence may be a consequence of seismic source location in relation to land based seismometers. The Cascadia Initiative (CI) amphibious community seismic experiment includes ocean bottom seismometers (OBS) deployed directly above the presumed locked seismogenic zone. We use the CI dataset to search for small magnitude interplate earthquakes previously undetected using the on-land sensors alone. We implement subspace detection to search for small earthquakes. We build our subspace with template events from existing earthquake catalogs that appear to have occurred on the plate interface, windowing waveforms on CI OBS and land seismometers. Although our efforts will target the entire CSZ margin and full 4-year CI deployment, here we focus on a previously identified cluster off the coast of Oregon, related to a subducting seamount. During the first year of CI deployment, this target area yields 293 unique detections with 86 well-located events. Thirty-two of these events occurred within the seamount cluster, and 13 events were located in another cluster to the northwest of the seamount. Events within the seamount cluster are separated into those whose depths place them on the plate interface, and a shallower set ( 5 km depth). These separate event groups track together temporally, and seem to agree with a model of seamount subduction that creates extensive fracturing around the seamount, rather than stress concentrated at the seamount-plate boundary. During CI year 2, this target area yields >1000 additional event detections.

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.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Calcium waves in a grid of clustered channels with synchronous IP3 binding and unbinding.

PubMed

Rückl, M; Rüdiger, S

2016-11-01

Calcium signals in cells occur at multiple spatial scales and variable temporal duration. However, a physical explanation for transitions between long-lasting global oscillations and localized short-term elevations (puffs) of cytoplasmic Ca 2+ is still lacking. Here we introduce a phenomenological, coarse-grained model for the calcium variable, which is represented by ordinary differential equations. Due to its small number of parameters, and its simplicity, this model allows us to numerically study the interplay of multi-scale calcium concentrations with stochastic ion channel gating dynamics even in larger systems. We apply this model to a single cluster of inositol trisphosphate (IP 3 ) receptor channels and find further evidence for the results presented in earlier work: a single cluster may be capable of producing different calcium release types, where long-lasting events are accompanied by unbinding of IP 3 from the receptor (Rückl et al., PLoS Comput. Biol. 11, e1003965 (2015)). Finally, we show the practicability of the model in a grid of 64 clusters which is computationally intractable with previous high-resolution models. Here long-lasting events can lead to synchronized oscillations and waves, while short events stay localized. The frequency of calcium releases as well as their coherence can thereby be regulated by the amplitude of IP 3 stimulation. Finally the model allows for a new explanation of oscillating [IP 3 ], which is not based on metabolic production and degradation of IP 3 .

Assessing the Impact of Socioeconomic Variables on Small Area Variations in Suicide Outcomes in England

PubMed Central

Congdon, Peter

2012-01-01

Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas. PMID:23271304

Assessing the impact of socioeconomic variables on small area variations in suicide outcomes in England.

PubMed

Congdon, Peter

2012-12-27

Ecological studies of suicide and self-harm have established the importance of area variables (e.g., deprivation, social fragmentation) in explaining variations in suicide risk. However, there are likely to be unobserved influences on risk, typically spatially clustered, which can be modeled as random effects. Regression impacts may be biased if no account is taken of spatially structured influences on risk. Furthermore a default assumption of linear effects of area variables may also misstate or understate their impact. This paper considers variations in suicide outcomes for small areas across England, and investigates the impact on them of area socio-economic variables, while also investigating potential nonlinearity in their impact and allowing for spatially clustered unobserved factors. The outcomes are self-harm hospitalisations and suicide mortality over 6,781 Middle Level Super Output Areas.

Atom-bond electronegativity equalization method fused into molecular mechanics. I. A seven-site fluctuating charge and flexible body water potential function for water clusters.

PubMed

Yang, Zhong-Zhi; Wu, Yang; Zhao, Dong-Xia

2004-02-08

Recently, experimental and theoretical studies on the water system are very active and noticeable. A transferable intermolecular potential seven points approach including fluctuation charges and flexible body (ABEEM-7P) based on a combination of the atom-bond electronegativity equalization and molecular mechanics (ABEEM/MM), and its application to small water clusters are explored and tested in this paper. The consistent combination of ABEEM and molecular mechanics (MM) is to take the ABEEM charges of atoms, bonds, and lone-pair electrons into the intermolecular electrostatic interaction term in molecular mechanics. To examine the charge transfer we have used two models coming from the charge constraint types: one is a charge neutrality constraint on whole water system and the other is on each water molecule. Compared with previous water force fields, the ABEEM-7P model has two characters: (1) the ABEEM-7P model not only presents the electrostatic interaction of atoms, bonds and lone-pair electrons and their changing in respond to different ambient environment but also introduces "the hydrogen bond interaction region" in which a new parameter k(lp,H)(R(lp,H)) is used to describe the electrostatic interaction of the lone-pair electron and the hydrogen atom which can form the hydrogen bond; (2) nonrigid but flexible water body permitting the vibration of the bond length and angle is allowed due to the combination of ABEEM and molecular mechanics, and for van der Waals interaction the ABEEM-7P model takes an all atom-atom interaction, i.e., oxygen-oxygen, hydrogen-hydrogen, oxygen-hydrogen interaction into account. The ABEEM-7P model based on ABEEM/MM gives quite accurate predictions for gas-phase state properties of the small water clusters (H(2)O)(n) (n=2-6), such as optimized geometries, monomer dipole moments, vibrational frequencies, and cluster interaction energies. Due to its explicit description of charges and the hydrogen bond, the ABEEM-7P model will be applied to discuss properties of liquid water, ice, aqueous solutions, and biological systems.

SLUG - stochastically lighting up galaxies - III. A suite of tools for simulated photometry, spectroscopy, and Bayesian inference with stochastic stellar populations

NASA Astrophysics Data System (ADS)

Krumholz, Mark R.; Fumagalli, Michele; da Silva, Robert L.; Rendahl, Theodore; Parra, Jonathan

2015-09-01

Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such as those found in individual star clusters, star-forming dwarf galaxies, and small segments of spiral galaxies, require that the population be treated stochastically. Conversely, accurate deductions of the properties of such objects also require consideration of stochasticity. Here we describe a comprehensive suite of modular, open-source software tools for tackling these related problems. These include the following: a greatly-enhanced version of the SLUG code introduced by da Silva et al., which computes spectra and photometry for stochastically or deterministically sampled stellar populations with nearly arbitrary star formation histories, clustering properties, and initial mass functions; CLOUDY_SLUG, a tool that automatically couples SLUG-computed spectra with the CLOUDY radiative transfer code in order to predict stochastic nebular emission; BAYESPHOT, a general-purpose tool for performing Bayesian inference on the physical properties of stellar systems based on unresolved photometry; and CLUSTER_SLUG and SFR_SLUG, a pair of tools that use BAYESPHOT on a library of SLUG models to compute the mass, age, and extinction of mono-age star clusters, and the star formation rate of galaxies, respectively. The latter two tools make use of an extensive library of pre-computed stellar population models, which are included in the software. The complete package is available at http://www.slugsps.com.

A second generation distributed point polarizable water model.

PubMed

Kumar, Revati; Wang, Fang-Fang; Jenness, Glen R; Jordan, Kenneth D

2010-01-07

A distributed point polarizable model (DPP2) for water, with explicit terms for charge penetration, induction, and charge transfer, is introduced. The DPP2 model accurately describes the interaction energies in small and large water clusters and also gives an average internal energy per molecule and radial distribution functions of liquid water in good agreement with experiment. A key to the success of the model is its accurate description of the individual terms in the n-body expansion of the interaction energies.

PHOTONICS AND NANOTECHNOLOGY Pulsed laser ablation of binary semiconductors: mechanisms of vaporisation and cluster formation

NASA Astrophysics Data System (ADS)

Bulgakov, A. V.; Evtushenko, A. B.; Shukhov, Yu G.; Ozerov, I.; Marin, W.

2010-12-01

Formation of small clusters during pulsed ablation of two binary semiconductors, zinc oxide and indium phosphide, in vacuum by UV, visible, and IR laser radiation is comparatively studied. The irradiation conditions favourable for generation of neutral and charged ZnnOm and InnPm clusters of different stoichiometry in the ablation products are found. The size and composition of the clusters, their expansion dynamics and reactivity are analysed by time-of-flight mass spectrometry. A particular attention is paid to the mechanisms of ZnO and InP ablation as a function of laser fluence, with the use of different ablation models. It is established that ZnO evapourates congruently in a wide range of irradiation conditions, while InP ablation leads to enrichment of the target surface with indium. It is shown that this radically different character of semiconductor ablation determines the composition of the nanostructures formed: zinc oxide clusters are mainly stoichiometric, whereas InnPm particles are significantly enriched with indium.

OGLE Collection of Star Clusters. New Objects in the Magellanic Bridge and the Outskirts of the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sitek, M.; Szymański, M. K.; Udalski, A.; Skowron, D. M.; Kostrzewa-Rutkowska, Z.; Skowron, J.; Karczmarek, P.; Cieślar, M.; Wyrzykowski, Ł.; Kozłowski, S.; Pietrukowicz, P.; Soszyński, I.; Mróz, P.; Pawlak, M.; Poleski, R.; Ulaczyk, K.

2017-12-01

The Magellanic System (MS) encompasses the nearest neighbors of the Milky Way, the Large (LMC) and Small (SMC) Magellanic Clouds, and the Magellanic Bridge (MBR). This system contains a diverse sample of star clusters. Their parameters, such as the spatial distribution, chemical composition and age distribution yield important information about the formation scenario of the whole Magellanic System. Using deep photometric maps compiled in the fourth phase of the Optical Gravitational Lensing Experiment (OGLE-IV) we present the most complete catalog of star clusters in the Magellanic System ever constructed from homogeneous, long time-scale photometric data. In this second paper of the series, we show the collection of star clusters found in the area of about 360 square degrees in the MBR and in the outer regions of the SMC. Our sample contains 198 visually identified star cluster candidates, 75 of which were not listed in any of the previously published catalogs. The new discoveries are mainly young small open clusters or clusters similar to associations.

Solving the scalability issue in quantum-based refinement: Q|R#1.

PubMed

Zheng, Min; Moriarty, Nigel W; Xu, Yanting; Reimers, Jeffrey R; Afonine, Pavel V; Waller, Mark P

2017-12-01

Accurately refining biomacromolecules using a quantum-chemical method is challenging because the cost of a quantum-chemical calculation scales approximately as n m , where n is the number of atoms and m (≥3) is based on the quantum method of choice. This fundamental problem means that quantum-chemical calculations become intractable when the size of the system requires more computational resources than are available. In the development of the software package called Q|R, this issue is referred to as Q|R#1. A divide-and-conquer approach has been developed that fragments the atomic model into small manageable pieces in order to solve Q|R#1. Firstly, the atomic model of a crystal structure is analyzed to detect noncovalent interactions between residues, and the results of the analysis are represented as an interaction graph. Secondly, a graph-clustering algorithm is used to partition the interaction graph into a set of clusters in such a way as to minimize disruption to the noncovalent interaction network. Thirdly, the environment surrounding each individual cluster is analyzed and any residue that is interacting with a particular cluster is assigned to the buffer region of that particular cluster. A fragment is defined as a cluster plus its buffer region. The gradients for all atoms from each of the fragments are computed, and only the gradients from each cluster are combined to create the total gradients. A quantum-based refinement is carried out using the total gradients as chemical restraints. In order to validate this interaction graph-based fragmentation approach in Q|R, the entire atomic model of an amyloid cross-β spine crystal structure (PDB entry 2oNA) was refined.

The Chemistry of Population III Supernova Ejecta. II. The Nucleation of Molecular Clusters as a Diagnostic for Dust in the Early Universe

NASA Astrophysics Data System (ADS)

Cherchneff, Isabelle; Dwek, Eli

2010-04-01

We study the formation of molecular precursors to dust in the ejecta of Population III supernovae (Pop. III SNe) using a chemical kinetic approach to follow the evolution of small dust cluster abundances from day 100 to day 1000 after explosion. Our work focuses on zero-metallicity 20 M sun and 170 M sun progenitors, and we consider fully macroscopically mixed and unmixed ejecta. The dust precursors comprise molecular chains, rings, and small clusters of chemical composition relevant to the initial elemental composition of the ejecta under study. The nucleation stage for small silica, metal oxides and sulfides, pure metal, and carbon clusters is described with a new chemical reaction network highly relevant to the kinetic description of dust formation in hot circumstellar environments. We consider the effect of the pressure dependence of critical nucleation rates and test the impact of microscopically mixed He+ on carbon dust formation. Two cases of metal depletion on silica clusters (full and no depletion) are considered to derive upper limits to the amounts of dust produced in SN ejecta at 1000 days, while the chemical composition of clusters gives a prescription for the type of dust formed in Pop. III SNe. We show that the cluster mass produced in the fully mixed ejecta of a 170 M sun progenitor is ~ 25 M sun whereas its 20 M sun counterpart forms ~ 0.16 M sun of clusters. The unmixed ejecta of a 170 M sun progenitor SN synthesize ~5.6 M sun of small clusters, while its 20 M sun counterpart produces ~0.103 M sun. Our results point to smaller amounts of dust formed in the ejecta of Pop. III SNe by a factor of ~ 5 compared to values derived by previous studies, and to different dust chemical compositions. Such deviations result from some erroneous assumptions made, the inappropriate use of classical nucleation theory to model dust formation, and the omission of the synthesis of molecules in SN ejecta. We also find that the unmixed ejecta of massive Pop. III SNe chiefly form silica and/or silicates, and pure silicon grains whereas their lower mass counterparts form a dust mixture dominated by silica and/or silicates, pure silicon, and iron sulfides. Amorphous carbon can only condense via the nucleation of carbon chains and rings characteristic of the synthesis of fullerenes when the ejecta carbon-rich zone is deprived of He+. The first dust enrichment to the primordial gas in the early universe from Pop. III massive SN comprises primarily pure silicon, silica, and silicates. If carbon dust is present at redshift z > 6, alternative dust sources must be considered.

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

Setyawan, Wahyu; Nandipati, Giridhar; Kurtz, Richard J.

The stability of tungsten self-interstitial atom (SIA) clusters is studied using first-principles methods. Clusters from one to seven SIAs are systematically explored from 1264 unique configurations. Finite-size effect of the simulation cell is corrected based on the scaling of formation energy versus inverse volume cell. Furthermore, the accuracy of the calculations is improved by treating the 5p semicore states as valence states. Configurations of the three most stable clusters in each cluster size n are presented, which consist of parallel [111] dumbbells. The evolution of these clusters leading to small dislocation loops is discussed. The binding energy of size-n clustersmore » is analyzed relative to an n → (n-1) + 1 dissociation and is shown to increase with size. Extrapolation for n > 7 is presented using a dislocation loop model. In addition, the interaction of these clusters with a substitutional Re, Os, or Ta solute is explored by replacing one of the dumbbells with the solute. Re and Os strongly attract these clusters, but Ta strongly repels. The strongest interaction is found when the solute is located on the periphery of the cluster rather than in the middle. The magnitude of this interaction decreases with cluster size. Empirical fits to describe the trend of the solute binding energy are presented.« less

The Initial Mass Function of the Arches Cluster

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Self-organization in a bimotility mixture of model microswimmers

NASA Astrophysics Data System (ADS)

Agrawal, Adyant; Babu, Sujin B.

2018-02-01

We study the cooperation and segregation dynamics in a bimotility mixture of microorganisms which swim at low Reynolds numbers via periodic deformations along the body. We employ a multiparticle collision dynamics method to simulate a two component mixture of artificial swimmers, termed as Taylor lines, which differ from each other only in the propulsion speed. The analysis reveals that a contribution of slower swimmers towards clustering, on average, is much larger as compared to the faster ones. We notice distinctive self-organizing dynamics, depending on the percentage difference in the speed of the two kinds. If this difference is large, the faster ones fragment the clusters of the slower ones in order to reach the boundary and form segregated clusters. Contrarily, when it is small, both kinds mix together at first, the faster ones usually leading the cluster and then gradually the slower ones slide out thereby also leading to segregation.

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

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

The vapor–liquid nucleation in a dense Lennard-Jones system is studied analytically and numerically. A solution of the nucleation kinetic equations, which includes the elementary processes of condensation/evaporation involving the lightest clusters, is obtained, and the nucleation rate is calculated. Based on the equation of state for the cluster vapor, the pre-exponential factor is obtained. The latter diverges as a spinodal is reached, which results in the nucleation enhancement. The work of critical cluster formation is calculated using the previously developed two-parameter model (TPM) of small clusters. A simple expression for the nucleation rate is deduced and it is shown thatmore » the work of cluster formation is reduced for a dense vapor. This results in the nucleation enhancement as well. To verify the TPM, a simulation is performed that mimics a steady-state nucleation experiments in the thermal diffusion cloud chamber. The nucleating vapor with and without a carrier gas is simulated using two different thermostats for the monomers and clusters. The TPM proves to match the simulation results of this work and of other studies.« less

Spectroscopic Study of Local Interactions of Platinum in Small [CexOy]Ptx' - Clusters

NASA Astrophysics Data System (ADS)

Ray, Manisha; Kafader, Jared O.; Chick Jarrold, Caroline

2016-06-01

Cerium oxide is a good ionic conductor, and the conductivity can be enhanced with oxygen vacancies and doping. This conductivity may play an important role in the enhancement of noble or coinage metal toward the water-gas shift reaction when supported by cerium oxide. The ceria-supported platinum catalyst in particular has received much attention because of higher activity at lower temperatures (LT) compared to the most common commercial LT-WGS catalyst. We have used a combination of anion photoelectron spectroscopy and density functional theory calculations to study the interesting molecular and electronic structures and properties of cluster models of ceria-supported platinum. [CexOy]Ptx' - (x,x'=1,2 ; y≤2x') clusters exhibit evidence of ionic bonding possible because of the high electron affinity of Pt and the low ionization potential of cerium oxide clusters. In addition, Pt- is a common daughter ion resulting from photodissociation of [CexOy]Ptx' - clusters. Finally, several of the anion and neutral clusters have profoundly different structures. These features may play a role in the enhancement of catalytic activity toward the water-gas shift reaction.

Adsorption and Formation of Small Na Clusters on Pristine and Double-Vacancy Graphene for Anodes of Na-Ion Batteries.

PubMed

Liang, Zhicong; Fan, Xiaofeng; Zheng, Weitao; Singh, David J

2017-05-24

Layered carbon is a likely anode material for Na-ion batteries (NIBs). Graphitic carbon has a low capacity of approximately 35 (mA h)/g due to the formation of NaC 64 . Using first-principles methods including van der Waals interactions, we analyze the adsorption of Na ions and clusters on graphene in the context of anodes. The interaction between Na ions and graphene is found to be weak. Small Na clusters are not stable on the surface of pristine graphene in the electrochemical environment of NIBs. However, we find that Na ions and clusters can be stored effectively on defected graphene that has double vacancies. In addition, the adsorption energy of small Na clusters near a double vacancy is found to decrease with increasing cluster size. With high concentrations of vacancies the capacity of Na on defective graphene is found to be as much as 10-30 times higher than that of graphitic carbon.

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

PubMed

Kornilov, Oleg; Toennies, J Peter

2015-02-21

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

Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

PubMed Central

Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

2016-01-01

Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

PubMed

Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

2015-10-01

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

Small scale clustering of late forming dark matter

NASA Astrophysics Data System (ADS)

Agarwal, S.; Corasaniti, P.-S.; Das, S.; Rasera, Y.

2015-09-01

We perform a study of the nonlinear clustering of matter in the late-forming dark matter (LFDM) scenario in which dark matter results from the transition of a nonminimally coupled scalar field from radiation to collisionless matter. A distinct feature of this model is the presence of a damped oscillatory cutoff in the linear matter power spectrum at small scales. We use a suite of high-resolution N-body simulations to study the imprints of LFDM on the nonlinear matter power spectrum, the halo mass and velocity functions and the halo density profiles. The model largely satisfies high-redshift matter power spectrum constraints from Lyman-α forest measurements, while it predicts suppressed abundance of low-mass halos (˜109- 1010 h-1 M⊙ ) at all redshifts compared to a vanilla Λ CDM model. The analysis of the LFDM halo velocity function shows a better agreement than the Λ CDM prediction with the observed abundance of low-velocity galaxies in the local volume. Halos with mass M ≳1011 h-1 M⊙ show minor departures of the density profiles from Λ CDM expectations, while smaller-mass halos are less dense, consistent with the fact that they form later than their Λ CDM counterparts.

X ray opacity in cluster cooling flows

NASA Technical Reports Server (NTRS)

Wise, Michael W.; Sarazin, Craig L.

1993-01-01

We have calculated the emergent x-ray properties for a set of spherically symmetric, steady-state cluster cooling flow models including the effects of radiative transfer. Opacity due to resonant x-ray lines, photoelectric absorption, and electron scattering have been included in these calculations, and homogeneous and inhomogeneous gas distributions were considered. The effects of photoionization opacity are small for both types of models. In contrast, resonant line optical depths can be quite high in both homogeneous and inhomogeneous models. The presence of turbulence in the gas can significantly lower the line opacity. We find that integrated x-ray spectra for the flow cooling now are only slightly affected by radiative transfer effects. However x-ray line surface brightness profiles can be dramatically affected by radiative transfer. Line profiles are also strongly affected by transfer effects. The combined effects of opacity and inflow cause many of the lines in optically thick models to be asymmetrical.

Modeling carbonaceous particle formation in an argon graphite cathode dc discharge

NASA Astrophysics Data System (ADS)

Michau, A.; Lombardi, G.; Colina Delacqua, L.; Redolfi, M.; Arnas, C.; Bonnin, X.; Hassouni, K.

2010-12-01

We develop a model for the nucleation, growth and transport of carbonaceous dust particles in a non-reactive gas dc discharge where the carbon source is provided by cathode sputtering. We consider only the initial phase of the discharge when the dust charge density remains small with respect to the electron density. We find that an electric field reversal at the entrance of the negative glow region promotes trapping of negatively charged clusters and dust particles, confining them for long times in the plasma and favoring molecular growth. An essential ingredient for this process is electron attachment, which negatively charges the initially neutral clusters. We perform sensitivity studies on several number parameters: size of the largest molecular edifice, sticking coefficient, etc.

Constraining AGN triggering mechanisms through the clustering analysis of active black holes

NASA Astrophysics Data System (ADS)

Gatti, M.; Shankar, F.; Bouillot, V.; Menci, N.; Lamastra, A.; Hirschmann, M.; Fiore, F.

2016-02-01

The triggering mechanisms for active galactic nuclei (AGN) are still debated. Some of the most popular ones include galaxy interactions (IT) and disc instabilities (DIs). Using an advanced semi-analytic model (SAM) of galaxy formation, coupled to accurate halo occupation distribution modelling, we investigate the imprint left by each separate triggering process on the clustering strength of AGN at small and large scales. Our main results are as follows: (I) DIs, irrespective of their exact implementation in the SAM, tend to fall short in triggering AGN activity in galaxies at the centre of haloes with Mh > 1013.5 h-1 M⊙. On the contrary, the IT scenario predicts abundance of active central galaxies that generally agrees well with observations at every halo mass. (II) The relative number of satellite AGN in DIs at intermediate-to-low luminosities is always significantly higher than in IT models, especially in groups and clusters. The low AGN satellite fraction predicted for the IT scenario might suggest that different feeding modes could simultaneously contribute to the triggering of satellite AGN. (III) Both scenarios are quite degenerate in matching large-scale clustering measurements, suggesting that the sole average bias might not be an effective observational constraint. (IV) Our analysis suggests the presence of both a mild luminosity and a more consistent redshift dependence in the AGN clustering, with AGN inhabiting progressively less massive dark matter haloes as the redshift increases. We also discuss the impact of different observational selection cuts in measuring AGN clustering, including possible discrepancies between optical and X-ray surveys.

Testing cold dark matter models using Hubble flow variations

NASA Astrophysics Data System (ADS)

Shi, Xiangdong

1999-05-01

COBE-normalized flat (matter plus cosmological constant) and open cold dark matter (CDM) models are tested by comparing their expected Hubble flow variations and the observed variations in a Type Ia supernova sample and a Tully-Fisher cluster sample. The test provides a probe of the CDM power spectrum on scales of 0.02h Mpc^-1<~ k<~ 0.2h Mpc^-1, free of the bias factor b. The results favour a low matter content universe, or a flat matter-dominated universe with a very low Hubble constant and/or a very small spectral index n^ps, with the best fits having Ο_0~ 0.3 to 0.4. The test is found to be more discriminative to the open CDM models than to the flat CDM models. For example, the test results are found to be compatible with those from the X-ray cluster abundance measurements at smaller length-scales, and consistent with the galaxy and cluster correlation analysis of Peacock & Dodds at similar length-scales, if our universe is flat; but the results are marginally incompatible with the X-ray cluster abundance measurements if our universe is open. The open CDM results are consistent with that of Peacock & Dodds only if the matter density of the universe is less than about 60 per cent of the critical density. The shortcoming of the test is discussed, so are ways to minimize it.

Competition of information channels in the spreading of innovations

NASA Astrophysics Data System (ADS)

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Critical behavior of a two-step contagion model with multiple seeds

NASA Astrophysics Data System (ADS)

Choi, Wonjun; Lee, Deokjae; Kahng, B.

2017-06-01

A two-step contagion model with a single seed serves as a cornerstone for understanding the critical behaviors and underlying mechanism of discontinuous percolation transitions induced by cascade dynamics. When the contagion spreads from a single seed, a cluster of infected and recovered nodes grows without any cluster merging process. However, when the contagion starts from multiple seeds of O (N ) where N is the system size, a node weakened by a seed can be infected more easily when it is in contact with another node infected by a different pathogen seed. This contagion process can be viewed as a cluster merging process in a percolation model. Here we show analytically and numerically that when the density of infectious seeds is relatively small but O (1 ) , the epidemic transition is hybrid, exhibiting both continuous and discontinuous behavior, whereas when it is sufficiently large and reaches a critical point, the transition becomes continuous. We determine the full set of critical exponents describing the hybrid and the continuous transitions. Their critical behaviors differ from those in the single-seed case.

Competition of information channels in the spreading of innovations.

PubMed

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Hydration of copper(II): new insights from density functional theory and the COSMO solvation model.

PubMed

Bryantsev, Vyacheslav S; Diallo, Mamadou S; van Duin, Adri C T; Goddard, William A

2008-09-25

The hydrated structure of the Cu(II) ion has been a subject of ongoing debate in the literature. In this article, we use density functional theory (B3LYP) and the COSMO continuum solvent model to characterize the structure and stability of [Cu(H2O)n](2+) clusters as a function of coordination number (4, 5, and 6) and cluster size (n = 4-18). We find that the most thermodynamically favored Cu(II) complexes in the gas phase have a very open four-coordinate structure. They are formed from a stable square-planar [Cu(H2O)8](2+) core stabilized by an unpaired electron in the Cu(II) ion d(x(2)-y(2)) orbital. This is consistent with cluster geometries suggested by recent mass-spectrometric experiments. In the aqueous phase, we find that the more compact five-coordinate square-pyramidal geometry is more stable than either the four-coordinate or six-coordinate clusters in agreement with recent combined EXAFS and XANES studies of aqueous solutions of Cu(II). However, a small energetic difference (approximately 1.4 kcal/mol) between the five- and six-coordinate models with two full hydration shells around the metal ion suggests that both forms may coexist in solution.

Plasma hydrodynamics of the intense laser-cluster interaction*

NASA Astrophysics Data System (ADS)

Milchberg, Howard

2002-11-01

We present a 1D hydrodynamic model of the intense laser-cluster interaction in which the laser field is treated self-consistently. We find that for clusters initially as small as 25Å in radius, for which the hydrodynamic model is appropriate, nonuniform expansion of the heated material results in long-time resonance of the laser field at the critical density plasma layer. A significant result of this is that the ponderomotive force, which is enhanced at the critical density surface, can be large enough to strongly modify the plasma hydrodynamics, even at laser intensities as low as 10^15 W/cm^2 for 800 nm laser pulses. Recent experiments in EUV and x-ray generation as a function of laser pulsewidth [1], and femtosecond time-resolved measurements of cluster transient polarizability [2] provide strong support for the basic physics of this model. Recent results using a 2D hybrid fluid/PIC code show qualitative agreement with the 1D hydrocode [3]. *Work supported by the National Science Foundation and the EUV-LLC. 1. E. Parra, I. Alexeev, J. Fan, K. Kim, S.J. McNaught, and H. M. Milchberg, Phys. Rev. E 62, R5931 (2000). 2. K.Y. Kim, I. Alexeev, E. Parra, and H.M. Milchberg, submitted for publication. 3. T. Taguchi, T. Antonsen, and H.M Milchberg, this meeting.

The Star Cluster System in the Local Group Starburst Galaxy IC 10

NASA Astrophysics Data System (ADS)

Lim, Sungsoon; Lee, Myung Gyoon

2015-05-01

We present a survey of star clusters in the halo of IC 10, a starburst galaxy in the Local Group, based on Subaru R-band images and NOAO Local Group Survey UBVRI images. We find five new star clusters. All of these star clusters are located far from the center of IC 10, while previously known star clusters are mostly located in the main body. Interestingly, the distribution of these star clusters shows an asymmetrical structure elongated along the east and southwest directions. We derive UBVRI photometry of 66 star clusters, including these new star clusters, as well as previously known star clusters. Ages of the star clusters are estimated from a comparison of their UBVRI spectral energy distribution with the simple stellar population models. We find that the star clusters in the halo are all older than 1 Gyr, while those in the main body have various ages, from very young (several Myr) to old (\\gt 1 Gyr). The young clusters (\\lt 10 Myr) are mostly located in the Hα emission regions and are concentrated on a small region at 2\\prime\\prime in the southeast direction from the galaxy center, while the old clusters are distributed in a wider area than the disk. Intermediate-age clusters (∼100 Myr) are found in two groups. One is close to the location of the young clusters and the other is at ∼ 4\\prime\\prime from the location of the young clusters. The latter may be related to past mergers or tidal interaction.

Balance of baryon number in the quark coalescence model

NASA Astrophysics Data System (ADS)

Bialas, A.; Rafelski, J.

2006-02-01

The charge and baryon balance functions are studied in the coalescence hadronization mechanism of quark-gluon plasma. Assuming that in the plasma phase the qqbar pairs form uncorrelated clusters whose decay is also uncorrelated, one can understand the observed small width of the charge balance function in the Gaussian approximation. The coalescence model predicts even smaller width of the baryon-antibaryon balance function: σBBbar /σ+ - =√{ 2 / 3 }.

Effect of dose and size on defect engineering in carbon cluster implanted silicon wafers

NASA Astrophysics Data System (ADS)

Okuyama, Ryosuke; Masada, Ayumi; Shigematsu, Satoshi; Kadono, Takeshi; Hirose, Ryo; Koga, Yoshihiro; Okuda, Hidehiko; Kurita, Kazunari

2018-01-01

Carbon-cluster-ion-implanted defects were investigated by high-resolution cross-sectional transmission electron microscopy toward achieving high-performance CMOS image sensors. We revealed that implantation damage formation in the silicon wafer bulk significantly differs between carbon-cluster and monomer ions after implantation. After epitaxial growth, small and large defects were observed in the implanted region of carbon clusters. The electron diffraction pattern of both small and large defects exhibits that from bulk crystalline silicon in the implanted region. On the one hand, we assumed that the silicon carbide structure was not formed in the implanted region, and small defects formed because of the complex of carbon and interstitial silicon. On the other hand, large defects were hypothesized to originate from the recrystallization of the amorphous layer formed by high-dose carbon-cluster implantation. These defects are considered to contribute to the powerful gettering capability required for high-performance CMOS image sensors.

Thermodynamic scaling of dynamic properties of liquid crystals: Verifying the scaling parameters using a molecular model

NASA Astrophysics Data System (ADS)

Satoh, Katsuhiko

2013-08-01

The thermodynamic scaling of molecular dynamic properties of rotation and thermodynamic parameters in a nematic phase was investigated by a molecular dynamic simulation using the Gay-Berne potential. A master curve for the relaxation time of flip-flop motion was obtained using thermodynamic scaling, and the dynamic property could be solely expressed as a function of TV^{γ _τ }, where T and V are the temperature and volume, respectively. The scaling parameter γτ was in excellent agreement with the thermodynamic parameter Γ, which is the logarithm of the slope of a line plotted for the temperature and volume at constant P2. This line was fairly linear, and as good as the line for p-azoxyanisole or using the highly ordered small cluster model. The equivalence relation between Γ and γτ was compared with results obtained from the highly ordered small cluster model. The possibility of adapting the molecular model for the thermodynamic scaling of other dynamic rotational properties was also explored. The rotational diffusion constant and rotational viscosity coefficients, which were calculated using established theoretical and experimental expressions, were rescaled onto master curves with the same scaling parameters. The simulation illustrates the universal nature of the equivalence relation for liquid crystals.

Excitonic Order and Superconductivity in the Two-Orbital Hubbard Model: Variational Cluster Approach

NASA Astrophysics Data System (ADS)

Fujiuchi, Ryo; Sugimoto, Koudai; Ohta, Yukinori

2018-06-01

Using the variational cluster approach based on the self-energy functional theory, we study the possible occurrence of excitonic order and superconductivity in the two-orbital Hubbard model with intra- and inter-orbital Coulomb interactions. It is known that an antiferromagnetic Mott insulator state appears in the regime of strong intra-orbital interaction, a band insulator state appears in the regime of strong inter-orbital interaction, and an excitonic insulator state appears between them. In addition to these states, we find that the s±-wave superconducting state appears in the small-correlation regime, and the dx2 - y2-wave superconducting state appears on the boundary of the antiferromagnetic Mott insulator state. We calculate the single-particle spectral function of the model and compare the band gap formation due to the superconducting and excitonic orders.

Invasive advance of an advantageous mutation: nucleation theory.

PubMed

O'Malley, Lauren; Basham, James; Yasi, Joseph A; Korniss, G; Allstadt, Andrew; Caraco, Thomas

2006-12-01

For sedentary organisms with localized reproduction, spatially clustered growth drives the invasive advance of a favorable mutation. We model competition between two alleles where recurrent mutation introduces a genotype with a rate of local propagation exceeding the resident's rate. We capture ecologically important properties of the rare invader's stochastic dynamics by assuming discrete individuals and local neighborhood interactions. To understand how individual-level processes may govern population patterns, we invoke the physical theory for nucleation of spatial systems. Nucleation theory discriminates between single-cluster and multi-cluster dynamics. A sufficiently low mutation rate, or a sufficiently small environment, generates single-cluster dynamics, an inherently stochastic process; a favorable mutation advances only if the invader cluster reaches a critical radius. For this mode of invasion, we identify the probability distribution of waiting times until the favored allele advances to competitive dominance, and we ask how the critical cluster size varies as propagation or mortality rates vary. Increasing the mutation rate or system size generates multi-cluster invasion, where spatial averaging produces nearly deterministic global dynamics. For this process, an analytical approximation from nucleation theory, called Avrami's Law, describes the time-dependent behavior of the genotype densities with remarkable accuracy.

Euchromatic Transposon Insertions Trigger Production of Novel Pi- and Endo-siRNAs at the Target Sites in the Drosophila Germline

PubMed Central

Olovnikov, Ivan; Abramov, Yuri; Kalmykova, Alla

2014-01-01

The control of transposable element (TE) activity in germ cells provides genome integrity over generations. A distinct small RNA–mediated pathway utilizing Piwi-interacting RNAs (piRNAs) suppresses TE expression in gonads of metazoans. In the fly, primary piRNAs derive from so-called piRNA clusters, which are enriched in damaged repeated sequences. These piRNAs launch a cycle of TE and piRNA cluster transcript cleavages resulting in the amplification of piRNA and TE silencing. Using genome-wide comparison of TE insertions and ovarian small RNA libraries from two Drosophila strains, we found that individual TEs inserted into euchromatic loci form novel dual-stranded piRNA clusters. Formation of the piRNA-generating loci by active individual TEs provides a more potent silencing response to the TE expansion. Like all piRNA clusters, individual TEs are also capable of triggering the production of endogenous small interfering (endo-si) RNAs. Small RNA production by individual TEs spreads into the flanking genomic regions including coding cellular genes. We show that formation of TE-associated small RNA clusters can down-regulate expression of nearby genes in ovaries. Integration of TEs into the 3′ untranslated region of actively transcribed genes induces piRNA production towards the 3′-end of transcripts, causing the appearance of genic piRNA clusters, a phenomenon that has been reported in different organisms. These data suggest a significant role of TE-associated small RNAs in the evolution of regulatory networks in the germline. PMID:24516406

Kinetics of Aggregation with Choice

DOE PAGES

Ben-Naim, Eli; Krapivsky, Paul

2016-12-01

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

OGLE Collection of Star Clusters. New Objects in the Outskirts of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sitek, M.; Szymański, M. K.; Skowron, D. M.; Udalski, A.; Kostrzewa-Rutkowska, Z.; Skowron, J.; Karczmarek, P.; Cieślar, M.; Wyrzykowski, Ł.; Kozłowski, S.; Pietrukowicz, P.; Soszyński, I.; Mróz, P.; Pawlak, M.; Poleski, R.; Ulaczyk, K.

2016-09-01

The Magellanic System (MS), consisting of the Large Magellanic Cloud (LMC), the Small Magellanic Cloud (SMC) and the Magellanic Bridge (MBR), contains diverse sample of star clusters. Their spatial distribution, ages and chemical abundances may provide important information about the history of formation of the whole System. We use deep photometric maps derived from the images collected during the fourth phase of the Optical Gravitational Lensing Experiment (OGLE-IV) to construct the most complete catalog of star clusters in the Large Magellanic Cloud using the homogeneous photometric data. In this paper we present the collection of star clusters found in the area of about 225 square degrees in the outer regions of the LMC. Our sample contains 679 visually identified star cluster candidates, 226 of which were not listed in any of the previously published catalogs. The new clusters are mainly young small open clusters or clusters similar to associations.

Convergent chaos

NASA Astrophysics Data System (ADS)

Pradas, Marc; Pumir, Alain; Huber, Greg; Wilkinson, Michael

2017-07-01

Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion should be refined. Despite their overall intrinsic instability, trajectories may be very strongly convergent in phase space over extremely long periods, as revealed by our investigation of a simple chaotic system (a realistic model for small bodies in a turbulent flow). We establish that this strong convergence is a multi-facetted phenomenon, in which the clustering is intense, widespread and balanced by lacunarity of other regions. Power laws, indicative of scale-free features, characterize the distribution of particles in the system. We use large-deviation and extreme-value statistics to explain the effect. Our results show that the interpretation of the ‘butterfly effect’ needs to be carefully qualified. We argue that the combination of mixing and clustering processes makes our specific model relevant to understanding the evolution of simple organisms. Lastly, this notion of convergent chaos, which implies the existence of conditions for which uncertainties are unexpectedly small, may also be relevant to the valuation of insurance and futures contracts.

Investigation of Metal and Metal Oxide Clusters Small Enough to Constitute the Critical Size for Gas Phase Nucleation in Combustion Processes.

DTIC Science & Technology

1980-11-01

Ao-A093 950 NORTHWESTERN UNIV EVANSTON IL DEPT OF M4ECHANICAL ND-ETC F/S 7/4 INVESTIGATION OF 1ETAL AND METAL OXIDE CLUSTERS S1ALL ENOUGH TO--ETC(U...34 " 18. SUPPLEMENTARY NOTES 19. KEY WORDS (Continue on reveroe side if necessary snd Identify by block number) Clusters , Nucleation, Molecular Beam, Free...contract a variety of techniques have been employed to study the properties of small atomic and molecular clusters formed in the gas phase via

Ultra-small rhenium clusters supported on graphene.

PubMed

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J; Mariscal, Marcelo M; Yacaman, Miguel José

2015-03-28

The adsorption of very small rhenium clusters (2-13 atoms) supported on graphene was studied by high-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional theory calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones.

Ultra-small rhenium clusters supported on graphene

PubMed Central

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J.; Mariscal, Marcelo M.; Yacaman, Miguel José

2015-01-01

The adsorption of very small rhenium clusters (2 – 13 atoms) supported on graphene was studied with high annular dark field - scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones. PMID:25721176

Topology in two dimensions. IV - CDM models with non-Gaussian initial conditions

NASA Astrophysics Data System (ADS)

Coles, Peter; Moscardini, Lauro; Plionis, Manolis; Lucchin, Francesco; Matarrese, Sabino; Messina, Antonio

1993-02-01

The results of N-body simulations with both Gaussian and non-Gaussian initial conditions are used here to generate projected galaxy catalogs with the same selection criteria as the Shane-Wirtanen counts of galaxies. The Euler-Poincare characteristic is used to compare the statistical nature of the projected galaxy clustering in these simulated data sets with that of the observed galaxy catalog. All the models produce a topology dominated by a meatball shift when normalized to the known small-scale clustering properties of galaxies. Models characterized by a positive skewness of the distribution of primordial density perturbations are inconsistent with the Lick data, suggesting problems in reconciling models based on cosmic textures with observations. Gaussian CDM models fit the distribution of cell counts only if they have a rather high normalization but possess too low a coherence length compared with the Lick counts. This suggests that a CDM model with extra large scale power would probably fit the available data.

Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis

NASA Astrophysics Data System (ADS)

Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S.; Qian, Pei-Yuan

2015-03-01

Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning ``plug-and-play'' approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis.

PubMed

Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S; Qian, Pei-Yuan

2015-03-24

Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning "plug-and-play" approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

Reduction of N2 by supported tungsten clusters gives a model of the process by nitrogenase

PubMed Central

Murakami, Junichi; Yamaguchi, Wataru

2012-01-01

Metalloenzymes catalyze difficult chemical reactions under mild conditions. Mimicking their functions is a challenging task and it has been investigated using homogeneous systems containing metal complexes. The nitrogenase that converts N2 to NH3 under mild conditions is one of such enzymes. Efforts to realize the biological function have continued for more than four decades, which has resulted in several reports of reduction of N2, ligated to metal complexes in solutions, to NH3 by protonation under mild conditions. Here, we show that seemingly distinct supported small tungsten clusters in a dry environment reduce N2 under mild conditions like the nitrogenase. N2 is reduced to NH3 via N2H4 by addition of neutral H atoms, which agrees with the mechanism recently proposed for the N2 reduction on the active site of nitrogenase. The process on the supported clusters gives a model of the biological N2 reduction. PMID:22586517

Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys

NASA Astrophysics Data System (ADS)

Yang, Xiaohu; Mo, H. J.; Jing, Y. P.; van den Bosch, Frank C.; Chu, YaoQuan

2004-06-01

In two recent papers, we developed a powerful technique to link the distribution of galaxies to that of dark matter haloes by considering halo occupation numbers as a function of galaxy luminosity and type. In this paper we use these distribution functions to populate dark matter haloes in high-resolution N-body simulations of the standard ΛCDM cosmology with Ωm= 0.3, ΩΛ= 0.7 and σ8= 0.9. Stacking simulation boxes of 100 h-1 Mpc and 300 h-1 Mpc with 5123 particles each we construct mock galaxy redshift surveys out to a redshift of z= 0.2 with a numerical resolution that guarantees completeness down to 0.01L*. We use these mock surveys to investigate various clustering statistics. The predicted two-dimensional correlation function ξ(rp, π) reveals clear signatures of redshift space distortions. The projected correlation functions for galaxies with different luminosities and types, derived from ξ(rp, π), match the observations well on scales larger than ~3 h-1 Mpc. On smaller scales, however, the model overpredicts the clustering power by about a factor two. Modelling the `finger-of-God' effect on small scales reveals that the standard ΛCDM model predicts pairwise velocity dispersions (PVD) that are ~400 km s-1 too high at projected pair separations of ~1 h-1 Mpc. A strong velocity bias in massive haloes, with bvel≡σgal/σdm~ 0.6 (where σgal and σdm are the velocity dispersions of galaxies and dark matter particles, respectively) can reduce the predicted PVD to the observed level, but does not help to resolve the overprediction of clustering power on small scales. Consistent results can be obtained within the standard ΛCDM model only when the average mass-to-light ratio of clusters is of the order of 1000 (M/L)solar in the B-band. Alternatively, as we show by a simple approximation, a ΛCDM model with σ8~= 0.75 may also reproduce the observational results. We discuss our results in light of the recent WMAP results and the constraints on σ8 obtained independently from other observations.

Power spectrum for the small-scale Universe

NASA Astrophysics Data System (ADS)

Widrow, Lawrence M.; Elahi, Pascal J.; Thacker, Robert J.; Richardson, Mark; Scannapieco, Evan

2009-08-01

The first objects to arise in a cold dark matter (CDM) universe present a daunting challenge for models of structure formation. In the ultra small-scale limit, CDM structures form nearly simultaneously across a wide range of scales. Hierarchical clustering no longer provides a guiding principle for theoretical analyses and the computation time required to carry out credible simulations becomes prohibitively high. To gain insight into this problem, we perform high-resolution (N = 7203-15843) simulations of an Einstein-de Sitter cosmology where the initial power spectrum is P(k) ~ kn, with -2.5 <= n <= - 1. Self-similar scaling is established for n = -1 and -2 more convincingly than in previous, lower resolution simulations and for the first time, self-similar scaling is established for an n = -2.25 simulation. However, finite box-size effects induce departures from self-similar scaling in our n = -2.5 simulation. We compare our results with the predictions for the power spectrum from (one-loop) perturbation theory and demonstrate that the renormalization group approach suggested by McDonald improves perturbation theory's ability to predict the power spectrum in the quasi-linear regime. In the non-linear regime, our power spectra differ significantly from the widely used fitting formulae of Peacock & Dodds and Smith et al. and a new fitting formula is presented. Implications of our results for the stable clustering hypothesis versus halo model debate are discussed. Our power spectra are inconsistent with predictions of the stable clustering hypothesis in the high-k limit and lend credence to the halo model. Nevertheless, the fitting formula advocated in this paper is purely empirical and not derived from a specific formulation of the halo model.

Modeling Physical Processes at the Nanoscale—Insight into Self-Organization of Small Systems (abstract)

NASA Astrophysics Data System (ADS)

Proykova, Ana

2009-04-01

Essential contributions have been made in the field of finite-size systems of ingredients interacting with potentials of various ranges. Theoretical simulations have revealed peculiar size effects on stability, ground state structure, phases, and phase transformation of systems confined in space and time. Models developed in the field of pure physics (atomic and molecular clusters) have been extended and successfully transferred to finite-size systems that seem very different—small-scale financial markets, autoimmune reactions, and social group reactions to advertisements. The models show that small-scale markets diverge unexpectedly fast as a result of small fluctuations; autoimmune reactions are sequences of two discontinuous phase transitions; and social groups possess critical behavior (social percolation) under the influence of an external field (advertisement). Some predicted size-dependent properties have been experimentally observed. These findings lead to the hypothesis that restrictions on an object's size determine the object's total internal (configuration) and external (environmental) interactions. Since phases are emergent phenomena produced by self-organization of a large number of particles, the occurrence of a phase in a system containing a small number of ingredients is remarkable.

Transient regulation of three clustered tomato class-I small heat-shock chaperone genes by ethylene is mediated by SIMADS-RIN transcription factor

USDA-ARS?s Scientific Manuscript database

An intronless cluster of three class I small heat shock protein (sHSP) chaperone genes, Sl17.6, Sl20.0 and Sl20.1, resident on the short arm of chromosome 6 in tomato, was previously characterized (Goyal et al., 2012). This shsp chaperone gene cluster was found decorated with cis sequences known to ...

Cluster-to-cluster transformation among Au6, Au8 and Au11 nanoclusters.

PubMed

Ren, Xiuqing; Fu, Junhong; Lin, Xinzhang; Fu, Xuemei; Yan, Jinghui; Wu, Ren'an; Liu, Chao; Huang, Jiahui

2018-05-22

We present the cluster-to-cluster transformations among three gold nanoclusters, [Au6(dppp)4]2+ (Au6), [Au8(dppp)4Cl2]2+ (Au8) and [Au11(dppp)5]3+ (Au11). The conversion process follows a rule that states that the transformation of a small cluster to a large cluster is achieved through an oxidation process with an oxidizing agent (H2O2) or with heating, while the conversion of a large cluster to a small one occurs through a reduction process with a reducing agent (NaBH4). All the reactions were monitored using UV-Vis spectroscopy and ESI-MS. This work may provide an alternative approach to the synthesis of novel gold nanoclusters and a further understanding of the structural transformation relationship of gold nanoclusters.

Quasi-planar elemental clusters in pair interactions approximation

NASA Astrophysics Data System (ADS)

Chkhartishvili, Levan

2016-01-01

The pair-interactions approximation, when applied to describe elemental clusters, only takes into account bonding between neighboring atoms. According to this approach, isomers of wrapped forms of 2D clusters - nanotubular and fullerene-like structures - and truly 3D clusters, are generally expected to be more stable than their quasi-planar counterparts. This is because quasi-planar clusters contain more peripheral atoms with dangling bonds and, correspondingly, fewer atoms with saturated bonds. However, the differences in coordination numbers between central and peripheral atoms lead to the polarization of bonds. The related corrections to the molar binding energy can make small, quasi-planar clusters more stable than their 2D wrapped allotropes and 3D isomers. The present work provides a general theoretical frame for studying the relative stability of small elemental clusters within the pair interactions approximation.

Myeloid Clusters Are Associated with a Pro-Metastatic Environment and Poor Prognosis in Smoking-Related Early Stage Non-Small Cell Lung Cancer

PubMed Central

Zhang, Wang; Pal, Sumanta K.; Liu, Xueli; Yang, Chunmei; Allahabadi, Sachin; Bhanji, Shaira; Figlin, Robert A.; Yu, Hua; Reckamp, Karen L.

2013-01-01

Background This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients. Methods Uninvolved regional lymph node sections from 67 patients with stage I–III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment. Results CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01). Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049) and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055). The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively). Conclusions Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted. PMID:23717691

Cluster-guided imaging-based CFD analysis of airflow and particle deposition in asthmatic human lungs

NASA Astrophysics Data System (ADS)

Choi, Jiwoong; Leblanc, Lawrence; Choi, Sanghun; Haghighi, Babak; Hoffman, Eric; Lin, Ching-Long

2017-11-01

The goal of this study is to assess inter-subject variability in delivery of orally inhaled drug products to small airways in asthmatic lungs. A recent multiscale imaging-based cluster analysis (MICA) of computed tomography (CT) lung images in an asthmatic cohort identified four clusters with statistically distinct structural and functional phenotypes associating with unique clinical biomarkers. Thus, we aimed to address inter-subject variability via inter-cluster variability. We selected a representative subject from each of the 4 asthma clusters as well as 1 male and 1 female healthy controls, and performed computational fluid and particle simulations on CT-based airway models of these subjects. The results from one severe and one non-severe asthmatic cluster subjects characterized by segmental airway constriction had increased particle deposition efficiency, as compared with the other two cluster subjects (one non-severe and one severe asthmatics) without airway constriction. Constriction-induced jets impinging on distal bifurcations led to excessive particle deposition. The results emphasize the impact of airway constriction on regional particle deposition rather than disease severity, demonstrating the potential of using cluster membership to tailor drug delivery. NIH Grants U01HL114494 and S10-RR022421, and FDA Grant U01FD005837. XSEDE.

First-principles investigation of the dissociation and coupling of methane on small copper clusters: Interplay of collision dynamics and geometric and electronic effects

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

Varghese, Jithin J.; Mushrif, Samir H., E-mail: shmushrif@ntu.edu.sg

Small metal clusters exhibit unique size and morphology dependent catalytic activity. The search for alternate minimum energy pathways and catalysts to transform methane to more useful chemicals and carbon nanomaterials led us to investigate collision induced dissociation of methane on small Cu clusters. We report here for the first time, the free energy barriers for the collision induced activation, dissociation, and coupling of methane on small Cu clusters (Cu{sub n} where n = 2–12) using ab initio molecular dynamics and metadynamics simulations. The collision induced activation of the stretching and bending vibrations of methane significantly reduces the free energy barriermore » for its dissociation. Increase in the cluster size reduces the barrier for dissociation of methane due to the corresponding increase in delocalisation of electron density within the cluster, as demonstrated using the electron localisation function topology analysis. This enables higher probability of favourable alignment of the C–H stretching vibration of methane towards regions of high electron density within the cluster and makes higher number of sites available for the chemisorption of CH{sub 3} and H upon dissociation. These characteristics contribute in lowering the barrier for dissociation of methane. Distortion and reorganisation of cluster geometry due to high temperature collision dynamics disturb electron delocalisation within them and increase the barrier for dissociation. Coupling reactions of CH{sub x} (x = 1–3) species and recombination of H with CH{sub x} have free energy barriers significantly lower than complete dehydrogenation of methane to carbon. Thus, competition favours the former reactions at high hydrogen saturation on the clusters.« less

An ecohealth assessment of poultry production clusters (PPCs) for the livelihood and biosecurity improvement of small poultry producers in Asia.

PubMed

Wang, Libin; Basuno, Edi; Nguyen, Tuan; Aengwanich, Worapol; Ilham, Nyak; Li, Xiaoyun

2015-01-01

Poultry production cluster (PPC) programs are key strategies in many Asian countries to engage small commercial poultry producers in high-value production chains and to control infectious poultry diseases. This study assessed the multiple impacts of PPCs through a transdisciplinary ecohealth approach in four Asian countries, and drew the implications for small producers to improve their livelihoods and reduce the risk of spreading infectious diseases in the poultry sector. The data collection combined both quantitative and qualitative methods. It comprised: formal structured household survey questionnaires, measuring the biosecurity level of poultry farms with a biosecurity score card; and key informant interviews. Descriptive statistics were used to process the quantitative data and a content analysis was used to process the qualitative data. This research found that poultry farms in clusters do not necessarily have better economic performance than those outside PPCs. Many farmers in PPCs only consider them to be an advantage for expanding the scale of their poultry operations and improving household incomes, and they are less concerned about-and have limited capacities to-enhancing biosecurity and environmental management. We measured the biosecurity level of farms in PPCs through a 14-item checklist and found that biosecurity is generally very low across all sample sites. The increased flies, mosquitoes, rats, and smells in and around PPCs not only pollute the environment, but also cause social conflicts with the surrounding communities. This research concluded that a poultry cluster, mainly driven by economic objectives, is not necessarily a superior model for the control of infectious diseases. The level of biosecurity in PPCs was found to be low. Given the intensity of poultry operations in PPCs (farms are densely packed into clusters), and the close proximity to residential areas of some PPCs, the risk of spreading infectious diseases, in fact, increases. Good management and collective action for implementing biosecurity measures are key for small producers in PPCs to address common challenges and pursue health-based animal production practices.

Thermal emission from interstellar dust in and near the Pleiades

NASA Technical Reports Server (NTRS)

White, Richard E.

1989-01-01

IRAS survey coadds for a 8.7 deg x 4.3 deg field near the Pleiades provide evidence for dynamical interaction between the cluster and the surrounding interstellar medium. The far-infrared images show large region of faint emission with bright rims east of the cluster, suggestive of a wake. Images of the far-infrared color temperature and 100 micron optical depth reveal temperature maxima and optical depth minima near the bright cluster stars, as well as a strong optical depth peak at the core of the adjacent CO cloud. Models for thermal dust emission near the stars indicate that most of the apparent optical depth minima near stars are illusory, but also provide indirect evidence for small interaction between the stars and the encroaching dust cloud.

How Many-Body Correlations and α Clustering Shape He 6

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

Romero-Redondo, Carolina; Quaglioni, Sofia; Navrátil, Petr

The Borromean 6He nucleus is an exotic system characterized by two halo neutrons orbiting around a compact 4He (or α) core, in which the binary subsystems are unbound. The simultaneous reproduction of its small binding energy and extended matter and point-proton radii has been a challenge for ab initio theoretical calculations based on traditional bound-state methods. Using soft nucleon-nucleon interactions based on chiral effective field theory potentials, we show that supplementing the model space with 4He + n + n cluster degrees of freedom largely solves this issue. Lastly, we analyze the role played by α clustering and many-body correlations,more » and study the dependence of the energy spectrum on the resolution scale of the interaction.« less

Thermodynamics and Charging of Interstellar Iron Nanoparticles

NASA Astrophysics Data System (ADS)

Hensley, Brandon S.; Draine, B. T.

2017-01-01

Interstellar iron in the form of metallic iron nanoparticles may constitute a component of the interstellar dust. We compute the stability of iron nanoparticles to sublimation in the interstellar radiation field, finding that iron clusters can persist down to a radius of ≃4.5 Å, and perhaps smaller. We employ laboratory data on small iron clusters to compute the photoelectric yields as a function of grain size and the resulting grain charge distribution in various interstellar environments, finding that iron nanoparticles can acquire negative charges, particularly in regions with high gas temperatures and ionization fractions. If ≳10% of the interstellar iron is in the form of ultrasmall iron clusters, the photoelectric heating rate from dust may be increased by up to tens of percent relative to dust models with only carbonaceous and silicate grains.

How Many-Body Correlations and α Clustering Shape He 6

DOE PAGES

Romero-Redondo, Carolina; Quaglioni, Sofia; Navrátil, Petr; ...

2016-11-23

The Borromean 6He nucleus is an exotic system characterized by two halo neutrons orbiting around a compact 4He (or α) core, in which the binary subsystems are unbound. The simultaneous reproduction of its small binding energy and extended matter and point-proton radii has been a challenge for ab initio theoretical calculations based on traditional bound-state methods. Using soft nucleon-nucleon interactions based on chiral effective field theory potentials, we show that supplementing the model space with 4He + n + n cluster degrees of freedom largely solves this issue. Lastly, we analyze the role played by α clustering and many-body correlations,more » and study the dependence of the energy spectrum on the resolution scale of the interaction.« less

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

The dynamics of social innovation

PubMed Central

Young, H. Peyton

2011-01-01

Social norms and institutions are mechanisms that facilitate coordination between individuals. A social innovation is a novel mechanism that increases the welfare of the individuals who adopt it compared with the status quo. We model the dynamics of social innovation as a coordination game played on a network. Individuals experiment with a novel strategy that would increase their payoffs provided that it is also adopted by their neighbors. The rate at which a social innovation spreads depends on three factors: the topology of the network and in particular the extent to which agents interact in small local clusters, the payoff gain of the innovation relative to the status quo, and the amount of noise in the best response process. The analysis shows that local clustering greatly enhances the speed with which social innovations spread. It also suggests that the welfare gains from innovation are more likely to occur in large jumps than in a series of small incremental improvements. PMID:22198762

The dynamics of social innovation.

PubMed

Young, H Peyton

2011-12-27

Social norms and institutions are mechanisms that facilitate coordination between individuals. A social innovation is a novel mechanism that increases the welfare of the individuals who adopt it compared with the status quo. We model the dynamics of social innovation as a coordination game played on a network. Individuals experiment with a novel strategy that would increase their payoffs provided that it is also adopted by their neighbors. The rate at which a social innovation spreads depends on three factors: the topology of the network and in particular the extent to which agents interact in small local clusters, the payoff gain of the innovation relative to the status quo, and the amount of noise in the best response process. The analysis shows that local clustering greatly enhances the speed with which social innovations spread. It also suggests that the welfare gains from innovation are more likely to occur in large jumps than in a series of small incremental improvements.

Predicting vacancy-mediated diffusion of interstitial solutes in α -Fe

NASA Astrophysics Data System (ADS)

Barouh, Caroline; Schuler, Thomas; Fu, Chu-Chun; Jourdan, Thomas

2015-09-01

Based on a systematic first-principles study, the lowest-energy migration mechanisms and barriers for small vacancy-solute clusters (VnXm ) are determined in α -Fe for carbon, nitrogen, and oxygen, which are the most frequent interstitial solutes in several transition metals. We show that the dominant clusters present at thermal equilibrium (V X and V X2 ) have very reduced mobility compared to isolated solutes, while clusters composed of a solute bound to a small vacancy cluster may be significantly more mobile. In particular, V3X is found to be the fastest cluster for all three solutes. This result relies on the large diffusivity of the most compact trivacancy in a bcc lattice. Therefore, it may also be expected for interstitial solutes in other bcc metals. In the case of iron, we find that V3X may be as fast as or even more mobile than an interstitial solute. At variance with common assumptions, the trapping of interstitial solutes by vacancies does not necessarily decrease the mobility of the solute. Additionally, cluster dynamics simulations are performed considering a simple iron system with supersaturation of vacancies, in order to investigate the impacts of small mobile vacancy-solute clusters on properties such as the transport of solute and the cluster size distributions.

Suppressed epidemics in multirelational networks

NASA Astrophysics Data System (ADS)

Xu, Elvis H. W.; Wang, Wei; Xu, C.; Tang, Ming; Do, Younghae; Hui, P. M.

2015-08-01

A two-state epidemic model in networks with links mimicking two kinds of relationships between connected nodes is introduced. Links of weights w1 and w0 occur with probabilities p and 1 -p , respectively. The fraction of infected nodes ρ (p ) shows a nonmonotonic behavior, with ρ drops with p for small p and increases for large p . For small to moderate w1/w0 ratios, ρ (p ) exhibits a minimum that signifies an optimal suppression. For large w1/w0 ratios, the suppression leads to an absorbing phase consisting only of healthy nodes within a range pL≤p ≤pR , and an active phase with mixed infected and healthy nodes for p pR . A mean field theory that ignores spatial correlation is shown to give qualitative agreement and capture all the key features. A physical picture that emphasizes the intricate interplay between infections via w0 links and within clusters formed by nodes carrying the w1 links is presented. The absorbing state at large w1/w0 ratios results when the clusters are big enough to disrupt the spread via w0 links and yet small enough to avoid an epidemic within the clusters. A theory that uses the possible local environments of a node as variables is formulated. The theory gives results in good agreement with simulation results, thereby showing the necessity of including longer spatial correlations.

Hot gas in the cold dark matter scenario: X-ray clusters from a high-resolution numerical simulation

NASA Technical Reports Server (NTRS)

Kang, Hyesung; Cen, Renyue; Ostriker, Jeremiah P.; Ryu, Dongsu

1994-01-01

A new, three-dimensional, shock-capturing hydrodynamic code is utilized to determine the distribution of hot gas in a standard cold dark matter (CDM) model of the universe. Periodic boundary conditions are assumed: a box with size 85 h(exp -1) Mpc having cell size 0.31 h(exp -1) Mpc is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, sigma(sub 8) = 1.05, omega(sub b) = 0.06, and assuming h = 0.5, we find the X-ray-emitting clusters and compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. We find that most of the total X-ray emissivity in our box originates in a relatively small number of identifiable clusters which occupy approximately 10(exp -3) of the box volume. This standard CDM model, normalized to COBE, produces approximately 5 times too much emission from clusters having L(sub x) is greater than 10(exp 43) ergs/s, a not-unexpected result. If all other parameters were unchanged, we would expect adequate agreement for sigma(sub 8) = 0.6. This provides a new and independent argument for lower small-scale power than standard CDM at the 8 h(exp -1) Mpc scale. The background radiation field at 1 keV due to clusters in this model is approximately one-third of the observed background, which, after correction for numerical effects, again indicates approximately 5 times too much emission and the appropriateness of sigma(sub 8) = 0.6. If we have used the observed ratio of gas to total mass in clusters, rather than basing the mean density on light-element nucleosynthesis, then the computed luminosity of each cluster would have increased still further, by a factor of approximately 10. The number density of clusters increases to z approximately 1, but the luminosity per typical cluster decreases, with the result that evolution in the number density of bright clusters is moderate in this redshift range, showing a broad peak near z = 0.7, and then a rapid decline above redshift z = 3. Detailed computations of the luminosity functions in the range L(sub x) = 10(exp 40) - 10(exp 44) ergs/s in various energy bands are presented for both cluster central regions and total luminosities to be used in comparison with ROSAT and other observational data sets. The quantitative results found disagree significantly with those found by other investigators using semianalytic techniques. We find little dependence of core radius on cluster luminosity and a dependence of temperature on luminosity given by log kT(sub x) = A + B log L(sub x), which is slightly steeper (B = 0.38) than is indicated by observations. Computed temperatures are somewhat higher than observed, as expected, in that COBE-normalized CDM has too much power on the relevant scales. A modest average temperature gradient is found, with temperatures dropping to 90% of central values at 0.4 h(exp -1) Mpc and 70% of central values at 0.9 h(exp -1) Mpc. Examining the ratio of gas to total mass in the clusters normalized to Omega(sub B) h(exp 2) = 0.015, and comparing with observations, we conclude, in agreement with White (1991), that the cluster observations argue for an open universe.

Influence of reactive gas admixture on transition metal cluster nucleation in a gas aggregation cluster source

NASA Astrophysics Data System (ADS)

Peter, Tilo; Polonskyi, Oleksandr; Gojdka, Björn; Mohammad Ahadi, Amir; Strunskus, Thomas; Zaporojtchenko, Vladimir; Biederman, Hynek; Faupel, Franz

2012-12-01

We quantitatively assessed the influence of reactive gases on the formation processes of transition metal clusters in a gas aggregation cluster source. A cluster source based on a 2 in. magnetron is used to study the production rate of titanium and cobalt clusters. Argon served as working gas for the DC magnetron discharge, and a small amount of reactive gas (oxygen and nitrogen) is added to promote reactive cluster formation. We found that the cluster production rate depends strongly on the reactive gas concentration for very small amounts of reactive gas (less than 0.1% of total working gas), and no cluster formation takes place in the absence of reactive species. The influence of discharge power, reactive gas concentration, and working gas pressure are investigated using a quartz micro balance in a time resolved manner. The strong influence of reactive gas is explained by a more efficient formation of nucleation seeds for metal-oxide or nitride than for pure metal.

Mass Distribution in Galaxy Cluster Cores

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

Hogan, M. T.; McNamara, B. R.; Pulido, F.

Many processes within galaxy clusters, such as those believed to govern the onset of thermally unstable cooling and active galactic nucleus feedback, are dependent upon local dynamical timescales. However, accurate mapping of the mass distribution within individual clusters is challenging, particularly toward cluster centers where the total mass budget has substantial radially dependent contributions from the stellar ( M {sub *}), gas ( M {sub gas}), and dark matter ( M {sub DM}) components. In this paper we use a small sample of galaxy clusters with deep Chandra observations and good ancillary tracers of their gravitating mass at both largemore » and small radii to develop a method for determining mass profiles that span a wide radial range and extend down into the central galaxy. We also consider potential observational pitfalls in understanding cooling in hot cluster atmospheres, and find tentative evidence for a relationship between the radial extent of cooling X-ray gas and nebular H α emission in cool-core clusters. At large radii the entropy profiles of our clusters agree with the baseline power law of K ∝ r {sup 1.1} expected from gravity alone. At smaller radii our entropy profiles become shallower but continue with a power law of the form K ∝ r {sup 0.67} down to our resolution limit. Among this small sample of cool-core clusters we therefore find no support for the existence of a central flat “entropy floor.”.« less

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

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

NASA Astrophysics Data System (ADS)

van den Berg, Maureen C.

2015-08-01

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

Mechanisms contributing to cluster formation in the inferior olivary nucleus in brainstem slices from postnatal mice

PubMed Central

Kølvraa, Mathias; Müller, Felix C; Jahnsen, Henrik; Rekling, Jens C

2014-01-01

Abstract The inferior olivary nucleus (IO) in in vitro slices from postnatal mice (P5.5–P15.5) spontaneously generates clusters of neurons with synchronous calcium transients, and intracellular recordings from IO neurons suggest that electrical coupling between neighbouring IO neurons may serve as a synchronizing mechanism. Here, we studied the cluster-forming mechanism and find that clusters overlap extensively with an overlap distribution that resembles the distribution for a random overlap model. The average somatodendritic field size of single curly IO neurons was ∼6400 μm2, which is slightly smaller than the average IO cluster size. Eighty-seven neurons with overlapping dendrites were estimated to be contained in the principal olive mean cluster size, and about six non-overlapping curly IO neurons could be contained within the largest clusters. Clusters could also be induced by iontophoresis with glutamate. Induced clusters were inhibited by tetrodotoxin, carbenoxelone and 18β-glycyrrhetinic acid, suggesting that sodium action potentials and electrical coupling are involved in glutamate-induced cluster formation, which could also be induced by activation of N-methyl-d-aspartate and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Spikelets and a small transient depolarizing response were observed during glutamate-induced cluster formation. Calcium transients spread with decreasing velocity during cluster formation, and somatic action potentials and cluster formation are accompanied by large dendritic calcium transients. In conclusion, cluster formation depends on gap junctions, sodium action potentials and spontaneous clusters occur randomly throughout the IO. The relative slow signal spread during cluster formation, combined with a strong dendritic influx of calcium, may signify that active dendritic properties contribute to cluster formation. PMID:24042500

Focus-based filtering + clustering technique for power-law networks with small world phenomenon

NASA Astrophysics Data System (ADS)

Boutin, François; Thièvre, Jérôme; Hascoët, Mountaz

2006-01-01

Realistic interaction networks usually present two main properties: a power-law degree distribution and a small world behavior. Few nodes are linked to many nodes and adjacent nodes are likely to share common neighbors. Moreover, graph structure usually presents a dense core that is difficult to explore with classical filtering and clustering techniques. In this paper, we propose a new filtering technique accounting for a user-focus. This technique extracts a tree-like graph with also power-law degree distribution and small world behavior. Resulting structure is easily drawn with classical force-directed drawing algorithms. It is also quickly clustered and displayed into a multi-level silhouette tree (MuSi-Tree) from any user-focus. We built a new graph filtering + clustering + drawing API and report a case study.

Early assembly of the most massive galaxies.

PubMed

Collins, Chris A; Stott, John P; Hilton, Matt; Kay, Scott T; Stanford, S Adam; Davidson, Michael; Hosmer, Mark; Hoyle, Ben; Liddle, Andrew; Lloyd-Davies, Ed; Mann, Robert G; Mehrtens, Nicola; Miller, Christopher J; Nichol, Robert C; Romer, A Kathy; Sahlén, Martin; Viana, Pedro T P; West, Michael J

2009-04-02

The current consensus is that galaxies begin as small density fluctuations in the early Universe and grow by in situ star formation and hierarchical merging. Stars begin to form relatively quickly in sub-galactic-sized building blocks called haloes which are subsequently assembled into galaxies. However, exactly when this assembly takes place is a matter of some debate. Here we report that the stellar masses of brightest cluster galaxies, which are the most luminous objects emitting stellar light, some 9 billion years ago are not significantly different from their stellar masses today. Brightest cluster galaxies are almost fully assembled 4-5 billion years after the Big Bang, having grown to more than 90 per cent of their final stellar mass by this time. Our data conflict with the most recent galaxy formation models based on the largest simulations of dark-matter halo development. These models predict protracted formation of brightest cluster galaxies over a Hubble time, with only 22 per cent of the stellar mass assembled at the epoch probed by our sample. Our findings suggest a new picture in which brightest cluster galaxies experience an early period of rapid growth rather than prolonged hierarchical assembly.

Hydrodynamical simulations of coupled and uncoupled quintessence models - II. Galaxy clusters

NASA Astrophysics Data System (ADS)

Carlesi, Edoardo; Knebe, Alexander; Lewis, Geraint F.; Yepes, Gustavo

2014-04-01

We study the z = 0 properties of clusters (and large groups) of galaxies within the context of interacting and non-interacting quintessence cosmological models, using a series of adiabatic SPH simulations. Initially, we examine the average properties of groups and clusters, quantifying their differences in ΛCold Dark Matter (ΛCDM), uncoupled Dark Energy (uDE) and coupled Dark Energy (cDE) cosmologies. In particular, we focus upon radial profiles of the gas density, temperature and pressure, and we also investigate how the standard hydrodynamic equilibrium hypothesis holds in quintessence cosmologies. While we are able to confirm previous results about the distribution of baryons, we also find that the main discrepancy (with differences up to 20 per cent) can be seen in cluster pressure profiles. We then switch attention to individual structures, mapping each halo in quintessence cosmology to its ΛCDM counterpart. We are able to identify a series of small correlations between the coupling in the dark sector and halo spin, triaxiality and virialization ratio. When looking at spin and virialization of dark matter haloes, we find a weak (5 per cent) but systematic deviation in fifth force scenarios from ΛCDM.

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Off-road truck-related accidents in U.S. mines.

PubMed

Dindarloo, Saeid R; Pollard, Jonisha P; Siami-Irdemoosa, Elnaz

2016-09-01

Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Confronting models of star formation quenching in galaxy clusters with archival Spitzer data

NASA Astrophysics Data System (ADS)

Rudnick, Gregory

Large scale structures in the universe form hierarchically: small structures merge to form larger ones. Over the same epoch where these structures experience significant growth, the fraction of star forming galaxies within them decreases, and at a faster rate than for field galaxies. It is now widely accepted that there must be physical processes at work in these dense environments to actively quench star formation. However, despite no shortage of candidate mechanisms, sophisticated cosmological simulations still cannot reproduce the star formation rate distributions within dense environments, such as galaxy clusters. Insufficient observational constraints are a primary obstacle to further progress. In particular, the interpretation of observations of nearby clusters relies on untested assumptions about the properties of galaxies before they entered the dense cluster environment at higher redshifts. Clearly, direct constraints on these properties are required. Our group has assembled two data sets designed to address these concerns. The first focuses on an intermediate wide-field cluster sample and the second focuses on a well-matched low-redshift cluster sample. We will use these samples, along with sophisticated models of hierarchical galaxy formation, to meet the following objectives: 1. Directly measure the SFR distribution of the progenitors of present-day cluster galaxies. We will use ground-based spectroscopy to identify cluster members within four virial radii of eight intermediate-redshift clusters. We will couple this with archival Spitzer/MIPS data to measure the SFRs of galaxies out to the cluster outskirts. 2. Measure the SFR distribution of the present-day cluster galaxies using Spitzer and WISE. Robust N-body simulations tell us statistically which galaxies at intermediate redshifts will have entered the cluster virial radius by the current epoch. By combining our wide-field coverage at high redshift with our local cluster sample, we will determine the evolution in cluster galaxy SFRs over 6 billion years making minimal assumptions about the infalling galaxy population. 3. Provide a rigorous test of the quenching processes embedded in the theoretical models. We will create observed realizations of the theoretical models by subjecting them to our observational selection. This will enable a fair comparison between the models and the data, which will provide a valuable test of current theoretical implementations of quenching processes. We will also modify the quenching prescriptions in the models to determine the parameters required to reproduce the observations. The proposed research is novel for several reasons. 1) We have wide-field Spitzer/MIPS data that allows us to robustly measure SFRs in our distant cluster galaxies. WISE data on local clusters will provide us with analogous measurements in the nearby Universe. 2) Our significant investment in ancillary spectroscopy allows us to identify infalling galaxies that will eventually join the central regions of the cluster z=0. 3) Our intermediate redshift cluster sample was chosen to have characteristics expected for the progenitors of a large fraction of the known clusters at z=0. 4) We will take advantage of our own cosmological simulations of structure growth to interpret our data. 5) We have optical photometry over the full infall region, allowing us to control for stellar masses and to distinguish passive from dusty star-forming galaxies. We will learn which, if any, of the quenching prescriptions currently employed in semi-analytic models correctly reproduces the observed characteristics of the galaxies that will become cluster galaxies at z=0. We will pinpoint the cluster-centric radii over which quenching takes place between. We will determine the timescale (as a function of stellar mass) over which it must take place. This program will cement the legacy of Spitzer and WISE as tools for studying galaxy formation in clusters.

Stability and minimum size of colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2012-02-01

A vertical force applied to each of two colloids, trapped at a liquid-air interface, induces their logarithmic pairwise attraction. I recently showed [Phys. Rev. E 79, 011407 (2009)] that in clusters of size R much larger than the capillary length λ, the attraction changes to that of a power law and is much stronger due to a many-body effect, and I derived two equations that describe the equilibrium coarse-grained meniscus profile and colloid density in such clusters. In this paper, this theory is shown also to describe small clusters with R≪ λ provided the number N of colloids therein is sufficiently large. An analytical solution for a small circular cluster with an arbitrary short-range power-law pairwise repulsion is found. The energy of a cluster is obtained as a function of its radius R and colloid number N. As in large clusters, the attraction force and energy universally scale with the distance L between colloids as L(-3) and L(-2), respectively, for any repulsion forces. The states of an equilibrium cluster, predicted by the theory, are shown to be stable with respect to small perturbations of the meniscus profile and colloid density. The minimum number of colloids in a circular cluster, which sustains the thermal motion, is estimated. For standard parameters, it can be very modest, e.g., in the range 20-200, which is in line with experimental findings on reversible clusterization on a liquid-air interface. © 2012 American Physical Society

Suppression of AGN-Driven G-Mode Turbulence by Magnetic Fields in a Magnetohydrodynamic Model of the Intracluster Medium

NASA Astrophysics Data System (ADS)

Bambic, Christopher J.; Morsony, Brian J.; Reynolds, Christopher S.

2017-08-01

We investigate the role of AGN feedback in turbulent heating of galaxy clusters. X-ray measurements of the Perseus Cluster intracluster medium (ICM) by the Hitomi Mission found a velocity dispersion measure of σ ˜ 164 km/s, indicating a large-scale turbulent energy of approximately 4% of the thermal energy. If this energy is transferred to small scales via a turbulent cascade and dissipated as heat, radiative cooling can be offset and the cluster can remain in the observed thermal equilibrium. Using 3D ideal MHD simulations and a plane-parallel model of the ICM, we analyze the production of turbulence by g-modes generated by the supersonic expansion and buoyant rise of AGN-driven bubbles. Previous work has shown that this process is inefficient, with less than 1% of the injected energy ending up in turbulence. Hydrodynamic instabilities shred the bubbles apart before they can excite sufficiently strong g-modes. We examine the role of a large-scale magnetic field which is able to drape around these rising bubbles, preserving them from instabilities. We show that a helical magnetic field geometry is able to better preserve bubbles, driving stronger g-modes; however, the production of turbulence is still inefficient. Magnetic tension acts to stabilize g-modes, preventing the nonlinear transition to turbulence. In addition, the magnetic tension force acts along the field lines to suppress the formation of small-scale vortices. These two effects halt the turbulent cascade. Our work shows that ideal MHD is an insufficient description for the cluster feedback process, and we discuss future work such as the inclusion of anisotropic viscosity as a means of simulating high β plasma kinetic effects. In addition, other mechanisms of heating the ICM plasma such as sound waves or cosmic rays may be responsible to account for observed feedback in galaxy clusters.

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

NASA Astrophysics Data System (ADS)

Lai, King C.; Liu, Da-Jiang; Evans, James W.

2017-12-01

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal (100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN˜ N-β with β =3 /2 . However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N <9 ; (ii) slow nucleation-mediated diffusion with small β <1 for "perfect" sizes N = Np= L2 or L (L +1 ) , for L =3 ,4 , ... having unique ground-state shapes, for moderate sizes 9 ≤N ≤O (102) ; the same also applies for N =Np+3 , Np+ 4 , ... (iii) facile diffusion but with large β >2 for N =Np+1 and Np+2 also for moderate sizes 9 ≤N ≤O (102) ; (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲β <3 /2 , reflecting the quasifacetted structure of clusters, for larger N =O (102) to N =O (103) ; (v) classic scaling with β =3 /2 for very large N =O (103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where we show that diffusivity cycles quasiperiodically from the slowest branch for Np+3 (not Np) to the fastest branch for Np+1 . Behavior is quantified by kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground-state and low-lying excited state cluster configurations, and also of kink populations.

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

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

Lai, King C.; Liu, Da -Jiang; Evans, James W.

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Diffusion of two-dimensional epitaxial clusters on metal (100) surfaces: Facile versus nucleation-mediated behavior and their merging for larger sizes

DOE PAGES

Lai, King C.; Liu, Da -Jiang; Evans, James W.

2017-12-05

For diffusion of two-dimensional homoepitaxial clusters of N atoms on metal(100) surfaces mediated by edge atom hopping, macroscale continuum theory suggests that the diffusion coefficient scales like DN ~ N -β with β = 3/2. However, we find quite different and diverse behavior in multiple size regimes. These include: (i) facile diffusion for small sizes N < 9; (ii) slow nucleation-mediated diffusion with small β < 1 for “perfect” sizes N = N p = L 2 or L(L+1), for L = 3, 4,… having unique ground state shapes, for moderate sizes 9 ≤ N ≤ O(10 2); the samemore » also applies for N = N p +3, N p + 4,… (iii) facile diffusion but with large β > 2 for N = Np + 1 and N p + 2 also for moderate sizes 9 ≤ N ≤ O(10 2); (iv) merging of the above distinct branches and subsequent anomalous scaling with 1 ≲ β < 3/2, reflecting the quasi-facetted structure of clusters, for larger N = O(10 2) to N = O(10 3); and (v) classic scaling with β = 3/2 for very large N = O(103) and above. The specified size ranges apply for typical model parameters. We focus on the moderate size regime where show that diffusivity cycles quasi-periodically from the slowest branch for N p + 3 (not Np) to the fastest branch for Np + 1. Behavior is quantified by Kinetic Monte Carlo simulation of an appropriate stochastic lattice-gas model. However, precise analysis must account for a strong enhancement of diffusivity for short time increments due to back-correlation in the cluster motion. Further understanding of this enhancement, of anomalous size scaling behavior, and of the merging of various branches, is facilitated by combinatorial analysis of the number of the ground state and low-lying excited state cluster configurations, and also of kink populations.« less

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

PubMed Central

Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

2018-01-01

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

Biased phylodynamic inferences from analysing clusters of viral sequences

PubMed Central

Xiang, Fei; Frost, Simon D. W.

2017-01-01

Abstract Phylogenetic methods are being increasingly used to help understand the transmission dynamics of measurably evolving viruses, including HIV. Clusters of highly similar sequences are often observed, which appear to follow a ‘power law’ behaviour, with a small number of very large clusters. These clusters may help to identify subpopulations in an epidemic, and inform where intervention strategies should be implemented. However, clustering of samples does not necessarily imply the presence of a subpopulation with high transmission rates, as groups of closely related viruses can also occur due to non-epidemiological effects such as over-sampling. It is important to ensure that observed phylogenetic clustering reflects true heterogeneity in the transmitting population, and is not being driven by non-epidemiological effects. We qualify the effect of using a falsely identified ‘transmission cluster’ of sequences to estimate phylodynamic parameters including the effective population size and exponential growth rate under several demographic scenarios. Our simulation studies show that taking the maximum size cluster to re-estimate parameters from trees simulated under a randomly mixing, constant population size coalescent process systematically underestimates the overall effective population size. In addition, the transmission cluster wrongly resembles an exponential or logistic growth model 99% of the time. We also illustrate the consequences of false clusters in exponentially growing coalescent and birth-death trees, where again, the growth rate is skewed upwards. This has clear implications for identifying clusters in large viral databases, where a false cluster could result in wasted intervention resources. PMID:28852573

The topology of large-scale structure. I - Topology and the random phase hypothesis. [galactic formation models

NASA Technical Reports Server (NTRS)

Weinberg, David H.; Gott, J. Richard, III; Melott, Adrian L.

1987-01-01

Many models for the formation of galaxies and large-scale structure assume a spectrum of random phase (Gaussian), small-amplitude density fluctuations as initial conditions. In such scenarios, the topology of the galaxy distribution on large scales relates directly to the topology of the initial density fluctuations. Here a quantitative measure of topology - the genus of contours in a smoothed density distribution - is described and applied to numerical simulations of galaxy clustering, to a variety of three-dimensional toy models, and to a volume-limited sample of the CfA redshift survey. For random phase distributions the genus of density contours exhibits a universal dependence on threshold density. The clustering simulations show that a smoothing length of 2-3 times the mass correlation length is sufficient to recover the topology of the initial fluctuations from the evolved galaxy distribution. Cold dark matter and white noise models retain a random phase topology at shorter smoothing lengths, but massive neutrino models develop a cellular topology.

Optical Materials with a Genome: Nanophotonics with DNA-Stabilized Silver Clusters

NASA Astrophysics Data System (ADS)

Copp, Stacy M.

Fluorescent silver clusters with unique rod-like geometries are stabilized by DNA. The sizes and colors of these clusters, or AgN-DNA, are selected by DNA base sequence, which can tune peak emission from blue-green into the near-infrared. Combined with DNA nanostructures, AgN-DNA promise exciting applications in nanophotonics and sensing. Until recently, however, a lack of understanding of the mechanisms controlling AgN-DNA fluorescence has challenged such applications. This dissertation discusses progress toward understanding the role of DNA as a "genome" for silver clusters and toward using DNA to achieve atomic-scale precision of silver cluster size and nanometer-scale precision of silver cluster position on a DNA breadboard. We also investigate sensitivity of AgN-DNA to local solvent environment, with an eye toward applications in chemical and biochemical sensing. Using robotic techniques to generate large data sets, we show that fluorescent silver clusters are templated by certain DNA base motifs that select "magic-sized" cluster cores of enhanced stabilities. The linear arrangement of bases on the phosphate backbone imposes a unique rod-like geometry on the clusters. Harnessing machine learning and bioinformatics techniques, we also demonstrate that sequences of DNA templates can be selected to stabilize silver clusters with desired optical properties, including high fluorescence intensity and specific fluorescence wavelengths, with much higher rates of success as compared to current strategies. The discovered base motifs can be also used to design modular DNA host strands that enable individual silver clusters with atomically precise sizes to bind at specific programmed locations on a DNA nanostructure. We show that DNA-mediated nanoscale arrangement enables near-field coupling of distinct clusters, demonstrated by dual-color cluster assemblies exhibiting resonant energy transfer. These results demonstrate a new degree of control over the optical properties and relative positions of nanoparticles, selected almost solely by the sequence of DNA. AgN-DNA are promising chemical and biochemical sensors due to the sensitivity of their fluorescence to local environment. However, the mechanisms behind many sensing schemes are not understood, and the nature of the excited state of the silver cluster itself remains unknown. To probe the fluorescence mechanisms of AgN-DNA, we investigate the behavior of purified solutions of these clusters in various solvents. We find that standard models for fluorophore solvatochromism, including the Lippert-Mataga model, do not describe AgN-DNA fluorescence because such models neglect specific interactions between the cluster and surrounding solvent molecules. Fluorescence colors are well-modeled by Mie-Gans theory, suggesting that the local dielectric environment of the cluster does play a role in fluorescence, although additional specific solvent interactions and cluster shape changes may also determine fluorescence color and intensity. These results suggest that AgN-DNA may be sensitive to changes in local dielectric environment on nanometer length scales and may also act as sensors for small molecules with affinity for DNA.

Comparing Effects of Cluster-Coupled Patterns on Opinion Dynamics

NASA Astrophysics Data System (ADS)

Liu, Yun; Si, Xia-Meng; Zhang, Yan-Chao

2012-07-01

Community structure is another important feature besides small-world and scale-free property of complex networks. Communities can be coupled through specific fixed links between nodes, or occasional encounter behavior. We introduce a model for opinion evolution with multiple cluster-coupled patterns, in which the interconnectivity denotes the coupled degree of communities by fixed links, and encounter frequency controls the coupled degree of communities by encounter behaviors. Considering the complicated cognitive system of people, the CODA (continuous opinions and discrete actions) update rules are used to mimic how people update their decisions after interacting with someone. It is shown that, large interconnectivity and encounter frequency both can promote consensus, reduce competition between communities and propagate some opinion successfully across the whole population. Encounter frequency is better than interconnectivity at facilitating the consensus of decisions. When the degree of social cohesion is same, small interconnectivity has better effects on lessening the competence between communities than small encounter frequency does, while large encounter frequency can make the greater degree of agreement across the whole populations than large interconnectivity can.

Theoretical and experimental insights into the origin of the catalytic activity of subnanometric gold clusters: attempts to predict reactivity with clusters and nanoparticles of gold.

PubMed

Boronat, Mercedes; Leyva-Pérez, Antonio; Corma, Avelino

2014-03-18

Particle size is one of the key parameters determining the unexpected catalytic activity of gold, with reactivity improving as the particle gets smaller. While this is valid in the 1-5 nm range, chemists are now investigating the influence of particle size in the subnanometer regime. This is due to recent advances in both characterization techniques and synthetic routes capable of stabilizing these size-controlled gold clusters. Researchers reported in early studies that small clusters or aggregates of a few atoms can be extremely active in some reactions, while 1-2 nm nanoparticles are catalytically more efficient for other reactions. Furthermore, the possibility that small gold clusters generated in situ from gold salts or complexes could be the real active species in homogeneous gold-catalyzed organic reactions should be considered. In this Account, we address two questions. First, what is the origin of the enhanced reactivity of gold clusters on the subnanometer scale? And second, how can we predict the reactions where small clusters should work better than larger nanoparticles? Both geometric factors and electronic or quantum size effects become important in the subnanometer regime. Geometric reasons play a key role in hydrogenation reactions, where only accessible low coordinated neutral Au atoms are needed to dissociate H2. The quantum size effects of gold clusters are important as well, as clusters formed by only a few atoms have discrete molecule-like electronic states and their chemical reactivity is related to interactions between the cluster's frontier molecular orbitals and those of the reactant molecules. From first principles calculations, we predict an enhanced reactivity of small planar clusters for reactions involving activation of CC multiple bonds in alkenes and alkynes through Lewis acid-base interactions, and a better catalytic performance of 3D gold nanoparticles in redox reactions involving bond dissociation by oxidative addition and new bond formation by reductive elimination. In oxidation reactions with molecular O2, initial dissociation of O2 into basic oxygen atoms would be more effectively catalyzed by gold nanoparticles of ∼1 nm diameter. In contrast, small planar clusters should be more active for reactions following a radical pathway involving peroxo or hydroperoxo intermediates. We have experimentally confirmed these predictions for a series of Lewis acid and oxidation reactions catalyzed by gold clusters and nanoparticles either in solution or supported on solid carriers.

Cosmology and astrophysics from relaxed galaxy clusters - III. Thermodynamic profiles and scaling relations

NASA Astrophysics Data System (ADS)

Mantz, A. B.; Allen, S. W.; Morris, R. G.; Schmidt, R. W.

2016-03-01

This is the third in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot (I.e. massive) in Papers I and II of this series. Here we consider the thermodynamics of the intracluster medium, in particular the profiles of density, temperature and related quantities, as well as integrated measurements of gas mass, average temperature, total luminosity and centre-excluded luminosity. We fit power-law scaling relations of each of these quantities as a function of redshift and cluster mass, which can be measured precisely and with minimal bias for these relaxed clusters using hydrostatic arguments. For the thermodynamic profiles, we jointly model the density and temperature and their intrinsic scatter as a function of radius, thus also capturing the behaviour of the gas pressure and entropy. For the integrated quantities, we also jointly fit a multidimensional intrinsic covariance. Our results reinforce the view that simple hydrodynamical models provide a good description of relaxed clusters outside their centres, but that additional heating and cooling processes are important in the inner regions (radii r ≲ 0.5 r2500 ≈ 0.15 r500). The thermodynamic profiles remain regular, with small intrinsic scatter, down to the smallest radii where deprojection is straightforward (˜20 kpc); within this radius, even the most relaxed systems show clear departures from spherical symmetry. Our results suggest that heating and cooling are continuously regulated in a tight feedback loop, allowing the cluster atmosphere to remain stratified on these scales.

The extended stellar substructures of four metal-poor globular clusters in the galactic bulge

NASA Astrophysics Data System (ADS)

Chun, Sang-Hyun; Sohn, Young-Jong

2015-08-01

We investigated stellar spatial density distribution around four metal-poor globular clusters (NGC 6266, NGC 6626, NGC 6642 and NGC 6723) in order to find extended stellar substructures. Wide-field deep J, H, and K imaging data were taken using the WFCAM near-infrared array on United Kingdom Infrared Telescope (UKIRT). The contamination of field stars around clusters was minimised by applying a statistical weighted filtering algorithm for the stars on the color-magnitude diagram. In two-dimensional isodensity contour map, we find that all four of the globular clusters shows tidal stripping stellar features in the form of tidal tails (NGC 6266 and NGC 6723) or small density lobes/chunk (NGC 6642 and NGC 6723). The stellar substructures extend toward the Galactic centre or anticancer, and the proper motion direction of the clusters. The radial density profiles of the clusters also depart from theoretical King and Wilson models and show overdensity feature with a break in a slope of profile at the outer region of clusters. The observed results indicate that four globular clusters in the Galactic bulge have experienced strong tidal force or bulge/disk shock effect of the Galaxy. These observational results provide us further constraints to understand the evolution of clusters in the Galactic bulge region as well as the formation of the Galaxy.

Use of a spatial scan statistic to identify clusters of births occurring outside Ghanaian health facilities for targeted intervention.

PubMed

Bosomprah, Samuel; Dotse-Gborgbortsi, Winfred; Aboagye, Patrick; Matthews, Zoe

2016-11-01

To identify and evaluate clusters of births that occurred outside health facilities in Ghana for targeted intervention. A retrospective study was conducted using a convenience sample of live births registered in Ghanaian health facilities from January 1 to December 31, 2014. Data were extracted from the district health information system. A spatial scan statistic was used to investigate clusters of home births through a discrete Poisson probability model. Scanning with a circular spatial window was conducted only for clusters with high rates of such deliveries. The district was used as the geographic unit of analysis. The likelihood P value was estimated using Monte Carlo simulations. Ten statistically significant clusters with a high rate of home birth were identified. The relative risks ranged from 1.43 ("least likely" cluster; P=0.001) to 1.95 ("most likely" cluster; P=0.001). The relative risks of the top five "most likely" clusters ranged from 1.68 to 1.95; these clusters were located in Ashanti, Brong Ahafo, and the Western, Eastern, and Greater regions of Accra. Health facility records, geospatial techniques, and geographic information systems provided locally relevant information to assist policy makers in delivering targeted interventions to small geographic areas. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Delivery of Iron-Sulfur Clusters to the Hydrogen-Oxidizing [NiFe]-Hydrogenases in Escherichia coli Requires the A-Type Carrier Proteins ErpA and IscA

PubMed Central

Pinske, Constanze; Sawers, R. Gary

2012-01-01

During anaerobic growth Escherichia coli synthesizes two membrane-associated hydrogen-oxidizing [NiFe]-hydrogenases, termed hydrogenase 1 and hydrogenase 2. Each enzyme comprises a catalytic subunit containing the [NiFe] cofactor, an electron-transferring small subunit with a particular complement of [Fe-S] (iron-sulfur) clusters and a membrane-anchor subunit. How the [Fe-S] clusters are delivered to the small subunit of these enzymes is unclear. A-type carrier (ATC) proteins of the Isc (iron-sulfur-cluster) and Suf (sulfur mobilization) [Fe-S] cluster biogenesis pathways are proposed to traffic pre-formed [Fe-S] clusters to apoprotein targets. Mutants that could not synthesize SufA had active hydrogenase 1 and hydrogenase 2 enzymes, thus demonstrating that the Suf machinery is not required for hydrogenase maturation. In contrast, mutants devoid of the IscA, ErpA or IscU proteins of the Isc machinery had no detectable hydrogenase 1 or 2 activities. Lack of activity of both enzymes correlated with the absence of the respective [Fe-S]-cluster-containing small subunit, which was apparently rapidly degraded. During biosynthesis the hydrogenase large subunits receive their [NiFe] cofactor from the Hyp maturation machinery. Subsequent to cofactor insertion a specific C-terminal processing step occurs before association of the large subunit with the small subunit. This processing step is independent of small subunit maturation. Using western blotting experiments it could be shown that although the amount of each hydrogenase large subunit was strongly reduced in the iscA and erpA mutants, some maturation of the large subunit still occurred. Moreover, in contrast to the situation in Isc-proficient strains, these processed large subunits were not membrane-associated. Taken together, our findings demonstrate that both IscA and ErpA are required for [Fe-S] cluster delivery to the small subunits of the hydrogen-oxidizing hydrogenases; however, delivery of the Fe atom to the active site might have different requirements. PMID:22363723

The Mass Function of Abell Clusters

NASA Astrophysics Data System (ADS)

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

1998-12-01

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

Dark energy domination in the Virgocentric flow

NASA Astrophysics Data System (ADS)

Chernin, A. D.; Karachentsev, I. D.; Nasonova, O. G.; Teerikorpi, P.; Valtonen, M. J.; Dolgachev, V. P.; Domozhilova, L. M.; Byrd, G. G.

2010-09-01

Context. The standard ΛCDM cosmological model implies that all celestial bodies are embedded in a perfectly uniform dark energy background, represented by Einstein's cosmological constant, and experience its repulsive antigravity action. Aims: Can dark energy have strong dynamical effects on small cosmic scales as well as globally? Continuing our efforts to clarify this question, we now focus on the Virgo Cluster and the flow of expansion around it. Methods: We interpret the Hubble diagram from a new database of velocities and distances of galaxies in the cluster and its environment, using a nonlinear analytical model, which incorporates the antigravity force in terms of Newtonian mechanics. The key parameter is the zero-gravity radius, the distance at which gravity and antigravity are in balance. Results: 1. The interplay between the gravity of the cluster and the antigravity of the dark energy background determines the kinematical structure of the system and controls its evolution. 2. The gravity dominates the quasi-stationary bound cluster, while the antigravity controls the Virgocentric flow, bringing order and regularity to the flow, which reaches linearity and the global Hubble rate at distances ⪆15 Mpc. 3. The cluster and the flow form a system similar to the Local Group and its outflow. In the velocity-distance diagram, the cluster-flow structure reproduces the group-flow structure with a scaling factor of about 10; the zero-gravity radius for the cluster system is also 10 times larger. Conclusions: The phase and dynamical similarity of the systems on the scales of 1-30 Mpc suggests that a two-component pattern may be universal for groups and clusters: a quasi-stationary bound central component and an expanding outflow around it, caused by the nonlinear gravity-antigravity interplay with the dark energy dominating in the flow component.

Magnetic nanostructures.

PubMed

Bennemann, K

2010-06-23

Characteristic results of magnetism in small particles, thin films and tunnel junctions are presented. As a consequence of the reduced atomic coordination in small clusters and thin films the electronic states and density of states are modified. Thus, magnetic moments and magnetization are affected. Generally, in clusters and thin films magnetic anisotropy plays a special role. In tunnel junctions the interplay of magnetism, spin currents and superconductivity are of particular interest. In ring-like mesoscopic systems Aharonov-Bohm-induced currents are studied. Results are given for single transition metal clusters, cluster ensembles, thin films, mesoscopic structures and tunnel systems. © 2010 IOP Publishing Ltd

Analysis of radiation-induced small Cu particle cluster formation in aqueous CuCl2

USGS Publications Warehouse

Jayanetti, Sumedha; Mayanovic, Robert A.; Anderson, Alan J.; Bassett, William A.; Chou, I.-Ming

2001-01-01

Radition-induced small Cu particle cluster formation in aqueous CuCl2 was analyzed. It was noticed that nearest neighbor distance increased with the increase in the time of irradiation. This showed that the clusters approached the lattice dimension of bulk copper. As the average cluster size approached its bulk dimensions, an increase in the nearest neighbor coordination number was found with the decrease in the surface to volume ratio. Radiolysis of water by incident x-ray beam led to the reduction of copper ions in the solution to themetallic state.

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

Phosphatidylinositol 4,5-Bisphosphate Clusters the Cell Adhesion Molecule CD44 and Assembles a Specific CD44-Ezrin Heterocomplex, as Revealed by Small Angle Neutron Scattering*

PubMed Central

Chen, Xiaodong; Khajeh, Jahan Ali; Ju, Jeong Ho; Gupta, Yogesh K.; Stanley, Christopher B.; Do, Changwoo; Heller, William T.; Aggarwal, Aneel K.; Callaway, David J. E.; Bu, Zimei

2015-01-01

The cell adhesion molecule CD44 regulates diverse cellular functions, including cell-cell and cell-matrix interaction, cell motility, migration, differentiation, and growth. In cells, CD44 co-localizes with the membrane-cytoskeleton adapter protein Ezrin that links the CD44 assembled receptor signaling complexes to the cytoskeletal actin network, which organizes the spatial and temporal localization of signaling events. Here we report that the cytoplasmic tail of CD44 (CD44ct) is largely disordered. Upon binding to the signaling lipid phosphatidylinositol 4,5-bisphosphate (PIP2), CD44ct clusters into aggregates. Further, contrary to the generally accepted model, CD44ct does not bind directly to the FERM domain of Ezrin or to the full-length Ezrin but only forms a complex with FERM or with the full-length Ezrin in the presence of PIP2. Using contrast variation small angle neutron scattering, we show that PIP2 mediates the assembly of a specific heterotetramer complex of CD44ct with Ezrin. This study reveals the role of PIP2 in clustering CD44 and in assembling multimeric CD44-Ezrin complexes. We hypothesize that polyvalent electrostatic interactions are responsible for the assembly of CD44 clusters and the multimeric PIP2-CD44-Ezrin complexes. PMID:25572402

Phosphatidylinositol 4,5-bisphosphate clusters the cell adhesion molecule CD44 and assembles a specific CD44-Ezrin heterocomplex, as revealed by small angle neutron scattering.

PubMed

Chen, Xiaodong; Khajeh, Jahan Ali; Ju, Jeong Ho; Gupta, Yogesh K; Stanley, Christopher B; Do, Changwoo; Heller, William T; Aggarwal, Aneel K; Callaway, David J E; Bu, Zimei

2015-03-06

The cell adhesion molecule CD44 regulates diverse cellular functions, including cell-cell and cell-matrix interaction, cell motility, migration, differentiation, and growth. In cells, CD44 co-localizes with the membrane-cytoskeleton adapter protein Ezrin that links the CD44 assembled receptor signaling complexes to the cytoskeletal actin network, which organizes the spatial and temporal localization of signaling events. Here we report that the cytoplasmic tail of CD44 (CD44ct) is largely disordered. Upon binding to the signaling lipid phosphatidylinositol 4,5-bisphosphate (PIP2), CD44ct clusters into aggregates. Further, contrary to the generally accepted model, CD44ct does not bind directly to the FERM domain of Ezrin or to the full-length Ezrin but only forms a complex with FERM or with the full-length Ezrin in the presence of PIP2. Using contrast variation small angle neutron scattering, we show that PIP2 mediates the assembly of a specific heterotetramer complex of CD44ct with Ezrin. This study reveals the role of PIP2 in clustering CD44 and in assembling multimeric CD44-Ezrin complexes. We hypothesize that polyvalent electrostatic interactions are responsible for the assembly of CD44 clusters and the multimeric PIP2-CD44-Ezrin complexes. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

A novel approach to internal crown characterization for coniferous tree species classification

NASA Astrophysics Data System (ADS)

Harikumar, A.; Bovolo, F.; Bruzzone, L.

2016-10-01

The knowledge about individual trees in forest is highly beneficial in forest management. High density small foot- print multi-return airborne Light Detection and Ranging (LiDAR) data can provide a very accurate information about the structural properties of individual trees in forests. Every tree species has a unique set of crown structural characteristics that can be used for tree species classification. In this paper, we use both the internal and external crown structural information of a conifer tree crown, derived from a high density small foot-print multi-return LiDAR data acquisition for species classification. Considering the fact that branches are the major building blocks of a conifer tree crown, we obtain the internal crown structural information using a branch level analysis. The structure of each conifer branch is represented using clusters in the LiDAR point cloud. We propose the joint use of the k-means clustering and geometric shape fitting, on the LiDAR data projected onto a novel 3-dimensional space, to identify branch clusters. After mapping the identified clusters back to the original space, six internal geometric features are estimated using a branch-level analysis. The external crown characteristics are modeled by using six least correlated features based on cone fitting and convex hull. Species classification is performed using a sparse Support Vector Machines (sparse SVM) classifier.

Monogenetic Volcano Clusters within the wider Michoacán-Guanajuato Volcanic Field (México) and their Significance

NASA Astrophysics Data System (ADS)

Siebe, C.

2017-12-01

The Trans-Mexican Volcanic Belt, one of the most complex and active continental arcs worldwide, displays several volcanic fields dominated by monogenetic volcanoes. Of these, the Plio-Quaternary Michoacán-Guanajuato Volcanic Field (MGVF) situated in central Mexico, is the largest monogenetic volcanic field in the world and includes more than 1000 scoria cones and associated lava flows and about 400 medium-sized volcanoes (Mexican shields). The smaller monogenetic vents occur either isolated or form small clusters within the wider MGVF. The recent identification of small clusters comprising several monogenetic volcanoes that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) in small areas within the much wider MGVF opens several questions in regard to future volcanic hazard assessments in this region: Are the youngest (Holocene) clusters still "active" and is a new eruption likely to occur within their surroundings? How long are such clusters "active"? Will the next monogenetic eruption in the MGVF be a single short-lived isolated eruption, or the beginning of a cluster? Furthermore, is it possible that the historic eruptions of Jorullo (1759) and Paricutin (1943) represent each the beginning of a cluster and should a new eruption in their proximity be expected in the future? In order to address these questions, two Holocene clusters, namely Tacámbaro and Malpaís de Zacapu are currently under study and preliminary results will be presented. Each comprises four monogenetic vents that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) within a small area (few tens of km2) Geologic mapping, geochemical analyses, radiometric dating, and paleomagnetic studies will help to establish the sequence of eruption of the different vents, and shed more light on the conditions that allow several magma sources to be formed and then tapped in close temporal and spatial proximity to each other and produce such small "flare-ups".

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

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

Kornilov, Oleg; Toennies, J. Peter

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

The effect of primary recoil spectrum on radiation induced segregation in nickel-silicon alloys

NASA Astrophysics Data System (ADS)

Averback, R. S.; Rehn, L. E.; Wagner, W.; Ehrhart, P.

1983-08-01

Segregation of silicon to the surface of Ni-12.7 at% Si alloys during 2.0-MeV He and 3.25-MeV Kr irradiations was measured using Rutherford backscattering spectrometry. For equal calculated defect production rates the Kr irradiation was < 3 % as efficient as the He irradiation for promoting segregation in the temperature range, 450 °C-580 °C. It was further observed that Kr preirradiation of specimens dramatically reduced segregation during subsequent He irradiation. A model for cascade annealing in Ni-Si alloys is presented which qualitatively explains the segregation results. The model assumes that small interstitial-atom-clusters form in individual cascades and that these clusters become trapped at silicon solute atoms. The vacancy thereby becomes the more mobile defect. The model should also have relevance for the observation that void swelling in nickel is suppressed by the addition of silicon solute.

A computational microscopy study of nanostructural evolution in irradiated pressure vessel steels

NASA Astrophysics Data System (ADS)

Odette, G. R.; Wirth, B. D.

1997-11-01

Nanostructural features that form in reactor pressure vessel steels under neutron irradiation at around 300°C lead to significant hardening and embrittlement. Continuum thermodynamic-kinetic based rate theories have been very successful in modeling the general characteristics of the copper and manganese nickel rich precipitate evolution, often the dominant source of embrittlement. However, a more detailed atomic scale understanding of these features is needed to interpret experimental measurements and better underpin predictive embrittlement models. Further, other embrittling features, believed to be subnanometer defect (vacancy)-solute complexes and small regions of modest enrichment of solutes are not well understood. A general approach to modeling embrittlement nanostructures, based on the concept of a computational microscope, is described. The objective of the computational microscope is to self-consistently integrate atomic scale simulations with other sources of information, including a wide range of experiments. In this work, lattice Monte Carlo (LMC) simulations are used to resolve the chemically and structurally complex nature of CuMnNiSi precipitates. The LMC simulations unify various nanoscale analytical characterization methods and basic thermodynamics. The LMC simulations also reveal that significant coupled vacancy and solute clustering takes place during cascade aging. The cascade clustering produces the metastable vacancy-cluster solute complexes that mediate flux effects. Cascade solute clustering may also play a role in the formation of dilute atmospheres of solute enrichment and enhance the nucleation of manganese-nickel rich precipitates at low Cu levels. Further, the simulations suggest that complex, highly correlated processes (e.g. cluster diffusion, formation of favored vacancy diffusion paths and solute scavenging vacancy cluster complexes) may lead to anomalous fast thermal aging kinetics at temperatures below about 450°C. The potential technical significance of these phenomena is described.

An improved model of homogeneous nucleation for high supersaturation conditions: aluminum vapor.

PubMed

Savel'ev, A M; Starik, A M

2016-12-21

A novel model of stationary nucleation, treating the thermodynamic functions of small clusters, has been built. The model is validated against the experimental data on the nucleation rate of water vapor obtained in a broad range of supersaturation values (S = 10-120), and, at high supersaturation values, it reproduces the experimental data much better than the traditional classical nucleation model. A comprehensive analysis of the nucleation of aluminum vapor with the usage of developed stationary and non-stationary nucleation models has been performed. It has been shown that, at some value of supersaturation, there exists a double potential nucleation barrier. It has been revealed that the existence of this barrier notably delayed the establishment of a stationary distribution of subcritical clusters. It has also been demonstrated that the non-stationary model of the present work and the model of liquid-droplet approximation predict different values of nucleation delay time, τ s . In doing so, the liquid-droplet model can underestimate notably (by more than an order of magnitude) the value of τ s .

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

Cluster size dependence of high-order harmonic generation

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

Fernando, Amendra; Weerawardene, K. L. Dimuthu M.; Karimova, Natalia V.

Here, metal, metal oxide, and metal chalcogenide materials have a wide variety of applications. For example, many metal clusters and nanoparticles are used as catalysts for reactions varying from the oxidation of carbon monoxide to the reduction of protons to hydrogen gas. Noble metal nanoparticles have unique optical properties such as a surface plasmon resonance for large nanoparticles that yield applications in sensing and photonics. In addition, a number of transition metal clusters are magnetic. Metal oxide clusters and surfaces are commonly used as catalysts for reactions such as water splitting. Both metal oxide and metal chalcogenide materials can bemore » semiconducting, which leads to applications in sensors, electronics, and solar cells. Many researchers have been interested in studying nanoparticles and/or small clusters of these materials. Some of the system sizes under investigation have been experimentally synthesized, which enables direct theory–experiment comparison. Other clusters that have been examined theoretically are of interest as models of larger systems or surfaces. Often, the size-dependence of their properties such as their HOMO–LUMO gap, magnetic properties, optical properties, etc., is of interest.« less

Evolution of colour-dependence of galaxy clustering up to z˜ 1.2 based on the data from the VVDS-Wide survey

NASA Astrophysics Data System (ADS)

Świetoń, Agnieszka; Pollo, Agnieszka; VVDS Team

2014-12-01

We discuss the dependence of galaxy clustering according to their colours up to z˜ 1.2. For that purpose we used one of the wide fields (F22) from the VIMOS-VLT Deep Survey (VVDS). For galaxies with absolute luminosities close to the characteristic Schechter luminosities M^* at a given redshift, we measured the projected two-point correlation function w_{p}(r_{p}) and we estimated the best-fit parameters for a single power-law model: ξ(r) = (r/r_0)^{-γ} , where r_0 is the correlation length and γ is the slope of correlation function. Our results show that red galaxies exhibit the strongest clustering in all epochs up to z˜ 1.2. Green valley represents the "intermediate" population and blue cloud shows the weakest clustering strength. We also compared the shape of w_p(r_p) for different galaxy populations. All three populations have different clustering properties on the small scales, similarly to the behaviour observed in the local catalogues.

Study of atmospheric dynamics and pollution in the coastal area of English Channel using clustering technique

NASA Astrophysics Data System (ADS)

Sokolov, Anton; Dmitriev, Egor; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmenten, Marc

2016-04-01

The problem of atmospheric contamination by principal air pollutants was considered in the industrialized coastal region of English Channel in Dunkirk influenced by north European metropolitan areas. MESO-NH nested models were used for the simulation of the local atmospheric dynamics and the online calculation of Lagrangian backward trajectories with 15-minute temporal resolution and the horizontal resolution down to 500 m. The one-month mesoscale numerical simulation was coupled with local pollution measurements of volatile organic components, particulate matter, ozone, sulphur dioxide and nitrogen oxides. Principal atmospheric pathways were determined by clustering technique applied to backward trajectories simulated. Six clusters were obtained which describe local atmospheric dynamics, four winds blowing through the English Channel, one coming from the south, and the biggest cluster with small wind speeds. This last cluster includes mostly sea breeze events. The analysis of meteorological data and pollution measurements allows relating the principal atmospheric pathways with local air contamination events. It was shown that contamination events are mostly connected with a channelling of pollution from local sources and low-turbulent states of the local atmosphere.

High-resolution Spectroscopic Abundances of Red Giant Branch Stars in NGC 6584 and NGC 7099

NASA Astrophysics Data System (ADS)

O’Malley, Erin M.; Chaboyer, Brian

2018-04-01

We obtain high-resolution spectra of red giant branch stars in NGC 6584 and NGC 7099 to perform a detailed abundance analysis. We confirm cluster membership for these stars based on consistent radial velocities measured in this study and small pixel offsets between the observations of Sarajedini et al. and Piotto et al. We find mean metallicities of [Fe/H] = ‑1.53 ± 0.08 dex and [Fe/H] = ‑2.29 ± 0.07 dex for NGC 6584 and NGC 7099, respectively. We also find these clusters to be enhanced in their [α/Fe] ratios, consistent with what is expected for metal-poor globular clusters. Additionally, we find evidence of a statistically significant Na–O anti-correlation in both clusters. Finally, with the use of HST photometry, we compare the location of the enhanced and pristine populations in chromosome maps of the clusters to confirm previous photometric evidence of multiple stellar populations. Although we cannot confirm the nature of the polluter stars responsible for the abundance differences, our results can be used to constrain pollution models.

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Use of advanced particle methods in modeling space propulsion and its supersonic expansions

NASA Astrophysics Data System (ADS)

Borner, Arnaud

This research discusses the use of advanced kinetic particle methods such as Molecular Dynamics (MD) and direct simulation Monte Carlo (DSMC) to model space propulsion systems such as electrospray thrusters and their supersonic expansions. MD simulations are performed to model an electrospray thruster for the ionic liquid (IL) EMIM--BF4 using coarse-grained (CG) potentials. The model is initially featuring a constant electric field applied in the longitudinal direction. Two coarse-grained potentials are compared, and the effective-force CG (EFCG) potential is found to predict the formation of the Taylor cone, the cone-jet, and other extrusion modes for similar electric fields and mass flow rates observed in experiments of a IL fed capillary-tip-extractor system better than the simple CG potential. Later, one-dimensional and fully transient three-dimensional electric fields, the latter solving Poisson's equation to take into account the electric field due to space charge at each timestep, are computed by coupling the MD model to a Poisson solver. It is found that the inhomogeneous electric field as well as that of the IL space-charge improve agreement between modeling and experiment. The boundary conditions (BCs) are found to have a substantial impact on the potential and electric field, and the tip BC is introduced and compared to the two previous BCs, named plate and needle, showing good improvement by reducing unrealistically high radial electric fields generated in the vicinity of the capillary tip. The influence of the different boundary condition models on charged species currents as a function of the mass flow rate is studied, and it is found that a constant electric field model gives similar agreement to the more rigorous and computationally expensive tip boundary condition at lower flow rates. However, at higher mass flow rates the MD simulations with the constant electric field produces extruded particles with higher Coulomb energy per ion, consistent with droplet formation. Supersonic expansions to vacuum produce clusters of sufficiently small size that properties such as heat capacities and latent heat of evaporation cannot be described by bulk vapor thermodynamic values. Therefore, MD simulations are performed to compute the evaporation rate of small water clusters as a function of temperature and size and the rates are found to agree with Unimolecular Dissociation Theory (UDT) and Classical Nucleation Theory (CNT). The heat capacities and latent heat of vaporization obtained from Monte-Carlo Canonical-Ensemble (MCCE) simulations are used in DSMC simulations of two experiments that measured Rayleigh scattering and terminal dimer mole fraction of supersonic water-jet expansions. Water-cluster temperature and size are found to be influenced by the use of kinetic rather than thermodynamic heat-capacity and latent-heat values as well as the nucleation model. Additionally, MD simulations of water condensation in a one-dimensional free expansion are performed to simulate the conditions in the core of a plume. We find that the internal structure of the clusters formed depends on the stagnation temperature conditions. Clusters of sizes 21 and 324 are studied in detail, and their radial distribution functions (RDF) are computed and compared to reported RDFs for solid amorphous ice clusters. Dielectric properties of liquid water and water clusters are investigated, and the static dielectric constant, dipole moment autocorrelation function and relative permittivity are computed by means of MD simulations.

Quantum Mechanical Studies of Large Metal, Metal Oxide, and Metal Chalcogenide Nanoparticles and Clusters

DOE PAGES

Fernando, Amendra; Weerawardene, K. L. Dimuthu M.; Karimova, Natalia V.; ...

2015-04-21

Here, metal, metal oxide, and metal chalcogenide materials have a wide variety of applications. For example, many metal clusters and nanoparticles are used as catalysts for reactions varying from the oxidation of carbon monoxide to the reduction of protons to hydrogen gas. Noble metal nanoparticles have unique optical properties such as a surface plasmon resonance for large nanoparticles that yield applications in sensing and photonics. In addition, a number of transition metal clusters are magnetic. Metal oxide clusters and surfaces are commonly used as catalysts for reactions such as water splitting. Both metal oxide and metal chalcogenide materials can bemore » semiconducting, which leads to applications in sensors, electronics, and solar cells. Many researchers have been interested in studying nanoparticles and/or small clusters of these materials. Some of the system sizes under investigation have been experimentally synthesized, which enables direct theory–experiment comparison. Other clusters that have been examined theoretically are of interest as models of larger systems or surfaces. Often, the size-dependence of their properties such as their HOMO–LUMO gap, magnetic properties, optical properties, etc., is of interest.« less

Aspects of Scale Invariance in Physics and Biology

NASA Astrophysics Data System (ADS)

Alba, Vasyl

We study three systems that have scale invariance. The first system is a conformal field theory in d > 3 dimensions. We prove that if there is a unique stress-energy tensor and at least one higher-spin conserved current in the theory, then the correlation functions of the stress-energy tensors and the conserved currents of higher-spin must coincide with one of the following possibilities: a) a theory of n free bosons, b) a theory of n free fermions or c) a theory of n (d-2)/2-forms. The second system is the primordial gravitational wave background in a theory with inflation. We show that the scale invariant spectrum of primordial gravitational waves is isotropic only in the zero-order approximation, and it gets a small correction due to the primordial scalar fluctuations. When anisotropy is measured experimentally, our result will allow us to distinguish between different inflationary models. The third system is a biological system. The question we are asking is whether there is some simplicity or universality underlying the complexities of natural animal behavior. We use the walking fruit fly (Drosophila melanogaster) as a model system. Based on the result that unsupervised flies' behaviors can be categorized into one hundred twenty-two discrete states (stereotyped movements), which all individuals from a single species visit repeatedly, we demonstrated that the sequences of states are strongly non-Markovian. In particular, correlations persist for an order of magnitude longer than expected from a model of random state-to-state transitions. The correlation function has a power-law decay, which is a hint of some kind of criticality in the system. We develop a generalization of the information bottleneck method that allows us to cluster these states into a small number of clusters. This more compact description preserves a lot of temporal correlation. We found that it is enough to use a two-cluster representation of the data to capture long-range correlations, which opens a way for a more quantitative description of the system. Usage of the maximal entropy method allowed us to find a description that closely resembles a famous inverse-square Ising model in 1d in a small magnetic field.

Kinetic Modeling of Slow Energy Release in Non-Ideal Carbon Rich Explosives

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

Vitello, P; Fried, L; Glaesemann, K

2006-06-20

We present here the first self-consistent kinetic based model for long time-scale energy release in detonation waves in the non-ideal explosive LX-17. Non-ideal, insensitive carbon rich explosives, such as those based on TATB, are believed to have significant late-time slow release in energy. One proposed source of this energy is diffusion-limited growth of carbon clusters. In this paper we consider the late-time energy release problem in detonation waves using the thermochemical code CHEETAH linked to a multidimensional ALE hydrodynamics model. The linked CHEETAH-ALE model dimensional treats slowly reacting chemical species using kinetic rate laws, with chemical equilibrium assumed for speciesmore » coupled via fast time-scale reactions. In the model presented here we include separate rate equations for the transformation of the un-reacted explosive to product gases and for the growth of a small particulate form of condensed graphite to a large particulate form. The small particulate graphite is assumed to be in chemical equilibrium with the gaseous species allowing for coupling between the instantaneous thermodynamic state and the production of graphite clusters. For the explosive burn rate a pressure dependent rate law was used. Low pressure freezing of the gas species mass fractions was also included to account for regions where the kinetic coupling rates become longer than the hydrodynamic time-scales. The model rate parameters were calibrated using cylinder and rate-stick experimental data. Excellent long time agreement and size effect results were achieved.« less

Constraints on Omega_0 and cluster evolution using the ROSAT log N-log S relation

NASA Astrophysics Data System (ADS)

Mathiesen, B.; Evrard, A. E.

1998-04-01

We examine the likelihoods of different cosmological models and cluster evolutionary histories by comparing semi-analytical predictions of X-ray cluster number counts with observational data from the ROSAT satellite. We model cluster abundance as a function of mass and redshift using a Press-Schechter distribution, and assume that the temperature T(M,z) and bolometric luminosity L_X(M,z) scale as power laws in mass and epoch, in order to construct expected counts as a function of X-ray flux. The L_X-M scaling is fixed using the local luminosity function, while the degree of evolution in the X-ray luminosity with redshift L_X~(1+z)^s is left open, with s an interesting free parameter which we investigate. We examine open and flat cosmologies with initial, scale-free fluctuation spectra having indices n=0, -1 and -2. An independent constraint arising from the slope of the luminosity-temperature relation strongly favours the n=-2 spectrum. The expected counts demonstrate a strong dependence on Omega_0 and s, with lesser dependence on lambda_0 and n. Comparison with the observed counts reveals a `ridge' of acceptable models in the Omega_0-s plane, roughly following the relation s~6Omega_0 and spanning low-density models with a small degree of evolution to Omega=1 models with strong evolution. Models with moderate evolution are revealed to have a strong lower limit of Omega_0>~0.3, and low-evolution models imply that Omega_0<1 at a very high confidence level. We suggest observational tests for breaking the degeneracy along this ridge, and discuss implications for evolutionary histories of the intracluster medium.

Hierarchically clustered adaptive quantization CMAC and its learning convergence.

PubMed

Teddy, S D; Lai, E M K; Quek, C

2007-11-01

The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC), learning convergence, nonuniform quantization.

Multiscale Computer Simulation of Tensile and Compressive Strain in Polymer- Coated Silica Aerogels

NASA Technical Reports Server (NTRS)

Good, Brian

2009-01-01

While the low thermal conductivities of silica aerogels have made them of interest to the aerospace community as lightweight thermal insulation, the application of conformal polymer coatings to these gels increases their strength significantly, making them potentially useful as structural materials as well. In this work we perform multiscale computer simulations to investigate the tensile and compressive strain behavior of silica and polymer-coated silica aerogels. Aerogels are made up of clusters of interconnected particles of amorphous silica of less than bulk density. We simulate gel nanostructure using a Diffusion Limited Cluster Aggregation (DLCA) procedure, which produces aggregates that exhibit fractal dimensions similar to those observed in real aerogels. We have previously found that model gels obtained via DLCA exhibited stress-strain curves characteristic of the experimentally observed brittle failure. However, the strain energetics near the expected point of failure were not consistent with such failure. This shortcoming may be due to the fact that the DLCA process produces model gels that are lacking in closed-loop substructures, compared with real gels. Our model gels therefore contain an excess of dangling strands, which tend to unravel under tensile strain, producing non-brittle failure. To address this problem, we have incorporated a modification to the DLCA algorithm that specifically produces closed loops in the model gels. We obtain the strain energetics of interparticle connections via atomistic molecular statics, and abstract the collective energy of the atomic bonds into a Morse potential scaled to describe gel particle interactions. Polymer coatings are similarly described. We apply repeated small uniaxial strains to DLCA clusters, and allow relaxation of the center eighty percent of the cluster between strains. The simulations produce energetics and stress-strain curves for looped and nonlooped clusters, for a variety of densities and interaction parameters.

Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches

PubMed Central

Boyack, Kevin W.; Newman, David; Duhon, Russell J.; Klavans, Richard; Patek, Michael; Biberstine, Joseph R.; Schijvenaars, Bob; Skupin, André; Ma, Nianli; Börner, Katy

2011-01-01

Background We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis. The few comparisons of clustering results from different similarity approaches have focused on small literature sets and have given conflicting results. Our study was designed to seek a robust answer to the question of which similarity approach would generate the most coherent clusters of a biomedical literature set of over two million documents. Methodology We used a corpus of 2.15 million recent (2004-2008) records from MEDLINE, and generated nine different document-document similarity matrices from information extracted from their bibliographic records, including titles, abstracts and subject headings. The nine approaches were comprised of five different analytical techniques with two data sources. The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models – BM25 and PMRA (PubMed Related Articles). The two data sources were a) MeSH subject headings, and b) words from titles and abstracts. Each similarity matrix was filtered to keep the top-n highest similarities per document and then clustered using a combination of graph layout and average-link clustering. Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE. Conclusions PubMed's own related article approach (PMRA) generated the most coherent and most concentrated cluster solution of the nine text-based similarity approaches tested, followed closely by the BM25 approach using titles and abstracts. Approaches using only MeSH subject headings were not competitive with those based on titles and abstracts. PMID:21437291

Assessing the capability of continuum and discrete particle methods to simulate gas-solids flow using DNS predictions as a benchmark

DOE PAGES

Lu, Liqiang; Liu, Xiaowen; Li, Tingwen; ...

2017-08-12

For this study, gas–solids flow in a three-dimension periodic domain was numerically investigated by direct numerical simulation (DNS), computational fluid dynamic-discrete element method (CFD-DEM) and two-fluid model (TFM). DNS data obtained by finely resolving the flow around every particle are used as a benchmark to assess the validity of coarser DEM and TFM approaches. The CFD-DEM predicts the correct cluster size distribution and under-predicts the macro-scale slip velocity even with a grid size as small as twice the particle diameter. The TFM approach predicts larger cluster size and lower slip velocity with a homogeneous drag correlation. Although the slip velocitymore » can be matched by a simple modification to the drag model, the predicted voidage distribution is still different from DNS: Both CFD-DEM and TFM over-predict the fraction of particles in dense regions and under-predict the fraction of particles in regions of intermediate void fractions. Also, the cluster aspect ratio of DNS is smaller than CFD-DEM and TFM. Since a simple correction to the drag model can predict a correct slip velocity, it is hopeful that drag corrections based on more elaborate theories that consider voidage gradient and particle fluctuations may be able to improve the current predictions of cluster distribution.« less

Assessing the capability of continuum and discrete particle methods to simulate gas-solids flow using DNS predictions as a benchmark

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

Lu, Liqiang; Liu, Xiaowen; Li, Tingwen

For this study, gas–solids flow in a three-dimension periodic domain was numerically investigated by direct numerical simulation (DNS), computational fluid dynamic-discrete element method (CFD-DEM) and two-fluid model (TFM). DNS data obtained by finely resolving the flow around every particle are used as a benchmark to assess the validity of coarser DEM and TFM approaches. The CFD-DEM predicts the correct cluster size distribution and under-predicts the macro-scale slip velocity even with a grid size as small as twice the particle diameter. The TFM approach predicts larger cluster size and lower slip velocity with a homogeneous drag correlation. Although the slip velocitymore » can be matched by a simple modification to the drag model, the predicted voidage distribution is still different from DNS: Both CFD-DEM and TFM over-predict the fraction of particles in dense regions and under-predict the fraction of particles in regions of intermediate void fractions. Also, the cluster aspect ratio of DNS is smaller than CFD-DEM and TFM. Since a simple correction to the drag model can predict a correct slip velocity, it is hopeful that drag corrections based on more elaborate theories that consider voidage gradient and particle fluctuations may be able to improve the current predictions of cluster distribution.« less

Implications of a localized zone of seismic activity near the Inner Piedmont-Blue Ridge boundary

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

Douglas, S.; Powell, C.

1994-03-01

A small but distinct cluster of earthquake activity is located in Henderson County, NC, near the boundary of the Inner Piedmont and Blue Ridge physiographic provinces. Over twenty events have occurred within the cluster since 1776 and four had body-wave magnitudes exceeding 3.0. Average focal depth for instrumentally recorded events is 7.7 km. Epicenters plot within the Inner Piedmont, roughly 13 km from the surface expression of the Brevard fault zone. The reason for sustained earthquake activity in Henderson County is not known but the close spatial association of the events with the Brevard fault suggests a causal relationship. Themore » Brevard zone dips steeply to the SE and the events could be associated with the fault at depth. An even more intriguing possibility is that the events are associated with the intersection of the Brevard zone and the decollemont; this possibility is compatible with available information concerning the depth to the decollemont and the dip on the Brevard zone. An association of seismic activity with the Brevard zone at depth is supported by the presence of another small cluster of activity located in Rutherford County, NC. This cluster is located in the Inner Piedmont, roughly 30 km NE of the Henderson cluster and 16 km from the Brevard fault zone. Association of seismic activity with known faults is very rare in the eastern US and has implications for tectonic models and hazard evaluation. Additional research must be conducted to determine the feasibility that activity is associated with the Brevard zone.« less

Dual structural transition in small nanoparticles of Cu-Au alloy

NASA Astrophysics Data System (ADS)

Gafner, Yuri; Gafner, Svetlana; Redel, Larisa; Zamulin, Ivan

2018-02-01

Cu-Au alloy nanoparticles are known to be widely used in the catalysis of various chemical reactions as it was experimentally defined that in many cases the partial substitution of copper with gold increases catalytic activity. However, providing the reaction capacity of alloy nanoparticles the surface electronic structure strongly depends on their atomic ordering. Therefore, to theoretically determine catalytic properties, one needs to use a most real structural model complying with Cu-Au nanoparticles under various external influences. So, thermal stability limits were studied for the initial L12 phase in Cu3Au nanoalloy clusters up to 8.0 nm and Cu-Au clusters up to 3.0 nm at various degrees of Au atom concentration, with molecular dynamics method using a modified tight-binding TB-SMA potential. Dual structural transition L12 → FCC and further FCC → Ih is shown to be possible under the thermal factor in Cu3Au and Cu-Au clusters with the diameter up to 3.0 nm. The temperature of the structural transition FCC → Ih is established to decrease for small particles of Cu-Au alloy under the increase of Au atom concentration. For clusters with this structural transition, the melting point is found to be a linear increasing function of concentration, and for clusters without FCC → Ih structural transition, the melting point is a linear decreasing function of Au content. Thus, the article shows that doping Cu nanoclusters with Au atoms allows to control the forming structure as well as the melting point.

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

PubMed

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

2015-11-10

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

Melting of size-selected gallium clusters with 60-183 atoms.

PubMed

Pyfer, Katheryne L; Kafader, Jared O; Yalamanchali, Anirudh; Jarrold, Martin F

2014-07-10

Heat capacities have been measured as a function of temperature for size-selected gallium cluster cations with between 60 and 183 atoms. Almost all clusters studied show a single peak in the heat capacity that is attributed to a melting transition. The peaks can be fit by a two-state model incorporating only fully solid-like and fully liquid-like species, and hence no partially melted intermediates. The exceptions are Ga90(+), which does not show a peak, and Ga80(+) and Ga81(+), which show two peaks. For the clusters with two peaks, the lower temperature peak is attributed to a structural transition. The melting temperatures for clusters with less than 50 atoms have previously been shown to be hundreds of degrees above the bulk melting point. For clusters with more than 60 atoms the melting temperatures decrease, approaching the bulk value (303 K) at around 95 atoms, and then show several small upward excursions with increasing cluster size. A plot of the latent heat against the entropy change for melting reveals two groups of clusters: the latent heats and entropy changes for clusters with less than 94 atoms are distinct from those for clusters with more than 93 atoms. This observation suggests that a significant change in the nature of the bonding or the structure of the clusters occurs at 93-94 atoms. Even though the melting temperatures are close to the bulk value for the larger clusters studied here, the latent heats and entropies of melting are still far from the bulk values.

Coulomb Fission in Multiply-Charged Ammonia Clusters: Accurate Measurements of the Rayleigh Instability Limit from Fragmentation Patterns.

PubMed

Harris, Christopher; Stace, Anthony J

2018-03-15

A series of experiments have been undertaken on the fragmentation of multiply charged ammonia clusters, (NH 3 ) n z+ , where z ≤ 8 and n ≤ 850, to establish Rayleigh instability limits, whereby clusters at certain critical sizes become unstable due to Coulomb repulsion between the resident charges. Experimental results on size-selected clusters are found to be in excellent agreement with theoretical predictions of Rayleigh instability limits at all values of the charge. Electrostatic theory has been used to help identify fragmentation patterns on the assumption that the clusters separate into two dielectric spheres, and the predicted Coulomb repulsion energies used to establish pathways and the sizes of cluster fragments. The results show that fragmentation is very asymmetric in terms of both the numbers of molecules involved and the amount of charge each fragment accommodates. For clusters carrying a charge ≤+4, the results show that fragmentation proceeds via the loss of small, singly charged clusters. When clusters carry a charge of +5 or more, the experimental observations suggest a marked switch in behavior. Although the laboratory measurements equate to fragmentation via the loss of a large dication cluster, electrostatic theory supports an interpretation that involves the sequential loss of two smaller, singly charged clusters possibly accompanied by the extensive evaporation of neutral molecules. It is suggested that this change in fragmentation pattern is driven by the channelling of Coulomb repulsion energy into intermolecular modes within these larger clusters. Overall, the results appear to support the ion evaporation model that is frequently used to interpret electrospray experiments.

Evaluating effective pair and multisite interactions for Ni-Mo system

NASA Astrophysics Data System (ADS)

Banerjee, Rumu H.; Arya, A.; Banerjee, S.

2018-04-01

Cluster expansion (CE) method was used to calculate the energies of various Ni-Mo phases. The clusters comprising of few nearest neighbours can describe any phase of Ni-Mo system by suitable choice of effective pair and multisite interaction parameters (ECI). The ECIs were evaluated in present study by fitting the ground state energies obtained by first principle calculations. The ECIs evaluated for Ni-Mo system were mostly pair clusters followed by triplets and quadruplet clusters with cluster diameters in the range 2.54 - 10.20 Å. The ECI values diminished for multi-body (triplets and quadruplets) clusters as compared to 2-point or pair clusters indicating a good convergence of CE model. With these ECIs the predicted energies of all the Ni-Mo structures across the Mo concentration range 0-100 at% were obtained. The quantitative error in the energies calculated by CE approach and first principle is very small (< 0.026 meV/atom). The appreciable values of 2-point ECIs upto 4th nearest neighbour reveal that two body interactions are dominant in the case of Ni-Mo system. These ECIs are compared with the reported values of compositional dependent effective pair interactions evaluated by first principle as well as by Monte Carlo method.

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

PubMed

Yao, Hiroshi; Iwatsu, Mana

2016-04-05

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

Growth of Ammonium Bisulfate Clusters by Adsorption of Oxygenated Organic Molecules

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

DePalma, Joseph W.; Wang, Jian; Wexler, Anthony S.

Quantum chemical calculations were employed to model the interactions of the [(NH 4 +) 4(HSO 4 -) 4] ammonium bisulfate cluster with one or more molecular products of monoterpene oxidation. A strong interaction was found between the bisulfate ion of the cluster and a carboxylic acid, aldehyde or ketone functionality of the organic molecule. Free energies of adsorption for carboxylic acids were in the -70 to -73 kJ/mol range, while those for aldehydes and ketones were in the -46 to -50 kJ/mol range. These values suggest that a small ambient ammonium bisulfate cluster, such as the [(NH 4 +) 4(SOmore » 4 -) 4] cluster, is able to adsorb an oxygenated organic molecule. Although adsorption of the first molecule is highly favorable, adsorption of subsequent molecules is not, suggesting that sustained uptake of organic molecules does not occur, and thus is not a pathway for continuing growth of the cluster. This result is consistent with ambient measurements showing that particles below ~1 nm grow slowly, while those above 1 nm grow at an increasing rate presumably due to a lower surface energy barrier enabling the uptake of organic molecules. This work provides insight into the molecular level interactions which affect sustained cluster growth by uptake of organic molecules.« less

Growth of Ammonium Bisulfate Clusters by Adsorption of Oxygenated Organic Molecules

DOE PAGES

DePalma, Joseph W.; Wang, Jian; Wexler, Anthony S.; ...

2015-10-21

Quantum chemical calculations were employed to model the interactions of the [(NH 4 +) 4(HSO 4 -) 4] ammonium bisulfate cluster with one or more molecular products of monoterpene oxidation. A strong interaction was found between the bisulfate ion of the cluster and a carboxylic acid, aldehyde or ketone functionality of the organic molecule. Free energies of adsorption for carboxylic acids were in the -70 to -73 kJ/mol range, while those for aldehydes and ketones were in the -46 to -50 kJ/mol range. These values suggest that a small ambient ammonium bisulfate cluster, such as the [(NH 4 +) 4(SOmore » 4 -) 4] cluster, is able to adsorb an oxygenated organic molecule. Although adsorption of the first molecule is highly favorable, adsorption of subsequent molecules is not, suggesting that sustained uptake of organic molecules does not occur, and thus is not a pathway for continuing growth of the cluster. This result is consistent with ambient measurements showing that particles below ~1 nm grow slowly, while those above 1 nm grow at an increasing rate presumably due to a lower surface energy barrier enabling the uptake of organic molecules. This work provides insight into the molecular level interactions which affect sustained cluster growth by uptake of organic molecules.« less

Local Higher-Order Graph Clustering

PubMed Central

Yin, Hao; Benson, Austin R.; Leskovec, Jure; Gleich, David F.

2018-01-01

Local graph clustering methods aim to find a cluster of nodes by exploring a small region of the graph. These methods are attractive because they enable targeted clustering around a given seed node and are faster than traditional global graph clustering methods because their runtime does not depend on the size of the input graph. However, current local graph partitioning methods are not designed to account for the higher-order structures crucial to the network, nor can they effectively handle directed networks. Here we introduce a new class of local graph clustering methods that address these issues by incorporating higher-order network information captured by small subgraphs, also called network motifs. We develop the Motif-based Approximate Personalized PageRank (MAPPR) algorithm that finds clusters containing a seed node with minimal motif conductance, a generalization of the conductance metric for network motifs. We generalize existing theory to prove the fast running time (independent of the size of the graph) and obtain theoretical guarantees on the cluster quality (in terms of motif conductance). We also develop a theory of node neighborhoods for finding sets that have small motif conductance, and apply these results to the case of finding good seed nodes to use as input to the MAPPR algorithm. Experimental validation on community detection tasks in both synthetic and real-world networks, shows that our new framework MAPPR outperforms the current edge-based personalized PageRank methodology. PMID:29770258

Constrained Maximum Likelihood Estimation of Relative Abundances of Protein Conformation in a Heterogeneous Mixture from Small Angle X-Ray Scattering Intensity Measurements

PubMed Central

Onuk, A. Emre; Akcakaya, Murat; Bardhan, Jaydeep P.; Erdogmus, Deniz; Brooks, Dana H.; Makowski, Lee

2015-01-01

In this paper, we describe a model for maximum likelihood estimation (MLE) of the relative abundances of different conformations of a protein in a heterogeneous mixture from small angle X-ray scattering (SAXS) intensities. To consider cases where the solution includes intermediate or unknown conformations, we develop a subset selection method based on k-means clustering and the Cramér-Rao bound on the mixture coefficient estimation error to find a sparse basis set that represents the space spanned by the measured SAXS intensities of the known conformations of a protein. Then, using the selected basis set and the assumptions on the model for the intensity measurements, we show that the MLE model can be expressed as a constrained convex optimization problem. Employing the adenylate kinase (ADK) protein and its known conformations as an example, and using Monte Carlo simulations, we demonstrate the performance of the proposed estimation scheme. Here, although we use 45 crystallographically determined experimental structures and we could generate many more using, for instance, molecular dynamics calculations, the clustering technique indicates that the data cannot support the determination of relative abundances for more than 5 conformations. The estimation of this maximum number of conformations is intrinsic to the methodology we have used here. PMID:26924916

Fault Network Reconstruction using Agglomerative Clustering: Applications to South Californian Seismicity

NASA Astrophysics Data System (ADS)

Kamer, Yavor; Ouillon, Guy; Sornette, Didier; Wössner, Jochen

2014-05-01

We present applications of a new clustering method for fault network reconstruction based on the spatial distribution of seismicity. Unlike common approaches that start from the simplest large scale and gradually increase the complexity trying to explain the small scales, our method uses a bottom-up approach, by an initial sampling of the small scales and then reducing the complexity. The new approach also exploits the location uncertainty associated with each event in order to obtain a more accurate representation of the spatial probability distribution of the seismicity. For a given dataset, we first construct an agglomerative hierarchical cluster (AHC) tree based on Ward's minimum variance linkage. Such a tree starts out with one cluster and progressively branches out into an increasing number of clusters. To atomize the structure into its constitutive protoclusters, we initialize a Gaussian Mixture Modeling (GMM) at a given level of the hierarchical clustering tree. We then let the GMM converge using an Expectation Maximization (EM) algorithm. The kernels that become ill defined (less than 4 points) at the end of the EM are discarded. By incrementing the number of initialization clusters (by atomizing at increasingly populated levels of the AHC tree) and repeating the procedure above, we are able to determine the maximum number of Gaussian kernels the structure can hold. The kernels in this configuration constitute our protoclusters. In this setting, merging of any pair will lessen the likelihood (calculated over the pdf of the kernels) but in turn will reduce the model's complexity. The information loss/gain of any possible merging can thus be quantified based on the Minimum Description Length (MDL) principle. Similar to an inter-distance matrix, where the matrix element di,j gives the distance between points i and j, we can construct a MDL gain/loss matrix where mi,j gives the information gain/loss resulting from the merging of kernels i and j. Based on this matrix, merging events resulting in MDL gain are performed in descending order until no gainful merging is possible anymore. We envision that the results of this study could lead to a better understanding of the complex interactions within the Californian fault system and hopefully use the acquired insights for earthquake forecasting.

Emergence of social structures via preferential selection

NASA Astrophysics Data System (ADS)

Lipowski, Adam; Lipowska, Dorota; Ferreira, Antonio Luis

2014-09-01

We examine a weighted-network multiagent model with preferential selection such that agents choose partners with probability p (w), where w is the number of their past selections. When p (w) increases sublinearly with the number of past selections [p(w)˜wα,α<1], agents develop a uniform preference for all other agents. At α =1, this state loses stability and more complex structures form. For a superlinear increase (α>1), strong heterogeneities emerge and agents make selections mainly within small and sometimes asymmetric clusters. Even in a few-agent case, the formation of such clusters resembles phase transitions with spontaneous symmetry breaking.

Tuberculosis outbreaks predicted by characteristics of first patients in a DNA fingerprint cluster.

PubMed

Kik, Sandra V; Verver, Suzanne; van Soolingen, Dick; de Haas, Petra E W; Cobelens, Frank G; Kremer, Kristin; van Deutekom, Henk; Borgdorff, Martien W

2008-07-01

Some clusters of patients who have Mycobacterium tuberculosis isolates with identical DNA fingerprint patterns grow faster than others. It is unclear what predictors determine cluster growth. To assess whether the development of a tuberculosis (TB) outbreak can be predicted by the characteristics of its first two patients. Demographic and clinical data of all culture-confirmed patients with TB in the Netherlands from 1993 through 2004 were combined with DNA fingerprint data. Clusters were restricted to cluster episodes of 2 years to only detect newly arising clusters. Characteristics of the first two patients were compared between small (2-4 cases) and large (5 or more cases) cluster episodes. Of 5,454 clustered cases, 1,756 (32%) were part of a cluster episode of 2 years. Of 622 cluster episodes, 54 (9%) were large and 568 (91%) were small episodes. Independent predictors for large cluster episodes were as follows: less than 3 months' time between the diagnosis of the first two patients, one or both patients were young (<35 yr), both patients lived in an urban area, and both patients came from sub-Saharan Africa. In the Netherlands, patients in new cluster episodes should be screened for these risk factors. When the risk pattern applies, targeted interventions (e.g., intensified contact investigation) should be considered to prevent further cluster expansion.

Application of a three-feature dispersed-barrier hardening model to neutron-irradiated Fe-Cr model alloys

NASA Astrophysics Data System (ADS)

Bergner, F.; Pareige, C.; Hernández-Mayoral, M.; Malerba, L.; Heintze, C.

2014-05-01

An attempt is made to quantify the contributions of different types of defect-solute clusters to the total irradiation-induced yield stress increase in neutron-irradiated (300 °C, 0.6 dpa), industrial-purity Fe-Cr model alloys (target Cr contents of 2.5, 5, 9 and 12 at.% Cr). Former work based on the application of transmission electron microscopy, atom probe tomography, and small-angle neutron scattering revealed the formation of dislocation loops, NiSiPCr-enriched clusters and α‧-phase particles, which act as obstacles to dislocation glide. The values of the dimensionless obstacle strength are estimated in the framework of a three-feature dispersed-barrier hardening model. Special attention is paid to the effect of measuring errors, experimental details and model details on the estimates. The three families of obstacles and the hardening model are well capable of reproducing the observed yield stress increase as a function of Cr content, suggesting that the nanostructural features identified experimentally are the main, if not the only, causes of irradiation hardening in these model alloys.

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.

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

Lupi, Laura; Kastelowitz, Noah; Molinero, Valeria, E-mail: Valeria.Molinero@utah.edu

Carbonaceous surfaces are a major source of atmospheric particles and could play an important role in the formation of ice. Here we investigate through molecular simulations the stability, metastability, and molecular pathways of deposition of amorphous ice, bilayer ice, and ice I from water vapor on graphitic and atomless Lennard-Jones surfaces as a function of temperature. We find that bilayer ice is the most stable ice polymorph for small cluster sizes, nevertheless it can grow metastable well above its region of thermodynamic stability. In agreement with experiments, the simulations predict that on increasing temperature the outcome of water deposition ismore » amorphous ice, bilayer ice, ice I, and liquid water. The deposition nucleation of bilayer ice and ice I is preceded by the formation of small liquid clusters, which have two wetting states: bilayer pancake-like (wetting) at small cluster size and droplet-like (non-wetting) at larger cluster size. The wetting state of liquid clusters determines which ice polymorph is nucleated: bilayer ice nucleates from wetting bilayer liquid clusters and ice I from non-wetting liquid clusters. The maximum temperature for nucleation of bilayer ice on flat surfaces, T{sub B}{sup max} is given by the maximum temperature for which liquid water clusters reach the equilibrium melting line of bilayer ice as wetting bilayer clusters. Increasing water-surface attraction stabilizes the pancake-like wetting state of liquid clusters leading to larger T{sub B}{sup max} for the flat non-hydrogen bonding surfaces of this study. The findings of this study should be of relevance for the understanding of ice formation by deposition mode on carbonaceous atmospheric particles, including soot.« less

Properties of Vacancy Complexes with Hydrogen and Helium Atoms in Tungsten from First Principles

DOE PAGES

Samolyuk, German D.; Osetsky, Yury N.; Stoller, Roger E.

2016-12-03

Tungsten and its alloys are the primary candidate materials for plasma-facing components in fusion reactors. The material is exposed to high-energy neutrons and the high flux of helium and hydrogen atoms. In this paper, we have studied the properties of vacancy clusters and their interaction with H and He in W using density functional theory. Convergence of calculations with respect to modeling cell size was investigated. It is demonstrated that vacancy cluster formation energy converges with small cells with a size of 6 × 6 × 6 (432 lattice sites) enough to consider a microvoid of up to six vacanciesmore » with high accuracy. Most of the vacancy clusters containing fewer than six vacancies are unstable. Introducing He or H atoms increases their binding energy potentially making gas-filled bubbles stable. Finally, according to the results of the calculations, the H 2 molecule is unstable in clusters containing six or fewer vacancies.« less

An ab initio-based Er–He interatomic potential in hcp Er

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

Yang, Li; ye, Yeting; Fan, K. M.

2014-09-01

We have developed an empirical erbium-helium (Er-He) potential by fitting to the results calculated from ab initio method. Based on the electronic hybridization between Er and He atoms, an s-band model, along with a repulsive pair potential, has been derived to describe the Er-He interaction. The atomic configurations and the formation energies of single He defects, small He interstitial clusters (Hen) and He-vacancy (HenV ) clusters obtained by ab initio calculations are used as the fitting database. The binding energies and relative stabilities of the HnVm clusters are studied by the present potential and compared with the ab initio calculations.more » The Er-He potential is also applied to study the migration of He in hcp-Er at different temperatures, and He clustering is found to occur at 600 K in hcp Er crystal, which may be due to the anisotropic migration behavior of He interstitials.« less

Experiments in clustered neuronal networks: A paradigm for complex modular dynamics

NASA Astrophysics Data System (ADS)

Teller, Sara; Soriano, Jordi

2016-06-01

Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.

Viscoelasticity promotes collective swimming of sperm

NASA Astrophysics Data System (ADS)

Tung, Chih-Kuan; Harvey, Benedict B.; Fiore, Alyssa G.; Ardon, Florencia; Suarez, Susan S.; Wu, Mingming

From flocking birds to swarming insects, interactions of organisms large and small lead to the emergence of collective dynamics. Here, we report striking collective swimming of bovine sperm, with sperm orienting in the same direction within each cluster, enabled by the viscoelasticity of the fluid. A long-chain polyacrylamide solution was used as a model viscoelastic fluid such that its rheology can be fine-tuned to mimic that of bovine cervical mucus. In viscoelastic fluid, sperm formed dynamic clusters, and the cluster size increased with elasticity of the polyacrylamide solution. In contrast, sperm swam randomly and individually in Newtonian fluids of similar viscosity. Analysis of the fluid motion surrounding individual swimming sperm indicated that sperm-fluid interaction is facilitated by the elastic component of the fluid. We note that almost all biological fluids (e.g. mucus and blood) are viscoelastic in nature, this finding highlights the importance of fluid elasticity in biological function. We will discuss what the orientation fluctuation within a cluster reveals about the interaction strength. Supported by NIH Grant 1R01HD070038.

THERMODYNAMICS AND CHARGING OF INTERSTELLAR IRON NANOPARTICLES

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

Hensley, Brandon S.; Draine, B. T., E-mail: brandon.s.hensley@jpl.nasa.gov

Interstellar iron in the form of metallic iron nanoparticles may constitute a component of the interstellar dust. We compute the stability of iron nanoparticles to sublimation in the interstellar radiation field, finding that iron clusters can persist down to a radius of ≃4.5 Å, and perhaps smaller. We employ laboratory data on small iron clusters to compute the photoelectric yields as a function of grain size and the resulting grain charge distribution in various interstellar environments, finding that iron nanoparticles can acquire negative charges, particularly in regions with high gas temperatures and ionization fractions. If ≳10% of the interstellar ironmore » is in the form of ultrasmall iron clusters, the photoelectric heating rate from dust may be increased by up to tens of percent relative to dust models with only carbonaceous and silicate grains.« less

Interactions of small platinum clusters with the TiC(001) surface

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

Mao, Jianjun; Li, Shasha; Chu, Xingli

2015-11-14

Density functional theory calculations are used to elucidate the interactions of small platinum clusters (Pt{sub n}, n = 1–5) with the TiC(001) surface. The results are analyzed in terms of geometric, energetic, and electronic properties. It is found that a single Pt atom prefers to be adsorbed at the C-top site, while a Pt{sub 2} cluster prefers dimerization and a Pt{sub 3} cluster forms a linear structure on the TiC(001). As for the Pt{sub 4} cluster, the three-dimensional distorted tetrahedral structure and the two-dimensional square structure almost have equal stability. In contrast with the two-dimensional isolated Pt{sub 5} cluster, the adsorbed Pt{submore » 5} cluster prefers a three-dimensional structure on TiC(001). Substantial charge transfer takes place from TiC(001) surface to the adsorbed Pt{sub n} clusters, resulting in the negatively charged Pt{sub n} clusters. At last, the d-band centers of the absorbed Pt atoms and their implications in the catalytic activity are discussed.« less

Spectroscopic determination of fundamental parameters of small angular diameter galactic open clusters

NASA Astrophysics Data System (ADS)

Ahumada, A. V.; Claria, J. J.; Bica, E.; Parisi, M. C.; Torres, M. C.; Pavani, D. B.

We present integrated spectra obtained at CASLEO (Argentina) for 9 galactic open clusters of small angular diameter. Two of them (BH 55 and Rup 159) have not been the target of previous research. The flux-calibrated spectra cover the spectral range approx. 3600-6900 A. Using the equivalent widths (EWs) of the Balmer lines and comparing the cluster spectra with template spectra, we determined E(B-V) colour excesses and ages for the present cluster sample. The parameters obtained for 6 of the clusters show good agreement with previous determinations based mainly on photometric methods. This is not the case, however, for BH 90, a scarcely reddened cluster, for which Moffat and Vogt (1975, Astron. and Astroph. SS, 20, 125) derived E(B-V) = 0.51. We explain and justify the strong discrepancy found for this object. According to the present analysis, 3 clusters are very young (Bo 14, Tr 15 and Tr 27), 2 are moderately young (NGC 6268 and BH 205), 3 are Hyades-like clusters (Rup 164, BH 90 and BH 55) and only one is an intermediate-age cluster (Rup 159).

The Origin of Dwarf Ellipticals in the Virgo Cluster

NASA Astrophysics Data System (ADS)

Boselli, A.; Boissier, S.; Cortese, L.; Gavazzi, G.

2008-02-01

We study the evolution of dwarf (LH < 109.6 LH⊙) star-forming and quiescent galaxies in the Virgo Cluster by comparing their UV to radio centimetric properties to the predictions of multizone chemospectrophotometric models of galaxy evolution especially tuned to take into account the perturbations induced by the interaction with the cluster intergalactic medium. Our models simulate one or multiple ram pressure stripping events and galaxy starvation. Models predict that all star-forming dwarf galaxies entering the cluster for the first time loose most, if not all, of their atomic gas content, quenching on short timescales (<=150 Myr) their activity of star formation. These dwarf galaxies soon become red and quiescent, gas metal-rich objects with spectrophotometric and structural properties similar to those of dwarf ellipticals. Young, low-luminosity, high surface brightness star-forming galaxies such as late-type spirals and BCDs are probably the progenitors of relatively massive dwarf ellipticals, while it is likely that low surface brightness Magellanic irregulars evolve into very low surface brightness quiescent objects hardly detectable in ground-based imaging surveys. The small number of dwarf galaxies with physical properties intermediate between those of star-forming and quiescent systems is consistent with a rapid (<1 Gyr) transitional phase between the two dwarf galaxy populations. These results, combined with statistical considerations, are consistent with the idea that most of the dwarf ellipticals dominating the faint end of the Virgo luminosity function were initially star-forming systems, accreted by the cluster and stripped of their gas by one or subsequent ram pressure stripping events.

Three-state Potts model on non-local directed small-world lattices

NASA Astrophysics Data System (ADS)

Ferraz, Carlos Handrey Araujo; Lima, José Luiz Sousa

2017-10-01

In this paper, we study the non-local directed Small-World (NLDSW) disorder effects in the three-state Potts model as a form to capture the essential features shared by real complex systems where non-locality effects play a important role in the behavior of these systems. Using Monte Carlo techniques and finite-size scaling analysis, we estimate the infinite lattice critical temperatures and the leading critical exponents in this model. In particular, we investigate the first- to second-order phase transition crossover when NLDSW links are inserted. A cluster-flip algorithm was used to reduce the critical slowing down effect in our simulations. We find that for a NLDSW disorder densities p

The formation and evolution of M33 as revealed by its star clusters

NASA Astrophysics Data System (ADS)

San Roman, Izaskun

2012-03-01

Numerical simulations based on the Lambda-Cold Dark Matter (Λ-CDM) model predict a scenario consistent with observational evidence in terms of the build-up of Milky Way-like halos. Under this scenario, large disk galaxies derive from the merger and accretion of many smaller subsystems. However, it is less clear how low-mass spiral galaxies fit into this picture. The best way to answer this question is to study the nearest example of a dwarf spiral galaxy, M33. We will use star clusters to understand the structure, kinematics and stellar populations of this galaxy. Star clusters provide a unique and powerful tool for studying the star formation histories of galaxies. In particular, the ages and metallicities of star clusters bear the imprint of the galaxy formation process. We have made use of the star clusters to uncover the formation and evolution of M33. In this dissertation, we have carried out a comprehensive study of the M33 star cluster system, including deep photometry as well as high signal-to-noise spectroscopy. In order to mitigate the significant incompleteness presents in previous catalogs, we have conducted ground-based and space-based photometric surveys of M33 star clusters. Using archival images, we have analyzed 12 fields using the Advanced Camera for Surveys Wide Field Channel onboard the Hubble Space Telescope (ACS/HST) along the major axis of the galaxy. We present integrated photometry and color-magnitude diagrams for 161 star clusters in M33, of which 115 were previously uncataloged. This survey extends the depth of the existing M33 cluster catalogs by ˜ 1 mag. We have expanded our search through a photometric survey in a 1° x 1° area centered on M33 using the MegaCam camera on the 3.6m Canada-France-Hawaii Telescope (CFHT). In this work we discuss the photometric properties of the sample, including color-color diagrams of 599 new candidate stellar clusters, and 204 confirmed clusters. Comparisons with models of simple stellar populations suggest a large range of ages some as old as ˜ 10 Gyr. In addition, we find in the color-color diagrams a significant population of very young clusters (< 10 Myr) possessing nebular emission. Analysis of the radial density distribution suggests that the cluster system of M33 has suffered from significant depletion, possibly due to interactions with M31. To further understand the properties of M33 star clusters, we have carried out a morphological study 161 star clusters in M33 using ACS/HST images. We have obtained, for the first time, ellipticities, position angles, and surface brightness profiles of a statistically significant number of clusters. Ellipticities show that, on average, M33 clusters are more flattened than those of the Milky Way and M31, and more similar to clusters in the Small Magellanic Cloud. The ellipticities do not show any correlation with age or mass, suggesting that rotation is not the main cause of elongation in the M33 clusters. The position angles of the clusters show a bimodality with a strong peak perpendicular to the position angle of the galaxy. These results support the notion that tidal forces are the reason for the cluster flattening. We have fit analytical models to the surface brightness profiles, and derived structural parameters. The overall analysis shows several differences between the structural properties of the M33 cluster system and cluster systems in nearby galaxies. Finally, we have performed a spectroscopic study of star clusters in the above mentioned catalog. We present high-precision velocity measures of 45 star clusters, based on observations from the 10.4m Gran Telescopio Canarias (GTC) using OSIRIS and 4.2m William Herschel Telescope (WHT) using WYFFOS. All the clusters have been previously confirmed using HST imaging, and ages and integrated photometry are known. The velocity of the clusters with respect to local disk motion increases with age for young and intermediate clusters. The mean dispersion velocity for the intermediate age clusters in our sample is significantly larger than in previous studies. Analysis of these velocities along the major axis of the galaxy show no net rotation of the intermediate age subsample. The small number of old clusters in our sample does not allow for any conclusive evidence in that age division.

PubChem3D: conformer ensemble accuracy

PubMed Central

2013-01-01

Background PubChem is a free and publicly available resource containing substance descriptions and their associated biological activity information. PubChem3D is an extension to PubChem containing computationally-derived three-dimensional (3-D) structures of small molecules. All the tools and services that are a part of PubChem3D rely upon the quality of the 3-D conformer models. Construction of the conformer models currently available in PubChem3D involves a clustering stage to sample the conformational space spanned by the molecule. While this stage allows one to downsize the conformer models to more manageable size, it may result in a loss of the ability to reproduce experimentally determined “bioactive” conformations, for example, found for PDB ligands. This study examines the extent of this accuracy loss and considers its effect on the 3-D similarity analysis of molecules. Results The conformer models consisting of up to 100,000 conformers per compound were generated for 47,123 small molecules whose structures were experimentally determined, and the conformers in each conformer model were clustered to reduce the size of the conformer model to a maximum of 500 conformers per molecule. The accuracy of the conformer models before and after clustering was evaluated using five different measures: root-mean-square distance (RMSD), shape-optimized shape-Tanimoto (STST-opt) and combo-Tanimoto (ComboTST-opt), and color-optimized color-Tanimoto (CTCT-opt) and combo-Tanimoto (ComboTCT-opt). On average, the effect of clustering decreased the conformer model accuracy, increasing the conformer ensemble’s RMSD to the bioactive conformer (by 0.18 ± 0.12 Å), and decreasing the STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt scores (by 0.04 ± 0.03, 0.16 ± 0.09, 0.09 ± 0.05, and 0.15 ± 0.09, respectively). Conclusion This study shows the RMSD accuracy performance of the PubChem3D conformer models is operating as designed. In addition, the effect of PubChem3D sampling on 3-D similarity measures shows that there is a linear degradation of average accuracy with respect to molecular size and flexibility. Generally speaking, one can likely expect the worst-case minimum accuracy of 90% or more of the PubChem3D ensembles to be 0.75, 1.09, 0.43, and 1.13, in terms of STST-opt, ComboTST-opt, CTCT-opt, and ComboTCT-opt, respectively. This expected accuracy improves linearly as the molecule becomes smaller or less flexible. PMID:23289532

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

NASA Astrophysics Data System (ADS)

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

2006-09-01

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

Sudden spreading of infections in an epidemic model with a finite seed fraction

NASA Astrophysics Data System (ADS)

Hasegawa, Takehisa; Nemoto, Koji

2018-03-01

We study a simple case of the susceptible-weakened-infected-removed model in regular random graphs in a situation where an epidemic starts from a finite fraction of initially infected nodes (seeds). Previous studies have shown that, assuming a single seed, this model exhibits a kind of discontinuous transition at a certain value of infection rate. Performing Monte Carlo simulations and evaluating approximate master equations, we find that the present model has two critical infection rates for the case with a finite seed fraction. At the first critical rate the system shows a percolation transition of clusters composed of removed nodes, and at the second critical rate, which is larger than the first one, a giant cluster suddenly grows and the order parameter jumps even though it has been already rising. Numerical evaluation of the master equations shows that such sudden epidemic spreading does occur if the degree of the underlying network is large and the seed fraction is small.

A Wsbnd Ne interatomic potential for simulation of neon implantation in tungsten

NASA Astrophysics Data System (ADS)

Backman, Marie; Juslin, Niklas; Huang, Guiyang; Wirth, Brian D.

2016-08-01

An interatomic pair potential for Wsbnd Ne is developed for atomistic molecular dynamics simulations of neon implantation in tungsten. The new potential predicts point defect energies and binding energies of small clusters that are in good agreement with electronic structure calculations. Molecular dynamics simulations of small neon clusters in tungsten show that trap mutation, in which an interstitial neon cluster displaces a tungsten atom from its lattice site, occurs for clusters of three or more neon atoms. However, near a free surface, trap mutation can occur at smaller sizes, including even a single neon interstitial in close proximity to a (100) or (110) surface.

A Theoretical Study of Structural, Electronic and Vibrational Properties of Small Fluoride Clusters

NASA Astrophysics Data System (ADS)

Waters, Kevin; Pandey, Ratnesh; Nigam, Sandeep; He, Haiying; Pingle, Subhash; Pandey, Avinash; Pandey, Ravindra

2014-03-01

Alkaline earth metal fluorides are an interesting family of ionic crystals having a wide range of applications in solid state lasers, luminescence, scintillators, to name just a few. In this work, small stoichiometric clusters of (MF2)n (M = Mg, Ca Sr, Ba, n =1-6) were studied for structural, vibrational and electronic properties using first-principles methods based on density functional theory. A clear trend of structural and electronic structure evolution was found for all the alkaline earth metal fluorides when the cluster size n increases from 1 to 6. Our study reveals that these fluoride clusters mimic the bulk-like behavior at the very small size. Among the four series of metal fluorides, however, (MgF2)n clusters stands out to be different in its preference of equilibrium structures owing to the much smaller ionic radius of Mg and the higher degree of covalency in the Mg-F bonding. The calculated binding energy, highest stretching frequency, ionization potential, and HOMO-LUMO gap decrease from MgF2 to BaF2 for the same cluster size. These variations are explained in terms of the change in the ionic radius and the basicity of the metal ions.

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes.

PubMed

Vegué, Marina; Perin, Rodrigo; Roxin, Alex

2017-08-30

The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering several distinct classes of network topology, including clustered networks, networks with distance-dependent connectivity, and those with broad degree distributions. To our surprise, we found that all of these qualitatively distinct topologies could account equally well for all reported nonrandom features despite being easily distinguishable from one another at the network level. This apparent paradox was a consequence of estimating network properties given only small sample sizes. In other words, networks that differ markedly in their global structure can look quite similar locally. This makes inferring network structure from small sample sizes, a necessity given the technical difficulty inherent in simultaneous intracellular recordings, problematic. We found that a network statistic called the sample degree correlation (SDC) overcomes this difficulty. The SDC depends only on parameters that can be estimated reliably given small sample sizes and is an accurate fingerprint of every topological family. We applied the SDC criterion to data from rat visual and somatosensory cortex and discovered that the connectivity was not consistent with any of these main topological classes. However, we were able to fit the experimental data with a more general network class, of which all previous topologies were special cases. The resulting network topology could be interpreted as a combination of physical spatial dependence and nonspatial, hierarchical clustering. SIGNIFICANCE STATEMENT The connectivity of cortical microcircuits exhibits features that are inconsistent with a simple random network. Here, we show that several classes of network models can account for this nonrandom structure despite qualitative differences in their global properties. This apparent paradox is a consequence of the small numbers of simultaneously recorded neurons in experiment: when inferred via small sample sizes, many networks may be indistinguishable despite being globally distinct. We develop a connectivity measure that successfully classifies networks even when estimated locally with a few neurons at a time. We show that data from rat cortex is consistent with a network in which the likelihood of a connection between neurons depends on spatial distance and on nonspatial, asymmetric clustering. Copyright © 2017 the authors 0270-6474/17/378498-13$15.00/0.

Reconciling large- and small-scale structure in Twin Higgs models

DOE PAGES

Prilepina, Valentina; Tsai, Yuhsin

2017-09-08

Here, we study possible extensions of the Twin Higgs model that solve the Hierarchy problem and simultaneously address problems of the large- and small-scale structures of the Universe. Besides naturally providing dark matter (DM) candidates as the lightest charged twin fermions, the twin sector contains a light photon and neutrinos, which can modify structure formation relative to the prediction from the ΛCDM paradigm. We focus on two viable scenarios. First, we study a Fraternal Twin Higgs model in which the spin-3/2 baryonmore » $$\\hat{Ω}$$~($$\\hat{b}$$$\\hat{b}$$$\\hat{b}$$) and the lepton twin tau $$\\hat{τ}$$ contribute to the dominant and subcomponent dark matter densities. A non-decoupled scattering between the twin tau and twin neutrino arising from a gauged twin lepton number symmetry provides a drag force that damps the density inhomogeneity of a dark matter subcomponent. Next, we consider the possibility of introducing a twin hydrogen atom $$\\hat{H}$$ as the dominant DM component. After recombination, a small fraction of the twin protons and leptons remains ionized during structure formation, and their scattering to twin neutrinos through a gauged U(1) B-L force provides the mechanism that damps the density inhomogeneity. Both scenarios realize the Partially Acoustic dark matter (PAcDM) scenario and explain the σ 8 discrepancy between the CMB and weak lensing results. Moreover, the self-scattering neutrino behaves as a dark fluid that enhances the size of the Hubble rate H 0 to accommodate the local measurement result while satisfying the CMB constraint. For the small-scale structure, the scattering of $$\\hat{Ω}$$ ’s and $$\\hat{H}$$’s through the twin photon exchange generates a self-interacting dark matter (SIDM) model that solves the mass deficit problem from dwarf galaxy to galaxy cluster scales. Furthermore, when varying general choices of the twin photon coupling, bounds from the dwarf galaxy and the cluster merger observations can set an upper limit on the twin electric coupling.« less

Reconciling large- and small-scale structure in Twin Higgs models

NASA Astrophysics Data System (ADS)

Prilepina, Valentina; Tsai, Yuhsin

2017-09-01

We study possible extensions of the Twin Higgs model that solve the Hierarchy problem and simultaneously address problems of the large- and small-scale structures of the Universe. Besides naturally providing dark matter (DM) candidates as the lightest charged twin fermions, the twin sector contains a light photon and neutrinos, which can modify structure formation relative to the prediction from the ΛCDM paradigm. We focus on two viable scenarios. First, we study a Fraternal Twin Higgs model in which the spin-3/2 baryon \\widehat{Ω}˜ (\\widehat{b}\\widehat{b}\\widehat{b}) and the lepton twin tau \\widehat{τ} contribute to the dominant and subcomponent dark matter densities. A non-decoupled scattering between the twin tau and twin neutrino arising from a gauged twin lepton number symmetry provides a drag force that damps the density inhomogeneity of a dark matter subcomponent. Next, we consider the possibility of introducing a twin hydrogen atom Ĥ as the dominant DM component. After recombination, a small fraction of the twin protons and leptons remains ionized during structure formation, and their scattering to twin neutrinos through a gauged U(1) B-L force provides the mechanism that damps the density inhomogeneity. Both scenarios realize the Partially Acoustic dark matter (PAcDM) scenario and explain the σ 8 discrepancy between the CMB and weak lensing results. Moreover, the self-scattering neutrino behaves as a dark fluid that enhances the size of the Hubble rate H 0 to accommodate the local measurement result while satisfying the CMB constraint. For the small-scale structure, the scattering of \\widehat{Ω} 's and Ĥ's through the twin photon exchange generates a self-interacting dark matter (SIDM) model that solves the mass deficit problem from dwarf galaxy to galaxy cluster scales. Furthermore, when varying general choices of the twin photon coupling, bounds from the dwarf galaxy and the cluster merger observations can set an upper limit on the twin electric coupling.

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

Tidal stripping stellar substructures around four metal-poor globular clusters in the galactic bulge

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

Chun, Sang-Hyun; Kang, Minhee; Jung, DooSeok

2015-01-01

We investigate the spatial density configuration of stars around four metal-poor globular clusters (NGC 6266, NGC 6626, NGC 6642, and NGC 6723) in the Galactic bulge region using wide-field deep J, H, and K imaging data obtained with the Wide Field Camera near-infrared array on the United Kingdom Infrared Telescope. A statistical weighted filtering algorithm for the stars on the color–magnitude diagram is applied in order to sort cluster member candidates from the field star contamination. In two-dimensional isodensity contour maps of the clusters, we find that all four of the globular clusters exhibit strong evidence of tidally stripped stellarmore » features beyond the tidal radius in the form of tidal tails or small density lobes/chunks. The orientations of the extended stellar substructures are likely to be associated with the effect of dynamic interaction with the Galaxy and the cluster's space motion. The observed radial density profiles of the four globular clusters also describe the extended substructures; they depart from theoretical King and Wilson models and have an overdensity feature with a break in the slope of the profile at the outer region of clusters. The observed results could imply that four globular clusters in the Galactic bulge region have experienced strong environmental effects such as tidal forces or bulge/disk shocks of the Galaxy during the dynamical evolution of globular clusters. These observational results provide further details which add to our understanding of the evolution of clusters in the Galactic bulge region as well as the formation of the Galaxy.« less

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Dating star clusters in the Small Magellanic Cloud by means of integrated spectra

NASA Astrophysics Data System (ADS)

Ahumada, A. V.; Clariá, J. J.; Bica, E.; Dutra, C. M.

2002-10-01

In this study flux-calibrated integrated spectra in the range (3600-6800) Å are presented for 16 concentrated star clusters in the Small Magellanic Cloud (SMC), approximately half of which constitute unstudied objects. We have estimated ages and foreground interstellar reddening values from the comparison of the line strengths and continuum distribution of the cluster spectra with those of template cluster spectra with known parameters. Most of the sample clusters are young blue clusters (6-50 Myr), while L 28, NGC 643 and L 114 are found to be intermediate-age clusters (1-6 Gyr). One well known SMC cluster (NGC 416) was observed for comparison purposes. The sample includes clusters in the surroundings and main body of the SMC, and the derived foreground reddening values are in the range 0.00 <= E(B-V) <= 0.15. The present data also make up a cluster spectral library at SMC metallicity. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina and the National Universities of La Plata, Córdoba and San Juan, Argentina.

Stochastic dynamics of small ensembles of non-processive molecular motors: The parallel cluster model

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

Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.

2013-11-07

Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors inmore » equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.« less

Food Choice Motives When Purchasing in Organic and Conventional Consumer Clusters: Focus on Sustainable Concerns (The NutriNet-Santé Cohort Study).

PubMed

Baudry, Julia; Péneau, Sandrine; Allès, Benjamin; Touvier, Mathilde; Hercberg, Serge; Galan, Pilar; Amiot, Marie-Josèphe; Lairon, Denis; Méjean, Caroline; Kesse-Guyot, Emmanuelle

2017-01-24

The purpose of this study was to examine food choice motives associated with various organic and conventional dietary patterns among 22,366 participants of the NutriNet-Santé study. Dietary intakes were estimated using a food frequency questionnaire. Food choice motives were assessed using a validated 63-item-questionnaire gathered into nine food choice motive dimension scores: "absence of contaminants", "avoidance for environmental reasons", "ethics and environment", "taste", "innovation", "local and traditional production", "price", "health" and "convenience". Five consumers' clusters were identified: "standard conventional food small eaters", "unhealthy conventional food big eaters", "standard organic food small eaters", "green organic food eaters" and "hedonist moderate organic food eaters". Relationships between food choice motive dimension scores and consumers' clusters were assessed using analysis of covariance (ANCOVA) models adjusted for sociodemographic factors. "Green organic food eaters" had the highest mean score for the "health" dimension, while "unhealthy conventional food big eaters" obtained the lowest mean score for the "absence of contaminants" dimension. "Standard organic food small eaters", "green organic food eaters" and "hedonist moderate organic food eaters" had comparable scores for the "taste" dimension. "Unhealthy conventional food big eaters" had the highest mean score for the "price" dimension while "green organic food eaters" had the lowest mean scores for the "innovation" and "convenience" dimensions. These results provide new insights into the food choice motives of diverse consumers' profiles including "green" and "hedonist" eaters.

The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth

ERIC Educational Resources Information Center

Steyvers, Mark; Tenenbaum, Joshua B.

2005-01-01

We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of…

Numerical analysis of stress effects on Frank loop evolution during irradiation in austenitic Fe&z.sbnd;Cr&z.sbnd;Ni alloy

NASA Astrophysics Data System (ADS)

Tanigawa, Hiroyasu; Katoh, Yutai; Kohyama, Akira

1995-08-01

Effects of applied stress on early stages of interstitial type Frank loop evolution were investigated by both numerical calculation and irradiation experiments. The final objective of this research is to propose a comprehensive model of complex stress effects on microstructural evolution under various conditions. In the experimental part of this work, the microstructural analysis revealed that the differences in resolved normal stress caused those in the nucleation rates of Frank loops on {111} crystallographic family planes, and that with increasing external applied stress the total nucleation rate of Frank loops was increased. A numerical calculation was carried out primarily to evaluate the validity of models of stress effects on nucleation processes of Frank loop evolution. The calculation stands on rate equuations which describe evolution of point defects, small points defect clusters and Frank loops. The rate equations of Frank loop evolution were formulated for {111} planes, considering effects of resolved normal stress to clustering processes of small point defects and growth processes of Frank loops, separately. The experimental results and the predictions from the numerical calculation qualitatively coincided well with each other.

The Faint End of the Lyman Alpha Luminosity Function at 2 < z < 3.8

NASA Astrophysics Data System (ADS)

Devarakonda, Yaswant; Livermore, Rachael; Indahl, Briana; Wold, Isak; Davis, Dustin; Finkelstein, Steven

2018-01-01

Most current models predict that our universe is mostly composed of small, dim galaxies. Due to these galaxies being so faint, it is very difficult to study these types of galaxies outside of our local universe. This is particularly an issue for studying how these small galaxies evolved over their lifetimes. With the benefit of gravitational lensing, however, we are able to observe galaxies that are farther and fainter than ever before possible. In this particular study, we focus on Lyman-Alpha emitting galaxies between the redshifts of 2-3.8, so that we may study these galaxies during the epoch of peak star formation in the universe. We use the McDonald Observatory 2.7, Harlan Smith telescope with the VIRUS-P IFU spectrograph to observe several Hubble Frontier Field lensing clusters to spectroscopically discover faint galaxies over this redshift range. In addition to providing insight into the faint-end slope of the Lyman alpha luminosity function, the spectroscopic redshifts will allow us to better constrain the mass models of the foreground clusters, such as Abell 370, so that we may better understand lensing effects for this and future studies.

The origin of low mass particles within and beyond the dust coma envelopes of Comet Halley

NASA Technical Reports Server (NTRS)

Simpson, J. A.; Rabinowitz, D.; Tuzzolino, A. J.; Ksanfomality, L. V.; Sagdeev, R. Z.

1987-01-01

Measurements from the Dust Counter and Mass Analyzer (DUCMA) instruments on VEGA-1 and -2 revealed unexpected fluxes of low mass (up to 10 to the minus 13th power g) dust particles at very great distances from the nucleus (300,000 to 600,000 km). These particles are detected in clusters (10 sec duration), preceded and followed by relatively long time intervals during which no dust is detected. This cluster phenomenon also occurs inside the envelope boundaries. Clusters of low mass particles are intermixed with the overall dust distribution throughout the coma. The clusters account for many of the short-term small-scale intensity enhancements previously ascribed to microjets in the coma. The origin of these clusters appears to be emission from the nucleus of large conglomerates which disintegrate in the coma to yield clusters of discrete, small particles continuing outward to the distant coma.

Equilibrium geometries, electronic and magnetic properties of small AunNi- (n = 1-9) clusters

NASA Astrophysics Data System (ADS)

Tang, Cui-Ming; Chen, Xiao-Xu; Yang, Xiang-Dong

2014-05-01

Geometrical, electronic and magnetic properties of small AunNi- (n = 1-9) clusters have been investigated based on density functional theory (DFT) at PW91P86 level. An extensive structural search shows that the relative stable structures of AunNi- (n = 1-9) clusters adopt 2D structure for n = 1-5, 7 and 3D structure for n = 6, 8-9. And the substitution of a Ni atom for an Au atom in the Au-n+1 cluster obviously changes the structure of the host cluster. Moreover, an odd-even alternation phenomenon has been found for HOMO-LUMO energy gaps, indicating that the relative stable structures of the AunNi- clusters with odd-numbered gold atoms have a higher relative stability. Finally, the natural population analysis (NPA) and the vertical detachment energies (VDE) are studied, respectively. The theoretical values of VDE are reported for the first time to our best knowledge.

Thermodynamic properties of small aggregates of rare-gas atoms

NASA Technical Reports Server (NTRS)

Etters, R. D.; Kaelberer, J.

1975-01-01

The present work reports on the equilibrium thermodynamic properties of small clusters of xenon, krypton, and argon atoms, determined from a biased random-walk Monte Carlo procedure. Cluster sizes ranged from 3 to 13 atoms. Each cluster was found to have an abrupt liquid-gas phase transition at a temperature much less than for the bulk material. An abrupt solid-liquid transition is observed for thirteen- and eleven-particle clusters. For cluster sizes smaller than 11, a gradual transition from solid to liquid occurred over a fairly broad range of temperatures. Distribution of number of bond lengths as a function of bond length was calculated for several systems at various temperatures. The effects of box boundary conditions are discussed. Results show the importance of a correct description of boundary conditions. A surprising result is the slow rate at which system properties approach bulk behavior as cluster size is increased.

Spatial analysis of under-5 mortality and potential risk factors in the Basse Health and Demographic Surveillance System, the Gambia.

PubMed

Quattrochi, John; Jasseh, Momodou; Mackenzie, Grant; Castro, Marcia C

2015-07-01

To describe the spatial pattern in under-5 mortality rates in the Basse Health and Demographic Surveillance System (BHDSS) and to test for associations between under-5 deaths and biodemographic and socio-economic risk factors. Using data on child survival from 2007 to 2011 in the BHDSS, we mapped under-5 mortality by km(2) . We tested for spatial clustering of high or low death rates using Kulldorff's spatial scan statistic. Associations between child death and a variety of biodemographic and socio-economic factors were assessed with Cox proportional hazards models, and deviance residuals from the best-fitting model were tested for spatial clustering. The overall death rate among children under 5 was 0.0195 deaths per child-year. We found two spatial clusters of high death rates and one spatial cluster of low death rates; children in the two high clusters died at a rate of 0.0264 and 0.0292 deaths per child-year, while in the low cluster, the rate was 0.0144 deaths per child-year. We also found that children born to Fula mothers experienced, on average, a higher hazard of death, whereas children born in the households in the upper two quintiles of asset ownership experienced, on average, a lower hazard of death. After accounting for the spatial distribution of biodemographic and socio-economic characteristics, we found no residual spatial pattern in child mortality risk. This study demonstrates that significant inequality in under-5 death rates can occur within a relatively small area (1100 km(2) ). Risks of under-5 mortality were associated with mother's ethnicity and household wealth. If high mortality clusters persist, then equity concerns may require additional public health efforts in those areas. © 2015 John Wiley & Sons Ltd.

Anisotropic thermal conduction with magnetic fields in galaxy clusters

NASA Astrophysics Data System (ADS)

Arth, Alexander; Dolag, Klaus; Beck, Alexander; Petkova, Margarita; Lesch, Harald

2015-08-01

Magnetic fields play an important role for the propagation and diffusion of charged particles, which are responsible for thermal conduction. In this poster, we present an implementation of thermal conduction including the anisotropic effects of magnetic fields for smoothed particle hydrodynamics (SPH). The anisotropic thermal conduction is mainly proceeding parallel to magnetic fields and suppressed perpendicular to the fields. We derive the SPH formalism for the anisotropic heat transport and solve the corresponding equation with an implicit conjugate gradient scheme. We discuss several issues of unphysical heat transport in the cases of extreme ansiotropies or unmagnetized regions and present possible numerical workarounds. We implement our algorithm into the cosmological simulation code GADGET and study its behaviour in several test cases. In general, we reproduce the analytical solutions of our idealised test problems, and obtain good results in cosmological simulations of galaxy cluster formations. Within galaxy clusters, the anisotropic conduction produces a net heat transport similar to an isotropic Spitzer conduction model with low efficiency. In contrast to isotropic conduction our new formalism allows small-scale structure in the temperature distribution to remain stable, because of their decoupling caused by magnetic field lines. Compared to observations, strong isotropic conduction leads to an oversmoothed temperature distribution within clusters, while the results obtained with anisotropic thermal conduction reproduce the observed temperature fluctuations well. A proper treatment of heat transport is crucial especially in the outskirts of clusters and also in high density regions. It's connection to the local dynamical state of the cluster also might contribute to the observed bimodal distribution of cool core and non cool core clusters. Our new scheme significantly advances the modelling of thermal conduction in numerical simulations and overall gives better results compared to observations.

Excitation energy shift and size difference of low-energy levels in p -shell Λ hypernuclei

NASA Astrophysics Data System (ADS)

Kanada-En'yo, Yoshiko

2018-02-01

Structures of low-lying 0 s -orbit Λ states in p -shell Λ hypernuclei (ZAΛ) are investigated by applying microscopic cluster models for nuclear structure and a single-channel folding potential model for a Λ particle. For A >10 systems, the size reduction of core nuclei is small, and the core polarization effect is regarded as a higher-order perturbation in the Λ binding. The present calculation qualitatively describes the systematic trend of experimental data for excitation energy change from Z-1A to ZAΛ, in A >10 systems. The energy change shows a clear correlation with the nuclear size difference between the ground and excited states. In Li7Λ and Be9Λ, the significant shrinkage of cluster structures occurs consistently with the prediction of other calculations.

Prediction (early recognition) of emerging flu strain clusters

NASA Astrophysics Data System (ADS)

Li, X.; Phillips, J. C.

2017-08-01

Early detection of incipient dominant influenza strains is one of the key steps in the design and manufacture of an effective annual influenza vaccine. Here we report the most current results for pandemic H3N2 flu vaccine design. A 2006 model of dimensional reduction (compaction) of viral mutational complexity derives two-dimensional Cartesian mutational maps (2DMM) that exhibit an emergent dominant strain as a small and distinct cluster of as few as 10 strains. We show that recent extensions of this model can detect incipient strains one year or more in advance of their dominance in the human population. Our structural interpretation of our unexpectedly rich 2DMM involves sialic acid, and is based on nearly 6000 strains in a series of recent 3-year time windows. Vaccine effectiveness is predicted best by analyzing dominant mutational epitopes.

Electronic behavior of highly correlated metals

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

Reich, A.

1988-10-01

This thesis addresses the question of the strongly interacting many-body problem: that is, systems where the interparticle correlations are so strong as to defy perturbative approaches. These subtle correlations occur in narrow band materials, such as the lanthanides and actinides, wherein the f-electrons are so localized that a variety of new phenomena, including intermediate-valence and heavy-fermionic behavior, may occur. As well, one has the alloying problem, where local interactions are paramount in determining the overall behavior. The technique employed in dealing with these systems is the Small Cluster method, wherein the full many-body Hamiltonian for a small grouping of atoms,more » coupled with periodic boundary conditions, is solved exactly. This is tantamount to solving a bulk crystal at the high points of symmetry in the Brillouin Zone. The mathematical overhead is further reduced by employing the full space group and spin symmetries. By its very nature, the Small Cluster method is well able to handle short-range interactions, as well as the combinatorial complexity of the many-body problem, on an equal footing. The nature of long-range order and phase transition behavior cannot be incorporated, but sometimes clues as to their origin can be discerned. The calculations presented include: a two-band Anderson model for an intermediate-valence system, wherein photoemission and fluctuation behavior is examined; a single-band Hubbard model for a ternary alloy system, such as copper-silver-gold; and a Hubbard model for a heavy- fermion system, wherein Fermi surface, transport, magnetic and superconducting properties are discussed. 148 refs., 31 figs., 24 tabs.« less

A new strategy for earthquake focal mechanisms using waveform-correlation-derived relative polarities and cluster analysis: Application to the 2014 Long Valley Caldera earthquake swarm

USGS Publications Warehouse

Shelly, David R.; Hardebeck, Jeanne L.; Ellsworth, William L.; Hill, David P.

2016-01-01

In microseismicity analyses, reliable focal mechanisms can typically be obtained for only a small subset of located events. We address this limitation here, presenting a framework for determining robust focal mechanisms for entire populations of very small events. To achieve this, we resolve relative P and S wave polarities between pairs of waveforms by using their signed correlation coefficients—a by-product of previously performed precise earthquake relocation. We then use cluster analysis to group events with similar patterns of polarities across the network. Finally, we apply a standard mechanism inversion to the grouped data, using either catalog or correlation-derived P wave polarity data sets. This approach has great potential for enhancing analyses of spatially concentrated microseismicity such as earthquake swarms, mainshock-aftershock sequences, and industrial reservoir stimulation or injection-induced seismic sequences. To demonstrate its utility, we apply this technique to the 2014 Long Valley Caldera earthquake swarm. In our analysis, 85% of the events (7212 out of 8494 located by Shelly et al. [2016]) fall within five well-constrained mechanism clusters, more than 12 times the number with network-determined mechanisms. Of the earthquakes we characterize, 3023 (42%) have magnitudes smaller than 0.0. We find that mechanism variations are strongly associated with corresponding hypocentral structure, yet mechanism heterogeneity also occurs where it cannot be resolved by hypocentral patterns, often confined to small-magnitude events. Small (5–20°) rotations between mechanism orientations and earthquake location trends persist when we apply 3-D velocity models and might reflect a geometry of en echelon, interlinked shear, and dilational faulting.

Universal clustering of dark matter in phase space

NASA Astrophysics Data System (ADS)

Zavala, Jesús; Afshordi, Niayesh

2016-03-01

We have recently introduced a novel statistical measure of dark matter clustering in phase space, the particle phase-space average density (P2SAD). In a two-paper series, we studied the structure of P2SAD in the Milky Way-size Aquarius haloes, constructed a physically motivated model to describe it, and illustrated its potential as a powerful tool to predict signals sensitive to the nanostructure of dark matter haloes. In this work, we report a remarkable universality of the clustering of dark matter in phase space as measured by P2SAD within the subhaloes of host haloes across different environments covering a range from dwarf-size to cluster-size haloes (1010-1015 M⊙). Simulations show that the universality of P2SAD holds for more than seven orders of magnitude, over a 2D phase space, covering over three orders of magnitude in distance/velocity, with a simple functional form that can be described by our model. Invoking the universality of P2SAD, we can accurately predict the non-linear power spectrum of dark matter at small scales all the way down to the decoupling mass limit of cold dark matter particles. As an application, we compute the subhalo boost to the annihilation of dark matter in a wide range of host halo masses.

Investigation of nucleation kinetics in H2SO4 vapor through modeling of gas phase kinetics coupled with particle dynamics

NASA Astrophysics Data System (ADS)

Carlsson, Philip T. M.; Zeuch, Thomas

2018-03-01

We have developed a new model utilizing our existing kinetic gas phase models to simulate experimental particle size distributions emerging in dry supersaturated H2SO4 vapor homogeneously produced by rapid oxidation of SO2 through stabilized Criegee-Intermediates from 2-butene ozonolysis. We use a sectional method for simulating the particle dynamics. The particle treatment in the model is based on first principles and takes into account the transition from the kinetic to the diffusion-limited regime. It captures the temporal evolution of size distributions at the end of the ozonolysis experiment well, noting a slight underrepresentation of coagulation effects for larger particle sizes. The model correctly predicts the shape and the modes of the experimentally observed particle size distributions. The predicted modes show an extremely high sensitivity to the H2SO4 evaporation rates of the initially formed H2SO4 clusters (dimer to pentamer), which were arbitrarily restricted to decrease exponentially with increasing cluster size. In future, the analysis presented in this work can be extended to allow a direct validation of quantum chemically predicted stabilities of small H2SO4 clusters, which are believed to initiate a significant fraction of atmospheric new particle formation events. We discuss the prospects and possible limitations of the here presented approach.

Extracting magnetic cluster size and its distributions in advanced perpendicular recording media with shrinking grain size using small angle x-ray scattering

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

Mehta, Virat; Ikeda, Yoshihiro; Takano, Ken

2015-05-18

We analyze the magnetic cluster size (MCS) and magnetic cluster size distribution (MCSD) in a variety of perpendicular magnetic recording (PMR) media designs using resonant small angle x-ray scattering at the Co L{sub 3} absorption edge. The different PMR media flavors considered here vary in grain size between 7.5 and 9.5 nm as well as in lateral inter-granular exchange strength, which is controlled via the segregant amount. While for high inter-granular exchange, the MCS increases rapidly for grain sizes below 8.5 nm, we show that for increased amount of segregant with less exchange the MCS remains relatively small, even for grain sizesmore » of 7.5 and 8 nm. However, the MCSD still increases sharply when shrinking grains from 8 to 7.5 nm. We show evidence that recording performance such as signal-to-noise-ratio on the spin stand correlates well with the product of magnetic cluster size and magnetic cluster size distribution.« less

A DFT study of the stability of SIAs and small SIA clusters in the vicinity of solute atoms in Fe

NASA Astrophysics Data System (ADS)

Becquart, C. S.; Ngayam Happy, R.; Olsson, P.; Domain, C.

2018-03-01

The energetics, defect volume and magnetic properties of single SIAs and small SIA clusters up to size 6 have been calculated by DFT for different configurations like the parallel 〈110〉 dumbbell, the non parallel 〈110〉 dumbbell and the C15 structure. The most stable configurations of each type have been further analyzed to determine the influence on their stability of various solute atoms (Ti, V, Cr, Mn, Co, Ni, Cu, Mo, W, Pd, Al, Si, P), relevant for steels used under irradiation. The results show that the presence of solute atoms does not change the relative stability order among SIA clusters. The small SIA clusters investigated can bind to both undersized and oversized solutes. Several descriptors have been considered to derive interesting trends from results. It appears that the local atomic volume available for the solute is the main physical quantity governing the binding energy evolution, whatever the solute type (undersized or oversized) and the cluster configuration (size and type).

Effects of manganese doping on the structure evolution of small-sized boron clusters

NASA Astrophysics Data System (ADS)

Zhao, Lingquan; Qu, Xin; Wang, Yanchao; Lv, Jian; Zhang, Lijun; Hu, Ziyu; Gu, Guangrui; Ma, Yanming

2017-07-01

Atomic doping of clusters is known as an effective approach to stabilize or modify the structures and properties of resulting doped clusters. We herein report the effect of manganese (Mn) doping on the structure evolution of small-sized boron (B) clusters. The global minimum structures of both neutral and charged Mn doped B cluster \\text{MnB}nQ (n  =  10-20 and Q  =  0, ±1) have been proposed through extensive first-principles swarm-intelligence based structure searches. It is found that Mn doping has significantly modified the grow behaviors of B clusters, leading to two novel structural transitions from planar to tubular and then to cage-like B structures in both neutral and charged species. Half-sandwich-type structures are most favorable for small \\text{MnB}n-/0/+ (n  ⩽  13) clusters and gradually transform to Mn-centered double-ring tubular structures at \\text{MnB}16-/0/+ clusters with superior thermodynamic stabilities compared with their neighbors. Most strikingly, endohedral cages become the ground-state structures for larger \\text{MnB}n-/0/+ (n  ⩾  19) clusters, among which \\text{MnB}20+ adopts a highly symmetric structure with superior thermodynamic stability and a large HOMO-LUMO gap of 4.53 eV. The unique stability of the endohedral \\text{MnB}\\text{20}+ cage is attributed to the geometric fit and formation of 18-electron closed-shell configuration. The results significantly advance our understanding about the structure and bonding of B-based clusters and strongly suggest transition-metal doping as a viable route to synthesize intriguing B-based nanomaterials.

Vapor deposition of water on graphitic surfaces: formation of amorphous ice, bilayer ice, ice I, and liquid water.

PubMed

Lupi, Laura; Kastelowitz, Noah; Molinero, Valeria

2014-11-14

Carbonaceous surfaces are a major source of atmospheric particles and could play an important role in the formation of ice. Here we investigate through molecular simulations the stability, metastability, and molecular pathways of deposition of amorphous ice, bilayer ice, and ice I from water vapor on graphitic and atomless Lennard-Jones surfaces as a function of temperature. We find that bilayer ice is the most stable ice polymorph for small cluster sizes, nevertheless it can grow metastable well above its region of thermodynamic stability. In agreement with experiments, the simulations predict that on increasing temperature the outcome of water deposition is amorphous ice, bilayer ice, ice I, and liquid water. The deposition nucleation of bilayer ice and ice I is preceded by the formation of small liquid clusters, which have two wetting states: bilayer pancake-like (wetting) at small cluster size and droplet-like (non-wetting) at larger cluster size. The wetting state of liquid clusters determines which ice polymorph is nucleated: bilayer ice nucleates from wetting bilayer liquid clusters and ice I from non-wetting liquid clusters. The maximum temperature for nucleation of bilayer ice on flat surfaces, T(B)(max) is given by the maximum temperature for which liquid water clusters reach the equilibrium melting line of bilayer ice as wetting bilayer clusters. Increasing water-surface attraction stabilizes the pancake-like wetting state of liquid clusters leading to larger T(B)(max) for the flat non-hydrogen bonding surfaces of this study. The findings of this study should be of relevance for the understanding of ice formation by deposition mode on carbonaceous atmospheric particles, including soot.

A Comparison of Heuristic Procedures for Minimum within-Cluster Sums of Squares Partitioning

ERIC Educational Resources Information Center

Brusco, Michael J.; Steinley, Douglas

2007-01-01

Perhaps the most common criterion for partitioning a data set is the minimization of the within-cluster sums of squared deviation from cluster centroids. Although optimal solution procedures for within-cluster sums of squares (WCSS) partitioning are computationally feasible for small data sets, heuristic procedures are required for most practical…

One dark matter mystery: halos in the cosmic web

NASA Astrophysics Data System (ADS)

Gaite, Jose

2015-01-01

The current cold dark matter cosmological model explains the large scale cosmic web structure but is challenged by the observation of a relatively smooth distribution of matter in galactic clusters. We consider various aspects of modeling the dark matter around galaxies as distributed in smooth halos and, especially, the smoothness of the dark matter halos seen in N-body cosmological simulations. We conclude that the problems of the cold dark matter cosmology on small scales are more serious than normally admitted.

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

PubMed

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

2004-04-02

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

Irradiation-induced microchemical changes in highly irradiated 316 stainless steel

NASA Astrophysics Data System (ADS)

Fujii, K.; Fukuya, K.

2016-02-01

Cold-worked 316 stainless steel specimens irradiated to 74 dpa in a pressurized water reactor (PWR) were analyzed by atom probe tomography (APT) to extend knowledge of solute clusters and segregation at higher doses. The analyses confirmed that those clusters mainly enriched in Ni-Si or Ni-Si-Mn were formed at high number density. The clusters were divided into three types based on their size and Mn content; small Ni-Si clusters (3-4 nm in diameter), and large Ni-Si and Ni-Si-Mn clusters (8-10 nm in diameter). The total cluster number density was 7.7 × 1023 m-3. The fraction of large clusters was almost 1/10 of the total density. The average composition (in at%) for small clusters was: Fe, 54; Cr, 12; Mn, 1; Ni, 22; Si, 11; Mo, 1, and for large clusters it was: Fe, 44; Cr, 9; Mn, 2; Ni, 29; Si, 14; Mo,1. It was likely that some of the Ni-Si clusters correspond to γ‧ phase precipitates while the Ni-Si-Mn clusters were precursors of G phase precipitates. The APT analyses at grain boundaries confirmed enrichment of Ni, Si, P and Cu and depletion of Fe, Cr, Mo and Mn. The segregation behavior was consistent with previous knowledge of radiation induced segregation.

Development of small scale cluster computer for numerical analysis

NASA Astrophysics Data System (ADS)

Zulkifli, N. H. N.; Sapit, A.; Mohammed, A. N.

2017-09-01

In this study, two units of personal computer were successfully networked together to form a small scale cluster. Each of the processor involved are multicore processor which has four cores in it, thus made this cluster to have eight processors. Here, the cluster incorporate Ubuntu 14.04 LINUX environment with MPI implementation (MPICH2). Two main tests were conducted in order to test the cluster, which is communication test and performance test. The communication test was done to make sure that the computers are able to pass the required information without any problem and were done by using simple MPI Hello Program where the program written in C language. Additional, performance test was also done to prove that this cluster calculation performance is much better than single CPU computer. In this performance test, four tests were done by running the same code by using single node, 2 processors, 4 processors, and 8 processors. The result shows that with additional processors, the time required to solve the problem decrease. Time required for the calculation shorten to half when we double the processors. To conclude, we successfully develop a small scale cluster computer using common hardware which capable of higher computing power when compare to single CPU processor, and this can be beneficial for research that require high computing power especially numerical analysis such as finite element analysis, computational fluid dynamics, and computational physics analysis.

The influence of particle shape on dielectric enhancement in metal-insulator composites

NASA Astrophysics Data System (ADS)

Doyle, W. T.; Jacobs, I. S.

1992-04-01

Disordered suspensions of conducting particles exhibit substantial permittivity enhancements beyond the predictions of the Clausius-Mossotti equation and other purely dipolar approximations. The magnitude of the enhancement depends upon the shape of the particles. A recently developed effective cluster model for spherical particles [Phys. Rev. B 42, 9319 (1990)] that treats a disordered suspension as a mixture, or mesosuspension, of isolated spheres and close-packed spherical clusters of arbitrary size is in excellent agreement with experiments on well-stirred suspensions of spheres over the entire accessible range of volume loading. In this paper, the effective cluster model is extended to be applicable to disordered suspensions of arbitrarily shaped conducting particles. Two physical parameters are used to characterize a general suspension: the angular average polarizability of an isolated particle, and the volume loading at closest packing of the suspension. Multipole interactions within the clusters are treated exactly. External particle-shape-dependent interactions between clusters and isolated particles are treated in the dipole approximation in two ways: explicitly, using the Clausius-Mossotti equation, and implicitly, using the Wiener equation. Both versions of the model are used to find the permittivity of a monodisperse suspension of conducting spheroids, for which the model parameters can be determined independently. The two versions are in good agreement when the axial ratio of the particles is not extreme. The Clausius-Mossotti version of the model yields a mesoscopic analogue of the dielectric virial expansion. It is limited to small volume loadings when the particles have an extremely nonspherical shape. The Wiener equation version of the model holds at all volume loadings for particles of arbitrary shape. Comparison of the two versions of the model leads to a simple physical interpretation of Wiener's equation. The models are compared with experiments of Kelly, Stenoien, and Isbell [J. Appl. Phys. 24, 258 (1953)] on aluminum and zinc particles in paraffin, with Nasuhoglu's experiments on iron particles in oil [Commun. Fac. Sci. Univ. Ankara 4, 108 (1952)], and with new X-band and Kα-band permittivity measurements on Ni-Cr alloy particles in a polyurethane binder.

Electronic structures and thermochemical properties of the small silicon-doped boron clusters B(n)Si (n=1-7) and their anions.

PubMed

Tai, Truong Ba; Kadłubański, Paweł; Roszak, Szczepan; Majumdar, Devashis; Leszczynski, Jerzy; Nguyen, Minh Tho

2011-11-18

We perform a systematic investigation on small silicon-doped boron clusters B(n)Si (n=1-7) in both neutral and anionic states using density functional (DFT) and coupled-cluster (CCSD(T)) theories. The global minima of these B(n)Si(0/-) clusters are characterized together with their growth mechanisms. The planar structures are dominant for small B(n)Si clusters with n≤5. The B(6)Si molecule represents a geometrical transition with a quasi-planar geometry, and the first 3D global minimum is found for the B(7)Si cluster. The small neutral B(n)Si clusters can be formed by substituting the single boron atom of B(n+1) by silicon. The Si atom prefers the external position of the skeleton and tends to form bonds with its two neighboring B atoms. The larger B(7)Si cluster is constructed by doping Si-atoms on the symmetry axis of the B(n) host, which leads to the bonding of the silicon to the ring boron atoms through a number of hyper-coordination. Calculations of the thermochemical properties of B(n)Si(0/-) clusters, such as binding energies (BE), heats of formation at 0 K (ΔH(f)(0)) and 298 K (ΔH(f)([298])), adiabatic (ADE) and vertical (VDE) detachment energies, and dissociation energies (D(e)), are performed using the high accuracy G4 and complete basis-set extrapolation (CCSD(T)/CBS) approaches. The differences of heats of formation (at 0 K) between the G4 and CBS approaches for the B(n)Si clusters vary in the range of 0.0-4.6 kcal mol(-1). The largest difference between two approaches for ADE values is 0.15 eV. Our theoretical predictions also indicate that the species B(2)Si, B(4)Si, B(3)Si(-) and B(7)Si(-) are systems with enhanced stability, exhibiting each a double (σ and π) aromaticity. B(5)Si(-) and B(6)Si are doubly antiaromatic (σ and π) with lower stability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Cosmic background radiation anisotropies in universes dominated by nonbaryonic dark matter

NASA Technical Reports Server (NTRS)

Bond, J. R.; Efstathiou, G.

1984-01-01

Detailed calculations of the temperature fluctuations in the cosmic background radiation for universes dominated by massive collisionless relics of the big bang are presented. An initially adiabatic constant curvature perturbation spectrum is assumed. In models with cold dark matter, the simplest hypothesis - that galaxies follow the mass distribution leads to small-scale anisotropies which exceed current observational limits if omega is less than 0.2 h to the -4/3. Since low values of omega are indicated by dynamical studies of galaxy clustering, cold particle models in which light traces mass are probably incorrect. Reheating of the pregalactic medium is unlikely to modify this conclusion. In cold particle or neutrino-dominated universes with omega = 1, presented predictions for small-scale and quadrupole anisotropies are below current limits. In all cases, the small-scale fluctuations are predicted to be about 10 percent linearly polarized.

Are Earthquake Clusters/Supercycles Real or Random?

NASA Astrophysics Data System (ADS)

Salditch, L.; Brooks, E. M.; Stein, S.; Spencer, B. D.

2016-12-01

Long records of earthquakes at plate boundaries such as the San Andreas or Cascadia often show that large earthquakes occur in temporal clusters, also termed supercycles, separated by less active intervals. These are intriguing because the boundary is presumably being loaded by steady plate motion. If so, earthquakes resulting from seismic cycles - in which their probability is small shortly after the past one, and then increases with time - should occur quasi-periodically rather than be more frequent in some intervals than others. We are exploring this issue with two approaches. One is to assess whether the clusters result purely by chance from a time-independent process that has no "memory." Thus a future earthquake is equally likely immediately after the past one and much later, so earthquakes can cluster in time. We analyze the agreement between such a model and inter-event times for Parkfield, Pallet Creek, and other records. A useful tool is transformation by the inverse cumulative distribution function, so the inter-event times have a uniform distribution when the memorylessness property holds. The second is via a time-variable model in which earthquake probability increases with time between earthquakes and decreases after an earthquake. The probability of an event increases with time until one happens, after which it decreases, but not to zero. Hence after a long period of quiescence, the probability of an earthquake can remain higher than the long-term average for several cycles. Thus the probability of another earthquake is path dependent, i.e. depends on the prior earthquake history over multiple cycles. Time histories resulting from simulations give clusters with properties similar to those observed. The sequences of earthquakes result from both the model parameters and chance, so two runs with the same parameters look different. The model parameters control the average time between events and the variation of the actual times around this average, so models can be strongly or weakly time-dependent.

Subaru Weak-Lensing Survey II: Multi-Object Spectroscopy and Cluster Masses

NASA Astrophysics Data System (ADS)

Hamana, Takashi; Miyazaki, Satoshi; Kashikawa, Nobunari; Ellis, Richard S.; Massey, Richard J.; Refregier, Alexandre; Taylor, James E.

2009-08-01

We present the first results of a multi-object spectroscopic campaign to follow up cluster candidates located via weak lensing. Our main goals are to search for spatial concentrations of galaxies that are plausible optical counterparts of the weak-lensing signals, and to determine the cluster redshifts from those of member galaxies. Around each of 36 targeted cluster candidates, we obtained 15-32 galaxy redshifts. For 28 of these targets, we confirmed a secure cluster identification, with more than five spectroscopic galaxies within a velocity of ±3000km s-1. This includes three cases where two clusters at different redshifts are projected along the same line-of-sight. In 6 of the 8 unconfirmed targets, we found multiple small galaxy concentrations at different redshifts, each containing at least three spectroscopic galaxies. The weak-lensing signal around those systems was thus probably created by the projection of groups or small clusters along the same line-of-sight. In both of the remaining two targets, a single small galaxy concentration was found. In some candidate super-cluster systems, we found additional evidence of filaments connecting the main density peak to an additional nearby structure. For a subsample of our most cleanly measured clusters, we investigated the statistical relation between their weak-lensing mass (MNFW, σSIS) and the velocity dispersion of their member galaxies (σv), comparing our sample with optically and X-ray selected samples from the literature. Our lensing-selected clusters are consistent with σv = σSIS, with a similar scatter to that of optically and X-ray selected clusters. We also derived an empirical relation between the cluster mass and the galaxy velocity dispersion, M200E(z) = 11.0 × 1014 × (σv/1000km s-1)3.0 h-1 Modot, which is in reasonable agreement with predictions of N-body simulations in the Λ CDM cosmology.

Use of a Latent Topic Model for Characteristic Extraction from Health Checkup Questionnaire Data.

PubMed

Hatakeyama, Y; Miyano, I; Kataoka, H; Nakajima, N; Watabe, T; Yasuda, N; Okuhara, Y

2015-01-01

When patients complete questionnaires during health checkups, many of their responses are subjective, making topic extraction difficult. Therefore, the purpose of this study was to develop a model capable of extracting appropriate topics from subjective data in questionnaires conducted during health checkups. We employed a latent topic model to group the lifestyle habits of the study participants and represented their responses to items on health checkup questionnaires as a probability model. For the probability model, we used latent Dirichlet allocation to extract 30 topics from the questionnaires. According to the model parameters, a total of 4381 study participants were then divided into groups based on these topics. Results from laboratory tests, including blood glucose level, triglycerides, and estimated glomerular filtration rate, were compared between each group, and these results were then compared with those obtained by hierarchical clustering. If a significant (p < 0.05) difference was observed in any of the laboratory measurements between groups, it was considered to indicate a questionnaire response pattern corresponding to the value of the test result. A comparison between the latent topic model and hierarchical clustering grouping revealed that, in the latent topic model method, a small group of participants who reported having subjective signs of urinary disorder were allocated to a single group. The latent topic model is useful for extracting characteristics from a small number of groups from questionnaires with a large number of items. These results show that, in addition to chief complaints and history of past illness, questionnaire data obtained during medical checkups can serve as useful judgment criteria for assessing the conditions of patients.

Line-of-sight structure toward strong lensing galaxy clusters

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

Bayliss, Matthew B.; Johnson, Traci; Sharon, Keren

2014-03-01

We present an analysis of the line-of-sight structure toward a sample of 10 strong lensing cluster cores. Structure is traced by groups that are identified spectroscopically in the redshift range, 0.1 ≤ z ≤ 0.9, and we measure the projected angular and comoving separations between each group and the primary strong lensing clusters in each corresponding line of sight. From these data we measure the distribution of projected angular separations between the primary strong lensing clusters and uncorrelated large-scale structure as traced by groups. We then compare the observed distribution of angular separations for our strong lensing selected lines ofmore » sight against the distribution of groups that is predicted for clusters lying along random lines of sight. There is clear evidence for an excess of structure along the line of sight at small angular separations (θ ≤ 6') along the strong lensing selected lines of sight, indicating that uncorrelated structure is a significant systematic that contributes to producing galaxy clusters with large cross sections for strong lensing. The prevalence of line-of-sight structure is one of several biases in strong lensing clusters that can potentially be folded into cosmological measurements using galaxy cluster samples. These results also have implications for current and future studies—such as the Hubble Space Telescope Frontier Fields—that make use of massive galaxy cluster lenses as precision cosmological telescopes; it is essential that the contribution of line-of-sight structure be carefully accounted for in the strong lens modeling of the cluster lenses.« less

Formation of charged nanoparticles in hydrocarbon flames: principal mechanisms

NASA Astrophysics Data System (ADS)

Starik, A. M.; Savel'ev, A. M.; Titova, N. S.

2008-11-01

The processes of charged gaseous and particulate species formation in sooting hydrocarbon/air flame are studied. The original kinetic model, comprising the chemistry of neutral and charged gaseous species, generation of primary clusters, which then undergo charging due to attachment of ions and electrons to clusters and via thermoemission, and coagulation of charged-charged, charged-neutral and neutral-neutral particles, is reported. The analysis shows that the principal mechanisms of charged particle origin in hydrocarbon flames are associated with the attachment of ions and electrons produced in the course of chemoionization reactions to primary small clusters and particles and coagulation via charged-charged and charged-neutral particle interaction. Thermal ionization of particles does not play a significant role in the particle charging. This paper was presented at the Third International Symposium on Nonequilibrium Process, combustion, and Atmospheric Phenomena (Dagomys, Sochi, Russia, 25-29 June 2007).

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

NASA Astrophysics Data System (ADS)

Titantah, John T.; Karttunen, Mikko

2016-05-01

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

The relationship of dynamical heterogeneity to the Adam-Gibbs and random first-order transition theories of glass formation.

PubMed

Starr, Francis W; Douglas, Jack F; Sastry, Srikanth

2013-03-28

We carefully examine common measures of dynamical heterogeneity for a model polymer melt and test how these scales compare with those hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories of relaxation in glass-forming liquids. To this end, we first analyze clusters of highly mobile particles, the string-like collective motion of these mobile particles, and clusters of relative low mobility. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times for the high- and low-mobility particles naturally explains the well-known decoupling of diffusion and structural relaxation time scales. Despite the inherent difference of dynamics between high- and low-mobility particles, we find a high degree of similarity in the geometrical structure of these particle clusters. In particular, we show that the fractal dimensions of these clusters are consistent with those of swollen branched polymers or branched polymers with screened excluded-volume interactions, corresponding to lattice animals and percolation clusters, respectively. In contrast, the fractal dimension of the strings crosses over from that of self-avoiding walks for small strings, to simple random walks for longer, more strongly interacting, strings, corresponding to flexible polymers with screened excluded-volume interactions. We examine the appropriateness of identifying the size scales of either mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the "mosaic" length of the RFOT model relaxes the conventional assumption that the "entropic droplets" are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

Mitochondrial filaments and clusters as intracellular power-transmitting cables.

PubMed

Skulachev, V P

2001-01-01

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

Comparisons of fish species traits from small streams to large rivers

USGS Publications Warehouse

Goldstein, R.M.; Meador, M.R.

2004-01-01

To examine the relations between fish community function and stream size, we classified 429 lotic freshwater fish species based on multiple categories within six species traits: (1) substrate preference, (2) geomorphic preference, (3) trophic ecology, (4) locomotion morphology, (5) reproductive strategy, and (6) stream size preference. Stream size categories included small streams, small, medium, and large rivers, and no size preference. The frequencies of each species trait category were determined for each stream size category based on life history information from the literature. Cluster analysis revealed the presence of covarying groups of species trait categories. One cluster (RUN) included the traits of planktivore and herbivore feeding ecology, migratory reproductive behavior and broadcast spawning, preferences for main-channel habitats, and a lack of preferences for substrate type. The frequencies of classifications for the RUN cluster varied significantly across stream size categories (P = 0.009), being greater for large rivers than for small streams and rivers. Another cluster (RIFFLE) included the traits of invertivore feeding ecology, simple nester reproductive behavior, a preference for riffles, and a preference for bedrock, boulder, and cobble-rubble substrate. No significant differences in the frequency of classifications among stream size categories were detected for the RIFFLE cluster (P = 0.328). Our results suggest that fish community function is structured by large-scale differences in habitat and is different for large rivers than for small streams and rivers. Our findings support theoretical predictions of variation in species traits among stream reaches based on ecological frameworks such as landscape filters, habitat templates, and the river continuum concept. We believe that the species trait classifications presented here provide an opportunity for further examination of fish species' relations to physical, chemical, and biological factors in lotic habitats ranging from small streams to large rivers.

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

PubMed Central

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

2014-01-01

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

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Predicting the points of interaction of small molecules in the NF-κB pathway

PubMed Central

2011-01-01

Background The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway. Results Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis. Conclusions The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis. PMID:21342508

Spatial clustering and halo occupation distribution modelling of local AGN via cross-correlation measurements with 2MASS galaxies

NASA Astrophysics Data System (ADS)

Krumpe, Mirko; Miyaji, Takamitsu; Coil, Alison L.; Aceves, Hector

2018-02-01

We present the clustering properties and halo occupation distribution (HOD) modelling of very low redshift, hard X-ray-detected active galactic nuclei (AGN) using cross-correlation function measurements with Two-Micron All Sky Survey galaxies. Spanning a redshift range of 0.007 < z < 0.037, with a median z = 0.024, we present a precise AGN clustering study of the most local AGN in the Universe. The AGN sample is drawn from the SWIFT/BAT 70-month and INTEGRAL/IBIS eight year all-sky X-ray surveys and contains both type I and type II AGN. We find a large-scale bias for the full AGN sample of b=1.04^{+0.10}_{-0.11}, which corresponds to a typical host dark matter halo mass of M_h^typ=12.84^{+0.22}_{-0.30} h^{-1} M_{⊙}. When split into low and high X-ray luminosity and type I and type II AGN subsamples, we detect no statistically significant differences in the large-scale bias parameters. However, there are differences in the small-scale clustering, which are reflected in the full HOD model results. We find that low and high X-ray luminosity AGN, as well as type I and type II AGN, occupy dark matter haloes differently, with 3.4σ and 4.0σ differences in their mean halo masses, respectively, when split by luminosity and type. The latter finding contradicts a simple orientation-based AGN unification model. As a by-product of our cross-correlation approach, we also present the first HOD model of 2MASS galaxies.

The different growth pathways of Brightest Cluster Galaxies and the Intra-Cluster Light

NASA Astrophysics Data System (ADS)

Contini, E.; Yi, S. K.; Kang, X.

2018-06-01

We study the growth pathways of Brightest Central Galaxies (BCGs) and Intra-Cluster Light (ICL) by means of a semi-analytic model. We assume that the ICL forms by stellar stripping of satellite galaxies and violent processes during mergers, and implement two independent models: (1) one considers both mergers and stellar stripping (named STANDARD model), and one considers only mergers (named MERGERS model). We find that BCGs and ICL form, grow and overall evolve at different times and with different timescales, but they show a clear co-evolution after redshift z ˜ 0.7 - 0.8. Around 90% of the ICL from stellar stripping is built-up in the innermost 150 Kpc from the halo centre and the dominant contribution comes from disk-like galaxies (B/T<0.4) through a large number of small/intermediate stripping events (Mstrip/Msat < 0.3). The fractions of stellar mass in BCGs and in ICL over the total stellar mass within the virial radius of the halo evolve differently with time. At high redshift, the BCG accounts for the bulk of the mass, but its contribution gradually decreases with time and stays constant after z ˜ 0.4 - 0.5. The ICL, instead, grows very fast and its contribution keeps increasing down to the present time. The STANDARD and the MERGERS models make very similar predictions in most of the cases, but predict different amounts of ICL associated to other galaxies within the virial radius of the group/cluster other than the BCG, at z = 0. We then suggest that this quantity is a valid observable that can shed light on the relative importance of mergers and stellar stripping for the formation of the ICL.

Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

PubMed Central

Gani, Abdullah; Anisi, Mohammad Hossein; Ab Hamid, Siti Hafizah; Akhunzada, Adnan; Khan, Muhammad Khurram

2016-01-01

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results. PMID:27658194

Drinker Types, Harm, and Policy-Related Variables: Results from the 2011 International Alcohol Control Study in New Zealand.

PubMed

Wall, Martin; Casswell, Sally

2017-05-01

The aim was to identify a typology of drinkers in New Zealand based on alcohol consumption, beverage choice, and public versus private drinking locations and investigate the relationship between drinker types, harms experienced, and policy-related variables. Model-based cluster analysis of male and female drinkers including volumes of alcohol consumed in the form of beer, wine, spirits, and ready-to-drinks (RTDs) in off- and on-premise settings. Cluster membership was then related to harm measures: alcohol dependence, self-rated health; and to 3 policy-relevant variables: liking for alcohol adverts, price paid for alcohol, and time of purchase. Males and females were analyzed separately. Men fell into 4 and women into 14 clearly discriminated clusters. The male clusters consumed a relatively high proportion of alcohol in the form of beer. Women had a number of small extreme clusters and some consumed mainly spirits-based RTDs, while others drank mainly wine. Those in the higher consuming clusters were more likely to have signs of alcohol dependency, to report lower satisfaction with their health, to like alcohol ads, and to have purchased late at night. Consumption patterns are sufficiently distinctive to identify typologies of male and female alcohol consumers. Women drinkers are more heterogeneous than men. The clusters relate differently to policy-related variables. Copyright © 2017 by the Research Society on Alcoholism.

MEASURING THE LUMINOSITY AND VIRIAL BLACK HOLE MASS DEPENDENCE OF QUASAR–GALAXY CLUSTERING AT z ∼ 0.8

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

Krolewski, Alex G.; Eisenstein, Daniel J., E-mail: akrolewski@college.harvard.edu

2015-04-10

We study the dependence of quasar clustering on quasar luminosity and black hole mass by measuring the angular overdensity of photometrically selected galaxies imaged by the Wide-field Infrared Survey Explorer (WISE) about z ∼ 0.8 quasars from SDSS. By measuring the quasar–galaxy cross-correlation function and using photometrically selected galaxies, we achieve a higher density of tracer objects and a more sensitive detection of clustering than measurements of the quasar autocorrelation function. We test models of quasar formation and evolution by measuring the luminosity dependence of clustering amplitude. We find a significant overdensity of WISE galaxies about z ∼ 0.8 quasarsmore » at 0.2–6.4 h{sup −1} Mpc in projected comoving separation. We find no appreciable increase in clustering amplitude with quasar luminosity across a decade in luminosity, and a power-law fit between luminosity and clustering amplitude gives an exponent of −0.01 ± 0.06 (1 σ error). We also fail to find a significant relationship between clustering amplitude and black hole mass, although our dynamic range in true mass is suppressed due to the large uncertainties in virial black hole mass estimates. Our results indicate that a small range in host dark matter halo mass maps to a large range in quasar luminosity.« less

The colour-magnitude relation as a constraint on the formation of rich cluster galaxies

NASA Astrophysics Data System (ADS)

Bower, Richard G.; Kodama, Tadayuki; Terlevich, Ale

1998-10-01

The colours and magnitudes of early-type galaxies in galaxy clusters are strongly correlated. The existence of such a correlation has been used to infer that early-type galaxies must be old passively evolving systems. Given the dominance of early-type galaxies in the cores of rich clusters, this view sits uncomfortably with the increasing fraction of blue galaxies found in clusters at intermediate redshifts, and with the late formation of galaxies favoured by cold dark matter type cosmologies. In this paper, we make a detailed investigation of these issues and examine the role that the colour-magnitude relation can play in constraining the formation history of galaxies currently found in the cores of rich clusters. We start by considering the colour evolution of galaxies after star formation ceases. We show that the scatter of the colour-magnitude relation places a strong constraint on the spread in age that is allowed for the bulk of the stellar population. In the extreme case that the stars are formed in a single event, the spread in age cannot be more than 4 Gyr. Although the bulk of stars must be formed in a short period, continuing formation of stars in a fraction of the galaxies is not so strongly constrained. We examine a model in which star formation occurs over an extended period of time in most galaxies with star formation being truncated randomly. This model is consistent with the formation of stars in a few systems until look-back times of ~5Gyr. An extension of this type of star formation history allows us to reconcile the small present-day scatter of the colour-magnitude relation with the observed blue galaxy fractions of intermediate redshift galaxy clusters. In addition to setting a limit on the variations in luminosity-weighted age between the stellar populations of cluster galaxies, the colour-magnitude relation can also be used to constrain the degree of merging between pre-existing stellar systems. This test relies on the slope of the colour-magnitude relation: mergers between galaxies of unequal mass tend to reduce the slope of the relation and to increase its scatter. We show that random mergers between galaxies very rapidly remove any well-defined colour-magnitude correlation. This model is not physically motivated, however, and we prefer to examine the merger process using a self-consistent merger tree. In such a model there are two effects. First, massive galaxies preferentially merge with systems of similar mass. Secondly, the rate of mass growth is considerably smaller than for the random merger case. As a result of both of these effects, the colour-magnitude correlation persists through a larger number of merger steps. The passive evolution of galaxy colours and their averaging in dissipationless mergers provide opposing constraints on the formation of cluster galaxies in a hierarchical model. At the level of current constraints, a compromise solution appears possible. The bulk of the stellar population must have formed before z=1, but cannot have formed in mass units much less than about half the mass of a present-day L_* galaxy. In this case, the galaxies are on average old enough that stellar population evolution is weak, yet formed recently enough that mass growth resulting from mergers is small.

THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY

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

Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.

The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less

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

PubMed

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

2012-03-28

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

OXYGEN AND SODIUM ABUNDANCES IN M13 (NGC 6205) GIANTS: LINKING GLOBULAR CLUSTER FORMATION SCENARIOS, DEEP MIXING, AND POST-RGB EVOLUTION

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

Johnson, Christian I.; Pilachowski, Catherine A., E-mail: cijohnson@astro.ucla.edu, E-mail: catyp@astro.indiana.edu

We present O, Na, and Fe abundances, as well as radial velocities, for 113 red giant branch (RGB) and asymptotic giant branch (AGB) stars in the globular cluster M13. The abundances and velocities are based on spectra obtained with the WIYN-Hydra spectrograph, and the observations range in luminosity from the horizontal branch (HB) to RGB tip. The results are examined in the context of recent globular cluster formation scenarios. We find that M13 exhibits many key characteristics that suggest its formation and chemical enrichment are well described by current models. Some of these observations include the central concentration of O-poormore » stars, the notable decrease in [O/Fe] (but small increase in [Na/Fe]) with increasing luminosity that affects primarily the 'extreme' population, the small fraction of stars with halo-like composition, and the paucity of O-poor AGB stars. In agreement with recent work, we conclude that the most O-poor M13 giants are likely He-enriched and that most (all?) O-poor RGB stars evolve to become extreme HB and AGB-manque stars. In contrast, the 'primordial' and 'intermediate' population stars appear to experience standard HB and AGB evolution.« less

Application of Scan Statistics to Detect Suicide Clusters in Australia

PubMed Central

Cheung, Yee Tak Derek; Spittal, Matthew J.; Williamson, Michelle Kate; Tung, Sui Jay; Pirkis, Jane

2013-01-01

Background Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. PMID:23342098

Stressful jobs and non-stressful jobs: a cluster analysis of office jobs.

PubMed

Carayon, P

1994-02-01

The purpose of the study was to determine if office jobs could be characterized by a small number of combinations of stressors that could be related to job-title information and self-report of psychological strain. Two-hundred-and-sixty-two office workers from three public service organizations provided data on nine job stressors and seven indicators of psychological strain. Using cluster analysis on the nine stressors, office jobs were classified into three clusters. The first cluster included jobs with high skill utilization, task clarity, job control and social support and low future ambiguity, but also high on job demands such as quantitative work-load, attention and work pressure. The second cluster included jobs with high demands and future ambiguity and low skill utilization, task clarity, job control and social support. The third cluster was intermediary between the first two clusters. The three clusters were related to job-title information. The second cluster was the highest on a range of psychological strain indicators, while the other two clusters were high on certain strain indicators but low on others. The study showed that office jobs could be characterized by a small number of combinations of stressors that were related to job-title information and psychological strain.

Towards a comprehensive knowledge of the star cluster population in the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, A. E.

2018-07-01

The Small Magellanic Cloud (SMC) has recently been found to harbour an increase of more than 200 per cent in its known cluster population. Here, we provide solid evidence that this unprecedented number of clusters could be greatly overestimated. On the one hand, the fully automatic procedure used to identify such an enormous cluster candidate sample did not recover ˜50 per cent, on average, of the known relatively bright clusters located in the SMC main body. On the other hand, the number of new cluster candidates per time unit as a function of time is noticeably different from the intrinsic SMC cluster frequency (CF), which should not be the case if these new detections were genuine physical systems. We found additionally that the SMC CF varies spatially, in such a way that it resembles an outside-in process coupled with the effects of a relatively recent interaction with the Large Magellanic Cloud. By assuming that clusters and field stars share the same formation history, we showed for the first time that the cluster dissolution rate also depends on position in the galaxy. The cluster dissolution becomes higher as the concentration of galaxy mass increases or if external tidal forces are present.

Modeling economic and carbon consequences of a shift to wood-based energy in a rural 'cluster'; a network analysis in southeast Alaska

Treesearch

David Saah; Trista Patterson; Thomas Buchholz; David Ganz; David Albert; Keith Rush

2014-01-01

Integrated ecological and economic solutions are increasingly sought after by communities to provide basic energy needs such as home heating, transport, and electricity, while reducing drivers of and vulnerability to climate change. Small rural communities may require a coordinated approach to overcome the limitations of economies of scale. Low-carbon development...

A Bayesian hierarchical model for mortality data from cluster-sampling household surveys in humanitarian crises.

PubMed

Heudtlass, Peter; Guha-Sapir, Debarati; Speybroeck, Niko

2018-05-31

The crude death rate (CDR) is one of the defining indicators of humanitarian emergencies. When data from vital registration systems are not available, it is common practice to estimate the CDR from household surveys with cluster-sampling design. However, sample sizes are often too small to compare mortality estimates to emergency thresholds, at least in a frequentist framework. Several authors have proposed Bayesian methods for health surveys in humanitarian crises. Here, we develop an approach specifically for mortality data and cluster-sampling surveys. We describe a Bayesian hierarchical Poisson-Gamma mixture model with generic (weakly informative) priors that could be used as default in absence of any specific prior knowledge, and compare Bayesian and frequentist CDR estimates using five different mortality datasets. We provide an interpretation of the Bayesian estimates in the context of an emergency threshold and demonstrate how to interpret parameters at the cluster level and ways in which informative priors can be introduced. With the same set of weakly informative priors, Bayesian CDR estimates are equivalent to frequentist estimates, for all practical purposes. The probability that the CDR surpasses the emergency threshold can be derived directly from the posterior of the mean of the mixing distribution. All observation in the datasets contribute to the estimation of cluster-level estimates, through the hierarchical structure of the model. In a context of sparse data, Bayesian mortality assessments have advantages over frequentist ones already when using only weakly informative priors. More informative priors offer a formal and transparent way of combining new data with existing data and expert knowledge and can help to improve decision-making in humanitarian crises by complementing frequentist estimates.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations

PubMed Central

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2018-01-01

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics. PMID:29744257

A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations.

PubMed

Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong

2016-10-16

Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.