A Cluster Analytic Study of Clinical Orientations among Chemical Dependency Counselors.

ERIC Educational Resources Information Center

Thombs, Dennis L.; Osborn, Cynthia J.

2001-01-01

Three distinct clinical orientations were identified in a sample of chemical dependency counselors (N=406). Based on cluster analysis, the largest group, identified and labeled as "uniform counselors," endorsed a simple, moral-disease model with little interest in psychosocial interventions. (Contains 50 references and 4 tables.) (GCP)

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

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

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

Modeling tensional homeostasis in multicellular clusters.

PubMed

Tam, Sze Nok; Smith, Michael L; Stamenović, Dimitrije

2017-03-01

Homeostasis of mechanical stress in cells, or tensional homeostasis, is essential for normal physiological function of tissues and organs and is protective against disease progression, including atherosclerosis and cancer. Recent experimental studies have shown that isolated cells are not capable of maintaining tensional homeostasis, whereas multicellular clusters are, with stability increasing with the size of the clusters. Here, we proposed simple mathematical models to interpret experimental results and to obtain insight into factors that determine homeostasis. Multicellular clusters were modeled as one-dimensional arrays of linearly elastic blocks that were either jointed or disjointed. Fluctuating forces that mimicked experimentally measured cell-substrate tractions were obtained from Monte Carlo simulations. These forces were applied to the cluster models, and the corresponding stress field in the cluster was calculated by solving the equilibrium equation. It was found that temporal fluctuations of the cluster stress field became attenuated with increasing cluster size, indicating that the cluster approached tensional homeostasis. These results were consistent with previously reported experimental data. Furthermore, the models revealed that key determinants of tensional homeostasis in multicellular clusters included the cluster size, the distribution of traction forces, and mechanical coupling between adjacent cells. Based on these findings, we concluded that tensional homeostasis was a multicellular phenomenon. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

SUSTAIN: a network model of category learning.

PubMed

Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

2004-04-01

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

Authentication of monofloral Yemeni Sidr honey using ultraviolet spectroscopy and chemometric analysis.

PubMed

Roshan, Abdul-Rahman A; Gad, Haidy A; El-Ahmady, Sherweit H; Khanbash, Mohamed S; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M

2013-08-14

This work describes a simple model developed for the authentication of monofloral Yemeni Sidr honey using UV spectroscopy together with chemometric techniques of hierarchical cluster analysis (HCA), principal component analysis (PCA), and soft independent modeling of class analogy (SIMCA). The model was constructed using 13 genuine Sidr honey samples and challenged with 25 honey samples of different botanical origins. HCA and PCA were successfully able to present a preliminary clustering pattern to segregate the genuine Sidr samples from the lower priced local polyfloral and non-Sidr samples. The SIMCA model presented a clear demarcation of the samples and was used to identify genuine Sidr honey samples as well as detect admixture with lower priced polyfloral honey by detection limits >10%. The constructed model presents a simple and efficient method of analysis and may serve as a basis for the authentication of other honey types worldwide.

On Defect Cluster Aggregation and Non-Reducibilty in Tin-Doped Indium Oxide

NASA Astrophysics Data System (ADS)

Warschkow, Oliver; Ellis, Donald E.; Gonzalez, Gabriela; Mason, Thomas O.

2003-03-01

The conductivity of tin-doped indium oxide (ITO), a transparent conductor, is critically dependent on the amount of tin-doping and oxygen partial pressure during preparation and annealing. Frank and Kostlin (Appl. Phys. A 27 (1982) 197-206) rationalized the carrier concentration dependence by postulating the formation of two types of neutral defect clusters at medium tin-doping levels: "Reducible" and "non-reducible" defect clusters; so named to indicate their ability to create carriers under reduction. According to Frank and Kostlin, both are composed of a single oxygen interstitial and two tin atoms substituting for indium, positioned in non-nearest and nearest coordination, respectively. This present work, seeking to distinguish reducible and non-reducible clusters by use of an atomistic model, finds only a weak correlation of oxygen interstitial binding energies with the relative positioning of dopants. Instead, the number of tin-dopants in the vicinity of the interstitial has a much larger effect on how strongly it is bound, a simple consequence of Coulomb interactions. We postulate that oxygen interstitials become non-reducible when clustered with three or more Sn_In. This occurs at higher doping levels as reducible clusters aggregate and share tin atoms. A simple probabilistic model, estimating the average number of clusters so aggregated, provides a qualitatively correct description of the carrier density in reduced ITO as a function of Sn doping level.

Hard X-ray emission from accretion shocks around galaxy clusters

NASA Astrophysics Data System (ADS)

Kushnir, Doron; Waxman, Eli

2010-02-01

We show that the hard X-ray (HXR) emission observed from several galaxy clusters is consistent with a simple model, in which the nonthermal emission is produced by inverse Compton scattering of cosmic microwave background photons by electrons accelerated in cluster accretion shocks: The dependence of HXR surface brightness on cluster temperature is consistent with that predicted by the model, and the observed HXR luminosity is consistent with the fraction of shock thermal energy deposited in relativistic electrons being lesssim0.1. Alternative models, where the HXR emission is predicted to be correlated with the cluster thermal emission, are disfavored by the data. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed.

Cluster analysis of multiple planetary flow regimes

NASA Technical Reports Server (NTRS)

Mo, Kingtse; Ghil, Michael

1988-01-01

A modified cluster analysis method developed for the classification of quasi-stationary events into a few planetary flow regimes and for the examination of transitions between these regimes is described. The method was applied first to a simple deterministic model and then to a 500-mbar data set for Northern Hemisphere (NH), for which cluster analysis was carried out in the subspace of the first seven empirical orthogonal functions (EOFs). Stationary clusters were found in the low-frequency band of more than 10 days, while transient clusters were found in the band-pass frequency window between 2.5 and 6 days. In the low-frequency band, three pairs of clusters determined EOFs 1, 2, and 3, respectively; they exhibited well-known regional features, such as blocking, the Pacific/North American pattern, and wave trains. Both model and low-pass data exhibited strong bimodality.

Submillimeter Galaxy Number Counts and Magnification by Galaxy Clusters

NASA Astrophysics Data System (ADS)

Lima, Marcos; Jain, Bhuvnesh; Devlin, Mark; Aguirre, James

2010-07-01

We present an analytical model that reproduces measured galaxy number counts from surveys in the wavelength range of 500 μm-2 mm. The model involves a single high-redshift galaxy population with a Schechter luminosity function that has been gravitationally lensed by galaxy clusters in the mass range 1013-1015 M sun. This simple model reproduces both the low-flux and the high-flux end of the number counts reported by the BLAST, SCUBA, AzTEC, and South Pole Telescope (SPT) surveys. In particular, our model accounts for the most luminous galaxies detected by SPT as the result of high magnifications by galaxy clusters (magnification factors of 10-30). This interpretation implies that submillimeter (submm) and millimeter surveys of this population may prove to be a useful addition to ongoing cluster detection surveys. The model also implies that the bulk of submm galaxies detected at wavelengths larger than 500 μm lie at redshifts greater than 2.

Clustering biomolecular complexes by residue contacts similarity.

PubMed

Rodrigues, João P G L M; Trellet, Mikaël; Schmitz, Christophe; Kastritis, Panagiotis; Karaca, Ezgi; Melquiond, Adrien S J; Bonvin, Alexandre M J J

2012-07-01

Inaccuracies in computational molecular modeling methods are often counterweighed by brute-force generation of a plethora of putative solutions. These are then typically sieved via structural clustering based on similarity measures such as the root mean square deviation (RMSD) of atomic positions. Albeit widely used, these measures suffer from several theoretical and technical limitations (e.g., choice of regions for fitting) that impair their application in multicomponent systems (N > 2), large-scale studies (e.g., interactomes), and other time-critical scenarios. We present here a simple similarity measure for structural clustering based on atomic contacts--the fraction of common contacts--and compare it with the most used similarity measure of the protein docking community--interface backbone RMSD. We show that this method produces very compact clusters in remarkably short time when applied to a collection of binary and multicomponent protein-protein and protein-DNA complexes. Furthermore, it allows easy clustering of similar conformations of multicomponent symmetrical assemblies in which chain permutations can occur. Simple contact-based metrics should be applicable to other structural biology clustering problems, in particular for time-critical or large-scale endeavors. Copyright © 2012 Wiley Periodicals, Inc.

Nonthermal emission from clusters of galaxies

NASA Astrophysics Data System (ADS)

Kushnir, Doron; Waxman, Eli

2009-08-01

We show that the spectral and radial distribution of the nonthermal emission of massive, M gtrsim 1014.5Msun, galaxy clusters may be approximately described by simple analytic expressions, which depend on the cluster thermal X-ray properties and on two model parameter, βcore and ηe. βcore is the ratio of the cosmic-ray (CR) energy density (within a logarithmic CR energy interval) and the thermal energy density at the cluster core, and ηe(p) is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of intra-cluster medium CRs, which are produced by accretion shocks, we find that βcore simeq ηp/200, nearly independent of cluster mass and with a scatter Δln βcore simeq 1 between clusters of given mass. We show that the hard X-ray (HXR) and γ-ray luminosities produced by inverse Compton scattering of CMB photons by electrons accelerated in accretion shocks (primary electrons) exceed the luminosities produced by secondary particles (generated in hadronic interactions within the cluster) by factors simeq 500(ηe/ηp)(T/10 keV)-1/2 and simeq 150(ηe/ηp)(T/10 keV)-1/2 respectively, where T is the cluster temperature. Secondary particle emission may dominate at the radio and very high energy (gtrsim 1 TeV) γ-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and γ-ray emission from clusters of galaxies are extended, since the emission is dominated at these energies by primary (rather than by secondary) electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for ηp ~ ηe ~ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) γ-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. In particular, we identify the clusters which are the best candidates for detection in γ-rays. Finally, we show that our model's results agree with results of detailed numerical calculations, and that discrepancies between the results of various numerical simulations (and between such results and our model) are due to inaccuracies in the numerical calculations.

Segmentation by fusion of histogram-based k-means clusters in different color spaces.

PubMed

Mignotte, Max

2008-05-01

This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable and accurate segmentation result. The different label fields to be fused in our application are given by the same and simple (K-means based) clustering technique on an input image expressed in different color spaces. Our fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation), and has been successfully applied on the Berkeley image database. The experiments herein reported in this paper illustrate the potential of this approach compared to the state-of-the-art segmentation methods recently proposed in the literature.

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.

Role of demographic stochasticity in a speciation model with sexual reproduction

NASA Astrophysics Data System (ADS)

Lafuerza, Luis F.; McKane, Alan J.

2016-03-01

Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.

No-Enclave Percolation Corresponds to Holes in the Cluster Backbone.

PubMed

Hu, Hao; Ziff, Robert M; Deng, Youjin

2016-10-28

The no-enclave percolation (NEP) model introduced recently by Sheinman et al. can be mapped to a problem of holes within a standard percolation backbone, and numerical measurements of such holes give the same size-distribution exponent τ=1.82(1) as found for the NEP model. An argument is given that τ=1+d_{B}/2≈1.822 for backbone holes, where d_{B} is the backbone dimension. On the other hand, a model of simple holes within a percolation cluster yields τ=1+d_{f}/2=187/96≈1.948, where d_{f} is the fractal dimension of the cluster, and this value is consistent with the experimental results of gel collapse of Sheinman et al., which give τ=1.91(6). This suggests that the gel clusters are of the universality class of percolation cluster holes. Both models give a discontinuous maximum hole size at p_{c}, signifying explosive percolation behavior.

Fractality à la carte: a general particle aggregation model.

PubMed

Nicolás-Carlock, J R; Carrillo-Estrada, J L; Dossetti, V

2016-01-19

In nature, fractal structures emerge in a wide variety of systems as a local optimization of entropic and energetic distributions. The fractality of these systems determines many of their physical, chemical and/or biological properties. Thus, to comprehend the mechanisms that originate and control the fractality is highly relevant in many areas of science and technology. In studying clusters grown by aggregation phenomena, simple models have contributed to unveil some of the basic elements that give origin to fractality, however, the specific contribution from each of these elements to fractality has remained hidden in the complex dynamics. Here, we propose a simple and versatile model of particle aggregation that is, on the one hand, able to reveal the specific entropic and energetic contributions to the clusters' fractality and morphology, and, on the other, capable to generate an ample assortment of rich natural-looking aggregates with any prescribed fractal dimension.

What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm.

PubMed

Raykov, Yordan P; Boukouvalas, Alexis; Baig, Fahd; Little, Max A

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism.

What to Do When K-Means Clustering Fails: A Simple yet Principled Alternative Algorithm

PubMed Central

Baig, Fahd; Little, Max A.

2016-01-01

The K-means algorithm is one of the most popular clustering algorithms in current use as it is relatively fast yet simple to understand and deploy in practice. Nevertheless, its use entails certain restrictive assumptions about the data, the negative consequences of which are not always immediately apparent, as we demonstrate. While more flexible algorithms have been developed, their widespread use has been hindered by their computational and technical complexity. Motivated by these considerations, we present a flexible alternative to K-means that relaxes most of the assumptions, whilst remaining almost as fast and simple. This novel algorithm which we call MAP-DP (maximum a-posteriori Dirichlet process mixtures), is statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling. This approach allows us to overcome most of the limitations imposed by K-means. The number of clusters K is estimated from the data instead of being fixed a-priori as in K-means. In addition, while K-means is restricted to continuous data, the MAP-DP framework can be applied to many kinds of data, for example, binary, count or ordinal data. Also, it can efficiently separate outliers from the data. This additional flexibility does not incur a significant computational overhead compared to K-means with MAP-DP convergence typically achieved in the order of seconds for many practical problems. Finally, in contrast to K-means, since the algorithm is based on an underlying statistical model, the MAP-DP framework can deal with missing data and enables model testing such as cross validation in a principled way. We demonstrate the simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism. PMID:27669525

Blue Stragglers in Clusters and Integrated Spectral Properties of Stellar Populations

NASA Astrophysics Data System (ADS)

Xin, Yu; Deng, Licai

Blue straggler stars are the most prominent bright objects in the colour-magnitude diagram of a star cluster that challenges the theory of stellar evolution. Star clusters are the closest counterparts of the theoretical concept of simple stellar populations (SSPs) in the Universe. SSPs are widely used as the basic building blocks to interpret stellar contents in galaxies. The concept of an SSP is a group of coeval stars which follows a given distribution in mass, and has the same chemical property and age. In practice, SSPs are more conveniently made by the latest stellar evolutionary models of single stars. In reality, however, stars can be more complicated than just single either at birth time or during the course of evolution in a typical environment. Observations of star clusters show that there are always exotic objects which do not follow the predictions of standard theory of stellar evolution. Blue straggler stars (BSSs), as discussed intensively in this book both observationally and theoretically, are very important in our context when considering the integrated spectral properties of a cluster, or a simple stellar population. In this chapter, we are going to describe how important the contribution of BSSs is to the total light of a cluster.

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

PubMed Central

Ahmed, Gulnaz; Zou, Jianhua; Zhao, Xi; Sadiq Fareed, Mian Muhammad

2017-01-01

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. PMID:28241492

Weak lensing calibration of mass bias in the REFLEX+BCS X-ray galaxy cluster catalogue

NASA Astrophysics Data System (ADS)

Simet, Melanie; Battaglia, Nicholas; Mandelbaum, Rachel; Seljak, Uroš

2017-04-01

The use of large, X-ray-selected Galaxy cluster catalogues for cosmological analyses requires a thorough understanding of the X-ray mass estimates. Weak gravitational lensing is an ideal method to shed light on such issues, due to its insensitivity to the cluster dynamical state. We perform a weak lensing calibration of 166 galaxy clusters from the REFLEX and BCS cluster catalogue and compare our results to the X-ray masses based on scaled luminosities from that catalogue. To interpret the weak lensing signal in terms of cluster masses, we compare the lensing signal to simple theoretical Navarro-Frenk-White models and to simulated cluster lensing profiles, including complications such as cluster substructure, projected large-scale structure and Eddington bias. We find evidence of underestimation in the X-ray masses, as expected, with = 0.75 ± 0.07 stat. ±0.05 sys. for our best-fitting model. The biases in cosmological parameters in a typical cluster abundance measurement that ignores this mass bias will typically exceed the statistical errors.

Scaling behavior of ground-state energy cluster expansion for linear polyenes

NASA Astrophysics Data System (ADS)

Griffin, L. L.; Wu, Jian; Klein, D. J.; Schmalz, T. G.; Bytautas, L.

Ground-state energies for linear-chain polyenes are additively expanded in a sequence of terms for chemically relevant conjugated substructures of increasing size. The asymptotic behavior of the large-substructure limit (i.e., high-polymer limit) is investigated as a means of characterizing the rapidity of convergence and consequent utility of this energy cluster expansion. Consideration is directed to computations via: simple Hückel theory, a refined Hückel scheme with geometry optimization, restricted Hartree-Fock self-consistent field (RHF-SCF) solutions of fixed bond-length Parisier-Parr-Pople (PPP)/Hubbard models, and ab initio SCF approaches with and without geometry optimization. The cluster expansion in what might be described as the more "refined" approaches appears to lead to qualitatively more rapid convergence: exponentially fast as opposed to an inverse power at the simple Hückel or SCF-Hubbard levels. The substructural energy cluster expansion then seems to merit special attention. Its possible utility in making accurate extrapolations from finite systems to extended polymers is noted.

Model validation of simple-graph representations of metabolism

PubMed Central

Holme, Petter

2009-01-01

The large-scale properties of chemical reaction systems, such as metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information, lists of chemical reactions, available in databases. Even for the simplest type of graph representation, this reduction can be done in several ways. We investigate different simple network representations by testing how well they encode information about one biologically important network structure—network modularity (the propensity for edges to be clustered into dense groups that are sparsely connected between each other). To achieve this goal, we design a model of reaction systems where network modularity can be controlled and measure how well the reduction to simple graphs captures the modular structure of the model reaction system. We find that the network types that best capture the modular structure of the reaction system are substrate–product networks (where substrates are linked to products of a reaction) and substance networks (with edges between all substances participating in a reaction). Furthermore, we argue that the proposed model for reaction systems with tunable clustering is a general framework for studies of how reaction systems are affected by modularity. To this end, we investigate statistical properties of the model and find, among other things, that it recreates correlations between degree and mass of the molecules. PMID:19158012

Exponents of non-linear clustering in scale-free one-dimensional cosmological simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sicard, François

2013-03-01

One-dimensional versions of dissipationless cosmological N-body simulations have been shown to share many qualitative behaviours of the three-dimensional problem. Their interest lies in the fact that they can resolve a much greater range of time and length scales, and admit exact numerical integration. We use such models here to study how non-linear clustering depends on initial conditions and cosmology. More specifically, we consider a family of models which, like the three-dimensional Einstein-de Sitter (EdS) model, lead for power-law initial conditions to self-similar clustering characterized in the strongly non-linear regime by power-law behaviour of the two-point correlation function. We study how the corresponding exponent γ depends on the initial conditions, characterized by the exponent n of the power spectrum of initial fluctuations, and on a single parameter κ controlling the rate of expansion. The space of initial conditions/cosmology divides very clearly into two parts: (1) a region in which γ depends strongly on both n and κ and where it agrees very well with a simple generalization of the so-called stable clustering hypothesis in three dimensions; and (2) a region in which γ is more or less independent of both the spectrum and the expansion of the universe. The boundary in (n, κ) space dividing the `stable clustering' region from the `universal' region is very well approximated by a `critical' value of the predicted stable clustering exponent itself. We explain how this division of the (n, κ) space can be understood as a simple physical criterion which might indeed be expected to control the validity of the stable clustering hypothesis. We compare and contrast our findings to results in three dimensions, and discuss in particular the light they may throw on the question of `universality' of non-linear clustering in this context.

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

The Battlefield Environment Division Modeling Framework (BMF). Part 1: Optimizing the Atmospheric Boundary Layer Environment Model for Cluster Computing

DTIC Science & Technology

2014-02-01

idle waiting for the wavefront to reach it. To overcome this, Reeve et al. (2001) 3 developed a scheme in analogy to the red-black Gauss - Seidel iterative ...understandable procedure calls. Parallelization of the SIMPLE iterative scheme with SIP used a red-black scheme similar to the red-black Gauss - Seidel ...scheme, the SIMPLE method, for pressure-velocity coupling. The result is a slowing convergence of the outer iterations . The red-black scheme excites a 2

Scaling Relations from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High-Redshift Galaxy Clusters

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall; LaRoque, Samuel J.; Carlstrom, John E.; Nagai, Daisuke; Marrone, Dan

2007-01-01

We present Sunyaev-Zel'dovich Effect (SZE) scaling relations for 38 massive galaxy clusters at redshifts 0.14 less than or equal to z less than or equal to 0.89, observed with both the Chandra X-ray Observatory and the centimeter-wave SZE imaging system at the BIMA and OVRO interferometric arrays. An isothermal ,Beta-model with central 100 kpc excluded from the X-ray data is used to model the intracluster medium and to measure global cluster properties. For each Cluster, we measure the X-ray spectroscopic temperature, SZE gas mass, total mass. and integrated Compton-gamma parameters within r(sub 2500). Our measurements are in agreement with the expectations based on a simple self-similar model of cluster formation and evolution. We compare the cluster properties derived from our SZE observations with and without Chandra spatial and spectral information and find them to be in good agreement: We compare our results with cosmological numerical simulations, and find that simulations that include radiative cooling, star formation and feedback match well both the slope and normalization of our SZE scaling relations.

Cluster kinetics model of particle separation in vibrated granular media.

PubMed

McCoy, Benjamin J; Madras, Giridhar

2006-01-01

We model the Brazil-nut effect (BNE) by hypothesizing that granules form clusters that fragment and aggregate. This provides a heterogeneous medium in which the immersed intruder particle rises (BNE) or sinks (reverse BNE) according to relative convection currents and buoyant and drag forces. A simple relationship proposed for viscous drag in terms of the vibrational intensity and the particle to grain density ratio allows simulation of published experimental data for rise and sink times as functions of particle radius, initial depth of the particle, and particle-grain density ratio. The proposed model correctly describes the experimentally observed maximum in risetime.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Stochastic theory of log-periodic patterns

NASA Astrophysics Data System (ADS)

Canessa, Enrique

2000-12-01

We introduce an analytical model based on birth-death clustering processes to help in understanding the empirical log-periodic corrections to power law scaling and the finite-time singularity as reported in several domains including rupture, earthquakes, world population and financial systems. In our stochastic theory log-periodicities are a consequence of transient clusters induced by an entropy-like term that may reflect the amount of co-operative information carried by the state of a large system of different species. The clustering completion rates for the system are assumed to be given by a simple linear death process. The singularity at t0 is derived in terms of birth-death clustering coefficients.

Understanding the complex dynamics of stock markets through cellular automata

NASA Astrophysics Data System (ADS)

Qiu, G.; Kandhai, D.; Sloot, P. M. A.

2007-04-01

We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

Factor Analysis for Clustered Observations.

ERIC Educational Resources Information Center

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

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."

TESTING STELLAR POPULATION SYNTHESIS MODELS WITH SLOAN DIGITAL SKY SURVEY COLORS OF M31's GLOBULAR CLUSTERS

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

Peacock, Mark B.; Zepf, Stephen E.; Maccarone, Thomas J.

2011-08-10

Accurate stellar population synthesis models are vital in understanding the properties and formation histories of galaxies. In order to calibrate and test the reliability of these models, they are often compared with observations of star clusters. However, relatively little work has compared these models in the ugriz filters, despite the recent widespread use of this filter set. In this paper, we compare the integrated colors of globular clusters in the Sloan Digital Sky Survey (SDSS) with those predicted from commonly used simple stellar population (SSP) models. The colors are based on SDSS observations of M31's clusters and provide the largestmore » population of star clusters with accurate photometry available from the survey. As such, it is a unique sample with which to compare SSP models with SDSS observations. From this work, we identify a significant offset between the SSP models and the clusters' g - r colors, with the models predicting colors which are too red by g - r {approx} 0.1. This finding is consistent with previous observations of luminous red galaxies in the SDSS, which show a similar discrepancy. The identification of this offset in globular clusters suggests that it is very unlikely to be due to a minority population of young stars. The recently updated SSP model of Maraston and Stroembaeck better represents the observed g - r colors. This model is based on the empirical MILES stellar library, rather than theoretical libraries, suggesting an explanation for the g - r discrepancy.« less

Alignment and integration of complex networks by hypergraph-based spectral clustering

NASA Astrophysics Data System (ADS)

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Alignment and integration of complex networks by hypergraph-based spectral clustering.

PubMed

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Observing Stellar Clusters in the Computer

NASA Astrophysics Data System (ADS)

Borch, A.; Spurzem, R.; Hurley, J.

2006-08-01

We present a new approach to combine direct N-body simulations to stellar population synthesis modeling in order to model the dynamical evolution and color evolution of globular clusters at the same time. This allows us to model the spectrum, colors and luminosities of each star in the simulated cluster. For this purpose the NBODY6++ code (Spurzem 1999) is used, which is a parallel version of the NBODY code. J. Hurley implemented simple recipes to follow the changes of stellar masses, radii, and luminosities due to stellar evolution into the NBODY6++ code (Hurley et al. 2001), in the sense that each simulation particle represents one star. These prescriptions cover all evolutionary phases and solar to globular cluster metallicities. We used the stellar parameters obtained by this stellar evolution routine and coupled them to the stellar library BaSeL 2.0 (Lejeune et al. 1997). As a first application we investigated the integrated broad band colors of simulated clusters. We modeled tidally disrupted globular clusters and compared the results with isolated globular clusters. Due to energy equipartition we expected a relative blueing of tidally disrupted clusters, because of the higher escape probability of red, low-mass stars. This behaviour we actually observe for concentrated globular clusters. The mass-to-light ratio of isolated clusters follows exactly a color-M/L correlation, similar as described in Bell and de Jong (2001) in the case of spiral galaxies. At variance to this correlation, in tidally disrupted clusters the M/L ratio becomes significantly lower at the time of cluster dissolution. Hence, for isolated clusters the behavior of the stellar population is not influenced by dynamical evolution, whereas the stellar population of tidally disrupted clusters is strongly influenced by dynamical effects.

Mid-infrared Integrated-light Photometry Of LMC Star Clusters

NASA Astrophysics Data System (ADS)

Pessev, Peter; Goudfrooij, P.; Puzia, T.; Chandar, R.

2008-03-01

Massive star clusters (Galactic Globular Clusters and Populous Clusters in the Magellanic Clouds) are the best available approximation of Simple Stellar Populations (SSPs). Since the stellar populations in these nearby objects are studied in details, they provide fundamental age/metallicity templates for interpretation of the galaxy properties, testing and calibration of the SSP Models. Magellanic Cloud clusters are particularly important since they populate a region of the age/metallicity parameter space that is not easily accessible in our Galaxy. We present the first Mid-IR integrated-light measurements for six LMC clusters based on our Spitzer IRAC imaging program. Since we are targeting a specific group of intermediate-age clusters, our imaging goes deeper compared to SAGE-LMC survey data. We present a literature compilation of clusters' properties along with multi-wavelength integrated light photometry database spanning from the optical (Johnson U band) to the Mid-IR (IRAC Channel 4). This data provides an important empirical baseline for the interpretation of galaxy colors in the Mid-IR (especially high-z objects whose integrated-light is dominated by TP-AGB stars emission). It is also a valuable tool to check the SSP model predictions in the intermediate-age regime and provides calibration data for the next generation of SSP models.

Chronology of the halo globular cluster system formation.

NASA Astrophysics Data System (ADS)

Salaris, M.; Weiss, A.

1997-11-01

Using up-to-date stellar models and isochrones we determine the age of 25 galactic halo clusters. The clusters are distributed into four groups according to metallicity. We measure the absolute age of a reference cluster in each group, and then find the relative ages of the other clusters relative to this one. This combination yields the most reliable results. We find that the oldest cluster group on average is 11.8+/-0.9Gyr or 12.3+/-0.3Gyr old, depending on whether we include Arp 2 and Rup 106. The average age of all clusters is about 10.5Gyr. Questions concerning a common age for all clusters and a relation between metallicity and age are addressed. The groups of lower metallicity appear to be coeval, but our results indicate that globally the sample has an age spread, and age and metallicity are correlated but not with a simple linear relation.

Modeling the stylized facts in finance through simple nonlinear adaptive systems

PubMed Central

Hommes, Cars H.

2002-01-01

Recent work on adaptive systems for modeling financial markets is discussed. Financial markets are viewed as evolutionary systems between different, competing trading strategies. Agents are boundedly rational in the sense that they tend to follow strategies that have performed well, according to realized profits or accumulated wealth, in the recent past. Simple technical trading rules may survive evolutionary competition in a heterogeneous world where prices and beliefs co-evolve over time. Evolutionary models can explain important stylized facts, such as fat tails, clustered volatility, and long memory, of real financial series. PMID:12011401

Tidal disruption of open clusters in their parent molecular clouds

NASA Technical Reports Server (NTRS)

Long, Kevin

1989-01-01

A simple model of tidal encounters has been applied to the problem of an open cluster in a clumpy molecular cloud. The parameters of the clumps are taken from the Blitz, Stark, and Long (1988) catalog of clumps in the Rosette molecular cloud. Encounters are modeled as impulsive, rectilinear collisions between Plummer spheres, but the tidal approximation is not invoked. Mass and binding energy changes during an encounter are computed by considering the velocity impulses given to individual stars in a random realization of a Plummer sphere. Mean rates of mass and binding energy loss are then computed by integrating over many encounters. Self-similar evolutionary calculations using these rates indicate that the disruption process is most sensitive to the cluster radius and relatively insensitive to cluster mass. The calculations indicate that clusters which are born in a cloud similar to the Rosette with a cluster radius greater than about 2.5 pc will not survive long enough to leave the cloud. The majority of clusters, however, have smaller radii and will survive the passage through their parent cloud.

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.

X-ray and Sunyaev-Zel'dovich Effect Measurements of the Gas Mass Fraction in Galaxy Clusters

NASA Technical Reports Server (NTRS)

LaRoque, Samuel J.; Bonamente, Massimiliano; Carlstrom, John E.; Joy, Marshall K.; Nagai, Daisuke; Reese, Erik D.; Dawson, Kyle S.

2006-01-01

We present gas mass fractions of 38 massive galaxy clusters spanning redshifts from 0.14 to 0.89, derived from Chandra X-ray data and OVRO/BIMA interferometric Sunyaev-Zel' dovich Effect (SZE) measurements. We use three models for the gas distribution: (1) an isothermal Beta-model fit jointly to the X-ray data at radii beyond 100 kpc and to all of the SZE data, (2) a nonisothermal double Beta-model fit jointly to all of the X-ray and SZE data, and (3) an isothermal Beta-model fit only to the SZE spatial data. We show that the simple isothermal model well characterizes the intracluster medium (ICM) outside of the cluster core, and provides consistently good fits to clusters spanning a wide range of morphological properties. The agreement in the results shows that the core can be satisfactorily accounted for by either excluding the core in fits to the X-ray data (the 100 kpc-cut model) or modeling the intracluster gas with a non-isothermal double Beta-model. We find that the SZE is largely insensitive to structure in the core.

A modern approach to the authentication and quality assessment of thyme using UV spectroscopy and chemometric analysis.

PubMed

Gad, Haidy A; El-Ahmady, Sherweit H; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M

2013-01-01

Recently, the fields of chemometrics and multivariate analysis have been widely implemented in the quality control of herbal drugs to produce precise results, which is crucial in the field of medicine. Thyme represents an essential medicinal herb that is constantly adulterated due to its resemblance to many other plants with similar organoleptic properties. To establish a simple model for the quality assessment of Thymus species using UV spectroscopy together with known chemometric techniques. The success of this model may also serve as a technique for the quality control of other herbal drugs. The model was constructed using 30 samples of authenticated Thymus vulgaris and challenged with 20 samples of different botanical origins. The methanolic extracts of all samples were assessed using UV spectroscopy together with chemometric techniques: principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and hierarchical cluster analysis (HCA). The model was able to discriminate T. vulgaris from other Thymus, Satureja, Origanum, Plectranthus and Eriocephalus species, all traded in the Egyptian market as different types of thyme. The model was also able to classify closely related species in clusters using PCA and HCA. The model was finally used to classify 12 commercial thyme varieties into clusters of species incorporated in the model as thyme or non-thyme. The model constructed is highly recommended as a simple and efficient method for distinguishing T. vulgaris from other related species as well as the classification of marketed herbs as thyme or non-thyme. Copyright © 2013 John Wiley & Sons, Ltd.

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

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.

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.

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2018-03-01

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

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2017-12-01

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

DARK MATTER SUBHALOS AND THE X-RAY MORPHOLOGY OF THE COMA CLUSTER

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

Andrade-Santos, Felipe; Nulsen, Paul E. J.; Kraft, Ralph P.

2013-04-01

Structure formation models predict that clusters of galaxies contain numerous massive subhalos. The gravity of a subhalo in a cluster compresses the surrounding intracluster gas and enhances its X-ray emission. We present a simple model, which treats subhalos as slow moving and gasless, for computing this effect. Recent weak lensing measurements by Okabe et al. have determined masses of {approx}10{sup 13} M{sub Sun} for three mass concentrations projected within 300 kpc of the center of the Coma Cluster, two of which are centered on the giant elliptical galaxies NGC 4889 and NGC 4874. Adopting a smooth spheroidal {beta}-model for themore » gas distribution in the unperturbed cluster, we model the effect of these subhalos on the X-ray morphology of the Coma Cluster, comparing our results to Chandra and XMM-Newton X-ray data. The agreement between the models and the X-ray morphology of the central Coma Cluster is striking. With subhalo parameters from the lensing measurements, the distances of the three subhalos from the Coma Cluster midplane along our line of sight are all tightly constrained. Using the model to fit the subhalo masses for NGC 4889 and NGC 4874 gives 9.1 Multiplication-Sign 10{sup 12} M{sub Sun} and 7.6 Multiplication-Sign 10{sup 12} M{sub Sun }, respectively, in good agreement with the lensing masses. These results lend strong support to the argument that NGC 4889 and NGC 4874 are each associated with a subhalo that resides near the center of the Coma Cluster. In addition to constraining the masses and 3-d location of subhalos, the X-ray data show promise as a means of probing the structure of central subhalos.« less

Simple Epidemiological Dynamics Explain Phylogenetic Clustering of HIV from Patients with Recent Infection

PubMed Central

Volz, Erik M.; Koopman, James S.; Ward, Melissa J.; Brown, Andrew Leigh; Frost, Simon D. W.

2012-01-01

Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection (‘excess clustering’) and also tend to cluster with other recent HIV infections rather than chronic, established infections (‘excess co-clustering’), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled. PMID:22761556

Implications for gravitational lensing and the dark matter content in clusters of galaxies from spatially resolved x-ray spectra

NASA Technical Reports Server (NTRS)

Loewenstein, M.

1994-01-01

A simple method for deriving well-behaved temperature solutions to the equation of hydrostatic equilibrium for intracluster media with X-ray imaging observations is presented and applied to a series of generalized models as well as to observations of the Perseus cluster and Abell 2256. In these applications the allowed range in the ratio of nonbaryons to baryons as a function of radius is derived, taking into account the uncertainties and crude spatial resolution of the X-ray spectra and considering a range of physically reasonable mass models with various scale heights. Particular attention is paid to the central regions of the cluster, and it is found that the dark matter can be sufficiently concentrated to be consistent with the high central mass surface densities for moderate-redshift clusters from their gravitational lensing properties.

Cluster-based analysis of multi-model climate ensembles

NASA Astrophysics Data System (ADS)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Intracluster age gradients in numerous young stellar clusters

NASA Astrophysics Data System (ADS)

Getman, K. V.; Feigelson, E. D.; Kuhn, M. A.; Bate, M. R.; Broos, P. S.; Garmire, G. P.

2018-05-01

The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc-1. The empirical finding reported in the present study - late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions - has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Combining symmetry collective states with coupled-cluster theory: Lessons from the Agassi model Hamiltonian

NASA Astrophysics Data System (ADS)

Hermes, Matthew R.; Dukelsky, Jorge; Scuseria, Gustavo E.

2017-06-01

The failures of single-reference coupled-cluster theory for strongly correlated many-body systems is flagged at the mean-field level by the spontaneous breaking of one or more physical symmetries of the Hamiltonian. Restoring the symmetry of the mean-field determinant by projection reveals that coupled-cluster theory fails because it factorizes high-order excitation amplitudes incorrectly. However, symmetry-projected mean-field wave functions do not account sufficiently for dynamic (or weak) correlation. Here we pursue a merger of symmetry projection and coupled-cluster theory, following previous work along these lines that utilized the simple Lipkin model system as a test bed [J. Chem. Phys. 146, 054110 (2017), 10.1063/1.4974989]. We generalize the concept of a symmetry-projected mean-field wave function to the concept of a symmetry projected state, in which the factorization of high-order excitation amplitudes in terms of low-order ones is guided by symmetry projection and is not exponential, and combine them with coupled-cluster theory in order to model the ground state of the Agassi Hamiltonian. This model has two separate channels of correlation and two separate physical symmetries which are broken under strong correlation. We show how the combination of symmetry collective states and coupled-cluster theory is effective in obtaining correlation energies and order parameters of the Agassi model throughout its phase diagram.

Ferromagnetic bond of Li{sub 10} cluster: An alternative approach in terms of effective ferromagnetic sites

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

Donoso, Roberto; Fuentealba, Patricio, E-mail: pfuentea@hotmail.es, E-mail: cardena@macul.ciencias.uchile.cl; Cárdenas, Carlos, E-mail: pfuentea@hotmail.es, E-mail: cardena@macul.ciencias.uchile.cl

In this work, a model to explain the unusual stability of atomic lithium clusters in their highest spin multiplicity is presented and used to describe the ferromagnetic bonding of high-spin Li{sub 10} and Li{sub 8} clusters. The model associates the (lack of-)fitness of Heisenberg Hamiltonian with the degree of (de-)localization of the valence electrons in the cluster. It is shown that a regular Heisenberg Hamiltonian with four coupling constants cannot fully explain the energy of the different spin states. However, a more simple model in which electrons are located not at the position of the nuclei but at the positionmore » of the attractors of the electron localization function succeeds in explaining the energy spectrum and, at the same time, explains the ferromagnetic bond found by Shaik using arguments of valence bond theory. In this way, two different points of view, one more often used in physics, the Heisenberg model, and the other in chemistry, valence bond, come to the same answer to explain those atypical bonds.« less

Cosmology and astrophysics from relaxed galaxy clusters - V. Consistency with cold dark matter structure formation

NASA Astrophysics Data System (ADS)

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

2016-10-01

This is the fifth 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 in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. We present constraints on the concentration-mass relation for massive clusters, finding a power-law mass dependence with a slope of κm = -0.16 ± 0.07, in agreement with CDM predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κζ = -0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ˜50 kpc-1 Mpc), and test for departures from the simple Navarro-Frenk-White (NFW) form, for which the logarithmic slope of the density profile tends to -1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σβ = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σα = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.

Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

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

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

This is the fifth 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 in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

DOE PAGES

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

2016-07-15

This is the fifth 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 in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

The Cosmological Dependence of Galaxy Cluster Morphologies

NASA Astrophysics Data System (ADS)

Crone, Mary Margaret

1995-01-01

Measuring the density of the universe has been a fundamental problem in cosmology ever since the "Big Bang" model was developed over sixty years ago. In this simple and successful model, the age and eventual fate of the universe are determined by its density, its rate of expansion, and the value of a universal "cosmological constant". Analytic models suggest that many properties of galaxy clusters are sensitive to cosmological parameters. In this thesis, I use N-body simulations to examine cluster density profiles, abundances, and degree of subclustering to test the feasibility of using them as cosmological tests. The dependence on both cosmology and initial density field is examined, using a grid of cosmologies and scale-free initial power spectra P(k)~ k n. Einstein-deSitter ( Omegao=1), open ( Omegao=0.2 and 0.1) and flat, low density (Omegao=0.2, lambdao=0.8) models are studied, with initial spectral indices n=-2, -1 and 0. Of particular interest are the results for cluster profiles and substructure. The average density profiles are well fit by a power law p(r)~ r ^{-alpha} for radii where the local density contrast is between 100 and 3000. There is a clear trend toward steeper slopes with both increasing n and decreasing Omegao, with profile slopes in the open models consistently higher than Omega=1 values for the range of n examined. The amount of substructure in each model is quantified and explained in terms of cluster merger histories and the behavior of substructure statistics. The statistic which best distinguishes models is a very simple measure of deviations from symmetry in the projected mass distribution --the "Center-of-Mass Shift" as a function of overdensity. Some statistics which are quite sensitive to substructure perform relatively poorly as cosmological indicators. Density profiles and the Center-of-Mass test are both well-suited for comparison with weak lensing data and galaxy distributions. Such data are currently being collected and should be available within the next few years. At that time the predictions described here can be used to set useful cosmological constraints.

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

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

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

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

PubMed Central

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

2005-01-01

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

Physical models of collective cell motility: from cell to tissue

NASA Astrophysics Data System (ADS)

Camley, B. A.; Rappel, W.-J.

2017-03-01

In this article, we review physics-based models of collective cell motility. We discuss a range of techniques at different scales, ranging from models that represent cells as simple self-propelled particles to phase field models that can represent a cell’s shape and dynamics in great detail. We also extensively review the ways in which cells within a tissue choose their direction, the statistics of cell motion, and some simple examples of how cell-cell signaling can interact with collective cell motility. This review also covers in more detail selected recent works on collective cell motion of small numbers of cells on micropatterns, in wound healing, and the chemotaxis of clusters of cells.

Predicting solar radiation based on available weather indicators

NASA Astrophysics Data System (ADS)

Sauer, Frank Joseph

Solar radiation prediction models are complex and require software that is not available for the household investor. The processing power within a normal desktop or laptop computer is sufficient to calculate similar models. This barrier to entry for the average consumer can be fixed by a model simple enough to be calculated by hand if necessary. Solar radiation modeling has been historically difficult to predict and accurate models have significant assumptions and restrictions on their use. Previous methods have been limited to linear relationships, location restrictions, or input data limits to one atmospheric condition. This research takes a novel approach by combining two techniques within the computational limits of a household computer; Clustering and Hidden Markov Models (HMMs). Clustering helps limit the large observation space which restricts the use of HMMs. Instead of using continuous data, and requiring significantly increased computations, the cluster can be used as a qualitative descriptor of each observation. HMMs incorporate a level of uncertainty and take into account the indirect relationship between meteorological indicators and solar radiation. This reduces the complexity of the model enough to be simply understood and accessible to the average household investor. The solar radiation is considered to be an unobservable state that each household will be unable to measure. The high temperature and the sky coverage are already available through the local or preferred source of weather information. By using the next day's prediction for high temperature and sky coverage, the model groups the data and then predicts the most likely range of radiation. This model uses simple techniques and calculations to give a broad estimate for the solar radiation when no other universal model exists for the average household.

Automatic building detection based on Purposive FastICA (PFICA) algorithm using monocular high resolution Google Earth images

NASA Astrophysics Data System (ADS)

Ghaffarian, Saman; Ghaffarian, Salar

2014-11-01

This paper proposes an improved FastICA model named as Purposive FastICA (PFICA) with initializing by a simple color space transformation and a novel masking approach to automatically detect buildings from high resolution Google Earth imagery. ICA and FastICA algorithms are defined as Blind Source Separation (BSS) techniques for unmixing source signals using the reference data sets. In order to overcome the limitations of the ICA and FastICA algorithms and make them purposeful, we developed a novel method involving three main steps: 1-Improving the FastICA algorithm using Moore-Penrose pseudo inverse matrix model, 2-Automated seeding of the PFICA algorithm based on LUV color space and proposed simple rules to split image into three regions; shadow + vegetation, baresoil + roads and buildings, respectively, 3-Masking out the final building detection results from PFICA outputs utilizing the K-means clustering algorithm with two number of clusters and conducting simple morphological operations to remove noises. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.6% and 85.5% overall pixel-based and object-based precision performances, respectively.

SUBMILLIMETER GALAXY NUMBER COUNTS AND MAGNIFICATION BY GALAXY CLUSTERS

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

Lima, Marcos; Jain, Bhuvnesh; Devlin, Mark

2010-07-01

We present an analytical model that reproduces measured galaxy number counts from surveys in the wavelength range of 500 {mu}m-2 mm. The model involves a single high-redshift galaxy population with a Schechter luminosity function that has been gravitationally lensed by galaxy clusters in the mass range 10{sup 13}-10{sup 15} M{sub sun}. This simple model reproduces both the low-flux and the high-flux end of the number counts reported by the BLAST, SCUBA, AzTEC, and South Pole Telescope (SPT) surveys. In particular, our model accounts for the most luminous galaxies detected by SPT as the result of high magnifications by galaxy clustersmore » (magnification factors of 10-30). This interpretation implies that submillimeter (submm) and millimeter surveys of this population may prove to be a useful addition to ongoing cluster detection surveys. The model also implies that the bulk of submm galaxies detected at wavelengths larger than 500 {mu}m lie at redshifts greater than 2.« less

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.

Gold Glyconanoparticles as Water-Soluble Polyvalent Models To Study Carbohydrate Interactions.

PubMed

de la Fuente, Jesús M; Barrientos, Africa G; Rojas, Teresa C; Rojo, Javier; Cañada, Javier; Fernández, Asunción; Penadés, Soledad

2001-06-18

Glycosphingolipid clustering and interactions at the cell membrane can be modeled by gold glyconanoparticles prepared with biologically significant oligosaccharides. Such water-soluble gold glyconanoparticles with highly polyvalent carbohydrate displays (see picture, gray hemisphere: gold nanoparticle) have been obtained by a simple and versatile strategy. © 2001 WILEY-VCH Verlag GmbH, Weinheim, Fed. Rep. of Germany.

Magnetic Properties of Strongly Correlated Hubbard Model and Quantum Spin-One Ferromagnets with Arbitrary Crystal-Field Potential: Linked Cluster Series Expansion Approach

NASA Astrophysics Data System (ADS)

Pan, Kok-Kwei

We have generalized the linked cluster expansion method to solve more many-body quantum systems, such as quantum spin systems with crystal-field potentials and the Hubbard model. The technique sums up all connected diagrams to a certain order of the perturbative Hamiltonian. The modified multiple-site Wick reduction theorem and the simple tau dependence of the standard basis operators have been used to facilitate the evaluation of the integration procedures in the perturbation expansion. Computational methods are developed to calculate all terms in the series expansion. As a first example, the perturbation series expansion of thermodynamic quantities of the single-band Hubbard model has been obtained using a linked cluster series expansion technique. We have made corrections to all previous results of several papers (up to fourth order). The behaviors of the three dimensional simple cubic and body-centered cubic systems have been discussed from the qualitative analysis of the perturbation series up to fourth order. We have also calculated the sixth-order perturbation series of this model. As a second example, we present the magnetic properties of spin-one Heisenberg model with arbitrary crystal-field potential using a linked cluster series expansion. The calculation of the thermodynamic properties using this method covers the whole range of temperature, in both magnetically ordered and disordered phases. The series for the susceptibility and magnetization have been obtained up to fourth order for this model. The method sums up all perturbation terms to certain order and estimates the result using a well -developed and highly successful extrapolation method (the standard ratio method). The dependence of critical temperature on the crystal-field potential and the magnetization as a function of temperature and crystal-field potential are shown. The critical behaviors at zero temperature are also shown. The range of the crystal-field potential for Ni(2+) compounds is roughly estimated based on this model using known experimental results.

Interaction of intense laser pulses with hydrogen atomic clusters

NASA Astrophysics Data System (ADS)

Du, Hong-Chuan; Wang, Hui-Qiao; Liu, Zuo-Ye; Sun, Shao-Hua; Li, Lu; Ma, Ling-Ling; Hu, Bi-Tao

2010-03-01

The interaction between intense femtosecond laser pulses and hydrogen atomic clusters is studied by a simplified Coulomb explosion model. The dependences of average proton kinetic energy on cluster size, pulse duration, laser intensity and wavelength are studied respectively. The calculated results indicate that the irradiation of a femtosecond laser of longer wavelength on hydrogen atomic clusters may be a simple, economical way to produce highly kinetic hydrogen ions. The phenomenon suggests that the irradiation of femtosecond laser of longer wavelength on deuterium atomic clusters may be easier than that of shorter wavelength to drive nuclear fusion reactions. The product of the laser intensity and the squared laser wavelength needed to make proton energy saturated as a function of the squared cluster radius is also investigated. The proton energy distribution calculated is also shown and compared with the experimental data. Our results are in agreement with the experimental results fairly well.

The halo model in a massive neutrino cosmology

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

Massara, Elena; Villaescusa-Navarro, Francisco; Viel, Matteo, E-mail: emassara@sissa.it, E-mail: villaescusa@oats.inaf.it, E-mail: viel@oats.inaf.it

2014-12-01

We provide a quantitative analysis of the halo model in the context of massive neutrino cosmologies. We discuss all the ingredients necessary to model the non-linear matter and cold dark matter power spectra and compare with the results of N-body simulations that incorporate massive neutrinos. Our neutrino halo model is able to capture the non-linear behavior of matter clustering with a ∼20% accuracy up to very non-linear scales of k = 10 h/Mpc (which would be affected by baryon physics). The largest discrepancies arise in the range k = 0.5 – 1 h/Mpc where the 1-halo and 2-halo terms are comparable and are present also inmore » a massless neutrino cosmology. However, at scales k < 0.2 h/Mpc our neutrino halo model agrees with the results of N-body simulations at the level of 8% for total neutrino masses of < 0.3 eV. We also model the neutrino non-linear density field as a sum of a linear and clustered component and predict the neutrino power spectrum and the cold dark matter-neutrino cross-power spectrum up to k = 1 h/Mpc with ∼30% accuracy. For masses below 0.15 eV the neutrino halo model captures the neutrino induced suppression, casted in terms of matter power ratios between massive and massless scenarios, with a 2% agreement with the results of N-body/neutrino simulations. Finally, we provide a simple application of the halo model: the computation of the clustering of galaxies, in massless and massive neutrinos cosmologies, using a simple Halo Occupation Distribution scheme and our halo model extension.« less

INTER- AND INTRA-CLUSTER AGE GRADIENTS IN MASSIVE STAR FORMING REGIONS AND INDIVIDUAL NEARBY STELLAR CLUSTERS REVEALED BY MYStIX

NASA Astrophysics Data System (ADS)

Getman, Konstantin V.; Feigelson, Eric; Kuhn, Michael A.; Broos, Patrick S; Townsley, Leisa K.; Naylor, Tim; Povich, Matthew S.; Luhman, Kevin; Garmire, Gordon

2014-08-01

The MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) project seeks to characterize 20 OB-dominated young star forming regions (SFRs) at distances <4 kpc using photometric catalogs from the Chandra X-ray Observatory, Spitzer Space Telescope, UKIRT and 2MASS surveys. As part of the MYStIX project, we developed a new stellar chronometer that employs near-infrared and X-ray photometry data, AgeJX. Computing AgeJX averaged over MYStIX (sub)clusters reveals previously unknown age gradients across most of the MYStIX regions as well as within some individual rich clusters. Within the SFRs, the inferred AgeJX ages are youngest in obscured locations in molecular clouds, intermediate in revealed stellar clusters, and oldest in distributed stellar populations. Noticeable intra-cluster gradients are seen in the NGC 2024 (Flame Nebula) star cluster and the Orion Nebula Cluster (ONC): stars in cluster cores appear younger and thus were formed later than stars in cluster halos. The latter result has two important implications for the formation of young stellar clusters. Clusters likely form slowly: they do not arise from a single nearly-instantaneous burst of star formation. The simple models where clusters form inside-out are likely incorrect, and more complex models are needed. We provide several star formation scenarios that alone or in combination may lead to the observed core-halo age gradients.

Are the gyro-ages of field stars underestimated?

NASA Astrophysics Data System (ADS)

Kovács, Géza

2015-09-01

By using the current photometric rotational data on eight galactic open clusters, we show that the evolutionary stellar model (isochrone) ages of these clusters are tightly correlated with the period shifts applied to the (B - V)0-Prot ridges that optimally align these ridges to the one defined by Praesepe and the Hyades. On the other hand, when the traditional Skumanich-type multiplicative transformation is used, the ridges become far less aligned due to the age-dependent slope change introduced by the period multiplication. Therefore, we employ our simple additive gyro-age calibration on various datasets of Galactic field stars to test its applicability. We show that, in the overall sense, the gyro-ages are systematically greater than the isochrone ages. The difference could exceed several giga years, depending on the stellar parameters. Although the age overlap between the open clusters used in the calibration and the field star samples is only partial, the systematic difference indicates the limitation of the currently available gyro-age methods and suggests that the rotation of field stars slows down with a considerably lower speed than we would expect from the simple extrapolation of the stellar rotation rates in open clusters.

Cosmic Ray Streaming in Galaxy Clusters

NASA Astrophysics Data System (ADS)

Wiener, Joshua; Gould Zweibel, Ellen; Oh, Siang P.

2017-08-01

The origin of diffuse radio emission in galaxy clusters remains an open question in astrophysics. This emission indicates the presence of cluster-wide magnetic fields and high energy cosmic ray (CR) electrons. I will discuss how the properties of the observed radio emission in clusters are shaped by different CR transport processes, namely CR streaming. Recent work has shown that fast streaming may turn off radio emission on relatively short time scales - a full treatment of magnetohydrodynamic (MHD) wave damping shows that streaming may be even faster than previously thought in high β environments. I will briefly introduce the physics behind CR transport, and present simple numerical simulations of the Coma cluster that predict radio emission, as well as other observable signatures such as gamma radiation that can differentiate between models for the source of the CR electrons.

Hybrid Percolation Transition in Cluster Merging Processes: Continuously Varying Exponents

NASA Astrophysics Data System (ADS)

Cho, Y. S.; Lee, J. S.; Herrmann, H. J.; Kahng, B.

2016-01-01

Consider growing a network, in which every new connection is made between two disconnected nodes. At least one node is chosen randomly from a subset consisting of g fraction of the entire population in the smallest clusters. Here we show that this simple strategy for improving connection exhibits a more unusual phase transition, namely a hybrid percolation transition exhibiting the properties of both first-order and second-order phase transitions. The cluster size distribution of finite clusters at a transition point exhibits power-law behavior with a continuously varying exponent τ in the range 2 <τ (g )≤2.5 . This pattern reveals a necessary condition for a hybrid transition in cluster aggregation processes, which is comparable to the power-law behavior of the avalanche size distribution arising in models with link-deleting processes in interdependent networks.

A Theoretical Study of the Luminosity-Temperature Relation for Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Del Popolo, A.; Hiotelis, N.; Peñarrubia, J.

2005-07-01

A luminosity-temperature relation is derived for clusters of galaxies. The two models used take into account the angular momentum acquisition by the protostructures during their expansion and collapse. The first model is a modification of the self-similar model, while the second is a modification of the punctuated equilibria model of Cavaliere et al. In both models the mass-temperature relation (M-T) used is based on previous calculations of Del Popolo. We show that the above models lead, in X-rays, to a luminosity-temperature relation that scales as L~T5 at the scale of groups, flattening to L~T3 for rich clusters and converging to L~T2 at higher temperatures. However, a fundamental result of our paper is that the nonsimilarity in the L-T relation can be explained by a simple model that takes into account the amount of angular momentum of a protostructure. This result is in disagreement with the widely accepted idea that the nonsimilarity is due to nongravitating processes, such as heating and/or cooling.

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.

Strong Lensing Analysis of the Galaxy Cluster MACS J1319.9+7003 and the Discovery of a Shell Galaxy

NASA Astrophysics Data System (ADS)

Zitrin, Adi

2017-01-01

We present a strong-lensing (SL) analysis of the galaxy cluster MACS J1319.9+7003 (z = 0.33, also known as Abell 1722), as part of our ongoing effort to analyze massive clusters with archival Hubble Space Telescope (HST) imaging. We spectroscopically measured with Keck/Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE) two galaxies multiply imaged by the cluster. Our analysis reveals a modest lens, with an effective Einstein radius of {θ }e(z=2)=12+/- 1\\prime\\prime , enclosing 2.1+/- 0.3× {10}13 M⊙. We briefly discuss the SL properties of the cluster, using two different modeling techniques (see the text for details), and make the mass models publicly available (ftp://wise-ftp.tau.ac.il/pub/adiz/MACS1319/). Independently, we identified a noteworthy, young shell galaxy (SG) system forming around two likely interacting cluster members, 20″ north of the brightest cluster galaxy. SGs are rare in galaxy clusters, and indeed, a simple estimate reveals that they are only expected in roughly one in several dozen, to several hundred, massive galaxy clusters (the estimate can easily change by an order of magnitude within a reasonable range of characteristic values relevant for the calculation). Taking advantage of our lens model best-fit, mass-to-light scaling relation for cluster members, we infer that the total mass of the SG system is ˜ 1.3× {10}11 {M}⊙ , with a host-to-companion mass ratio of about 10:1. Despite being rare in high density environments, the SG constitutes an example to how stars of cluster galaxies are efficiently redistributed to the intra-cluster medium. Dedicated numerical simulations for the observed shell configuration, perhaps aided by the mass model, might cast interesting light on the interaction history and properties of the two galaxies. An archival HST search in galaxy cluster images can reveal more such systems.

Ultraviolet gas absorption and dust extinction toward M8

NASA Technical Reports Server (NTRS)

Boggs, Don; Bohm-Vitense, Erika

1990-01-01

Interstellar absorption lines are analyzed using high-resolution IUE spectra of 11 stars in the young cluster NGC 6530 located in the M8 region. High-velocity clouds at -35 km/s and -60 km/s are seen toward all cluster stars. The components arise in gases that are part of large interstellar bubbles centered on the cluster and driven by stellar winds of the most luminous members. Absorption lines of species of different ionization states are separated in velocity. The velocity stratification is best explained as a 'champagne' flow of ionized gas away from the cluster. The C IV/Si IV ratios toward the hotter cluster members are consistent with simple photoionization models if the gas-phase C/Si ratio is increased by preferential accretion onto dust grains. High ion column densities in the central cluster decline with distance from W93, suggesting that radiation from a hot source near W93 has photoionized gas in the central cluster.

Estimating global distribution of boreal, temperate, and tropical tree plant functional types using clustering techniques

NASA Astrophysics Data System (ADS)

Wang, Audrey; Price, David T.

2007-03-01

A simple integrated algorithm was developed to relate global climatology to distributions of tree plant functional types (PFT). Multivariate cluster analysis was performed to analyze the statistical homogeneity of the climate space occupied by individual tree PFTs. Forested regions identified from the satellite-based GLC2000 classification were separated into tropical, temperate, and boreal sub-PFTs for use in the Canadian Terrestrial Ecosystem Model (CTEM). Global data sets of monthly minimum temperature, growing degree days, an index of climatic moisture, and estimated PFT cover fractions were then used as variables in the cluster analysis. The statistical results for individual PFT clusters were found consistent with other global-scale classifications of dominant vegetation. As an improvement of the quantification of the climatic limitations on PFT distributions, the results also demonstrated overlapping of PFT cluster boundaries that reflected vegetation transitions, for example, between tropical and temperate biomes. The resulting global database should provide a better basis for simulating the interaction of climate change and terrestrial ecosystem dynamics using global vegetation models.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

MASSCLEANCOLORS-MASS-DEPENDENT INTEGRATED COLORS FOR STELLAR CLUSTERS DERIVED FROM 30 MILLION MONTE CARLO SIMULATIONS

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

Popescu, Bogdan; Hanson, M. M.

2010-04-10

We present Monte Carlo models of open stellar clusters with the purpose of mapping out the behavior of integrated colors with mass and age. Our cluster simulation package allows for stochastic variations in the stellar mass function to evaluate variations in integrated cluster properties. We find that UBVK colors from our simulations are consistent with simple stellar population (SSP) models, provided the cluster mass is large, M {sub cluster} {>=} 10{sup 6} M {sub sun}. Below this mass, our simulations show two significant effects. First, the mean value of the distribution of integrated colors moves away from the SSP predictionsmore » and is less red, in the first 10{sup 7} to 10{sup 8} years in UBV colors, and for all ages in (V - K). Second, the 1{sigma} dispersion of observed colors increases significantly with lower cluster mass. We attribute the former to the reduced number of red luminous stars in most of the lower mass clusters and the latter to the increased stochastic effect of a few of these stars on lower mass clusters. This latter point was always assumed to occur, but we now provide the first public code able to quantify this effect. We are completing a more extensive database of magnitudes and colors as a function of stellar cluster age and mass that will allow the determination of the correlation coefficients among different bands, and improve estimates of cluster age and mass from integrated photometry.« less

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.

Particle-Size-Exclusion Clogging Regimes in Porous Media

NASA Astrophysics Data System (ADS)

Gerber, G.; Rodts, S.; Aimedieu, P.; Faure, P.; Coussot, P.

2018-04-01

From observations of the progressive deposition of noncolloidal particles by geometrical exclusion effects inside a 3D model porous medium, we get a complete dynamic view of particle deposits over a full range of regimes from transport over a long distance to clogging and caking. We show that clogging essentially occurs in the form of an accumulation of elements in pore size clusters, which ultimately constitute regions avoided by the flow. The clusters are dispersed in the medium, and their concentration (number per volume) decreases with the distance from the entrance; caking is associated with the final stage of this effect (for a critical cluster concentration at the entrance). A simple probabilistic model, taking into account the impact of clogging on particle transport, allows us to quantitatively predict all these trends up to a large cluster concentration, based on a single parameter: the clogging probability, which is a function of the confinement ratio. This opens the route towards a unification of the different fields of particle transport, clogging, caking, and filtration.

A Multivariate Analysis of Galaxy Cluster Properties

NASA Astrophysics Data System (ADS)

Ogle, P. M.; Djorgovski, S.

1993-05-01

We have assembled from the literature a data base on on 394 clusters of galaxies, with up to 16 parameters per cluster. They include optical and x-ray luminosities, x-ray temperatures, galaxy velocity dispersions, central galaxy and particle densities, optical and x-ray core radii and ellipticities, etc. In addition, derived quantities, such as the mass-to-light ratios and x-ray gas masses are included. Doubtful measurements have been identified, and deleted from the data base. Our goal is to explore the correlations between these parameters, and interpret them in the framework of our understanding of evolution of clusters and large-scale structure, such as the Gott-Rees scaling hierarchy. Among the simple, monovariate correlations we found, the most significant include those between the optical and x-ray luminosities, x-ray temperatures, cluster velocity dispersions, and central galaxy densities, in various mutual combinations. While some of these correlations have been discussed previously in the literature, generally smaller samples of objects have been used. We will also present the results of a multivariate statistical analysis of the data, including a principal component analysis (PCA). Such an approach has not been used previously for studies of cluster properties, even though it is much more powerful and complete than the simple monovariate techniques which are commonly employed. The observed correlations may lead to powerful constraints for theoretical models of formation and evolution of galaxy clusters. P.M.O. was supported by a Caltech graduate fellowship. S.D. acknowledges a partial support from the NASA contract NAS5-31348 and the NSF PYI award AST-9157412.

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.

Density-functional theory study of ionic inhomogeneity in metal clusters using SC-ISJM

NASA Astrophysics Data System (ADS)

Payami, Mahmoud; Mahmoodi, Tahereh

2017-12-01

In this work we have applied the recently formulated self-compressed inhomogeneous stabilized jellium model [51] to describe the equilibrium electronic and geometric properties of atomic-closed-shell simple metal clusters of AlN (N = 13, 19, 43, 55, 79, 87, 135, 141), NaN, and CsN (N = 9, 15, 27, 51, 59, 65, 89, 113). To validate the results, we have also performed first-principles pseudo-potential calculations and used them as our reference. In the model, we have considered two regions consisting of ;surface; and ;inner; ones, the border separating them being sharp. This generalization makes possible to decouple the relaxations of different parts of the system. The results show that the present model correctly predicts the size reductions seen in most of the clusters. It also predicts increase in size of some clusters, as observed from first-principles results. Moreover, the changes in inter-layer distances, being as contractions or expansions, are in good agreement with the atomic simulation results. For a more realistic description of the properties, it is possible to improve the method of choosing the surface thicknesses or generalize the model to include more regions than just two.

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.

Self-organization of cosmic radiation pressure instability. II - One-dimensional simulations

NASA Technical Reports Server (NTRS)

Hogan, Craig J.; Woods, Jorden

1992-01-01

The clustering of statistically uniform discrete absorbing particles moving solely under the influence of radiation pressure from uniformly distributed emitters is studied in a simple one-dimensional model. Radiation pressure tends to amplify statistical clustering in the absorbers; the absorbing material is swept into empty bubbles, the biggest bubbles grow bigger almost as they would in a uniform medium, and the smaller ones get crushed and disappear. Numerical simulations of a one-dimensional system are used to support the conjecture that the system is self-organizing. Simple statistics indicate that a wide range of initial conditions produce structure approaching the same self-similar statistical distribution, whose scaling properties follow those of the attractor solution for an isolated bubble. The importance of the process for large-scale structuring of the interstellar medium is briefly discussed.

The cosmological analysis of X-ray cluster surveys. III. 4D X-ray observable diagrams

NASA Astrophysics Data System (ADS)

Pierre, M.; Valotti, A.; Faccioli, L.; Clerc, N.; Gastaud, R.; Koulouridis, E.; Pacaud, F.

2017-11-01

Context. Despite compelling theoretical arguments, the use of clusters as cosmological probes is, in practice, frequently questioned because of the many uncertainties surrounding cluster-mass estimates. Aims: Our aim is to develop a fully self-consistent cosmological approach of X-ray cluster surveys, exclusively based on observable quantities rather than masses. This procedure is justified given the possibility to directly derive the cluster properties via ab initio modelling, either analytically or by using hydrodynamical simulations. In this third paper, we evaluate the method on cluster toy-catalogues. Methods: We model the population of detected clusters in the count-rate - hardness-ratio - angular size - redshift space and compare the corresponding four-dimensional diagram with theoretical predictions. The best cosmology+physics parameter configuration is determined using a simple minimisation procedure; errors on the parameters are estimated by averaging the results from ten independent survey realisations. The method allows a simultaneous fit of the cosmological parameters of the cluster evolutionary physics and of the selection effects. Results: When using information from the X-ray survey alone plus redshifts, this approach is shown to be as accurate as the modelling of the mass function for the cosmological parameters and to perform better for the cluster physics, for a similar level of assumptions on the scaling relations. It enables the identification of degenerate combinations of parameter values. Conclusions: Given the considerably shorter computer times involved for running the minimisation procedure in the observed parameter space, this method appears to clearly outperform traditional mass-based approaches when X-ray survey data alone are available.

LOCUSS: THE MID-INFRARED BUTCHER-OEMLER EFFECT

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

Haines, C. P.; Smith, G. P.; Sanderson, A. J. R.

2009-10-10

We study the mid-infrared (MIR) properties of galaxies in 30 massive galaxy clusters at 0.02 <= z <= 0.40, using panoramic Spitzer/MIPS 24 mum and near-infrared data, including 27 new observations from the LoCuSS and ACCESS surveys. This is the largest sample of clusters to date with such high-quality and uniform MIR data covering not only the cluster cores, but extending into the infall regions. We use these data to revisit the so-called Butcher-Oemler (BO) effect, measuring the fraction of massive infrared luminous galaxies (K < K* + 1.5, L {sub IR} > 5 x 10{sup 10} L {sub sun})more » within r {sub 200}, finding a steady increase in the fraction with redshift from approx3% at z = 0.02 to approx10% by z = 0.30, and an rms cluster-to-cluster scatter about this trend of 0.03. The best-fit redshift evolution model of the form f {sub SF} propor to (1 + z) {sup n} has n = 5.7{sup +2.1} {sub -1.8}, which is stronger redshift evolution than that of L*{sub IR} in both clusters and the field. We find that, statistically, this excess is associated with galaxies found at large cluster-centric radii, specifically r {sub 500} < r < r {sub 200}, implying that the MIR BO effect can be explained by a combination of both the global decline in star formation in the universe since z approx 1 and enhanced star formation in the infall regions of clusters at intermediate redshifts. This picture is supported by a simple infall model based on the Millennium Simulation semianalytic galaxy catalogs, whereby star formation in infalling galaxies is instantaneously quenched upon their first passage through the cluster, in that the observed radial trends of f {sub SF} trace those inferred from the simulations. The observed f {sub SF} values, however, lie systematically above the predictions, suggesting an overall excess of star formation, either due to triggering by environmental processes, or a gradual quenching. We also find that f {sub SF} does not depend on simple indicators of the dynamical state of clusters, including the offset between the brightest cluster galaxy and the peak of the X-ray emission. This is consistent with the picture described above in that most new star formation in clusters occurs in the infall regions, and is thus not sensitive to the details of cluster-cluster mergers in the core regions.« less

The use of cluster analysis techniques in spaceflight project cost risk estimation

NASA Technical Reports Server (NTRS)

Fox, G.; Ebbeler, D.; Jorgensen, E.

2003-01-01

Project cost risk is the uncertainty in final project cost, contingent on initial budget, requirements and schedule. For a proposed mission, a dynamic simulation model relying for some of its input on a simple risk elicitation is used to identify and quantify systemic cost risk.

Optimal control of the strong-field ionization of silver clusters in helium droplets

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

Truong, N. X.; Goede, S.; Przystawik, A.

Optimal control techniques combined with femtosecond laser pulse shaping are applied to steer and enhance the strong-field induced emission of highly charged atomic ions from silver clusters embedded in helium nanodroplets. With light fields shaped in amplitude and phase we observe a substantial increase of the Ag{sup q+} yield for q>10 when compared to bandwidth-limited and optimally stretched pulses. A remarkably simple double-pulse structure, containing a low-intensity prepulse and a stronger main pulse, turns out to produce the highest atomic charge states up to Ag{sup 20+}. A negative chirp during the main pulse hints at dynamic frequency locking to themore » cluster plasmon. A numerical optimal control study on pure silver clusters with a nanoplasma model converges to a similar pulse structure and corroborates that the optimal light field adapts to the resonant excitation of cluster surface plasmons for efficient ionization.« less

Search For Cosmic-Ray-Induced Gamma-Ray Emission In Galaxy Clusters

DOE PAGES

Ackermann, M.

2014-04-30

Current theories predict relativistic hadronic particle populations in clusters of galaxies in addition to the already observed relativistic leptons. In these scenarios hadronic interactions give rise to neutral pions which decay into rays that are potentially observable with the Large Area Telescope (LAT) on board the Fermi space telescope. We present a joint likelihood analysis searching for spatially extended γ-ray emission at the locations of 50 galaxy clusters in 4 years of Fermi-LAT data under the assumption of the universal cosmic-ray model proposed by Pinzke & Pfrommer (2010). We find an excess at a significance of 2.7 σ which uponmore » closer inspection is however correlated to individual excess emission towards three galaxy clusters: Abell 400, Abell 1367 and Abell 3112. We discuss these cases in detail and conservatively attribute the emission to unmodeled background (for example, radio galaxies within the clusters). Through the combined analysis of 50 clusters we exclude hadronic injection efficiencies in simple hadronic models above 21% and establish limits on the cosmic-ray to thermal pressure ratio within the virial radius, R200, to be below 1.2-1.4% depending on the morphological classification. In addition we derive new limits on the γ-ray flux from individual clusters in our sample.« less

Search for Cosmic-Ray-Induced Gamma-Ray Emission in Galaxy Clusters

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Albert, A.; Allafort, A.; Atwood, W. B.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bechtol, K.;

A simple physical model for deep moonquake occurrence times

USGS Publications Warehouse

Weber, R.C.; Bills, B.G.; Johnson, C.L.

2010-01-01

The physical process that results in moonquakes is not yet fully understood. The periodic occurrence times of events from individual clusters are clearly related to tidal stress, but also exhibit departures from the temporal regularity this relationship would seem to imply. Even simplified models that capture some of the relevant physics require a large number of variables. However, a single, easily accessible variable - the time interval I(n) between events - can be used to reveal behavior not readily observed using typical periodicity analyses (e.g., Fourier analyses). The delay-coordinate (DC) map, a particularly revealing way to display data from a time series, is a map of successive intervals: I(n+. 1) plotted vs. I(n). We use a DC approach to characterize the dynamics of moonquake occurrence. Moonquake-like DC maps can be reproduced by combining sequences of synthetic events that occur with variable probability at tidal periods. Though this model gives a good description of what happens, it has little physical content, thus providing only little insight into why moonquakes occur. We investigate a more mechanistic model. In this study, we present a series of simple models of deep moonquake occurrence, with consideration of both tidal stress and stress drop during events. We first examine the behavior of inter-event times in a delay-coordinate context, and then examine the output, in that context, of a sequence of simple models of tidal forcing and stress relief. We find, as might be expected, that the stress relieved by moonquakes influences their occurrence times. Our models may also provide an explanation for the opposite-polarity events observed at some clusters. ?? 2010.

Equilibrium Phase Behavior of a Continuous-Space Microphase Former.

PubMed

Zhuang, Yuan; Zhang, Kai; Charbonneau, Patrick

2016-03-04

Periodic microphases universally emerge in systems for which short-range interparticle attraction is frustrated by long-range repulsion. The morphological richness of these phases makes them desirable material targets, but our relatively coarse understanding of even simple models hinders controlling their assembly. We report here the solution of the equilibrium phase behavior of a microscopic microphase former through specialized Monte Carlo simulations. The results for cluster crystal, cylindrical, double gyroid, and lamellar ordering qualitatively agree with a Landau-type free energy description and reveal the nontrivial interplay between cluster, gel, and microphase formation.

Review of methods for handling confounding by cluster and informative cluster size in clustered data

PubMed Central

Seaman, Shaun; Pavlou, Menelaos; Copas, Andrew

2014-01-01

Clustered data are common in medical research. Typically, one is interested in a regression model for the association between an outcome and covariates. Two complications that can arise when analysing clustered data are informative cluster size (ICS) and confounding by cluster (CBC). ICS and CBC mean that the outcome of a member given its covariates is associated with, respectively, the number of members in the cluster and the covariate values of other members in the cluster. Standard generalised linear mixed models for cluster-specific inference and standard generalised estimating equations for population-average inference assume, in general, the absence of ICS and CBC. Modifications of these approaches have been proposed to account for CBC or ICS. This article is a review of these methods. We express their assumptions in a common format, thus providing greater clarity about the assumptions that methods proposed for handling CBC make about ICS and vice versa, and about when different methods can be used in practice. We report relative efficiencies of methods where available, describe how methods are related, identify a previously unreported equivalence between two key methods, and propose some simple additional methods. Unnecessarily using a method that allows for ICS/CBC has an efficiency cost when ICS and CBC are absent. We review tools for identifying ICS/CBC. A strategy for analysis when CBC and ICS are suspected is demonstrated by examining the association between socio-economic deprivation and preterm neonatal death in Scotland. PMID:25087978

MASSCLEANage—Stellar Cluster Ages from Integrated Colors

NASA Astrophysics Data System (ADS)

Popescu, Bogdan; Hanson, M. M.

2010-11-01

We present the recently updated and expanded MASSCLEANcolors, a database of 70 million Monte Carlo models selected to match the properties (metallicity, ages, and masses) of stellar clusters found in the Large Magellanic Cloud (LMC). This database shows the rather extreme and non-Gaussian distribution of integrated colors and magnitudes expected with different cluster age and mass and the enormous age degeneracy of integrated colors when mass is unknown. This degeneracy could lead to catastrophic failures in estimating age with standard simple stellar population models, particularly if most of the clusters are of intermediate or low mass, like in the LMC. Utilizing the MASSCLEANcolors database, we have developed MASSCLEANage, a statistical inference package which assigns the most likely age and mass (solved simultaneously) to a cluster based only on its integrated broadband photometric properties. Finally, we use MASSCLEANage to derive the age and mass of LMC clusters based on integrated photometry alone. First, we compare our cluster ages against those obtained for the same seven clusters using more accurate integrated spectroscopy. We find improved agreement with the integrated spectroscopy ages over the original photometric ages. A close examination of our results demonstrates the necessity of solving simultaneously for mass and age to reduce degeneracies in the cluster ages derived via integrated colors. We then selected an additional subset of 30 photometric clusters with previously well-constrained ages and independently derive their age using the MASSCLEANage with the same photometry with very good agreement. The MASSCLEANage program is freely available under GNU General Public License.

On the missing second generation AGB stars in NGC 6752

NASA Astrophysics Data System (ADS)

Cassisi, Santi; Salaris, Maurizio; Pietrinferni, Adriano; Vink, Jorick S.; Monelli, Matteo

2014-11-01

In recent years the view of Galactic globular clusters as simple stellar populations has changed dramatically, it is now thought that basically all globular clusters host multiple stellar populations, each with its own chemical abundance pattern and colour-magnitude diagram sequence. Recent spectroscopic observations of asymptotic giant branch stars in the globular cluster NGC 6752 have disclosed a low [Na/Fe] abundance for the whole sample, suggesting that they are all first generation stars, and that all second generation stars fail to reach the AGB in this cluster. A scenario proposed to explain these observations invokes strong mass loss in second generation horizontal branch stars - all located at the hot side of the blue and extended horizontal branch of this cluster - possibly induced by the metal enhancement associated to radiative levitation. This enhanced mass loss would prevent second generation stars from reaching the asymptotic giant branch phase, thus explaining at the same time the low value of the ratio between horizontal branch and asymptotic giant branch stars (the R2 parameter) observed in NGC 6752. We have critically discussed this mass-loss scenario, finding that the required mass-loss rates are of the order of 10-9 M⊙ yr-1, significantly higher than current theoretical and empirical constraints. By making use of synthetic horizontal branch simulations, we demonstrate that our modelling correctly predicts the R2 parameter for NGC 6752, without the need to invoke very efficient mass loss during the core He-burning stage. As a test of our stellar models we show that we can reproduce the observed value of R2 for both M 3, a cluster of approximately the same metallicity and with a redder horizontal branch morphology, and M 13, a cluster with a horizontal branch very similar to NGC 6752. However, our simulations for the NGC 6752 horizontal branch predict however the presence of a significant fraction of second generation stars (about 50%) along the cluster asymptotic giant branch. We conclude that there is no simple explanation for the lack of second generation stars in the spectroscopically surveyed sample, although the interplay between mass loss (with low rates) and radiative levitation may play a role in explaining this puzzle.

A screened independent atom model for the description of ion collisions from atomic and molecular clusters

NASA Astrophysics Data System (ADS)

Lüdde, Hans Jürgen; Horbatsch, Marko; Kirchner, Tom

2018-05-01

We apply a recently introduced model for an independent-atom-like calculation of ion-impact electron transfer and ionization cross sections to proton collisions from water, neon, and carbon clusters. The model is based on a geometrical interpretation of the cluster cross section as an effective area composed of overlapping circular disks that are representative of the atomic contributions. The latter are calculated using a time-dependent density-functional-theory-based single-particle description with accurate exchange-only ground-state potentials. We find that the net capture and ionization cross sections in p-X n collisions are proportional to n α with 2/3 ≤ α ≤ 1. For capture from water clusters at 100 keV impact energy α is close to one, which is substantially different from the value α = 2/3 predicted by a previous theoretical work based on the simplest-level electron nuclear dynamics method. For ionization at 100 keV and for capture at lower energies we find smaller α values than for capture at 100 keV. This can be understood by considering the magnitude of the atomic cross sections and the resulting overlaps of the circular disks that make up the cluster cross section in our model. Results for neon and carbon clusters confirm these trends. Simple parametrizations are found which fit the cross sections remarkably well and suggest that they depend on the relevant bond lengths.

Investigation on the correlation between energy deposition and clustered DNA damage induced by low-energy electrons.

PubMed

Liu, Wei; Tan, Zhenyu; Zhang, Liming; Champion, Christophe

2018-05-01

This study presents the correlation between energy deposition and clustered DNA damage, based on a Monte Carlo simulation of the spectrum of direct DNA damage induced by low-energy electrons including the dissociative electron attachment. Clustered DNA damage is classified as simple and complex in terms of the combination of single-strand breaks (SSBs) or double-strand breaks (DSBs) and adjacent base damage (BD). The results show that the energy depositions associated with about 90% of total clustered DNA damage are below 150 eV. The simple clustered DNA damage, which is constituted of the combination of SSBs and adjacent BD, is dominant, accounting for 90% of all clustered DNA damage, and the spectra of the energy depositions correlating with them are similar for different primary energies. One type of simple clustered DNA damage is the combination of a SSB and 1-5 BD, which is denoted as SSB + BD. The average contribution of SSB + BD to total simple clustered DNA damage reaches up to about 84% for the considered primary energies. In all forms of SSB + BD, the SSB + BD including only one base damage is dominant (above 80%). In addition, for the considered primary energies, there is no obvious difference between the average energy depositions for a fixed complexity of SSB + BD determined by the number of base damage, but average energy depositions increase with the complexity of SSB + BD. In the complex clustered DNA damage constituted by the combination of DSBs and BD around them, a relatively simple type is a DSB combining adjacent BD, marked as DSB + BD, and it is of substantial contribution (on average up to about 82%). The spectrum of DSB + BD is given mainly by the DSB in combination with different numbers of base damage, from 1 to 5. For the considered primary energies, the DSB combined with only one base damage contributes about 83% of total DSB + BD, and the average energy deposition is about 106 eV. However, the energy deposition increases with the complexity of clustered DNA damage, and therefore, the clustered DNA damage with high complexity still needs to be considered in the study of radiation biological effects, in spite of their small contributions to all clustered DNA damage.

Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

PubMed

Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

2012-07-01

Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

Composition formulas of Fe-based transition metals-metalloid bulk metallic glasses derived from dual-cluster model of binary eutectics.

PubMed

Naz, Gul Jabeen; Dong, Dandan; Geng, Yaoxiang; Wang, Yingmin; Dong, Chuang

2017-08-22

It is known that bulk metallic glasses follow simple composition formulas [cluster](glue atom) 1 or 3 with 24 valence electrons within the framework of the cluster-plus-glue-atom model. Though the relevant nearest-neighbor cluster can be readily identified from a devitrification phase, the glue atoms remains poorly defined. The present work is devoted to understanding the composition rule of Fe-(B,P,C) based multi-component bulk metallic glasses, by introducing a cluster-based eutectic liquid model. This model regards a eutectic liquid to be composed of two stable liquids formulated respectively by cluster formulas for ideal metallic glasses from the two eutectic phases. The dual cluster formulas are first established for binary Fe-(B,C,P) eutectics: [Fe-Fe 14 ]B 2 Fe + [B-B 2 Fe 8 ]Fe ≈ Fe 83.3 B 16.7 for eutectic Fe 83 B 17 , [P-Fe 14 ]P + [P-Fe 9 ]P 2 Fe≈Fe 82.8 P 17.2 for Fe 83 P 17 , and [C-Fe 6 ]Fe 3  + [C-Fe 9 ]C 2 Fe ≈ Fe 82.6 C 17.4 for Fe 82.7 C 17.3 . The second formulas in these dual-cluster formulas, being respectively relevant to devitrification phases Fe 2 B, Fe 3 P, and Fe 3 C, well explain the compositions of existing Fe-based transition metals-metalloid bulk metallic glasses. These formulas also satisfy the 24-electron rule. The proposition of the composition formulas for good glass formers, directly from known eutectic points, constitutes a new route towards understanding and eventual designing metallic glasses of high glass forming abilities.

Core-halo age gradients and star formation in the Orion Nebula and NGS 2024 young stellar clusters

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

Getman, Konstantin V.; Feigelson, Eric D.; Kuhn, Michael A.

2014-06-01

We analyze age distributions of two nearby rich stellar clusters, the NGC 2024 (Flame Nebula) and Orion Nebula cluster (ONC) in the Orion molecular cloud complex. Our analysis is based on samples from the MYStIX survey and a new estimator of pre-main sequence (PMS) stellar ages, Age{sub JX} , derived from X-ray and near-infrared photometric data. To overcome the problem of uncertain individual ages and large spreads of age distributions for entire clusters, we compute median ages and their confidence intervals of stellar samples within annular subregions of the clusters. We find core-halo age gradients in both the NGC 2024more » cluster and ONC: PMS stars in cluster cores appear younger and thus were formed later than PMS stars in cluster peripheries. These findings are further supported by the spatial gradients in the disk fraction and K-band excess frequency. Our age analysis is based on Age{sub JX} estimates for PMS stars and is independent of any consideration of OB stars. The result has important implications for the formation of young stellar clusters. One basic implication is that clusters form slowly and the apparent age spreads in young stellar clusters, which are often controversial, are (at least in part) real. The result further implies that simple models where clusters form inside-out are incorrect and more complex models are needed. We provide several star formation scenarios that alone or in combination may lead to the observed core-halo age gradients.« less

Gas expulsion in highly substructured embedded star clusters

NASA Astrophysics Data System (ADS)

Farias, J. P.; Fellhauer, M.; Smith, R.; Domínguez, R.; Dabringhausen, J.

2018-06-01

We investigate the response of initially substructured, young, embedded star clusters to instantaneous gas expulsion of their natal gas. We introduce primordial substructure to the stars and the gas by simplistically modelling the star formation process so as to obtain a variety of substructure distributed within our modelled star-forming regions. We show that, by measuring the virial ratio of the stars alone (disregarding the gas completely), we can estimate how much mass a star cluster will retain after gas expulsion to within 10 per cent accuracy, no matter how complex the background structure of the gas is, and we present a simple analytical recipe describing this behaviour. We show that the evolution of the star cluster while still embedded in the natal gas, and the behaviour of the gas before being expelled, is crucial process that affect the time-scale on which the cluster can evolve into a virialized spherical system. Embedded star clusters that have high levels of substructure are subvirial for longer times, enabling them to survive gas expulsion better than a virialized and spherical system. By using a more realistic treatment for the background gas than our previous studies, we find it very difficult to destroy the young clusters with instantaneous gas expulsion. We conclude that gas removal may not be the main culprit for the dissolution of young star clusters.

Quenching of satellite galaxies at the outskirts of galaxy clusters

NASA Astrophysics Data System (ADS)

Zinger, Elad; Dekel, Avishai; Kravtsov, Andrey V.; Nagai, Daisuke

2018-04-01

We find, using cosmological simulations of galaxy clusters, that the hot X-ray emitting intracluster medium (ICM) enclosed within the outer accretion shock extends out to Rshock ˜ (2-3)Rvir, where Rvir is the standard virial radius of the halo. Using a simple analytic model for satellite galaxies in the cluster, we evaluate the effect of ram-pressure stripping on the gas in the inner discs and in the haloes at different distances from the cluster centre. We find that significant removal of star-forming disc gas occurs only at r ≲ 0.5Rvir, while gas removal from the satellite halo is more effective and can occur when the satellite is found between Rvir and Rshock. Removal of halo gas sets the stage for quenching of the star formation by starvation over 2-3 Gyr, prior to the satellite entry to the inner cluster halo. This scenario explains the presence of quenched galaxies, preferentially discs, at the outskirts of galaxy clusters, and the delayed quenching of satellites compared to central galaxies.

LCGTO-Xα model cluster study for the chemisorption of CO on twofold sites of Ni surfaces

NASA Astrophysics Data System (ADS)

Jörg, H.; Rösch, N.

The cluster Ni 2CO is studied as a simplified model for the chemisorption of CO on twofold bridging sites of transition metal surfaces. Using the LCGTO-Xα method we have calculated the potential energy surface for the totally symmetric stretching motion keeping the Ni-Ni distance fixed at the bulk value. The minimum energy is found at a Ni-C distance of 1.72 Å and a C-O bond length of 1.19 Å. The vibrational frequency for the CO bond (1850 cm -1) shows reasonable agreement with EELS data (1810, 1870 cm -1), whereas the (Ni 2)-C frequency of 495 cm -1 is remarkably higher than the experimental values (380, 400 cm -1) indicating an overestimation of the chemisorption bond strength in this simple cluster model. The bonding between CO and Ni is analyzed using orbital correlations, ionization energies and Mulliken population analysis. Important bonding contributions from π backdonation are identified while the a 1 orbital manifold exhibits strong antibonding effects.

LCGTO-Xα model cluster study for the chemisorption of CO on twofold sites of Ni surfaces

NASA Astrophysics Data System (ADS)

Jörg, H.; Rösch, N.

1985-11-01

The cluster Ni 2CO is studied as a simplified model for the chemisorption of CO on twofold bridging sites of transition metal surfaces. Using the LCGTO-Xα method we have calculated the potential energy surface for the totally symmetric stretching motion keeping the NiNi distance fixed at the bulk value. The minimum energy is found at a NiC distance of 1.72 Å and a CO bond length of 1.19 Å. The vibrational frequency for the CO bond (1850 cm -1) shows reasonable agreement with EELS data (1810, 1870 cm -1), whereas the (Ni 2)C frequency of 495 cm -1 is remarkably higher than the experimental values (380, 400 cm -1) indicating an overestimation of the chemisorption bond strength in this simple cluster model. The bonding between CO and Ni is analyzed using orbital correlations, ionization energies and Mulliken population analysis. Important bonding contributions from π backdonation are identified while the a 1orbital manifold exhibits strong antibonding effects.

Uniform Contribution of Supernova Explosions to the Chemical Enrichment of Abell 3112 out to R{sub 200}

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

Ezer, Cemile; Ercan, E. Nihal; Bulbul, Esra

2017-02-10

The spatial distribution of the metals residing in the intra-cluster medium (ICM) of galaxy clusters records all the information on a cluster’s nucleosynthesis and chemical enrichment history. We present measurements from a total of 1.2 Ms Suzaku XIS and 72 ks Chandra observations of the cool-core galaxy cluster Abell 3112 out to its virial radius (∼1470 kpc). We find that the ratio of the observed supernova type Ia explosions to the total supernova explosions has a uniform distribution at a level of 12%–16% out to the cluster’s virial radius. The observed fraction of type Ia supernova explosions is in agreementmore » with the corresponding fraction found in our Galaxy and the chemical enrichment of our Galaxy. The non-varying supernova enrichment suggests that the ICM in cluster outskirts was enriched by metals at an early stage before the cluster itself was formed during a period of intense star formation activity. Additionally, we find that the 2D delayed detonation model CDDT produce significantly worse fits to the X-ray spectra compared to simple 1D W7 models. This is due to the relative overestimate of Si, and the underestimate of Mg in these models with respect to the measured abundances.« less

Image texture segmentation using a neural network

NASA Astrophysics Data System (ADS)

Sayeh, Mohammed R.; Athinarayanan, Ragu; Dhali, Pushpuak

1992-09-01

In this paper we use a neural network called the Lyapunov associative memory (LYAM) system to segment image texture into different categories or clusters. The LYAM system is constructed by a set of ordinary differential equations which are simulated on a digital computer. The clustering can be achieved by using a single tuning parameter in the simplest model. Pattern classes are represented by the stable equilibrium states of the system. Design of the system is based on synthesizing two local energy functions, namely, the learning and recall energy functions. Before the implementation of the segmentation process, a Gauss-Markov random field (GMRF) model is applied to the raw image. This application suitably reduces the image data and prepares the texture information for the neural network process. We give a simple image example illustrating the capability of the technique. The GMRF-generated features are also used for a clustering, based on the Euclidean distance.

Phylogenetic relationships of chrysanthemums in Korea based on novel SSR markers.

PubMed

Khaing, A A; Moe, K T; Hong, W J; Park, C S; Yeon, K H; Park, H S; Kim, D C; Choi, B J; Jung, J Y; Chae, S C; Lee, K M; Park, Y J

2013-11-07

Chrysanthemums are well known for their esthetic and medicinal values. Characterization of chrysanthemums is vital for their conservation and management as well as for understanding their genetic relationships. We found 12 simple sequence repeat markers (SSRs) of 100 designed primers to be polymorphic. These novel SSR markers were used to evaluate 95 accessions of chrysanthemums (3 indigenous and 92 cultivated accessions). Two hundred alleles were identified, with an average of 16.7 alleles per locus. KNUCRY-77 gave the highest polymorphic information content value (0.879), while KNUCRY-10 gave the lowest (0.218). Similar patterns of grouping were observed with a distance-based dendrogram developed using PowerMarker and model-based clustering with Structure. Three clusters with some admixtures were identified by model-based clustering. These newly developed SSR markers will be useful for further studies of chrysanthemums, such as taxonomy and marker-assisted selection breeding.

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

PubMed

Riniker, Sereina; van Gunsteren, Wilfred F

2011-02-28

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

Spatial cluster detection using dynamic programming.

PubMed

Sverchkov, Yuriy; Jiang, Xia; Cooper, Gregory F

2012-03-25

The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm.

Spatial cluster detection using dynamic programming

PubMed Central

2012-01-01

Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP) estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic programming algorithm performs on-par with other available methods for spatial cluster detection and point to its low computational cost and extendability as advantages in favor of further research and use of the algorithm. PMID:22443103

Automatic Verification of Serializers.

DTIC Science & Technology

1980-03-01

31 2.5 Using semaphores to implement sei ;alizers ......................... 32 2.6 A comparison of...of concurrency control, while Hewitt has concentrated on more primitive control of concurrency in a context where programs communicate by passing...translation oflserializers into clusters and semaphores is given as a possible implementation strategy. Chapter 3 presents a simple semantic model that supl

Developing a "Productive" Account of Young People's Transition Perspectives

ERIC Educational Resources Information Center

Vaughan, Karen; Roberts, Josie

2007-01-01

This article draws on the first two years of a longitudinal study of young people's pathway and career-related experiences and perspectives. It argues for a richer conceptualisation of young people's transition to study, training and employment than what simple school-to-labour market models allow. We present four clusters of young people's…

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.

Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings.

PubMed

Eyler, Lauren; Hubbard, Alan; Juillard, Catherine

2016-10-01

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

Wiggler magnetic field assisted third harmonic generation in expanding clusters

NASA Astrophysics Data System (ADS)

Vij, Shivani

2018-04-01

A simple theoretical model is constructed to study the wiggler magnetic field assisted third harmonic generation of intense short pulse laser in a cluster in its expanding phase. The ponderomotive force of laser causes density perturbations in cluster electron density which couples with wiggler magnetic field to produce a nonlinear current that generates transverse third harmonic. An intense short pulse laser propagating through a gas embedded with atomic clusters, converts it into hot plasma balls via tunnel ionization. Initially, the electron plasma frequency inside the clusters ω pe > \\sqrt{3}{ω }1 (with ω 1 being the frequency of the laser). As the cluster expands under Coulomb force and hydrodynamic pressure, ω pe decreases to \\sqrt{3}{ω }1. At this time, there is resonant enhancement in the efficiency of the third harmonic generation. The efficiency of third harmonic generation is enhanced due to cluster plasmon resonance and by phase matching due to wiggler magnetic field. The effect of cluster size on the expansion rate is studied to observe that the clusters of different radii would expand differently. The impact of laser intensity and wiggler magnetic field on the efficiency of third harmonic generation is also explored.

Baryon acoustic oscillations in 2D. II. Redshift-space halo clustering in N-body simulations

NASA Astrophysics Data System (ADS)

Nishimichi, Takahiro; Taruya, Atsushi

2011-08-01

We measure the halo power spectrum in redshift space from cosmological N-body simulations, and test the analytical models of redshift distortions particularly focusing on the scales of baryon acoustic oscillations. Remarkably, the measured halo power spectrum in redshift space exhibits a large-scale enhancement in amplitude relative to the real-space clustering, and the effect becomes significant for the massive or highly biased halo samples. These findings cannot be simply explained by the so-called streaming model frequently used in the literature. By contrast, a physically motivated perturbation theory model developed in the previous paper reproduces the halo power spectrum very well, and the model combining a simple linear scale-dependent bias can accurately characterize the clustering anisotropies of halos in two dimensions, i.e., line-of-sight and its perpendicular directions. The results highlight the significance of nonlinear coupling between density and velocity fields associated with two competing effects of redshift distortions, i.e., Kaiser and Finger-of-God effects, and a proper account of this effect would be important in accurately characterizing the baryon acoustic oscillations in two dimensions.

Discrete bivariate population balance modelling of heteroaggregation processes.

PubMed

Rollié, Sascha; Briesen, Heiko; Sundmacher, Kai

2009-08-15

Heteroaggregation in binary particle mixtures was simulated with a discrete population balance model in terms of two internal coordinates describing the particle properties. The considered particle species are of different size and zeta-potential. Property space is reduced with a semi-heuristic approach to enable an efficient solution. Aggregation rates are based on deterministic models for Brownian motion and stability, under consideration of DLVO interaction potentials. A charge-balance kernel is presented, relating the electrostatic surface potential to the property space by a simple charge balance. Parameter sensitivity with respect to the fractal dimension, aggregate size, hydrodynamic correction, ionic strength and absolute particle concentration was assessed. Results were compared to simulations with the literature kernel based on geometric coverage effects for clusters with heterogeneous surface properties. In both cases electrostatic phenomena, which dominate the aggregation process, show identical trends: impeded cluster-cluster aggregation at low particle mixing ratio (1:1), restabilisation at high mixing ratios (100:1) and formation of complex clusters for intermediate ratios (10:1). The particle mixing ratio controls the surface coverage extent of the larger particle species. Simulation results are compared to experimental flow cytometric data and show very satisfactory agreement.

Reentrant and Isostructural Transitions in the Cluster-Crystal Forming GEM-4

NASA Astrophysics Data System (ADS)

Zhang, Kai; Charbonneau, Patrick; Mladek, Bianca

2011-03-01

Systems governed by soft, bounded, purely repulsive interactions show two possible equilibrium behaviors under compression: reentrant melting, as in the Gaussian core model (GCM), or clustering, as in the penetrable sphere model (PSM). The generalized exponential model of power 4 (GEM-4), which is the intermedia of the GCM and PSM with a simple isotropic pair interaction u (r) ~e-r4 , is thought to belong to the second family and was indeed found to form clusters at sufficiently high densities at high temperatures. Here, we present the low-temperature behavior of GEM-4 through Monte Carlo simulations using a specially developed free energy integration scheme. We find the phase behavior to be hybrid between the GCM and the PSM limits, showing a surprisingly rich phase behavior in spite of the simplicity of the interaction form. For instance, S- shaped doubly reentrant phase sequences and evidence of a cascade of critical isostructural transitions between crystals of different average lattice site occupancy are observed. The possible annihilation of lattice sites and accompanying clustering moreover leads to an unusual softening upon compression, which suggest that these materials may have interesting mechanical properties. We discuss possible experimental realizations and challenges of this class of materials.

The origin of and conditions for clustering in fluids with competing interactions

NASA Astrophysics Data System (ADS)

Jadrich, Ryan; Bollinger, Jonathan; Truskett, Thomas

2015-03-01

Fluids with competing short-range attractions and long-range repulsions exhibit a rich phase behavior characterized by intermediate range order (IRO), as quantified via the static structure factor. This phase behavior includes cluster formation depending upon density-controlled packing effects and the magnitude and range of the attractive and repulsive interactions. Such model systems mimic (to zeroth order) screened, charge-stabilized, aqueous colloidal dispersions of, e.g., proteins. We employ molecular dynamics simulations and integral equation theory to elucidate a more fundamental microscopic explanation for IRO-driven clustering. A simple criterion is identified that indicates when dynamic, amorphous clustering emerges in a polydisperse system, namely when the Ornstein-Zernike thermal correlation length in the system exceeds the repulsive potential tail range. Remarkably, this criterion also appears tightly correlated to crystalline cluster formation in a monodisperse system. Our new gauge is compared to another phenomenological condition for clustering which is when the IRO peak magnitude exceeds ~ 2.7. Ramifications of crystalline versus amorphous clustering are discussed and potential ways of using our new measure in experiment are put forward.

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

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.

SLURM: Simple Linux Utility for Resource Management

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

Jette, M; Grondona, M

2002-12-19

Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters of thousands of nodes. Components include machine status, partition management, job management, scheduling and stream copy modules. This paper presents an overview of the SLURM architecture and functionality.

Clustering approaches to feature change detection

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

MASSCLEANage-STELLAR CLUSTER AGES FROM INTEGRATED COLORS

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

Popescu, Bogdan; Hanson, M. M., E-mail: popescb@mail.uc.ed, E-mail: margaret.hanson@uc.ed

2010-11-20

We present the recently updated and expanded MASSCLEANcolors, a database of 70 million Monte Carlo models selected to match the properties (metallicity, ages, and masses) of stellar clusters found in the Large Magellanic Cloud (LMC). This database shows the rather extreme and non-Gaussian distribution of integrated colors and magnitudes expected with different cluster age and mass and the enormous age degeneracy of integrated colors when mass is unknown. This degeneracy could lead to catastrophic failures in estimating age with standard simple stellar population models, particularly if most of the clusters are of intermediate or low mass, like in the LMC.more » Utilizing the MASSCLEANcolors database, we have developed MASSCLEANage, a statistical inference package which assigns the most likely age and mass (solved simultaneously) to a cluster based only on its integrated broadband photometric properties. Finally, we use MASSCLEANage to derive the age and mass of LMC clusters based on integrated photometry alone. First, we compare our cluster ages against those obtained for the same seven clusters using more accurate integrated spectroscopy. We find improved agreement with the integrated spectroscopy ages over the original photometric ages. A close examination of our results demonstrates the necessity of solving simultaneously for mass and age to reduce degeneracies in the cluster ages derived via integrated colors. We then selected an additional subset of 30 photometric clusters with previously well-constrained ages and independently derive their age using the MASSCLEANage with the same photometry with very good agreement. The MASSCLEANage program is freely available under GNU General Public License.« less

Energetic Selection of Topology in Ferredoxins

PubMed Central

Kim, J. Dongun; Rodriguez-Granillo, Agustina; Case, David A.; Nanda, Vikas; Falkowski, Paul G.

2012-01-01

Models of early protein evolution posit the existence of short peptides that bound metals and ions and served as transporters, membranes or catalysts. The Cys-X-X-Cys-X-X-Cys heptapeptide located within bacterial ferredoxins, enclosing an Fe4S4 metal center, is an attractive candidate for such an early peptide. Ferredoxins are ancient proteins and the simple α+β fold is found alone or as a domain in larger proteins throughout all three kingdoms of life. Previous analyses of the heptapeptide conformation in experimentally determined ferredoxin structures revealed a pervasive right-handed topology, despite the fact that the Fe4S4 cluster is achiral. Conformational enumeration of a model CGGCGGC heptapeptide bound to a cubane iron-sulfur cluster indicates both left-handed and right-handed folds could exist and have comparable stabilities. However, only the natural ferredoxin topology provides a significant network of backbone-to-cluster hydrogen bonds that would stabilize the metal-peptide complex. The optimal peptide configuration (alternating αL,αR) is that of an α-sheet, providing an additional mechanism where oligomerization could stabilize the peptide and facilitate iron-sulfur cluster binding. PMID:22496635

Using clustering and a modified classification algorithm for automatic text summarization

NASA Astrophysics Data System (ADS)

Aries, Abdelkrime; Oufaida, Houda; Nouali, Omar

2013-01-01

In this paper we describe a modified classification method destined for extractive summarization purpose. The classification in this method doesn't need a learning corpus; it uses the input text to do that. First, we cluster the document sentences to exploit the diversity of topics, then we use a learning algorithm (here we used Naive Bayes) on each cluster considering it as a class. After obtaining the classification model, we calculate the score of a sentence in each class, using a scoring model derived from classification algorithm. These scores are used, then, to reorder the sentences and extract the first ones as the output summary. We conducted some experiments using a corpus of scientific papers, and we have compared our results to another summarization system called UNIS.1 Also, we experiment the impact of clustering threshold tuning, on the resulted summary, as well as the impact of adding more features to the classifier. We found that this method is interesting, and gives good performance, and the addition of new features (which is simple using this method) can improve summary's accuracy.

A model of jam formation in congested traffic

NASA Astrophysics Data System (ADS)

Bunzarova, N. Zh; Pesheva, N. C.; Priezzhev, V. B.; Brankov, J. G.

2017-12-01

We study a model of irreversible jam formation in congested vehicular traffic on an open segment of a single-lane road. The vehicles obey a stochastic discrete-time dynamics which is a limiting case of the generalized Totally Asymmetric Simple Exclusion Process. Its characteristic features are: (a) the existing clusters of jammed cars cannot break into parts; (b) when the leading vehicle of a cluster hops to the right, the whole cluster follows it deterministically, and (c) any two clusters of vehicles, occupying consecutive positions on the chain, may become nearest-neighbors and merge irreversibly into a single cluster. The above dynamics was used in a one-dimensional model of irreversible aggregation by Bunzarova and Pesheva [Phys. Rev. E 95, 052105 (2017)]. The model has three stationary non-equilibrium phases, depending on the probabilities of injection (α), ejection (β), and hopping (p) of particles: a many-particle one, MP, a completely jammed phase CF, and a mixed MP+CF phase. An exact expression for the stationary probability P(1) of a completely jammed configuration in the mixed MP+CF phase is obtained. The gap distribution between neighboring clusters of jammed cars at large lengths L of the road is studied. Three regimes of evolution of the width of a single gap are found: (i) growing gaps with length of the order O(L) when β > p; (ii) shrinking gaps with length of the order O(1) when β < p; and (iii) critical gaps at β = p, of the order O(L 1/2). These results are supported by extensive Monte Carlo calculations.

Continuum analyzing power for 4He(p-->,p') at 100 MeV

NASA Astrophysics Data System (ADS)

Lawrie, J. J.; Whittal, D. M.; Cowley, A. A.

1990-08-01

Distorted-wave impulse approximation calculations of the continuum analyzing power for the inclusive reaction 4He(p-->,p') at an incident energy of 100 MeV are presented. In addition to the quasifree knockout of nucleons, contributions from the knockout of deuteron, triton, and helion clusters are taken into account, together with a breakup component. Whereas nucleon knockout by itself does not account for the experimentally observed analyzing power, the inclusion of clusters has a large effect. Thus a simple knockout model is able to provide a reasonable description of the experimental continuum analyzing power.

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

Selection of intracellular calcium patterns in a model with clustered Ca2+ release channels

NASA Astrophysics Data System (ADS)

Shuai, J. W.; Jung, P.

2003-03-01

A two-dimensional model is proposed for intracellular Ca2+ waves, which incorporates both the discrete nature of Ca2+ release sites in the endoplasmic reticulum membrane and the stochastic dynamics of the clustered inositol 1,4,5-triphosphate (IP3) receptors. Depending on the Ca2+ diffusion coefficient and concentration of IP3, various spontaneous Ca2+ patterns, such as calcium puffs, local waves, abortive waves, global oscillation, and tide waves, can be observed. We further investigate the speed of the global waves as a function of the IP3 concentration and the Ca2+ diffusion coefficient and under what conditions the spatially averaged Ca2+ response can be described by a simple set of ordinary differential equations.

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.

A simple model to quantitatively account for periodic outbreaks of the measles in the Dutch Bible Belt

NASA Astrophysics Data System (ADS)

Bier, Martin; Brak, Bastiaan

2015-04-01

In the Netherlands there has been nationwide vaccination against the measles since 1976. However, in small clustered communities of orthodox Protestants there is widespread refusal of the vaccine. After 1976, three large outbreaks with about 3000 reported cases of the measles have occurred among these orthodox Protestants. The outbreaks appear to occur about every twelve years. We show how a simple Kermack-McKendrick-like model can quantitatively account for the periodic outbreaks. Approximate analytic formulae to connect the period, size, and outbreak duration are derived. With an enhanced model we take the latency period in account. We also expand the model to follow how different age groups are affected. Like other researchers using other methods, we conclude that large scale underreporting of the disease must occur.

A simple transferable adaptive potential to study phase separation in large-scale xMgO-(1-x)SiO2 binary glasses.

PubMed

Bidault, Xavier; Chaussedent, Stéphane; Blanc, Wilfried

2015-10-21

A simple transferable adaptive model is developed and it allows for the first time to simulate by molecular dynamics the separation of large phases in the MgO-SiO2 binary system, as experimentally observed and as predicted by the phase diagram, meaning that separated phases have various compositions. This is a real improvement over fixed-charge models, which are often limited to an interpretation involving the formation of pure clusters, or involving the modified random network model. Our adaptive model, efficient to reproduce known crystalline and glassy structures, allows us to track the formation of large amorphous Mg-rich Si-poor nanoparticles in an Mg-poor Si-rich matrix from a 0.1MgO-0.9SiO2 melt.

An X-ray and optical study of the cluster of galaxies Abell 754

NASA Technical Reports Server (NTRS)

Fabricant, D.; Beers, T. C.; Geller, M. J.; Gorenstein, P.; Huchra, J. P.

1986-01-01

X-ray and optical data for A754 are used to study the relative distribution of the luminous and dark matter in this dense, rich cluster of galaxies with X-ray luminosity comparable to that of the Coma Cluster. A quantitative statistical comparison is made of the galaxy positions with the total mass responsible for maintaining the X-ray emitting gas in hydrostatic equilibrium. A simple bimodal model which fits both the X-ray and optical data suggests that the galaxies are distributed consistently with the projected matter distribution within the region covered by the X-ray map (0.5-1 Mpc). The X-ray and optical estimates of the mass in the central region of the cluster are 2.9 x 10 to the 14th and 3.6 + or - 0.5 x 10 to the 14th solar masses, respectively.

Effect of magnetic field on noncollinear magnetism in classical bilinear-biquadratic Heisenberg model

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

Pasrija, Kanika, E-mail: kanikapasrija@iisermohali.ac.in; Kumar, Sanjeev, E-mail: sanjeev@iisermohali.ac.in

We present a Monte Carlo simulation study of a bilinear-biquadratic Heisenberg model on a two-dimensional square lattice in the presence of an external magnetic field. The study is motivated by the relevance of this simple model to the non-collinear magnetism and the consequent ferroelectric behavior in the recently discovered high-temperature multiferroic, cupric oxide (CuO). We show that an external magnetic field stabilizes a non-coplanar magnetic phase, which is characterized by a finite ferromagnetic moment along the direction of the applied magnetic field and a spiral spin texture if projected in the plane perpendicular to the magnetic field. Real-space analysis highlightsmore » a coexistence of non-collinear regions with ferromagnetic clusters. The results are also supported by simple variational calculations.« less

Cluster dynamics of pulse coupled oscillators

NASA Astrophysics Data System (ADS)

O'Keeffe, Kevin; Strogatz, Steven; Krapivsky, Paul

2015-03-01

We study the dynamics of networks of pulse coupled oscillators. Much attention has been devoted to the ultimate fate of the system: which conditions lead to a steady state in which all the oscillators are firing synchronously. But little is known about how synchrony builds up from an initially incoherent state. The current work addresses this question. Oscillators start to synchronize by forming clusters of different sizes that fire in unison. First pairs of oscillators, then triplets and so on. These clusters progressively grow by coalescing with others, eventually resulting in the fully synchronized state. We study the mean field model in which the coupling between oscillators is all to all. We use probabilistic arguments to derive a recursive set of evolution equations for these clusters. Using a generating function formalism, we derive simple equations for the moments of these clusters. Our results are in good agreement simulation. We then numerically explore the effects of non-trivial connectivity. Our results have potential application to ultra-low power ``impulse radio'' & sensor networks.

Conditional Subspace Clustering of Skill Mastery: Identifying Skills that Separate Students

ERIC Educational Resources Information Center

Nugent, Rebecca; Ayers, Elizabeth; Dean, Nema

2009-01-01

In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of mastering. As the number of examinees, items, and skills increases, the estimation of even simple cognitive diagnosis models becomes difficult. We adopt a faster, simpler approach:…

Effects of scale-dependent non-Gaussianity on cosmological structures

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

LoVerde, Marilena; Miller, Amber; Shandera, Sarah

2008-04-15

The detection of primordial non-Gaussianity could provide a powerful means to test various inflationary scenarios. Although scale-invariant non-Gaussianity (often described by the f{sub NL} formalism) is currently best constrained by the CMB, single-field models with changing sound speed can have strongly scale-dependent non-Gaussianity. Such models could evade the CMB constraints but still have important effects at scales responsible for the formation of cosmological objects such as clusters and galaxies. We compute the effect of scale-dependent primordial non-Gaussianity on cluster number counts as a function of redshift, using a simple ansatz to model scale-dependent features. We forecast constraints on these modelsmore » achievable with forthcoming datasets. We also examine consequences for the galaxy bispectrum. Our results are relevant for the Dirac-Born-Infeld model of brane inflation, where the scale dependence of the non-Gaussianity is directly related to the geometry of the extra dimensions.« less

Simulations of Xe and U diffusion in UO2

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

Andersson, Anders D.; Vyas, Shyam; Tonks, Michael R.

2012-09-10

Diffusion of xenon (Xe) and uranium (U) in UO{sub 2} is controlled by vacancy mechanisms and under irradiation the formation of mobile vacancy clusters is important. Based on the vacancy and cluster diffusion mechanisms established from density functional theory (DFT) calculations, we derive continuum thermodynamic and diffusion models for Xe and U in UO{sub 2}. In order to capture the effects of irradiation, vacancies (Va) are explicitly coupled to the Xe and U dynamics. Segregation of defects to grain boundaries in UO{sub 2} is described by combining the bulk diffusion model with models of the interaction between Xe atoms andmore » vacancies with grain boundaries, which were derived from atomistic calculations. The diffusion and segregation models were implemented in the MOOSE-Bison-Marmot (MBM) finite element (FEM) framework and the Xe/U redistribution was simulated for a few simple microstructures.« less

Extending cluster Lot Quality Assurance Sampling designs for surveillance programs

PubMed Central

Hund, Lauren; Pagano, Marcello

2014-01-01

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance based on the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible non-parametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. PMID:24633656

Extending cluster lot quality assurance sampling designs for surveillance programs.

PubMed

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Analysis of capture-recapture models with individual covariates using data augmentation

USGS Publications Warehouse

Royle, J. Andrew

2009-01-01

I consider the analysis of capture-recapture models with individual covariates that influence detection probability. Bayesian analysis of the joint likelihood is carried out using a flexible data augmentation scheme that facilitates analysis by Markov chain Monte Carlo methods, and a simple and straightforward implementation in freely available software. This approach is applied to a study of meadow voles (Microtus pennsylvanicus) in which auxiliary data on a continuous covariate (body mass) are recorded, and it is thought that detection probability is related to body mass. In a second example, the model is applied to an aerial waterfowl survey in which a double-observer protocol is used. The fundamental unit of observation is the cluster of individual birds, and the size of the cluster (a discrete covariate) is used as a covariate on detection probability.

Exploring gravitational lensing model variations in the Frontier Fields galaxy clusters

NASA Astrophysics Data System (ADS)

Harris James, Nicholas John; Raney, Catie; Brennan, Sean; Keeton, Charles

2018-01-01

Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups’ models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups’ models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.

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

Toda Systems, Cluster Characters, and Spectral Networks

NASA Astrophysics Data System (ADS)

Williams, Harold

2016-11-01

We show that the Hamiltonians of the open relativistic Toda system are elements of the generic basis of a cluster algebra, and in particular are cluster characters of nonrigid representations of a quiver with potential. Using cluster coordinates defined via spectral networks, we identify the phase space of this system with the wild character variety related to the periodic nonrelativistic Toda system by the wild nonabelian Hodge correspondence. We show that this identification takes the relativistic Toda Hamiltonians to traces of holonomies around a simple closed curve. In particular, this provides nontrivial examples of cluster coordinates on SL n -character varieties for n > 2 where canonical functions associated to simple closed curves can be computed in terms of quivers with potential, extending known results in the SL 2 case.

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.

SLURM: Simple Linux Utility for Resource Management

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

Jette, M; Dunlap, C; Garlick, J

2002-07-08

Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters of thousands of nodes. Components include machine status, partition management, job management, scheduling and stream copy modules. The design also includes a scalable, general-purpose communication infrastructure. This paper presents a overview of the SLURM architecture and functionality.

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

The dynamics of aloof baby Skyrmions

DOE PAGES

Salmi, Petja; Sutcliffe, Paul

2016-01-25

The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)- dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper wemore » present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.« less

The dynamics of aloof baby Skyrmions

NASA Astrophysics Data System (ADS)

Salmi, Petja; Sutcliffe, Paul

2016-01-01

The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)-dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper we present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.

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

Salmi, Petja; Sutcliffe, Paul

The aloof baby Skyrme model is a (2+1)-dimensional theory with solitons that are lightly bound. It is a low-dimensional analogue of a similar Skyrme model in (3+1)- dimensions, where the lightly bound solitons have binding energies comparable to nuclei. A previous study of static solitons in the aloof baby Skyrme model revealed that multi-soliton bound states have a cluster structure, with constituents that preserve their individual identities due to the short-range repulsion and long-range attraction between solitons. Furthermore, there are many different local energy minima that are all well-described by a simple binary species particle model. In this paper wemore » present the first results on soliton dynamics in the aloof baby Skyrme model. Numerical field theory simulations reveal that the lightly bound cluster structure results in a variety of exotic soliton scattering events that are novel in comparison to standard Skyrmion scattering. A dynamical version of the binary species point particle model is shown to provide a good qualitative description of the dynamics.« less

Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines

NASA Astrophysics Data System (ADS)

Ntampaka, Michelle; Trac, Hy; Sutherland, Dougal; Fromenteau, Sebastien; Poczos, Barnabas; Schneider, Jeff

2018-01-01

We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership infor- mation and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width E=0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (E=2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (E=0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncon- taminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

The structure of clusters of galaxies

NASA Astrophysics Data System (ADS)

Fox, David Charles

When infalling gas is accreted onto a cluster of galaxies, its kinetic energy is converted to thermal energy in a shock, heating the ions. Using a self-similar spherical model, we calculate the collisional heating of the electrons by the ions, and predict the electron and ion temperature profiles. While there are significant differences between the two, they occur at radii larger than currently observable, and too large to explain observed X-ray temperature declines in clusters. Numerical simulations by Navarro, Frenk, & White (1996) predict a universal dark matter density profile. We calculate the expected number of multiply-imaged background galaxies in the Hubble Deep Field due to foreground groups and clusters with this profile. Such groups are up to 1000 times less efficient at lensing than the standard singular isothermal spheres. However, with either profile, the expected number of galaxies lensed by groups in the Hubble Deep Field is at most one, consistent with the lack of clearly identified group lenses. X-ray and Sunyaev-Zel'dovich (SZ) effect observations can be combined to determine the distance to clusters of galaxies, provided the clusters are spherical. When applied to an aspherical cluster, this method gives an incorrect distance. We demonstrate a method for inferring the three-dimensional shape of a cluster and its correct distance from X-ray, SZ effect, and weak gravitational lensing observations, under the assumption of hydrostatic equilibrium. We apply this method to simple, analytic models of clusters, and to a numerically simulated cluster. Using artificial observations based on current X-ray and SZ effect instruments, we recover the true distance without detectable bias and with uncertainties of 4 percent.

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.

Detecting DNA regulatory motifs by incorporating positional trendsin information content

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

Kechris, Katherina J.; van Zwet, Erik; Bickel, Peter J.

2004-05-04

On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.

Power-Law Template for IR Point Source Clustering

NASA Technical Reports Server (NTRS)

Addison, Graeme E.; Dunkley, Joanna; Hajian, Amir; Viero, Marco; Bond, J. Richard; Das, Sudeep; Devlin, Mark; Halpern, Mark; Hincks, Adam; Hlozek, Renee;

Fragment-based 13C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

NASA Astrophysics Data System (ADS)

Hartman, Joshua D.; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J. O.

2015-09-01

We assess the quality of fragment-based ab initio isotropic 13C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic 13C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

Fragment-based (13)C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods.

PubMed

Hartman, Joshua D; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J O

2015-09-14

We assess the quality of fragment-based ab initio isotropic (13)C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic (13)C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

A simple prescription for simulating and characterizing gravitational arcs

NASA Astrophysics Data System (ADS)

Furlanetto, C.; Santiago, B. X.; Makler, M.; de Bom, C.; Brandt, C. H.; Neto, A. F.; Ferreira, P. C.; da Costa, L. N.; Maia, M. A. G.

2013-01-01

Simple models of gravitational arcs are crucial for simulating large samples of these objects with full control of the input parameters. These models also provide approximate and automated estimates of the shape and structure of the arcs, which are necessary for detecting and characterizing these objects on massive wide-area imaging surveys. We here present and explore the ArcEllipse, a simple prescription for creating objects with a shape similar to gravitational arcs. We also present PaintArcs, which is a code that couples this geometrical form with a brightness distribution and adds the resulting object to images. Finally, we introduce ArcFitting, which is a tool that fits ArcEllipses to images of real gravitational arcs. We validate this fitting technique using simulated arcs and apply it to CFHTLS and HST images of tangential arcs around clusters of galaxies. Our simple ArcEllipse model for the arc, associated to a Sérsic profile for the source, recovers the total signal in real images typically within 10%-30%. The ArcEllipse+Sérsic models also automatically recover visual estimates of length-to-width ratios of real arcs. Residual maps between data and model images reveal the incidence of arc substructure. They may thus be used as a diagnostic for arcs formed by the merging of multiple images. The incidence of these substructures is the main factor that prevents ArcEllipse models from accurately describing real lensed systems.

An alternative validation strategy for the Planck cluster catalogue and y-distortion maps

NASA Astrophysics Data System (ADS)

Khatri, Rishi

2016-07-01

We present an all-sky map of the y-type distortion calculated from the full mission Planck High Frequency Instrument (HFI) data using the recently proposed approach to component separation, which is based on parametric model fitting and model selection. This simple model-selection approach enables us to distinguish between carbon monoxide (CO) line emission and y-type distortion, something that is not possible using the internal linear combination based methods. We create a mask to cover the regions of significant CO emission relying on the information in the χ2 map that was obtained when fitting for the y-distortion and CO emission to the lowest four HFI channels. We revisit the second Planck cluster catalogue and try to quantify the quality of the cluster candidates in an approach that is similar in spirit to Aghanim et al. (2015, A&A, 580, A138). We find that at least 93% of the clusters in the cosmology sample are free of CO contamination. We also find that 59% of unconfirmed candidates may have significant contamination from molecular clouds. We agree with Planck Collaboration XXVII (2016, A&A, in press) on the worst offenders. We suggest an alternative validation strategy of measuring and subtracting the CO emission from the Planck cluster candidates using radio telescopes, thus improving the reliability of the catalogue. Our CO mask and annotations to the Planck cluster catalogue, identifying cluster candidates with possible CO contamination, are made publicly available. The full Tables 1-3 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/592/A48

Age and Mass for 920 Large Magellanic Cloud Clusters Derived from 100 Million Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Popescu, Bogdan; Hanson, M. M.; Elmegreen, Bruce G.

2012-06-01

We present new age and mass estimates for 920 stellar clusters in the Large Magellanic Cloud (LMC) based on previously published broadband photometry and the stellar cluster analysis package, MASSCLEANage. Expressed in the generic fitting formula, d 2 N/dMdtvpropM α t β, the distribution of observed clusters is described by α = -1.5 to -1.6 and β = -2.1 to -2.2. For 288 of these clusters, ages have recently been determined based on stellar photometric color-magnitude diagrams, allowing us to gauge the confidence of our ages. The results look very promising, opening up the possibility that this sample of 920 clusters, with reliable and consistent age, mass, and photometric measures, might be used to constrain important characteristics about the stellar cluster population in the LMC. We also investigate a traditional age determination method that uses a χ2 minimization routine to fit observed cluster colors to standard infinite-mass limit simple stellar population models. This reveals serious defects in the derived cluster age distribution using this method. The traditional χ2 minimization method, due to the variation of U, B, V, R colors, will always produce an overdensity of younger and older clusters, with an underdensity of clusters in the log (age/yr) = [7.0, 7.5] range. Finally, we present a unique simulation aimed at illustrating and constraining the fading limit in observed cluster distributions that includes the complex effects of stochastic variations in the observed properties of stellar clusters.

Mapping of terrain by computer clustering techniques using multispectral scanner data and using color aerial film

NASA Technical Reports Server (NTRS)

Smedes, H. W.; Linnerud, H. J.; Woolaver, L. B.; Su, M. Y.; Jayroe, R. R.

1972-01-01

Two clustering techniques were used for terrain mapping by computer of test sites in Yellowstone National Park. One test was made with multispectral scanner data using a composite technique which consists of (1) a strictly sequential statistical clustering which is a sequential variance analysis, and (2) a generalized K-means clustering. In this composite technique, the output of (1) is a first approximation of the cluster centers. This is the input to (2) which consists of steps to improve the determination of cluster centers by iterative procedures. Another test was made using the three emulsion layers of color-infrared aerial film as a three-band spectrometer. Relative film densities were analyzed using a simple clustering technique in three-color space. Important advantages of the clustering technique over conventional supervised computer programs are (1) human intervention, preparation time, and manipulation of data are reduced, (2) the computer map, gives unbiased indication of where best to select the reference ground control data, (3) use of easy to obtain inexpensive film, and (4) the geometric distortions can be easily rectified by simple standard photogrammetric techniques.

Microstructure-based modelling of arbitrary deformation histories of filler-reinforced elastomers

NASA Astrophysics Data System (ADS)

Lorenz, H.; Klüppel, M.

2012-11-01

A physically motivated theory of rubber reinforcement based on filler cluster mechanics is presented considering the mechanical behaviour of quasi-statically loaded elastomeric materials subjected to arbitrary deformation histories. This represents an extension of a previously introduced model describing filler induced stress softening and hysteresis of highly strained elastomers. These effects are referred to the hydrodynamic reinforcement of rubber elasticity due to strain amplification by stiff filler clusters and cyclic breakdown and re-aggregation (healing) of softer, already damaged filler clusters. The theory is first developed for the special case of outer stress-strain cycles with successively increasing maximum strain. In this more simple case, all soft clusters are broken at the turning points of the cycle and the mechanical energy stored in the strained clusters is completely dissipated, i.e. only irreversible stress contributions result. Nevertheless, the description of outer cycles involves already all material parameters of the theory and hence they can be used for a fitting procedure. In the general case of an arbitrary deformation history, the cluster mechanics of the material is complicated due to the fact that not all soft clusters are broken at the turning points of a cycle. For that reason additional reversible stress contributions considering the relaxation of clusters upon retraction have to be taken into account for the description of inner cycles. A special recursive algorithm is developed constituting a frame of the mechanical response of encapsulated inner cycles. Simulation and measurement are found to be in fair agreement for CB and silica filled SBR/BR and EPDM samples, loaded in compression and tension along various deformation histories.

Enhancement of magnetocaloric effect in the Gd 2Al phase by Co alloying

DOE PAGES

Huang, Z. Y.; Fu, H.; Hadimani, R. L.; ...

2014-11-14

We observe that Cu clusters grow on surface terraces of graphite as a result of physical vapor deposition in ultrahigh vacuum. We show that the observation is incompatible with a variety of models incorporating homogeneous nucleation and high level calculations of atomic-scale energetics. An alternative explanation, ion-mediated heterogeneous nucleation, is proposed and validated, both with theory and experiment. This serves as a case study in identifying when and whether the simple, common observation of metal clusters on carbon-rich surfaces can be interpreted in terms of homogeneous nucleation. We describe a general approach for making system-specific and laboratory-specific predictions.

Solvent induced temperature dependencies of NMR parameters of hydrogen bonded anionic clusters

NASA Astrophysics Data System (ADS)

Golubev, Nikolai S.; Shenderovich, Ilja G.; Tolstoy, Peter M.; Shchepkin, Dmitry N.

2004-07-01

The solvent induced temperature dependence of NMR parameters (proton and fluorine chemical shifts, the two-bond scalar spin coupling constant across the hydrogen bridge, 2hJFF) for dihydrogen trifluoride anion, (FH) 2F -, in a polar aprotic solvent, CDF 3/CDF 2Cl, is reported and discussed. The results are interpreted in terms of a simple electrostatic model, accounting a decrease of electrostatic repulsion of two negatively charged fluorine atoms on placing into a dielectric medium. The conclusion is drawn that polar medium causes some contraction of hydrogen bonds in ionic clusters combined with a decrease of hydrogen bond asymmetry.

Determining whether metals nucleate homogeneously on graphite: A case study with copper

DOE PAGES

Appy, David; Lei, Huaping; Han, Yong; ...

2014-11-05

In this study, we observe that Cu clusters grow on surface terraces of graphite as a result of physical vapor deposition in ultrahigh vacuum. We show that the observation is incompatible with a variety of models incorporating homogeneous nucleation and calculations of atomic-scale energetics. An alternative explanation, ion-mediated heterogeneous nucleation, is proposed and validated, both with theory and experiment. This serves as a case study in identifying when and whether the simple, common observation of metal clusters on carbon-rich surfaces can be interpreted in terms of homogeneous nucleation. We describe a general approach for making system-specific and laboratory-specific predictions.

Theoretical modelling on thermal expansion of Al, Ag and Cu nanomaterials

NASA Astrophysics Data System (ADS)

Manu, Mehul; Dubey, Vikash

2018-05-01

A simple theoretical model is developed for the calculating the coefficient of volume thermal expansion (CTE) and volume thermal expansion (VTE) of Al, Ag and Cu nanomaterials by considering the cubo-octahedral structure with the change of temperature and the cluster size. At the room temperature, the coefficient of volume thermal expansion decreases sharply below 20-25 nm and the decrement of the coefficient of volume thermal expansion becomes slower above 20-25 nm. We also saw a variation in the volume thermal expansion with the variation of temperature and cluster size. At a fixed cluster size, the volume thermal expansion increases with an increase of temperature at below the melting temperature and show a linear relation of volume thermal expansion with the temperature. At a constant temperature, the volume thermal expansion decreases rapidly with an increase in cluster size below 20-25 nm and after 20-25 nm the decrement of volume thermal expansion becomes slower with the increase of the size of the cluster. Thermal expansion is due to the anharmonicity of the atom interaction. As the temperature rises the amplitude of crystal lattice vibration increases, but the equilibrium distance shifts as the atom spend more time at distance greater than the original spacing due as the repulsion at short distance greater than the corresponding attraction at farther distance. In considering the cubo- octahedral structure with the cluster order, the model prediction on the CTE and the VTE are in good agreement with the available experimental data which demonstrate the validity of our work.

Simple and efficient self-healing strategy for damaged complex networks

NASA Astrophysics Data System (ADS)

Gallos, Lazaros K.; Fefferman, Nina H.

2015-11-01

The process of destroying a complex network through node removal has been the subject of extensive interest and research. Node loss typically leaves the network disintegrated into many small and isolated clusters. Here we show that these clusters typically remain close to each other and we suggest a simple algorithm that is able to reverse the inflicted damage by restoring the network's functionality. After damage, each node decides independently whether to create a new link depending on the fraction of neighbors it has lost. In addition to relying only on local information, where nodes do not need knowledge of the global network status, we impose the additional constraint that new links should be as short as possible (i.e., that the new edge completes a shortest possible new cycle). We demonstrate that this self-healing method operates very efficiently, both in model and real networks. For example, after removing the most connected airports in the USA, the self-healing algorithm rejoined almost 90% of the surviving airports.

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.

Modified Baryonic Dynamics: two-component cosmological simulations with light sterile neutrinos

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

Angus, G.W.; Gentile, G.; Diaferio, A.

2014-10-01

In this article we continue to test cosmological models centred on Modified Newtonian Dynamics (MOND) with light sterile neutrinos, which could in principle be a way to solve the fine-tuning problems of the standard model on galaxy scales while preserving successful predictions on larger scales. Due to previous failures of the simple MOND cosmological model, here we test a speculative model where the modified gravitational field is produced only by the baryons and the sterile neutrinos produce a purely Newtonian field (hence Modified Baryonic Dynamics). We use two-component cosmological simulations to separate the baryonic N-body particles from the sterile neutrinomore » ones. The premise is to attenuate the over-production of massive galaxy cluster halos which were prevalent in the original MOND plus light sterile neutrinos scenario. Theoretical issues with such a formulation notwithstanding, the Modified Baryonic Dynamics model fails to produce the correct amplitude for the galaxy cluster mass function for any reasonable value of the primordial power spectrum normalisation.« less

MARMOT simulations of Xe segregation to grain boundaries in UO2

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

Andersson, Anders D.; Tonks, Michael; Casillas, Luis

2012-06-20

Diffusion of Xe and U in UO{sub 2} is controlled by vacancy mechanisms and under irradiation the formation of mobile vacancy clusters is important. We derive continuum thermodynamic and diffusion models for Xe and U in UO{sub 2} based on the vacancy and cluster diffusion mechanisms established from recent density functional theory (DFT) calculations. Segregation of defects to grain boundaries in UO{sub 2} is described by combining the diffusion model with models of the interaction between Xe atoms and vacancies with grain boundaries derived from separate atomistic calculations. The diffusion and segregation models are implemented in the MOOSE/MARMOT (MBM) finitemore » element (FEM) framework and we simulate Xe redistribution for a few simple microstructures. In this report we focus on segregation to grain boundaries. The U or vacancy diffusion model as well as the coupled diffusion of vacancies and Xe have also been implemented, but results are not included in this report.« less

Depletion of interstitial oxygen in silicon and the thermal donor model

NASA Technical Reports Server (NTRS)

Borenstein, Jeffrey T.; Singh, Vijay A.; Corbett, James W.

1987-01-01

It is shown here that the experimental results of Newman (1985) and Tan et al. (1986) regarding the loss of oxygen interstitials during 450 C annealing of Czochralski silicon are consistent with the recently proposed model of Borenstein, Peak, and Corbett (1986) for thermal donor formation. Calculations were carried out for TD cores corresponding to O2, O3, O4, and/or O5 clusters. A simple model which attempts to capture the essential physics of the interstitial depletion has been constructed, and is briefly described.

Self-organization, the cascade model, and natural hazards.

PubMed

Turcotte, Donald L; Malamud, Bruce D; Guzzetti, Fausto; Reichenbach, Paola

2002-02-19

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions.

Self-organization, the cascade model, and natural hazards

PubMed Central

Turcotte, Donald L.; Malamud, Bruce D.; Guzzetti, Fausto; Reichenbach, Paola

2002-01-01

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions. PMID:11875206

Simulating Self-Assembly with Simple Models

NASA Astrophysics Data System (ADS)

Rapaport, D. C.

Results from recent molecular dynamics simulations of virus capsid self-assembly are described. The model is based on rigid trapezoidal particles designed to form polyhedral shells of size 60, together with an atomistic solvent. The underlying bonding process is fully reversible. More extensive computations are required than in previous work on icosahedral shells built from triangular particles, but the outcome is a high yield of closed shells. Intermediate clusters have a variety of forms, and bond counts provide a useful classification scheme

Ising model simulation in directed lattices and networks

NASA Astrophysics Data System (ADS)

Lima, F. W. S.; Stauffer, D.

2006-01-01

On directed lattices, with half as many neighbours as in the usual undirected lattices, the Ising model does not seem to show a spontaneous magnetisation, at least for lower dimensions. Instead, the decay time for flipping of the magnetisation follows an Arrhenius law on the square and simple cubic lattice. On directed Barabási-Albert networks with two and seven neighbours selected by each added site, Metropolis and Glauber algorithms give similar results, while for Wolff cluster flipping the magnetisation decays exponentially with time.

Efficient gradient-based Monte Carlo simulation of materials: Applications to amorphous Si and Fe and Ni clusters

NASA Astrophysics Data System (ADS)

Limbu, Dil; Biswas, Parthapratim

We present a simple and efficient Monte-Carlo (MC) simulation of Iron (Fe) and Nickel (Ni) clusters with N =5-100 and amorphous Silicon (a-Si) starting from a random configuration. Using Sutton-Chen and Finnis-Sinclair potentials for Ni (in fcc lattice) and Fe (in bcc lattice), and Stillinger-Weber potential for a-Si, respectively, the total energy of the system is optimized by employing MC moves that include both the stochastic nature of MC simulations and the gradient of the potential function. For both iron and nickel clusters, the energy of the configurations is found to be very close to the values listed in the Cambridge Cluster Database, whereas the maximum force on each cluster is found to be much lower than the corresponding value obtained from the optimized structural configurations reported in the database. An extension of the method to model the amorphous state of Si is presented and the results are compared with experimental data and those obtained from other simulation methods. The work is partially supported by the NSF under Grant Number DMR 1507166.

Cluster structures influenced by interaction with a surface.

PubMed

Witt, Christopher; Dieterich, Johannes M; Hartke, Bernd

2018-05-30

Clusters on surfaces are vitally important for nanotechnological applications. Clearly, cluster-surface interactions heavily influence the preferred cluster structures, compared to clusters in vacuum. Nevertheless, systematic explorations and an in-depth understanding of these interactions and how they determine the cluster structures are still lacking. Here we present an extension of our well-established non-deterministic global optimization package OGOLEM from isolated clusters to clusters on surfaces. Applying this approach to intentionally simple Lennard-Jones test systems, we produce a first systematic exploration that relates changes in cluster-surface interactions to resulting changes in adsorbed cluster structures.

Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor)

PubMed Central

Zhang, Jingjing; Dennis, Todd E.

2015-01-01

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known ‘artificial behaviours’ comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified. PMID:25922935

Extending the Functionality of Behavioural Change-Point Analysis with k-Means Clustering: A Case Study with the Little Penguin (Eudyptula minor).

PubMed

Zhang, Jingjing; O'Reilly, Kathleen M; Perry, George L W; Taylor, Graeme A; Dennis, Todd E

2015-01-01

We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known 'artificial behaviours' comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.

Spanish Dyslexic Spelling Abilities: The Case of Consonant Clusters

ERIC Educational Resources Information Center

Serrano, Francisca; Defior, Sylvia

2012-01-01

This paper investigates Spanish dyslexic spelling abilities: specifically, the influence of syllabic linguistic structure (simple vs consonant cluster) on children's spelling performance. Consonant clusters are phonologically complex structures, so it was anticipated that there would be lower spelling performance for these syllabic structures than…

Cellular packing, mechanical stress and the evolution of multicellularity

NASA Astrophysics Data System (ADS)

Jacobeen, Shane; Pentz, Jennifer T.; Graba, Elyes C.; Brandys, Colin G.; Ratcliff, William C.; Yunker, Peter J.

2018-03-01

The evolution of multicellularity set the stage for sustained increases in organismal complexity1-5. However, a fundamental aspect of this transition remains largely unknown: how do simple clusters of cells evolve increased size when confronted by forces capable of breaking intracellular bonds? Here we show that multicellular snowflake yeast clusters6-8 fracture due to crowding-induced mechanical stress. Over seven weeks ( 291 generations) of daily selection for large size, snowflake clusters evolve to increase their radius 1.7-fold by reducing the accumulation of internal stress. During this period, cells within the clusters evolve to be more elongated, concomitant with a decrease in the cellular volume fraction of the clusters. The associated increase in free space reduces the internal stress caused by cellular growth, thus delaying fracture and increasing cluster size. This work demonstrates how readily natural selection finds simple, physical solutions to spatial constraints that limit the evolution of group size—a fundamental step in the evolution of multicellularity.

Not-so-simple stellar populations in nearby, resolved massive star clusters

NASA Astrophysics Data System (ADS)

de Grijs, Richard; Li, Chengyuan

2018-02-01

Around the turn of the last century, star clusters of all kinds were considered ‘simple’ stellar populations. Over the past decade, this situation has changed dramatically. At the same time, star clusters are among the brightest stellar population components and, as such, they are visible out to much greater distances than individual stars, even the brightest, so that understanding the intricacies of star cluster composition and their evolution is imperative for understanding stellar populations and the evolution of galaxies as a whole. In this review of where the field has moved to in recent years, we place particular emphasis on the properties and importance of binary systems, the effects of rapid stellar rotation, and the presence of multiple populations in Magellanic Cloud star clusters across the full age range. Our most recent results imply a reverse paradigm shift, back to the old simple stellar population picture for at least some intermediate-age (˜1-3 Gyr old) star clusters, opening up exciting avenues for future research efforts.

Social aggregation as a cooperative game

NASA Astrophysics Data System (ADS)

Vilone, Daniele; Guazzini, Andrea

2011-07-01

A new approach for the description of phenomena of social aggregation is suggested. On the basis of psychological concepts (as for instance social norms and cultural coordinates), we deduce a general mechanism for social aggregation in which different clusters of individuals can merge according to cooperation among the agents. In their turn, the agents can cooperate or defect according to the clusters' distribution inside the system. The fitness of an individual increases with the size of its cluster, but decreases with the work the individual had to do in order to join it. In order to test the reliability of such a new approach, we introduce a couple of simple toy models with the features illustrated above. We see, from this preliminary study, how cooperation is the most convenient strategy only in the presence of very large clusters, while on the other hand it is not necessary to have one hundred percent of cooperators for reaching a totally ordered configuration with only one megacluster filling the whole system.

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Application of 2D and 3D image technologies to characterise morphological attributes of grapevine clusters.

PubMed

Tello, Javier; Cubero, Sergio; Blasco, José; Tardaguila, Javier; Aleixos, Nuria; Ibáñez, Javier

2016-10-01

Grapevine cluster morphology influences the quality and commercial value of wine and table grapes. It is routinely evaluated by subjective and inaccurate methods that do not meet the requirements set by the food industry. Novel two-dimensional (2D) and three-dimensional (3D) machine vision technologies emerge as promising tools for its automatic and fast evaluation. The automatic evaluation of cluster length, width and elongation was successfully achieved by the analysis of 2D images, significant and strong correlations with the manual methods being found (r = 0.959, 0.861 and 0.852, respectively). The classification of clusters according to their shape can be achieved by evaluating their conicity in different sections of the cluster. The geometric reconstruction of the morphological volume of the cluster from 2D features worked better than the direct 3D laser scanning system, showing a high correlation (r = 0.956) with the manual approach (water displacement method). In addition, we constructed and validated a simple linear regression model for cluster compactness estimation. It showed a high predictive capacity for both the training and validation subsets of clusters (R(2)  = 84.5 and 71.1%, respectively). The methodologies proposed in this work provide continuous and accurate data for the fast and objective characterisation of cluster morphology. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

CO2 Cluster Ion Beam, an Alternative Projectile for Secondary Ion Mass Spectrometry

NASA Astrophysics Data System (ADS)

Tian, Hua; Maciążek, Dawid; Postawa, Zbigniew; Garrison, Barbara J.; Winograd, Nicholas

2016-09-01

The emergence of argon-based gas cluster ion beams for SIMS experiments opens new possibilities for molecular depth profiling and 3D chemical imaging. These beams generally leave less surface chemical damage and yield mass spectra with reduced fragmentation compared with smaller cluster projectiles. For nanoscale bioimaging applications, however, limited sensitivity due to low ionization probability and technical challenges of beam focusing remain problematic. The use of gas cluster ion beams based upon systems other than argon offer an opportunity to resolve these difficulties. Here we report on the prospects of employing CO2 as a simple alternative to argon. Ionization efficiency, chemical damage, sputter rate, and beam focus are investigated on model compounds using a series of CO2 and Ar cluster projectiles (cluster size 1000-5000) with the same mass. The results show that the two projectiles are very similar in each of these aspects. Computer simulations comparing the impact of Ar2000 and (CO2)2000 on an organic target also confirm that the CO2 molecules in the cluster projectile remain intact, acting as a single particle of m/z 44. The imaging resolution employing CO2 cluster projectiles is improved by more than a factor of two. The advantage of CO2 versus Ar is also related to the increased stability which, in addition, facilitates the operation of the gas cluster ion beams (GCIB) system at lower backing pressure.

Spontaneous emergence of catalytic cycles with colloidal spheres

NASA Astrophysics Data System (ADS)

Zeravcic, Zorana; Brenner, Michael P.

2017-04-01

Colloidal particles endowed with specific time-dependent interactions are a promising route for realizing artificial materials that have the properties of living ones. Previous work has demonstrated how this system can give rise to self-replication. Here, we introduce the process of colloidal catalysis, in which clusters of particles catalyze the creation of other clusters through templating reactions. Surprisingly, we find that simple templating rules generically lead to the production of huge numbers of clusters. The templating reactions among this sea of clusters give rise to an exponentially growing catalytic cycle, a specific realization of Dyson’s notion of an exponentially growing metabolism. We demonstrate this behavior with a fixed set of interactions between particles chosen to allow a catalysis of a specific six-particle cluster from a specific seven-particle cluster, yet giving rise to the catalytic production of a sea of clusters of sizes between 2 and 11 particles. The fact that an exponentially growing cycle emerges naturally from such a simple scheme demonstrates that the emergence of exponentially growing metabolisms could be simpler than previously imagined.

Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning

NASA Astrophysics Data System (ADS)

Ntampaka, M.; Trac, H.; Sutherland, D. J.; Fromenteau, S.; Póczos, B.; Schneider, J.

2016-11-01

We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership information and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width of {{Δ }}ε ≈ 0.87. Interlopers introduce additional scatter, significantly widening the error distribution further ({{Δ }}ε ≈ 2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement ({{Δ }}ε ≈ 0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncontaminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

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.

Plasma Properties in the Plume of a Hall Thruster Cluster

DTIC Science & Technology

2003-06-04

The Hall thruster cluster is an attractive propulsion approach for spacecraft requiring very high-power electric propulsion systems. This article...probes in the plume of a low-power, four-engine Hall thruster cluster. Simple analytical formulas are introduced that allow these quantities to be

Prediction of sea ice thickness cluster in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Fuckar, Neven-Stjepan; Guemas, Virginie; Johnson, Nathaniel; Doblas-Reyes, Francisco

2016-04-01

Sea ice thickness (SIT) has a potential to contain substantial climate memory and predictability in the northern hemisphere (NH) sea ice system. We use 5-member NH SIT, reconstructed with an ocean-sea-ice general circulation model (NEMOv3.3 with LIM2) with a simple data assimilation routine, to determine NH SIT modes of variability disentangled from the long-term climate change. Specifically, we apply the K-means cluster analysis - one of nonhierarchical clustering methods that partition data into modes or clusters based on their distances in the physical - to determine optimal number of NH SIT clusters (K=3) and their historical variability. To examine prediction skill of NH SIT clusters in EC-Earth2.3, a state-of-the-art coupled climate forecast system, we use 5-member ocean and sea ice initial conditions (IC) from the same ocean-sea-ice historical reconstruction and atmospheric IC from ERA-Interim reanalysis. We focus on May 1st and Nov 1st start dates from 1979 to 2010. Common skill metrics of probability forecast, such as rank probability skill core and ROC (relative operating characteristics - hit rate versus false alarm rate) and reliability diagrams show that our dynamical model predominately perform better than the 1st order Marko chain forecast (that beats climatological forecast) over the first forecast year. On average May 1st start dates initially have lower skill than Nov 1st start dates, but their skill is degraded at slower rate than skill of forecast started on Nov 1st.

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.

Understanding the Cu-Zn brass alloys using a short-range-order cluster model: significance of specific compositions of industrial alloys

PubMed Central

Hong, H. L.; Wang, Q.; Dong, C.; Liaw, Peter K.

2014-01-01

Metallic alloys show complex chemistries that are not yet understood so far. It has been widely accepted that behind the composition selection lies a short-range-order mechanism for solid solutions. The present paper addresses this fundamental question by examining the face-centered-cubic Cu-Zn α-brasses. A new structural approach, the cluster-plus-glue-atom model, is introduced, which suits specifically for the description of short-range-order structures in disordered systems. Two types of formulas are pointed out, [Zn-Cu12]Zn1~6 and [Zn-Cu12](Zn,Cu)6, which explain the α-brasses listed in the American Society for Testing and Materials (ASTM) specifications. In these formulas, the bracketed parts represent the 1st-neighbor cluster, and each cluster is matched with one to six 2nd-neighbor Zn atoms or with six mixed (Zn,Cu) atoms. Such a cluster-based formulism describes the 1st- and 2nd-neighbor local atomic units where the solute and solvent interactions are ideally satisfied. The Cu-Ni industrial alloys are also explained, thus proving the universality of the cluster-formula approach in understanding the alloy selections. The revelation of the composition formulas for the Cu-(Zn,Ni) industrial alloys points to the common existence of simple composition rules behind seemingly complex chemistries of industrial alloys, thus offering a fundamental and practical method towards composition interpretations of all kinds of alloys. PMID:25399835

Understanding the Cu-Zn brass alloys using a short-range-order cluster model: Significance of specific compositions of industrial alloys

DOE PAGES

Hong, H. L.; Wang, Q.; Dong, C.; ...

2014-11-17

Metallic alloys show complex chemistries that are not yet understood so far. It has been widely accepted that behind the composition selection lies a short-range-order mechanism for solid solutions. The present paper addresses this fundamental question by examining the face-centered-cubic Cu-Zn α-brasses. A new structural approach, the cluster-plus-glue-atom model, is introduced, which suits specifically for the description of short-range-order structures in disordered systems. Two types of formulas are pointed out, [Zn-Cu 12]Zn 1~6 and [Zn-Cu 12](Zn,Cu) 6, which explain the α-brasses listed in the American Society for Testing and Materials (ASTM) specifications. In these formulas, the bracketed parts represent themore » 1 st-neighbor cluster, and each cluster is matched with one to six 2 nd-neighbor Zn atoms or with six mixed (Zn,Cu) atoms. Such a cluster-based formulism describes the 1 st- and 2 nd-neighbor local atomic units where the solute and solvent interactions are ideally satisfied. The Cu-Ni industrial alloys are also explained, thus proving the universality of the cluster-formula approach in understanding the alloy selections. As a result, the revelation of the composition formulas for the Cu-(Zn,Ni) industrial alloys points to the common existence of simple composition rules behind seemingly complex chemistries of industrial alloys, thus offering a fundamental and practical method towards composition interpretations of all kinds of alloys.« less

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

Electric-field-induced assembly and propulsion of chiral colloidal clusters.

PubMed

Ma, Fuduo; Wang, Sijia; Wu, David T; Wu, Ning

2015-05-19

Chiral molecules with opposite handedness exhibit distinct physical, chemical, or biological properties. They pose challenges as well as opportunities in understanding the phase behavior of soft matter, designing enantioselective catalysts, and manufacturing single-handed pharmaceuticals. Microscopic particles, arranged in a chiral configuration, could also exhibit unusual optical, electric, or magnetic responses. Here we report a simple method to assemble achiral building blocks, i.e., the asymmetric colloidal dimers, into a family of chiral clusters. Under alternating current electric fields, two to four lying dimers associate closely with a central standing dimer and form both right- and left-handed clusters on a conducting substrate. The cluster configuration is primarily determined by the induced dipolar interactions between constituent dimers. Our theoretical model reveals that in-plane dipolar repulsion between petals in the cluster favors the achiral configuration, whereas out-of-plane attraction between the central dimer and surrounding petals favors a chiral arrangement. It is the competition between these two interactions that dictates the final configuration. The theoretical chirality phase diagram is found to be in excellent agreement with experimental observations. We further demonstrate that the broken symmetry in chiral clusters induces an unbalanced electrohydrodynamic flow surrounding them. As a result, they rotate in opposite directions according to their handedness. Both the assembly and propulsion mechanisms revealed here can be potentially applied to other types of asymmetric particles. Such kinds of chiral colloids will be useful for fabricating metamaterials, making model systems for both chiral molecules and active matter, or building propellers for microscale transport.

THE DYNAMICS OF MERGING CLUSTERS: A MONTE CARLO SOLUTION APPLIED TO THE BULLET AND MUSKET BALL CLUSTERS

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

Dawson, William A., E-mail: wadawson@ucdavis.edu

2013-08-01

Merging galaxy clusters have become one of the most important probes of dark matter, providing evidence for dark matter over modified gravity and even constraints on the dark matter self-interaction cross-section. To properly constrain the dark matter cross-section it is necessary to understand the dynamics of the merger, as the inferred cross-section is a function of both the velocity of the collision and the observed time since collision. While the best understanding of merging system dynamics comes from N-body simulations, these are computationally intensive and often explore only a limited volume of the merger phase space allowed by observed parametermore » uncertainty. Simple analytic models exist but the assumptions of these methods invalidate their results near the collision time, plus error propagation of the highly correlated merger parameters is unfeasible. To address these weaknesses I develop a Monte Carlo method to discern the properties of dissociative mergers and propagate the uncertainty of the measured cluster parameters in an accurate and Bayesian manner. I introduce this method, verify it against an existing hydrodynamic N-body simulation, and apply it to two known dissociative mergers: 1ES 0657-558 (Bullet Cluster) and DLSCL J0916.2+2951 (Musket Ball Cluster). I find that this method surpasses existing analytic models-providing accurate (10% level) dynamic parameter and uncertainty estimates throughout the merger history. This, coupled with minimal required a priori information (subcluster mass, redshift, and projected separation) and relatively fast computation ({approx}6 CPU hours), makes this method ideal for large samples of dissociative merging clusters.« less

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.

Power-Law Template for Infrared Point-Source Clustering

NASA Technical Reports Server (NTRS)

Addison, Graeme E; Dunkley, Joanna; Hajian, Amir; Viero, Marco; Bond, J. Richard; Das, Sudeep; Devlin, Mark J.; Halpern, Mark; Hincks, Adam D; Hlozek, Renee;

MOCCA-SURVEY Database. I. Eccentric Black Hole Mergers during Binary–Single Interactions in Globular Clusters

NASA Astrophysics Data System (ADS)

Samsing, Johan; Askar, Abbas; Giersz, Mirek

2018-03-01

We estimate the population of eccentric gravitational wave (GW) binary black hole (BBH) mergers forming during binary–single interactions in globular clusters (GCs), using ∼800 GC models that were evolved using the MOCCA code for star cluster simulations as part of the MOCCA-Survey Database I project. By re-simulating BH binary–single interactions extracted from this set of GC models using an N-body code that includes GW emission at the 2.5 post-Newtonian level, we find that ∼10% of all the BBHs assembled in our GC models that merge at present time form during chaotic binary–single interactions, and that about half of this sample have an eccentricity >0.1 at 10 Hz. We explicitly show that this derived rate of eccentric mergers is ∼100 times higher than one would find with a purely Newtonian N-body code. Furthermore, we demonstrate that the eccentric fraction can be accurately estimated using a simple analytical formalism when the interacting BHs are of similar mass, a result that serves as the first successful analytical description of eccentric GW mergers forming during three-body interactions in realistic GCs.

Keep it simple - A case study of model development in the context of the Dynamic Stocks and Flows (DSF) task

NASA Astrophysics Data System (ADS)

Halbrügge, Marc

2010-12-01

This paper describes the creation of a cognitive model submitted to the ‘Dynamic Stocks and Flows’ (DSF) modeling challenge. This challenge aims at comparing computational cognitive models for human behavior during an open ended control task. Participants in the modeling competition were provided with a simulation environment and training data for benchmarking their models while the actual specification of the competition task was withheld. To meet this challenge, the cognitive model described here was designed and optimized for generalizability. Only two simple assumptions about human problem solving were used to explain the empirical findings of the training data. In-depth analysis of the data set prior to the development of the model led to the dismissal of correlations or other parametric statistics as goodness-of-fit indicators. A new statistical measurement based on rank orders and sequence matching techniques is being proposed instead. This measurement, when being applied to the human sample, also identifies clusters of subjects that use different strategies for the task. The acceptability of the fits achieved by the model is verified using permutation tests.

Structural and electronic properties for atomic clusters

NASA Astrophysics Data System (ADS)

Sun, Yan

We have studied the structural and electronic properties for different groups of atomic clusters by doing a global search on the potential energy surface using the Taboo Search in Descriptors Space (TSDS) method and calculating the energies with Kohn-Sham Density Functional Theory (KS-DFT). Our goal was to find the structural and electronic principles for predicting the structure and stability of clusters. For Ben (n = 3--20), we have found that the evolution of geometric and electronic properties with size reflects a change in the nature of the bonding from van der Waals to metallic and then bulk-like. The cluster sizes with extra stability agree well with the predictions of the jellium model. In the 4d series of transition metal (TM) clusters, as the d-type bonding becomes more important, the preferred geometric structure changes from icosahedral (Y, Zr), to distorted compact structures (Nb, Mo), and FCC or simple cubic crystal fragments (Tc, Ru, Rh) due to the localized nature of the d-type orbital. Analysis of relative isomer energies and their electronic density of states suggest that these clusters tend to follow a maximum hardness principle (MHP). For A4B12 clusters (A is divalent, B is monovalent), we found unusually large (on average 1.95 eV) HOMO-LUMO gap values. This shows the extra stability at an electronic closed shell (20 electrons) predicted by the jellium model. The importance of symmetry, closed electronic and ionic shells in stability is shown by the relative stability of homotops of Mg4Ag12 which also provides support for the hypothesis that clusters that satisfy more than one stability criterion ("double magic") should be particularly stable.

CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data.

PubMed

Fidaner, Işık Barış; Cankorur-Cetinkaya, Ayca; Dikicioglu, Duygu; Kirdar, Betul; Cemgil, Ali Taylan; Oliver, Stephen G

2016-02-01

Simple bioinformatic tools are frequently used to analyse time-series datasets regardless of their ability to deal with transient phenomena, limiting the meaningful information that may be extracted from them. This situation requires the development and exploitation of tailor-made, easy-to-use and flexible tools designed specifically for the analysis of time-series datasets. We present a novel statistical application called CLUSTERnGO, which uses a model-based clustering algorithm that fulfils this need. This algorithm involves two components of operation. Component 1 constructs a Bayesian non-parametric model (Infinite Mixture of Piecewise Linear Sequences) and Component 2, which applies a novel clustering methodology (Two-Stage Clustering). The software can also assign biological meaning to the identified clusters using an appropriate ontology. It applies multiple hypothesis testing to report the significance of these enrichments. The algorithm has a four-phase pipeline. The application can be executed using either command-line tools or a user-friendly Graphical User Interface. The latter has been developed to address the needs of both specialist and non-specialist users. We use three diverse test cases to demonstrate the flexibility of the proposed strategy. In all cases, CLUSTERnGO not only outperformed existing algorithms in assigning unique GO term enrichments to the identified clusters, but also revealed novel insights regarding the biological systems examined, which were not uncovered in the original publications. The C++ and QT source codes, the GUI applications for Windows, OS X and Linux operating systems and user manual are freely available for download under the GNU GPL v3 license at http://www.cmpe.boun.edu.tr/content/CnG. sgo24@cam.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Measuring the density of a molecular cluster injector via visible emission from an electron beam.

PubMed

Lundberg, D P; Kaita, R; Majeski, R; Stotler, D P

2010-10-01

A method to measure the density distribution of a dense hydrogen gas jet is presented. A Mach 5.5 nozzle is cooled to 80 K to form a flow capable of molecular cluster formation. A 250 V, 10 mA electron beam collides with the jet and produces H(α) emission that is viewed by a fast camera. The high density of the jet, several 10(16) cm(-3), results in substantial electron depletion, which attenuates the H(α) emission. The attenuated emission measurement, combined with a simplified electron-molecule collision model, allows us to determine the molecular density profile via a simple iterative calculation.

A null model for microbial diversification

PubMed Central

Straub, Timothy J.

2017-01-01

Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation (“speciation”). However, observed patterns are rarely compared with those obtainable with simple null models of diversification under stochastic lineage birth and death and random genetic drift. Via a combination of simulations and analyses of core and phylogenetic marker genes, we show that patterns of diversity for the genera Escherichia, Neisseria, and Borrelia are generally indistinguishable from patterns arising under a null model. We suggest that caution should thus be taken in interpreting observed clustering as a result of selective evolutionary forces. Unknown forces do, however, appear to play a role in Helicobacter pylori, and some individual genes in all groups fail to conform to the null model. Taken together, we recommend the presented birth−death model as a null hypothesis in prokaryotic speciation studies. It is only when the real data are statistically different from the expectations under the null model that some speciation process should be invoked. PMID:28630293

Generic Features of Tertiary Chromatin Structure as Detected in Natural Chromosomes

PubMed Central

Müller, Waltraud G.; Rieder, Dietmar; Kreth, Gregor; Cremer, Christoph; Trajanoski, Zlatko; McNally, James G.

2004-01-01

Knowledge of tertiary chromatin structure in mammalian interphase chromosomes is largely derived from artificial tandem arrays. In these model systems, light microscope images reveal fibers or beaded fibers after high-density targeting of transactivators to insertional domains spanning several megabases. These images of fibers have lent support to chromonema fiber models of tertiary structure. To assess the relevance of these studies to natural mammalian chromatin, we identified two different ∼400-kb regions on human chromosomes 6 and 22 and then examined light microscope images of interphase tertiary chromatin structure when the regions were transcriptionally active and inactive. When transcriptionally active, these natural chromosomal regions elongated, yielding images characterized by a series of adjacent puncta or “beads”, referred to hereafter as beaded images. These elongated structures required transcription for their maintenance. Thus, despite marked differences in the density and the mode of transactivation, the natural and artificial systems showed similarities, suggesting that beaded images are generic features of transcriptionally active tertiary chromatin. We show here, however, that these images do not necessarily favor chromonema fiber models but can also be explained by a radial-loop model or even a simple nucleosome affinity, random-chain model. Thus, light microscope images of tertiary structure cannot distinguish among competing models, although they do impose key constraints: chromatin must be clustered to yield beaded images and then packaged within each cluster to enable decondensation into adjacent clusters. PMID:15485905

Percolation on fitness landscapes: effects of correlation, phenotype, and incompatibilities

PubMed Central

Gravner, Janko; Pitman, Damien; Gavrilets, Sergey

2009-01-01

We study how correlations in the random fitness assignment may affect the structure of fitness landscapes, in three classes of fitness models. The first is a phenotype space in which individuals are characterized by a large number n of continuously varying traits. In a simple model of random fitness assignment, viable phenotypes are likely to form a giant connected cluster percolating throughout the phenotype space provided the viability probability is larger than 1/2n. The second model explicitly describes genotype-to-phenotype and phenotype-to-fitness maps, allows for neutrality at both phenotype and fitness levels, and results in a fitness landscape with tunable correlation length. Here, phenotypic neutrality and correlation between fitnesses can reduce the percolation threshold, and correlations at the point of phase transition between local and global are most conducive to the formation of the giant cluster. In the third class of models, particular combinations of alleles or values of phenotypic characters are “incompatible” in the sense that the resulting genotypes or phenotypes have zero fitness. This setting can be viewed as a generalization of the canonical Bateson-Dobzhansky-Muller model of speciation and is related to K- SAT problems, prominent in computer science. We analyze the conditions for the existence of viable genotypes, their number, as well as the structure and the number of connected clusters of viable genotypes. We show that analysis based on expected values can easily lead to wrong conclusions, especially when fitness correlations are strong. We focus on pairwise incompatibilities between diallelic loci, but we also address multiple alleles, complex incompatibilities, and continuous phenotype spaces. In the case of diallelic loci, the number of clusters is stochastically bounded and each cluster contains a very large sub-cube. Finally, we demonstrate that the discrete NK model shares some signature properties of models with high correlations. PMID:17692873

High-redshift Luminous Red Galaxies clustering analysis in SDSS Stripe82

NASA Astrophysics Data System (ADS)

Nikoloudakis, N.

2012-01-01

We have measured the clustering of Luminous Red Galaxies in Stripe 82 using the angular correlation function. We have selected 130000 LRGs via colour cuts in R-I:I-K with the K band data coming from UKIDSS LAS. We have used the cross-correlation technique of Newman (2008) to establish the redshift distribution of the LRGs as a function of colour cut, cross-correlating the LRGs with SDSS QSOs, DEEP2 and VVDS galaxies. We also used the AUS LRG redshift survey to establish the n(z) at z<1. We then compare the w(theta) results to the results of Sawangwit et al (2010) from 3 samples of SDSS LRGs at lower redshift to measure the dependence of clustering on redshift and LRG luminosity. We have compared the results for luminosity-matched LRG samples with simple evolutionary models, such as those expected from long-lived, passive models for LRGs and for the HOD models of Wake et al (2009) and find that the long-lived model may be a poorer fit than at lower redshifts. We find some evidence for evolution in the LRG correlation function slope in that the 2-halo term appears to flatten in slope at z>1. We present arguments that this is not caused by systematics.

Fragment-based {sup 13}C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

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

Hartman, Joshua D.; Beran, Gregory J. O., E-mail: gregory.beran@ucr.edu; Monaco, Stephen

2015-09-14

We assess the quality of fragment-based ab initio isotropic {sup 13}C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic {sup 13}C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readilymore » in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.« less

Neurons in cat V1 show significant clustering by degree of tuning

PubMed Central

Ziskind, Avi J.; Emondi, Al A.; Kurgansky, Andrei V.; Rebrik, Sergei P.

2015-01-01

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29–35% (drifting gratings) or 15–25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs. PMID:25652921

Surface anisotropy of iron oxide nanoparticles and slabs from first principles: Influence of coatings and ligands as a test of the Heisenberg model

NASA Astrophysics Data System (ADS)

Brymora, Katarzyna; Calvayrac, Florent

2017-07-01

We performed ab initio computations of the magnetic properties of simple iron oxide clusters and slabs. We considered an iron oxide cluster functionalized by a molecule or glued to a gold cluster of the same size. We also considered a magnetite slab coated by cobalt oxide or a mixture of iron oxide and cobalt oxide. The changes in magnetic behavior were explored using constrained magnetic calculations. A possible value for the surface anisotropy was estimated from the fit of a classical Heisenberg model on ab initio results. The value was found to be compatible with estimations obtained by other means, or inferred from experimental results. The addition of a ligand, coating, or of a metallic nanoparticle to the systems degraded the quality of the description by the Heisenberg Hamiltonian. Proposing a change in the anisotropies allowing for the proportion of each transition atom we could get a much better description of the magnetism of series of hybrid cobalt and iron oxide systems.

Heavy-ion dominance near Cluster perigees

NASA Astrophysics Data System (ADS)

Ferradas, C. P.; Zhang, J.-C.; Kistler, L. M.; Spence, H. E.

2015-12-01

Time periods in which heavy ions dominate over H+ in the energy range of 1-40 keV were observed by the Cluster Ion Spectrometry (CIS)/COmposition DIstribution Function (CODIF) instrument onboard Cluster Spacecraft 4 at L values less than 4. The characteristic feature is a narrow flux peak at around 10 keV that extends into low L values, with He+ and/or O+ dominating. In the present work we perform a statistical study of these events and examine their temporal occurrence and spatial distribution. The observed features, both the narrow energy range and the heavy-ion dominance, can be interpreted using a model of ion drift from the plasma sheet, subject to charge exchange losses. The narrow energy range corresponds to the only energy range that has direct drift access from the plasma sheet during quiet times. The drift time to these locations from the plasma sheet is > 30 h, so that charge exchange has a significant impact on the population. We show that a simple drift/loss model can explain the dependence on L shell and MLT of these heavy-ion-dominant time periods.

Distribution of nuclei in equilibrium stellar matter from the free-energy density in a Wigner-Seitz cell

NASA Astrophysics Data System (ADS)

Grams, G.; Giraud, S.; Fantina, A. F.; Gulminelli, F.

2018-03-01

The aim of the present study is to calculate the nuclear distribution associated at finite temperature to any given equation of state of stellar matter based on the Wigner-Seitz approximation, for direct applications in core-collapse simulations. The Gibbs free energy of the different configurations is explicitly calculated, with special care devoted to the calculation of rearrangement terms, ensuring thermodynamic consistency. The formalism is illustrated with two different applications. First, we work out the nuclear statistical equilibrium cluster distribution for the Lattimer and Swesty equation of state, widely employed in supernova simulations. Secondly, we explore the effect of including shell structure, and consider realistic nuclear mass tables from the Brussels-Montreal Hartree-Fock-Bogoliubov model (specifically, HFB-24). We show that the whole collapse trajectory is dominated by magic nuclei, with extremely spread and even bimodal distributions of the cluster probability around magic numbers, demonstrating the importance of cluster distributions with realistic mass models in core-collapse simulations. Simple analytical expressions are given, allowing further applications of the method to any relativistic or nonrelativistic subsaturation equation of state.

GEANT4 distributed computing for compact clusters

NASA Astrophysics Data System (ADS)

Harrawood, Brian P.; Agasthya, Greeshma A.; Lakshmanan, Manu N.; Raterman, Gretchen; Kapadia, Anuj J.

2014-11-01

A new technique for distribution of GEANT4 processes is introduced to simplify running a simulation in a parallel environment such as a tightly coupled computer cluster. Using a new C++ class derived from the GEANT4 toolkit, multiple runs forming a single simulation are managed across a local network of computers with a simple inter-node communication protocol. The class is integrated with the GEANT4 toolkit and is designed to scale from a single symmetric multiprocessing (SMP) machine to compact clusters ranging in size from tens to thousands of nodes. User designed 'work tickets' are distributed to clients using a client-server work flow model to specify the parameters for each individual run of the simulation. The new g4DistributedRunManager class was developed and well tested in the course of our Neutron Stimulated Emission Computed Tomography (NSECT) experiments. It will be useful for anyone running GEANT4 for large discrete data sets such as covering a range of angles in computed tomography, calculating dose delivery with multiple fractions or simply speeding the through-put of a single model.

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

PubMed Central

2013-01-01

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

Can group-based reassuring information alter low back pain behavior? A cluster-randomized controlled trial

PubMed Central

Indahl, Aage; Andersen, Lars L.; Burton, Kim; Hertzum-Larsen, Rasmus

2017-01-01

Background Low back pain (LBP) is common in the population and multifactorial in nature, often involving negative consequences. Reassuring information to improve coping is recommended for reducing the negative consequences of LBP. Adding a simple non-threatening explanation for the pain (temporary muscular dysfunction) has been successful at altering beliefs and behavior when delivered with other intervention elements. This study investigates the isolated effect of this specific information on future occupational behavior outcomes when delivered to the workforce. Design A cluster-randomized controlled trial. Methods Publically employed workers (n = 505) from 11 Danish municipality centers were randomized at center-level (cluster) to either intervention (two 1-hour group-based talks at the workplace) or control. The talks provided reassuring information together with a simple non-threatening explanation for LBP—the ‘functional-disturbance’-model. Data collections took place monthly over a 1-year period using text message tracking (SMS). Primary outcomes were self-reported days of cutting down usual activities and work participation. Secondary outcomes were self-reported back beliefs, work ability, number of healthcare visits, bothersomeness, restricted activity, use of pain medication, and sadness/depression. Results There was no between-group difference in the development of LBP during follow-up. Cumulative logistic regression analyses showed no between-group difference on days of cutting down activities, but increased odds for more days of work participation in the intervention group (OR = 1.83 95% CI: 1.08–3.12). Furthermore, the intervention group was more likely to report: higher work ability, reduced visits to healthcare professionals, lower bothersomeness, lower levels of sadness/depression, and positive back beliefs. Conclusion Reassuring information involving a simple non-threatening explanation for LBP significantly increased the odds for days of work participation and higher work ability among workers who went on to experience LBP during the 12-month follow-up. Our results confirm the potential for public-health education for LBP, and add to the discussion of simple versus multidisciplinary interventions. PMID:28346472

Clustering of Farsi sub-word images for whole-book recognition

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2015-01-01

Redundancy of word and sub-word occurrences in large documents can be effectively utilized in an OCR system to improve recognition results. Most OCR systems employ language modeling techniques as a post-processing step; however these techniques do not use important pictorial information that exist in the text image. In case of large-scale recognition of degraded documents, this information is even more valuable. In our previous work, we proposed a subword image clustering method for the applications dealing with large printed documents. In our clustering method, the ideal case is when all equivalent sub-word images lie in one cluster. To overcome the issues of low print quality, the clustering method uses an image matching algorithm for measuring the distance between two sub-word images. The measured distance with a set of simple shape features were used to cluster all sub-word images. In this paper, we analyze the effects of adding more shape features on processing time, purity of clustering, and the final recognition rate. Previously published experiments have shown the efficiency of our method on a book. Here we present extended experimental results and evaluate our method on another book with totally different font face. Also we show that the number of the new created clusters in a page can be used as a criteria for assessing the quality of print and evaluating preprocessing phases.

Effectiveness of Key Knowledge Spreader Identification in Online Communities of Practice: A Simulation Study from Network Perspective

ERIC Educational Resources Information Center

Cao, Yu

2017-01-01

With the rapid development of online communities of practice (CoPs), how to identify key knowledge spreader (KKS) in online CoPs has grown up to be a hot issue. In this paper, we construct a network with variable clustering based on Holme-Kim model to represent CoPs, a simple dynamics of knowledge sharing is considered. Kendall's Tau coefficient…

Synthesis and evaluation of α-Ag2WO4 as novel antifungal agent

NASA Astrophysics Data System (ADS)

Foggi, Camila C.; Fabbro, Maria T.; Santos, Luís P. S.; de Santana, Yuri V. B.; Vergani, Carlos E.; Machado, Ana L.; Cordoncillo, Eloisa; Andrés, Juan; Longo, Elson

2017-04-01

Because of the need for new antifungal materials with greater potency, microcrystals of α-Ag2WO4, a complex metal oxide, have been synthetized by a simple co-precipitation method, and their antifungal activity against Candida albicans has been investigated. A theoretical model based on clusters that are building blocks of α-Ag2WO4 has been proposed to explain the experimental results.

Constraints on Cosmology and Gravity from the Growth of X-ray Luminous Galaxy Clusters

NASA Astrophysics Data System (ADS)

Mantz, Adam; Allen, S. W.; Rapetti, D.; Ebeling, H.; Drlica-Wagner, A.

2010-03-01

I will present simultaneous constraints on galaxy cluster X-ray scaling relations and models of cosmology and gravity obtained from observations of the growth of massive clusters. The data set consists of 238 flux-selected clusters at redshifts z≤0.5 drawn from the ROSAT All-Sky Survey, and incorporates extensive Chandra follow-up observations. Our results on the scaling relations are consistent with excess heating of the intracluster medium, although the evolution of the relations remains consistent with the predictions of simple gravitational collapse models. For spatially flat, constant-w cosmological models, the cluster data yield Ωm=0.23±0.04, σ8=0.82±0.05, and w=-1.01±0.20, including conservative allowances for systematic uncertainties. Our results are consistent and competitive with a variety of independent cosmological data. In evolving-w models, marginalizing over transition redshifts in the range 0.05-1, the combination of the growth of structure data with the cosmic microwave background, supernovae, cluster gas mass fractions and baryon acoustic oscillations constrains the dark energy equation of state at late and early times to be respectively w0=-0.88±0.21 and wet=-1.05+0.20-0.36. Applying this combination of data to the problem of determining fundamental neutrino properties, we place an upper limit on the species-summed neutrino mass at 0.33eV (95% CL) and constrain the effective number of relativistic species to 3.4±0.6. In addition to dark energy and related problems, such data can be used to test the predictions of General Relativity. Introducing the standard Peebles/Linder parametrization of the linear growth rate, we use the cluster data to constrain the growth of structure, independent of the expansion of the Universe. Our analysis provides a tight constraint on the combination γ(σ8/0.8)6.8=0.55+0.13-0.10, and is simultaneously consistent with the predictions of relativity (γ=0.55) and the cosmological constant expansion model. This work was funded by NASA, the U.S. Department of Energy, and Stanford University.

Optical depth in particle-laden turbulent flows

NASA Astrophysics Data System (ADS)

Frankel, A.; Iaccarino, G.; Mani, A.

2017-11-01

Turbulent clustering of particles causes an increase in the radiation transmission through gas-particle mixtures. Attempts to capture the ensemble-averaged transmission lead to a closure problem called the turbulence-radiation interaction. A simple closure model based on the particle radial distribution function is proposed to capture the effect of turbulent fluctuations in the concentration on radiation intensity. The model is validated against a set of particle-resolved ray tracing experiments through particle fields from direct numerical simulations of particle-laden turbulence. The form of the closure model is generalizable to arbitrary stochastic media with known two-point correlation functions.

Fast trimers in a one-dimensional extended Fermi-Hubbard model

NASA Astrophysics Data System (ADS)

Dhar, A.; Törmä, P.; Kinnunen, J. J.

2018-04-01

We consider a one-dimensional two-component extended Fermi-Hubbard model with nearest-neighbor interactions and mass imbalance between the two species. We study the binding energy of trimers, various observables for detecting them, and expansion dynamics. We generalize the definition of the trimer gap to include the formation of different types of clusters originating from nearest-neighbor interactions. Expansion dynamics reveal rapidly propagating trimers, with speeds exceeding doublon propagation in the strongly interacting regime. We present a simple model for understanding this unique feature of the movement of the trimers, and we discuss the potential for experimental realization.

STAR CLUSTERS IN M33: UPDATED UBVRI PHOTOMETRY, AGES, METALLICITIES, AND MASSES

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

Fan, Zhou; De Grijs, Richard, E-mail: zfan@bao.ac.cn, E-mail: grijs@pku.edu.cn

2014-04-01

The photometric characterization of M33 star clusters is far from complete. In this paper, we present homogeneous UBVRI photometry of 708 star clusters and cluster candidates in M33 based on archival images from the Local Group Galaxies Survey, which covers 0.8 deg{sup 2} along the galaxy's major axis. Our photometry includes 387, 563, 616, 580, and 478 objects in the UBVRI bands, respectively, of which 276, 405, 430, 457, and 363 do not have previously published UBVRI photometry. Our photometry is consistent with previous measurements (where available) in all filters. We adopted Sloan Digital Sky Survey ugriz photometry for complementarymore » purposes, as well as Two Micron All Sky Survey near-infrared JHK photometry where available. We fitted the spectral-energy distributions of 671 star clusters and candidates to derive their ages, metallicities, and masses based on the updated PARSEC simple stellar populations synthesis models. The results of our χ{sup 2} minimization routines show that only 205 of the 671 clusters (31%) are older than 2 Gyr, which represents a much smaller fraction of the cluster population than that in M31 (56%), suggesting that M33 is dominated by young star clusters (<1 Gyr). We investigate the mass distributions of the star clusters—both open and globular clusters—in M33, M31, the Milky Way, and the Large Magellanic Cloud. Their mean values are log (M {sub cl}/M {sub ☉}) = 4.25, 5.43, 2.72, and 4.18, respectively. The fraction of open to globular clusters is highest in the Milky Way and lowest in M31. Our comparisons of the cluster ages, masses, and metallicities show that our results are basically in agreement with previous studies (where objects in common are available); differences can be traced back to differences in the models adopted, the fitting methods used, and stochastic sampling effects.« less

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.

PubMed

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-09-07

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications.

Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing

PubMed Central

Udrescu, Lucreţia; Sbârcea, Laura; Topîrceanu, Alexandru; Iovanovici, Alexandru; Kurunczi, Ludovic; Bogdan, Paul; Udrescu, Mihai

2016-01-01

Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new drug discovery tools. We present a new approach to analyzing drug-drug interaction networks, based on clustering and topological community detection techniques that are specific to complex network science. Our methodology uncovers functional drug categories along with the intricate relationships between them. Using modularity-based and energy-model layout community detection algorithms, we link the network clusters to 9 relevant pharmacological properties. Out of the 1141 drugs from the DrugBank 4.1 database, our extensive literature survey and cross-checking with other databases such as Drugs.com, RxList, and DrugBank 4.3 confirm the predicted properties for 85% of the drugs. As such, we argue that network analysis offers a high-level grasp on a wide area of pharmacological aspects, indicating possible unaccounted interactions and missing pharmacological properties that can lead to drug repositioning for the 15% drugs which seem to be inconsistent with the predicted property. Also, by using network centralities, we can rank drugs according to their interaction potential for both simple and complex multi-pathology therapies. Moreover, our clustering approach can be extended for applications such as analyzing drug-target interactions or phenotyping patients in personalized medicine applications. PMID:27599720

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.

Sydney Playground Project: A Cluster-Randomized Trial to Increase Physical Activity, Play, and Social Skills

ERIC Educational Resources Information Center

Bundy, Anita; Engelen, Lina; Wyver, Shirley; Tranter, Paul; Ragen, Jo; Bauman, Adrian; Baur, Louise; Schiller, Wendy; Simpson, Judy M.; Niehues, Anita N.; Perry, Gabrielle; Jessup, Glenda; Naughton, Geraldine

2017-01-01

Background: We assessed the effectiveness of a simple intervention for increasing children's physical activity, play, perceived competence/social acceptance, and social skills. Methods: A cluster-randomized controlled trial was conducted, in which schools were the clusters. Twelve Sydney (Australia) primary schools were randomly allocated to…

Foreshock and aftershocks in simple earthquake models.

PubMed

Kazemian, J; Tiampo, K F; Klein, W; Dominguez, R

2015-02-27

Many models of earthquake faults have been introduced that connect Gutenberg-Richter (GR) scaling to triggering processes. However, natural earthquake fault systems are composed of a variety of different geometries and materials and the associated heterogeneity in physical properties can cause a variety of spatial and temporal behaviors. This raises the question of how the triggering process and the structure interact to produce the observed phenomena. Here we present a simple earthquake fault model based on the Olami-Feder-Christensen and Rundle-Jackson-Brown cellular automata models with long-range interactions that incorporates a fixed percentage of stronger sites, or asperity cells, into the lattice. These asperity cells are significantly stronger than the surrounding lattice sites but eventually rupture when the applied stress reaches their higher threshold stress. The introduction of these spatial heterogeneities results in temporal clustering in the model that mimics that seen in natural fault systems along with GR scaling. In addition, we observe sequences of activity that start with a gradually accelerating number of larger events (foreshocks) prior to a main shock that is followed by a tail of decreasing activity (aftershocks). This work provides further evidence that the spatial and temporal patterns observed in natural seismicity are strongly influenced by the underlying physical properties and are not solely the result of a simple cascade mechanism.

Analytics For Distracted Driver Behavior Modeling in Dilemma Zone

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

Li, Jan-Mou; Malikopoulos, Andreas; Thakur, Gautam

2014-01-01

In this paper, we present the results obtained and insights gained through the analysis of TRB contest data. We used exploratory analysis, regression, and clustering models for gaining insights into the driver behavior in a dilemma zone while driving under distraction. While simple exploratory analysis showed the distinguishing driver behavior patterns among different popu- lation groups in the dilemma zone, regression analysis showed statically signification relationships between groups of variables. In addition to analyzing the contest data, we have also looked into the possible impact of distracted driving on the fuel economy.

Probing primordial features with future galaxy surveys

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

Ballardini, M.; Fedeli, C.; Moscardini, L.

2016-10-01

We study the capability of future measurements of the galaxy clustering power spectrum to probe departures from a power-law spectrum for primordial fluctuations. On considering the information from the galaxy clustering power spectrum up to quasi-linear scales, i.e. k < 0.1 h Mpc{sup −1}, we present forecasts for DESI, Euclid and SPHEREx in combination with CMB measurements. As examples of departures in the primordial power spectrum from a simple power-law, we consider four Planck 2015 best-fits motivated by inflationary models with different breaking of the slow-roll approximation. At present, these four representative models provide an improved fit to CMB temperaturemore » anisotropies, although not at statistical significant level. As for other extensions in the matter content of the simplest ΛCDM model, the complementarity of the information in the resulting matter power spectrum expected from these galaxy surveys and in the primordial power spectrum from CMB anisotropies can be effective in constraining cosmological models. We find that the three galaxy surveys can add significant information to CMB to better constrain the extra parameters of the four models considered.« less

Targeting excited states in all-trans polyenes with electron-pair states.

PubMed

Boguslawski, Katharina

2016-12-21

Wavefunctions restricted to electron pair states are promising models for strongly correlated systems. Specifically, the pair Coupled Cluster Doubles (pCCD) ansatz allows us to accurately describe bond dissociation processes and heavy-element containing compounds with multiple quasi-degenerate single-particle states. Here, we extend the pCCD method to model excited states using the equation of motion (EOM) formalism. As the cluster operator of pCCD is restricted to electron-pair excitations, EOM-pCCD allows us to target excited electron-pair states only. To model singly excited states within EOM-pCCD, we modify the configuration interaction ansatz of EOM-pCCD to contain also single excitations. Our proposed model represents a simple and cost-effective alternative to conventional EOM-CC methods to study singly excited electronic states. The performance of the excited state models is assessed against the lowest-lying excited states of the uranyl cation and the two lowest-lying excited states of all-trans polyenes. Our numerical results suggest that EOM-pCCD including single excitations is a good starting point to target singly excited states.

Atomic clusters and atomic surfaces in icosahedral quasicrystals.

PubMed

Quiquandon, Marianne; Portier, Richard; Gratias, Denis

2014-05-01

This paper presents the basic tools commonly used to describe the atomic structures of quasicrystals with a specific focus on the icosahedral phases. After a brief recall of the main properties of quasiperiodic objects, two simple physical rules are discussed that lead one to eventually obtain a surprisingly small number of atomic structures as ideal quasiperiodic models for real quasicrystals. This is due to the fact that the atomic surfaces (ASs) used to describe all known icosahedral phases are located on high-symmetry special points in six-dimensional space. The first rule is maximizing the density using simple polyhedral ASs that leads to two possible sets of ASs according to the value of the six-dimensional lattice parameter A between 0.63 and 0.79 nm. The second rule is maximizing the number of complete orbits of high symmetry to construct as large as possible atomic clusters similar to those observed in complex intermetallic structures and approximant phases. The practical use of these two rules together is demonstrated on two typical examples of icosahedral phases, i-AlMnSi and i-CdRE (RE = Gd, Ho, Tm).

Simplicity and efficiency of integrate-and-fire neuron models.

PubMed

Plesser, Hans E; Diesmann, Markus

2009-02-01

Lovelace and Cios (2008) recently proposed a very simple spiking neuron (VSSN) model for simulations of large neuronal networks as an efficient replacement for the integrate-and-fire neuron model. We argue that the VSSN model falls behind key advances in neuronal network modeling over the past 20 years, in particular, techniques that permit simulators to compute the state of the neuron without repeated summation over the history of input spikes and to integrate the subthreshold dynamics exactly. State-of-the-art solvers for networks of integrate-and-fire model neurons are substantially more efficient than the VSSN simulator and allow routine simulations of networks of some 10(5) neurons and 10(9) connections on moderate computer clusters.

CO2 Cluster Ion Beam, an Alternative Projectile for Secondary Ion Mass Spectrometry.

PubMed

Tian, Hua; Maciążek, Dawid; Postawa, Zbigniew; Garrison, Barbara J; Winograd, Nicholas

2016-09-01

The emergence of argon-based gas cluster ion beams for SIMS experiments opens new possibilities for molecular depth profiling and 3D chemical imaging. These beams generally leave less surface chemical damage and yield mass spectra with reduced fragmentation compared with smaller cluster projectiles. For nanoscale bioimaging applications, however, limited sensitivity due to low ionization probability and technical challenges of beam focusing remain problematic. The use of gas cluster ion beams based upon systems other than argon offer an opportunity to resolve these difficulties. Here we report on the prospects of employing CO2 as a simple alternative to argon. Ionization efficiency, chemical damage, sputter rate, and beam focus are investigated on model compounds using a series of CO2 and Ar cluster projectiles (cluster size 1000-5000) with the same mass. The results show that the two projectiles are very similar in each of these aspects. Computer simulations comparing the impact of Ar2000 and (CO2)2000 on an organic target also confirm that the CO2 molecules in the cluster projectile remain intact, acting as a single particle of m/z 44. The imaging resolution employing CO2 cluster projectiles is improved by more than a factor of two. The advantage of CO2 versus Ar is also related to the increased stability which, in addition, facilitates the operation of the gas cluster ion beams (GCIB) system at lower backing pressure. Graphical Abstract ᅟ.

DNA damage induced by the direct effect of radiation

NASA Astrophysics Data System (ADS)

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

2008-10-01

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

Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System

NASA Astrophysics Data System (ADS)

Demirdjian, L.; Zhou, Y.; Huffman, G. J.

2016-12-01

This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.

The Spatial Scale of Convective Aggregation in Cloud Resolving Simulations of Radiative Convective Equilibrium

NASA Astrophysics Data System (ADS)

Patrizio, Casey

A three-dimensional cloud-resolving model (CRM) was used to investigate the preferred separation distance between humid, rainy regions formed by convective aggregation in radiative-convective equilibrium without rotation. We performed the simulations with doubly-periodic square domains of widths 768 km, 1536 km and 3072 km over a time period of about 200 days. The simulations in the larger domains were initialized using multiple copies of the results in the small domain at day 90, plus a small perturbation. With all three domain sizes, the simulations evolved to a single statistically steady convective cluster surrounded by a broader region of dry, subsiding air by about day 150. In the largest domain case, however, we found that an additional convective cluster formed when we the simulation was run for an extended period of time. Specifically, a smaller convective cluster formed at around day 185 at a maximum radial distance from the larger cluster and then re-merged with the larger cluster after about 10 days. We explored how the aggregated state was different in each domain case, before the smaller cluster formed in the large domain. In particular, we investigated changes in the radial structure of the aggregated state by calculating profiles for the water, dynamics and radiation as a function of distance from the center of the convective region. Changes in the vertical structure were also investigated by compositing on the convective region and dry, subsiding region at each height. We found that, with increasing domain size, the convective region boundary layer became more buoyant, the convective cores reached deeper into the troposphere, the mesoscale convective updraft became weaker, and the mesoscale convective region spread out. Additionally, as the domain size was increased, conditions in the remote environment became favorable for convection. We describe a physical mechanism for the weakening of the mesoscale convective updraft and associated broadening of the convective region with increasing domain size, which involves mid-level stable layer enhancement as a result of the deeper convection. Finally, a simple analytical model of the aggregated state was used to explore the dependency of the convective fractional area on the domain size. The simple model solutions that had net radiative cooling and surface evaporation in the convective region were consistent with the simulation results. In particular, the solutions captured the broadening of the convective region, the weakening of the convective region updraft, as well as the positive and declining gross moist stability (GMS) that occurred with increasing domain size in the simulations. Furthermore, the simple model transitioned from positive to negative GMS at a domain length of about 7000 km because the convective region boundary layer became progressively more humid with increasing domain size. This suggests that the spatial scale of the aggregated RCE state in the simulations would be limited to a length scale of about 7000 km, as convectively-active areas are commonly observed to have positive GMS. This work additionally suggests that the processes that influence the water vapor content in the convective region boundary layer, such as convectively-driven turbulent water vapor fluxes, are important for determining the spatial scale of the aggregated RCE state.

Stability and dynamic of strain mediated adatom superlattices on Cu<111 >

NASA Astrophysics Data System (ADS)

Kappus, Wolfgang

2013-03-01

Substrate strain mediated adatom equilibrium density distributions have been calculated for Cu<111 > surfaces using two complementing methods. A hexagonal adatom superlattice in a coverage range up to 0.045 ML is derived for repulsive short range interactions. For zero short range interactions a hexagonal superstructure of adatom clusters is derived in a coverage range about 0.08 ML. Conditions for the stability of the superlattice against formation of dimers or clusters and degradation are analyzed using simple neighborhood models. Such models are also used to investigate the dynamic of adatoms within their superlattice neighborhood. Collective modes of adatom diffusion are proposed from the analogy with bulk lattice dynamics and methods for measurement are suggested. The recently put forward explanation of surface state mediated interactions for superstructures found in scanning tunneling microscopy experiments is put in question and strain mediated interactions are proposed as an alternative.

Critical properties of unlimited gliding: Unexpected flocking behavior driven by the exchange of information

NASA Astrophysics Data System (ADS)

Bigus-Kwiatkowska, Marta; Fronczak, Agata; Fronczak, Piotr

2018-03-01

Inspired by albatrosses that use thermal lifts to fly across oceans we develop a simple model of gliders that serves us to study theoretical limitations of unlimited exploration of the Earth. Our studies, grounded in physical theory of continuous percolation and biased random walks, allow us to identify a variety of percolation transitions, which are understood as providing potentially unlimited movement through a space in a specified direction. We discover an unexpected phenomenon of self-organization of gliders in clusters, which resembles the flock organization of birds. This self-organization is intriguing, as it occurs thanks to exchange of information only and without any particular rules that could favor the clustering of the gliders (in contrast to the causes well known in literature, like, for example, attractive forces used in the Vicsek-type models or fitness functions used in evolutionary computation).

Bayesian Analysis and Characterization of Multiple Populations in Galactic Globular Clusters

NASA Astrophysics Data System (ADS)

Wagner-Kaiser, Rachel A.; Stenning, David; Sarajedini, Ata; von Hippel, Ted; van Dyk, David A.; Robinson, Elliot; Stein, Nathan; Jefferys, William H.; BASE-9, HST UVIS Globular Cluster Treasury Program

2017-01-01

Globular clusters have long been important tools to unlock the early history of galaxies. Thus, it is crucial we understand the formation and characteristics of the globular clusters (GCs) themselves. Historically, GCs were thought to be simple and largely homogeneous populations, formed via collapse of a single molecular cloud. However, this classical view has been overwhelmingly invalidated by recent work. It is now clear that the vast majority of globular clusters in our Galaxy host two or more chemically distinct populations of stars, with variations in helium and light elements at discrete abundance levels. No coherent story has arisen that is able to fully explain the formation of multiple populations in globular clusters nor the mechanisms that drive stochastic variations from cluster to cluster.We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival ACS Treasury observations of 30 Galactic Globular Clusters to characterize two distinct stellar populations. A sophisticated Bayesian technique is employed to simultaneously sample the joint posterior distribution of age, distance, and extinction for each cluster, as well as unique helium values for two populations within each cluster and the relative proportion of those populations. We find the helium differences among the two populations in the clusters fall in the range of 0.04 to 0.11. Because adequate models varying in CNO are not presently available, we view these spreads as upper limits and present them with statistical rather than observational uncertainties. Evidence supports previous studies suggesting an increase in helium content concurrent with increasing mass of the cluster. We also find that the proportion of the first population of stars increases with mass. Our results are examined in the context of proposed globular cluster formation scenarios.

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

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

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

A Cluster Analysis of Tic Symptoms in Children and Adults with Tourette Syndrome: Clinical Correlates and Treatment Outcome

PubMed Central

McGuire, Joseph F.; Nyirabahizi, Epiphanie; Kircanski, Katharina; Piacentini, John; Peterson, Alan L.; Woods, Douglas W.; Wilhelm, Sabine; Walkup, John T.; Scahill, Lawrence

2013-01-01

Cluster analytic methods have examined the symptom presentation of chronic tic disorders (CTDs), with limited agreement across studies. The present study investigated patterns, clinical correlates, and treatment outcome of tic symptoms. 239 youth and adults with CTDs completed a battery of assessments at baseline to determine diagnoses, tic severity, and clinical characteristics. Participants were randomly assigned to receive either a comprehensive behavioral intervention for tics (CBIT) or psychoeducation and supportive therapy (PST). A cluster analysis was conducted on the baseline Yale Global Tic Severity Scale (YGTSS) symptom checklist to identify the constellations of tic symptoms. Four tic clusters were identified: Impulse Control and Complex Phonic Tics; Complex Motor Tics; Simple Head Motor/Vocal Tics; and Primarily Simple Motor Tics. Frequencies of tic symptoms showed few differences across youth and adults. Tic clusters had small associations with clinical characteristics and showed no associations to the presence of coexisting psychiatric conditions. Cluster membership scores did not predict treatment response to CBIT or tic severity reductions. Tic symptoms distinctly cluster with few difference across youth and adults, or coexisting conditions. This study, which is the first to examine tic clusters in relation to treatment, suggested that tic symptom profiles respond equally well to CBIT. PMID:24144615

Assessing map accuracy in a remotely sensed, ecoregion-scale cover map

USGS Publications Warehouse

Edwards, T.C.; Moisen, Gretchen G.; Cutler, D.R.

1998-01-01

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from these efforts is how best to assess the accuracy of the cover maps, especially when they can exceed 1000 s/km2 in size. Here we develop and describe a methodological approach for assessing the accuracy of large-area cover maps, using as a test case the 21.9 million ha cover map developed for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost function on the relative efficiency of cluster sample designs to simple random designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility (hereafter a mixed design). We next outline estimation formulas for simple map accuracy measures under our mixed design and report results for eight major cover types and the three ecoregions mapped as part of the Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by cover type varied, ranging from a low of 50.4% for barren to a high of 90.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In regard to precision, our mixed design was more precise than a simple random design, given fixed sample costs. We close with a discussion of the logistical constraints facing attempts to assess the accuracy of large-area, remotely sensed cover maps.

Cancerous tumor: the high frequency of a rare event.

PubMed

Galam, S; Radomski, J P

2001-05-01

A simple model for cancer growth is presented using cellular automata. Cells diffuse randomly on a two-dimensional square lattice. Individual cells can turn cancerous at a very low rate. During each diffusive step, local fights may occur between healthy and cancerous cells. Associated outcomes depend on some biased local rules, which are independent of the overall cancerous cell density. The models unique ingredients are the frequency of local fights and the bias amplitude. While each isolated cancerous cell is eventually destroyed, an initial two-cell tumor cluster is found to have a nonzero probabilty to spread over the whole system. The associated phase diagram for survival or death is obtained as a function of both the rate of fight and the bias distribution. Within the model, although the occurrence of a killing cluster is a very rare event, it turns out to happen almost systematically over long periods of time, e.g., on the order of an adults life span. Thus, after some age, survival from tumorous cancer becomes random.

Cluster dynamics modeling and experimental investigation of the effect of injected interstitials

NASA Astrophysics Data System (ADS)

Michaut, B.; Jourdan, T.; Malaplate, J.; Renault-Laborne, A.; Sefta, F.; Décamps, B.

2017-12-01

The effect of injected interstitials on loop and cavity microstructures is investigated experimentally and numerically for 304L austenitic stainless steel irradiated at 450 °C with 10 MeV Fe5+ ions up to about 100 dpa. A cluster dynamics model is parametrized on experimental results obtained by transmission electron microscopy (TEM) in a region where injected interstitials can be safely neglected. It is then used to model the damage profile and study the impact of self-ion injection. Results are compared to TEM observations on cross-sections of specimens. It is shown that injected interstitials have a significant effect on cavity density and mean size, even in the sink-dominated regime. To quantitatively match the experimental data in the self-ions injected area, a variation of some parameters is necessary. We propose that the fraction of freely migrating species may vary as a function of depth. Finally, we show that simple rate theory considerations do not seem to be valid for these experimental conditions.

A stochastic reaction-diffusion model for protein aggregation on DNA

NASA Astrophysics Data System (ADS)

Voulgarakis, Nikolaos K.

Vital functions of DNA, such as transcription and packaging, depend on the proper clustering of proteins on the double strand. The present study investigates how the interplay between DNA allostery and electrostatic interactions affects protein clustering. The statistical analysis of a simple but transparent computational model reveals two major consequences of this interplay. First, depending on the protein and salt concentration, protein filaments exhibit a bimodal DNA stiffening and softening behavior. Second, within a certain domain of the control parameters, electrostatic interactions can cause energetic frustration that forces proteins to assemble in rigid spiral configurations. Such spiral filaments might trigger both positive and negative supercoiling, which can ultimately promote gene compaction and regulate the promoter. It has been experimentally shown that bacterial histone-like proteins assemble in similar spiral patterns and/or exhibit the same bimodal behavior. The proposed model can, thus, provide computational insights into the physical mechanisms used by proteins to control the mechanical properties of the DNA.

Automated clustering-based workload characterization

NASA Technical Reports Server (NTRS)

Pentakalos, Odysseas I.; Menasce, Daniel A.; Yesha, Yelena

1996-01-01

The demands placed on the mass storage systems at various federal agencies and national laboratories are continuously increasing in intensity. This forces system managers to constantly monitor the system, evaluate the demand placed on it, and tune it appropriately using either heuristics based on experience or analytic models. Performance models require an accurate workload characterization. This can be a laborious and time consuming process. It became evident from our experience that a tool is necessary to automate the workload characterization process. This paper presents the design and discusses the implementation of a tool for workload characterization of mass storage systems. The main features of the tool discussed here are: (1)Automatic support for peak-period determination. Histograms of system activity are generated and presented to the user for peak-period determination; (2) Automatic clustering analysis. The data collected from the mass storage system logs is clustered using clustering algorithms and tightness measures to limit the number of generated clusters; (3) Reporting of varied file statistics. The tool computes several statistics on file sizes such as average, standard deviation, minimum, maximum, frequency, as well as average transfer time. These statistics are given on a per cluster basis; (4) Portability. The tool can easily be used to characterize the workload in mass storage systems of different vendors. The user needs to specify through a simple log description language how the a specific log should be interpreted. The rest of this paper is organized as follows. Section two presents basic concepts in workload characterization as they apply to mass storage systems. Section three describes clustering algorithms and tightness measures. The following section presents the architecture of the tool. Section five presents some results of workload characterization using the tool.Finally, section six presents some concluding remarks.

Spectroscopic study of formation, evolution and interaction of M31 and M33 with star clusters

NASA Astrophysics Data System (ADS)

Fan, Zhou; Yang, Yanbin

2016-02-01

The recent studies show that the formation and evolution process of the nearby galaxies are still unclear. By using the Canada France Hawaii Telescope (CFHT) 3.6m telescope, the PanDAS shows complicated substructures (dwarf satellite galaxies, halo globular clusters, extended clusters, star streams, etc.) in the halo of M31 to ~150 kpc from the center of galaxy and M31-M33 interaction has been studied. In our work, we would like to investigate formation, evolution and interaction of M31 and M33, which are the nearest two spiral galaxies in Local Group. The star cluster systems of the two galaxies are good tracers to study the dynamics of the substructures and the interaction. Since 2010, the Xinglong 2.16m, Lijiang 2.4m and MMT 6.5m telescopes have been used for our spectroscopic observations. The radial velocities and Lick absorption-line indices can thus be measured with the spectroscopy and then ages, metallicities and masses of the star clusters can be fitted with the simple stellar population models. These parameters could be used as the input physical parameters for numerical simulations of M31-M33 interaction.

Electric-field–induced assembly and propulsion of chiral colloidal clusters

PubMed Central

Ma, Fuduo; Wang, Sijia; Wu, David T.; Wu, Ning

2015-01-01

Chiral molecules with opposite handedness exhibit distinct physical, chemical, or biological properties. They pose challenges as well as opportunities in understanding the phase behavior of soft matter, designing enantioselective catalysts, and manufacturing single-handed pharmaceuticals. Microscopic particles, arranged in a chiral configuration, could also exhibit unusual optical, electric, or magnetic responses. Here we report a simple method to assemble achiral building blocks, i.e., the asymmetric colloidal dimers, into a family of chiral clusters. Under alternating current electric fields, two to four lying dimers associate closely with a central standing dimer and form both right- and left-handed clusters on a conducting substrate. The cluster configuration is primarily determined by the induced dipolar interactions between constituent dimers. Our theoretical model reveals that in-plane dipolar repulsion between petals in the cluster favors the achiral configuration, whereas out-of-plane attraction between the central dimer and surrounding petals favors a chiral arrangement. It is the competition between these two interactions that dictates the final configuration. The theoretical chirality phase diagram is found to be in excellent agreement with experimental observations. We further demonstrate that the broken symmetry in chiral clusters induces an unbalanced electrohydrodynamic flow surrounding them. As a result, they rotate in opposite directions according to their handedness. Both the assembly and propulsion mechanisms revealed here can be potentially applied to other types of asymmetric particles. Such kinds of chiral colloids will be useful for fabricating metamaterials, making model systems for both chiral molecules and active matter, or building propellers for microscale transport. PMID:25941383

Under What Circumstances Does External Knowledge about the Correlation Structure Improve Power in Cluster Randomized Designs?

ERIC Educational Resources Information Center

Rhoads, Christopher

2014-01-01

Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…

Kinematics and dynamics of the MKW/AWM poor clusters

NASA Technical Reports Server (NTRS)

Beers, Timothy C.; Kriessler, Jeffrey R.; Bird, Christina M.; Huchra, John P.

1995-01-01

We report 472 new redshifts for 416 galaxies in the regions of the 23 poor clusters of galaxies originally identified by Morgan, Kayser, and White (MKW), and Albert, White, and Morgan (AWM). Eighteen of the poor clusters now have 10 or more available redshifts within 1.5/h Mpc of the central galaxy; 11 clusters have at least 20 available redshifts. Based on the 21 clusters for which we have sufficient velocity information, the median velocity scale is 336 km/s, a factor of 2 smaller than found for rich clusters. Several of the poor clusters exhibit complex velocity distributions due to the presence of nearby clumps of galaxies. We check on the velocity of the dominant galaxy in each poor cluster relative to the remaining cluster members. Significantly high relative velocities of the dominant galaxy are found in only 4 of 21 poor clusters, 3 of which we suspect are due to contamination of the parent velocity distribution. Several statistical tests indicate that the D/cD galaxies are at the kinematic centers of the parent poor cluster velocity distributions. Mass-to-light ratios for 13 of the 15 poor clusters for which we have the required data are in the range 50 less than or = M/L(sub B(0)) less than or = 200 solar mass/solar luminosity. The complex nature of the regions surrounding many of the poor clusters suggests that these groupings may represent an early epoch of cluster formation. For example, the poor clusters MKW7 and MKWS are shown to be gravitationally bound and likely to merge to form a richer cluster within the next several Gyrs. Eight of the nine other poor clusters for which simple two-body dynamical models can be carried out are consistent with being bound to other clumps in their vicinity. Additional complex systems with more than two gravitationally bound clumps are observed among the poor clusters.

A TALE OF DWARFS AND GIANTS: USING A z = 1.62 CLUSTER TO UNDERSTAND HOW THE RED SEQUENCE GREW OVER THE LAST 9.5 BILLION YEARS

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

Rudnick, Gregory H.; Tran, Kim-Vy; Papovich, Casey

2012-08-10

We study the red sequence in a cluster of galaxies at z = 1.62 and follow its evolution over the intervening 9.5 Gyr to the present day. Using deep YJK{sub s} imaging with the HAWK-I instrument on the Very Large Telescope, we identify a tight red sequence and construct its rest-frame i-band luminosity function (LF). There is a marked deficit of faint red galaxies in the cluster that causes a turnover in the LF. We compare the red-sequence LF to that for clusters at z < 0.8, correcting the luminosities for passive evolution. The shape of the cluster red-sequence LFmore » does not evolve between z = 1.62 and z = 0.6 but at z < 0.6 the faint population builds up significantly. Meanwhile, between z = 1.62 and 0.6 the inferred total light on the red sequence grows by a factor of {approx}2 and the bright end of the LF becomes more populated. We construct a simple model for red-sequence evolution that grows the red sequence in total luminosity and matches the constant LF shape at z > 0.6. In this model the cluster accretes blue galaxies from the field whose star formation is quenched and who are subsequently allowed to merge. We find that three to four mergers among cluster galaxies during the 4 Gyr between z = 1.62 and z = 0.6 match the observed LF evolution between the two redshifts. The inferred merger rate is consistent with other studies of this cluster. Our result supports the picture that galaxy merging during the major growth phase of massive clusters is an important process in shaping the red-sequence population at all luminosities.« less

A Simple MO Treatment of Metal Clusters.

ERIC Educational Resources Information Center

Sahyun, M. R. V.

1980-01-01

Illustrates how a qualitative description of the geometry and electronic characteristics of homogeneous metal clusters can be obtained using semiempirical MO (molecular orbital theory) methods. Computer applications of MO methods to inorganic systems are also described. (CS)

Satellite quenching time-scales in clusters from projected phase space measurements matched to simulated orbits

NASA Astrophysics Data System (ADS)

Oman, Kyle A.; Hudson, Michael J.

2016-12-01

We measure the star formation quenching efficiency and time-scale in cluster environments. Our method uses N-body simulations to estimate the probability distribution of possible orbits for a sample of observed Sloan Digital Sky Survey galaxies in and around clusters based on their position and velocity offsets from their host cluster. We study the relationship between their star formation rates and their likely orbital histories via a simple model in which star formation is quenched once a delay time after infall has elapsed. Our orbit library method is designed to isolate the environmental effect on the star formation rate due to a galaxy's present-day host cluster from `pre-processing' in previous group hosts. We find that quenching of satellite galaxies of all stellar masses in our sample (109-10^{11.5}M_{⊙}) by massive (> 10^{13} M_{⊙}) clusters is essentially 100 per cent efficient. Our fits show that all galaxies quench on their first infall, approximately at or within a Gyr of their first pericentric passage. There is little variation in the onset of quenching from galaxy-to-galaxy: the spread in this time is at most ˜2 Gyr at fixed M*. Higher mass satellites quench earlier, with very little dependence on host cluster mass in the range probed by our sample.

Medical image segmentation based on SLIC superpixels model

NASA Astrophysics Data System (ADS)

Chen, Xiang-ting; Zhang, Fan; Zhang, Ruo-ya

2017-01-01

Medical imaging has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, medical images have many unstable factors such as complex imaging mechanism, the target displacement will cause constructed defect and the partial volume effect will lead to error and equipment wear, which increases the complexity of subsequent image processing greatly. The segmentation algorithm which based on SLIC (Simple Linear Iterative Clustering, SLIC) superpixels is used to eliminate the influence of constructed defect and noise by means of the feature similarity in the preprocessing stage. At the same time, excellent clustering effect can reduce the complexity of the algorithm extremely, which provides an effective basis for the rapid diagnosis of experts.

Measurement of the relaxation rate of the magnetization in Mn12O12-acetate using proton NMR echo

PubMed

Jang; Lascialfari; Borsa; Gatteschi

2000-03-27

We present a novel method to measure the relaxation rate W of the magnetization of Mn 12O (12)-acetate (Mn12) magnetic molecular cluster in its S = 10 ground state at low T. It is based on the observation of an exponential growth in time of the proton NMR signal during the thermal equilibration of the magnetization of the molecules. We can explain the novel effect with a simple model which relates the intensity of the proton echo signal to the microscopic reversal of the magnetization of each individual Mn12 molecule during the equilibration process. The method should find wide application in the study of magnetic molecular clusters in off-equilibrium conditions.

Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME.

PubMed

Reboul, Cyril F; Eager, Michael; Elmlund, Dominika; Elmlund, Hans

2018-01-01

Cryogenic electron microscopy (cryo-EM) and single-particle analysis now enables the determination of high-resolution structures of macromolecular assemblies that have resisted X-ray crystallography and other approaches. We developed the SIMPLE open-source image-processing suite for analysing cryo-EM images of single-particles. A core component of SIMPLE is the probabilistic PRIME algorithm for identifying clusters of images in 2D and determine relative orientations of single-particle projections in 3D. Here, we extend our previous work on PRIME and introduce new stochastic optimization algorithms that improve the robustness of the approach. Our refined method for identification of homogeneous subsets of images in accurate register substantially improves the resolution of the cluster centers and of the ab initio 3D reconstructions derived from them. We now obtain maps with a resolution better than 10 Å by exclusively processing cluster centers. Excellent parallel code performance on over-the-counter laptops and CPU workstations is demonstrated. © 2017 The Protein Society.

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

NASA Astrophysics Data System (ADS)

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

2017-11-01

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, DN ˜ N-β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for "perfect" sizes Np = L2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for Np+3, Np+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes Np+1 and Np+2. DN versus N oscillates strongly between the slowest branch (for Np+3) and the fastest branch (for Np+1). All branches merge for N = O(102), but macroscale behavior is only achieved for much larger N = O(103). This analysis reveals the unprecedented diversity of behavior on the nanoscale.

Clustering method for counting passengers getting in a bus with single camera

NASA Astrophysics Data System (ADS)

Yang, Tao; Zhang, Yanning; Shao, Dapei; Li, Ying

2010-03-01

Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.

Dielectric aggregation kinetics of cells in a uniform AC electric field.

PubMed

Tada, Shigeru; Natsuya, Tomoyuki; Tsukamoto, Akira

2014-01-01

Cell manipulation and separation technologies have potential biological and medical applications, including advanced clinical protocols such as tissue engineering. An aggregation model was developed for a human carcinoma (HeLa) cell suspension exposed to a uniform AC electric field, in order to explore the field-induced structure formation and kinetics of cell aggregates. The momentum equations of cells under the action of the dipole-dipole interaction were solved theoretically and the total time required to form linear string-like cluster was derived. The results were compared with those of a numerical simulation. Experiments using HeLa cells were also performed for comparison. The total time required to form linear string-like clusters was derived from a simple theoretical model of the cell cluster kinetics. The growth rates of the average string length of cell aggregates showed good agreement with those of the numerical simulation. In the experiment, cells were found to form massive clusters on the bottom of a chamber. The results imply that the string-like cluster grows rapidly by longitudinal attraction when the electric field is first applied and that this process slows at later times and is replaced by lateral coagulation of short strings. The findings presented here are expected to enable design of methods for the organization of three-dimensional (3D) cellular structures without the use of micro-fabricated substrates, such as 3D biopolymer scaffolds, to manipulate cells into spatial arrangement.

The geometry of chaotic dynamics — a complex network perspective

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Lipid Clustering Correlates with Membrane Curvature as Revealed by Molecular Simulations of Complex Lipid Bilayers

PubMed Central

Koldsø, Heidi; Shorthouse, David; Hélie, Jean; Sansom, Mark S. P.

2014-01-01

Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins. PMID:25340788

Lipid clustering correlates with membrane curvature as revealed by molecular simulations of complex lipid bilayers.

PubMed

Koldsø, Heidi; Shorthouse, David; Hélie, Jean; Sansom, Mark S P

2014-10-01

Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.

Black Hole Mergers in Galactic Nuclei Induced by the Eccentric Kozai–Lidov Effect

NASA Astrophysics Data System (ADS)

Hoang, Bao-Minh; Naoz, Smadar; Kocsis, Bence; Rasio, Frederic A.; Dosopoulou, Fani

2018-04-01

Nuclear star clusters around a central massive black hole (MBH) are expected to be abundant in stellar black hole (BH) remnants and BH–BH binaries. These binaries form a hierarchical triple system with the central MBH, and gravitational perturbations from the MBH can cause high-eccentricity excitation in the BH–BH binary orbit. During this process, the eccentricity may approach unity, and the pericenter distance may become sufficiently small so that gravitational-wave emission drives the BH–BH binary to merge. In this work, we construct a simple proof-of-concept model for this process, and specifically, we study the eccentric Kozai–Lidov mechanism in unequal-mass, soft BH–BH binaries. Our model is based on a set of Monte Carlo simulations for BH–BH binaries in galactic nuclei, taking into account quadrupole- and octupole-level secular perturbations, general relativistic precession, and gravitational-wave emission. For a typical steady-state number of BH–BH binaries, our model predicts a total merger rate of ∼1–3 {Gpc} ‑3 {yr} ‑1, depending on the assumed density profile in the nucleus. Thus, our mechanism could potentially compete with other dynamical formation processes for merging BH–BH binaries, such as the interactions of stellar BHs in globular clusters or in nuclear star clusters without an MBH.

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.

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.

Optimal Cluster Mill Pass Scheduling With an Accurate and Rapid New Strip Crown Model

NASA Astrophysics Data System (ADS)

Malik, Arif S.; Grandhi, Ramana V.; Zipf, Mark E.

2007-05-01

Besides the requirement to roll coiled sheet at high levels of productivity, the optimal pass scheduling of cluster-type reversing cold mills presents the added challenge of assigning mill parameters that facilitate the best possible strip flatness. The pressures of intense global competition, and the requirements for increasingly thinner, higher quality specialty sheet products that are more difficult to roll, continue to force metal producers to commission innovative flatness-control technologies. This means that during the on-line computerized set-up of rolling mills, the mathematical model should not only determine the minimum total number of passes and maximum rolling speed, it should simultaneously optimize the pass-schedule so that desired flatness is assured, either by manual or automated means. In many cases today, however, on-line prediction of strip crown and corresponding flatness for the complex cluster-type rolling mills is typically addressed either by trial and error, by approximate deflection models for equivalent vertical roll-stacks, or by non-physical pattern recognition style models. The abundance of the aforementioned methods is largely due to the complexity of cluster-type mill configurations and the lack of deflection models with sufficient accuracy and speed for on-line use. Without adequate assignment of the pass-schedule set-up parameters, it may be difficult or impossible to achieve the required strip flatness. In this paper, we demonstrate optimization of cluster mill pass-schedules using a new accurate and rapid strip crown model. This pass-schedule optimization includes computations of the predicted strip thickness profile to validate mathematical constraints. In contrast to many of the existing methods for on-line prediction of strip crown and flatness on cluster mills, the demonstrated method requires minimal prior tuning and no extensive training with collected mill data. To rapidly and accurately solve the multi-contact problem and predict the strip crown, a new customized semi-analytical modeling technique that couples the Finite Element Method (FEM) with classical solid mechanics was developed to model the deflection of the rolls and strip while under load. The technique employed offers several important advantages over traditional methods to calculate strip crown, including continuity of elastic foundations, non-iterative solution when using predetermined foundation moduli, continuous third-order displacement fields, simple stress-field determination, and a comparatively faster solution time.

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.

Understanding the determinants of volatility clustering in terms of stationary Markovian processes

NASA Astrophysics Data System (ADS)

Miccichè, S.

2016-11-01

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ-β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock's volatility is a linear function of the average correlation of such stock's volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still keep some of the original volatility stylized facts. As a result, the diagonalized volatilities result to share with the original volatilities either the power-law decay of the probability density function and the power-law decay of the autocorrelation function. This would indicate that volatility clustering is already present in the diagonalized un-correlated volatilities. We therefore present a parsimonious univariate model based on a non-linear Langevin equation that well reproduces these two stylized facts of volatility. The model helps us in understanding that the main source of volatility clustering, once volatilities have been diagonalized, is that the economic forces driving volatility can be modeled in terms of a Smoluchowski potential with logarithmic tails.

Language competition in a population of migrating agents.

PubMed

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

Language competition in a population of migrating agents

NASA Astrophysics Data System (ADS)

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

The Effect of Cluster Sampling Design in Survey Research on the Standard Error Statistic.

ERIC Educational Resources Information Center

Wang, Lin; Fan, Xitao

Standard statistical methods are used to analyze data that is assumed to be collected using a simple random sampling scheme. These methods, however, tend to underestimate variance when the data is collected with a cluster design, which is often found in educational survey research. The purposes of this paper are to demonstrate how a cluster design…

A Framework for Designing Cluster Randomized Trials with Binary Outcomes

ERIC Educational Resources Information Center

Spybrook, Jessaca; Martinez, Andres

2011-01-01

The purpose of this paper is to provide a frame work for approaching a power analysis for a CRT (cluster randomized trial) with a binary outcome. The authors suggest a framework in the context of a simple CRT and then extend it to a blocked design, or a multi-site cluster randomized trial (MSCRT). The framework is based on proportions, an…

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

Career Cluster Activity Book, Intermediate Level. Learn About the Fifteen Career Clusters and Color the Pictures.

ERIC Educational Resources Information Center

White Hawk, Sharon, Ed.

Simple black and white illustrations portray one occupation for each of 15 career clusters. Directed toward the Indian student and showing Indians at work in the occupations depicted, the illustrations are intended to create an awareness, understanding, and motivation for Indian students to become involved in work, both on and off the reservation.…

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.

Surface heating of electrons in atomic clusters irradiated by ultrashort laser pulses

NASA Astrophysics Data System (ADS)

Krainov, V. P.; Sofronov, A. V.

2014-04-01

We consider a mechanism for electron heating in atomic clusters at the reflections of free electrons from the cluster surface. Electrons acquire energy from the external laser field during these reflections. A simple analytical expression has been obtained for acquired electron kinetic energy during the laser pulse. We find conditions when this mechanism dominates compared to the electron heating due to the well-known induced inverse bremsstrahlung at the electron-ion collisions inside clusters.

A cluster analysis of tic symptoms in children and adults with Tourette syndrome: clinical correlates and treatment outcome.

PubMed

McGuire, Joseph F; Nyirabahizi, Epiphanie; Kircanski, Katharina; Piacentini, John; Peterson, Alan L; Woods, Douglas W; Wilhelm, Sabine; Walkup, John T; Scahill, Lawrence

2013-12-30

Cluster analytic methods have examined the symptom presentation of chronic tic disorders (CTDs), with limited agreement across studies. The present study investigated patterns, clinical correlates, and treatment outcome of tic symptoms. 239 youth and adults with CTDs completed a battery of assessments at baseline to determine diagnoses, tic severity, and clinical characteristics. Participants were randomly assigned to receive either a comprehensive behavioral intervention for tics (CBIT) or psychoeducation and supportive therapy (PST). A cluster analysis was conducted on the baseline Yale Global Tic Severity Scale (YGTSS) symptom checklist to identify the constellations of tic symptoms. Four tic clusters were identified: Impulse Control and Complex Phonic Tics; Complex Motor Tics; Simple Head Motor/Vocal Tics; and Primarily Simple Motor Tics. Frequencies of tic symptoms showed few differences across youth and adults. Tic clusters had small associations with clinical characteristics and showed no associations to the presence of coexisting psychiatric conditions. Cluster membership scores did not predict treatment response to CBIT or tic severity reductions. Tic symptoms distinctly cluster with little difference across youth and adults, or coexisting conditions. This study, which is the first to examine tic clusters and response to treatment, suggested that tic symptom profiles respond equally well to CBIT. Clinical trials.gov. identifiers: NCT00218777; NCT00231985. © 2013 Elsevier Ireland Ltd. All rights reserved.

Distributions of Gas and Galaxies from Galaxy Clusters to Larger Scales

NASA Astrophysics Data System (ADS)

Patej, Anna

2017-01-01

We address the distributions of gas and galaxies on three scales: the outskirts of galaxy clusters, the clustering of galaxies on large scales, and the extremes of the galaxy distribution. In the outskirts of galaxy clusters, long-standing analytical models of structure formation and recent simulations predict the existence of density jumps in the gas and dark matter profiles. We use these features to derive models for the gas density profile, obtaining a simple fiducial model that is in agreement with both observations of cluster interiors and simulations of the outskirts. We next consider the galaxy density profiles of clusters; under the assumption that the galaxies in cluster outskirts follow similar collisionless dynamics as the dark matter, their distribution should show a steep jump as well. We examine the profiles of a low-redshift sample of clusters and groups, finding evidence for the jump in some of these clusters. Moving to larger scales where massive galaxies of different types are expected to trace the same large-scale structure, we present a test of this prediction by measuring the clustering of red and blue galaxies at z 0.6, finding low stochasticity between the two populations. These results address a key source of systematic uncertainty - understanding how target populations of galaxies trace large-scale structure - in galaxy redshift surveys. Such surveys use baryon acoustic oscillations (BAO) as a cosmological probe, but are limited by the expense of obtaining sufficiently dense spectroscopy. With the intention of leveraging upcoming deep imaging data, we develop a new method of detecting the BAO in sparse spectroscopic samples via cross-correlation with a dense photometric catalog. This method will permit the extension of BAO measurements to higher redshifts than possible with the existing spectroscopy alone. Lastly, we connect galaxies near and far: the Local Group dwarfs and the high redshift galaxies observed by Hubble and Spitzer. We examine how the local dwarfs may have appeared in the past and compare their properties to the detection limits of the upcoming James Webb Space Telescope (JWST), finding that JWST should be able to detect galaxies similar to the progenitors of a few of the brightest of the local galaxies, revealing a hitherto unobserved population of galaxies at high redshifts.

EMBEDDED LENSING TIME DELAYS, THE FERMAT POTENTIAL, AND THE INTEGRATED SACHS–WOLFE EFFECT

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

Chen, Bin; Kantowski, Ronald; Dai, Xinyu, E-mail: bchen3@fsu.edu

2015-05-01

We derive the Fermat potential for a spherically symmetric lens embedded in a Friedman–Lemaître–Robertson–Walker cosmology and use it to investigate the late-time integrated Sachs–Wolfe (ISW) effect, i.e., secondary temperature fluctuations in the cosmic microwave background (CMB) caused by individual large-scale clusters and voids. We present a simple analytical expression for the temperature fluctuation in the CMB across such a lens as a derivative of the lens’ Fermat potential. This formalism is applicable to both linear and nonlinear density evolution scenarios, to arbitrarily large density contrasts, and to all open and closed background cosmologies. It is much simpler to use andmore » makes the same predictions as conventional approaches. In this approach the total temperature fluctuation can be split into a time-delay part and an evolutionary part. Both parts must be included for cosmic structures that evolve and both can be equally important. We present very simple ISW models for cosmic voids and galaxy clusters to illustrate the ease of use of our formalism. We use the Fermat potentials of simple cosmic void models to compare predicted ISW effects with those recently extracted from WMAP and Planck data by stacking large cosmic voids using the aperture photometry method. If voids in the local universe with large density contrasts are no longer evolving we find that the time delay contribution alone predicts values consistent with the measurements. However, we find that for voids still evolving linearly, the evolutionary contribution cancels a significant part of the time delay contribution and results in predicted signals that are much smaller than recently observed.« less

Modelling Market Dynamics with a "Market Game"

NASA Astrophysics Data System (ADS)

Katahira, Kei; Chen, Yu

In the financial market, traders, especially speculators, typically behave as to yield capital gains by the difference between selling and buying prices. Making use of the structure of Minority Game, we build a novel market toy model which takes account of such the speculative mind involving a round-trip trade to analyze the market dynamics as a system. Even though the micro-level behavioral rules of players in this new model is quite simple, its macroscopic aggregational output has the reproducibility of the well-known stylized facts such as volatility clustering and heavy tails. The proposed model may become a new alternative bottom-up approach in order to study the emerging mechanism of those stylized qualitative properties of asset returns.

Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory.

PubMed

Gruenenfelder, Thomas M; Recchia, Gabriel; Rubin, Tim; Jones, Michael N

2016-08-01

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on an associative network (POC) successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts (e.g., the relation between pea and bean, or between sparrow and robin), and contextual representations may be used to process information about more abstract concepts. Copyright © 2015 Cognitive Science Society, Inc.

Fingerprinting of Non-resolved Three-axis Stabilized Space Objects Using a Two-Facet Analytical Model

DTIC Science & Technology

2011-09-01

Crawford, K., " Time - Resolved Infrared Spectrophotometric Observations of IRIDIUM satellites and related Resident Space Objects", IAC-09-A6.1.17...Figure 10 for a geosynchronous (GEO) satellite . The figure shows three sets of multi-spectral signatures were collected at different times of the...provides a simple method to determine suitable observation conditions for the cluster of satellites . For instance, on Day 0, the times of the

BUDHIES II: a phase-space view of H I gas stripping and star formation quenching in cluster galaxies

NASA Astrophysics Data System (ADS)

Jaffé, Yara L.; Smith, Rory; Candlish, Graeme N.; Poggianti, Bianca M.; Sheen, Yun-Kyeong; Verheijen, Marc A. W.

2015-04-01

We investigate the effect of ram-pressure from the intracluster medium on the stripping of H I gas in galaxies in a massive, relaxed, X-ray bright, galaxy cluster at z = 0.2 from the Blind Ultra Deep H I Environmental Survey (BUDHIES). We use cosmological simulations, and velocity versus position phase-space diagrams to infer the orbital histories of the cluster galaxies. In particular, we embed a simple analytical description of ram-pressure stripping in the simulations to identify the regions in phase-space where galaxies are more likely to have been sufficiently stripped of their H I gas to fall below the detection limit of our survey. We find a striking agreement between the model predictions and the observed location of H I-detected and non-detected blue (late-type) galaxies in phase-space, strongly implying that ram-pressure plays a key role in the gas removal from galaxies, and that this can happen during their first infall into the cluster. However, we also find a significant number of gas-poor, red (early-type) galaxies in the infall region of the cluster that cannot easily be explained with our model of ram-pressure stripping alone. We discuss different possible additional mechanisms that could be at play, including the pre-processing of galaxies in their previous environment. Our results are strengthened by the distribution of galaxy colours (optical and UV) in phase-space, that suggests that after a (gas-rich) field galaxy falls into the cluster, it will lose its gas via ram-pressure stripping, and as it settles into the cluster, its star formation will decay until it is completely quenched. Finally, this work demonstrates the utility of phase-space diagrams to analyse the physical processes driving the evolution of cluster galaxies, in particular H I gas stripping.

Jellyfish: Observational Properties of Extreme Ram-Pressure Stripping Events in Massive Galaxy Clusters

NASA Astrophysics Data System (ADS)

Conor, McPartland; Ebeling, Harald; Roediger, Elke

2015-08-01

We investigate the physical origin and observational signatures of extreme ram-pressure stripping (RPS) in 63 massive galaxy clusters at z=0.3-0.7, based on data in the F606W passband obtained with the Advanced Camera for Surveys aboard the Hubble Space Telescope. Using a training set of a dozen ``jellyfish" galaxies identified earlier in the same imaging data, we define quantitative morphological criteria to select candidate galaxies which are similar to known cases of RPS. Considering a sample of 16 ``jellyfish" galaxies (10 of which we present for the first time), we visually derive estimates of the projected direction of motion based on dynamical features such as apparent compression shocks and debris trails. Our findings suggest that the observed events occur primarily at large distances from the cluster core and involve infall trajectories featuring high impact parameters. Simple models of cluster growth show that such trajectories are consistent with two scenarios: 1) galaxy infall along filaments; and 2) infall at high velocities (≥1000 km/s) characteristic of cluster mergers. The observed distribution of events is best described by timescales of ˜few Myr in agreement with recent numerical simulations of RPS. The broader areal coverage of the Hubble Frontier Fields should provide an even larger sample of RPS events to determine the relative contributions of infall and cluster mergers. Prompted by the discovery of several jellyfish galaxies whose brightness in the F606W passband rivals or exceeds that of the respective brightest cluster galaxy, we attempt to constrain the luminosity function of galaxies undergoing RPS. The observed significant excess at the bright end compared to the luminosity functions of blue cluster members strongly suggests enhanced star formation, thus challenging theoretical and numerical studies according to which RPS merely displaces existing star-forming regions. In-depth studies of individual objects will help test our conclusions and allow a quantitative comparison with predictions of theoretical and numerical models of ram-pressure stripping.

Magnetic levitating polymeric nano/microparticular substrates for three-dimensional tumor cell culture.

PubMed

Lee, Woong Ryeol; Oh, Kyung Taek; Park, So Young; Yoo, Na Young; Ahn, Yong Sik; Lee, Don Haeng; Youn, Yu Seok; Lee, Deok-Keun; Cha, Kyung-Hoi; Lee, Eun Seong

2011-07-01

Herein, we describe magnetic cell levitation models using conventional polymeric microparticles or nanoparticles as a substrate for the three-dimensional tumor cell culture. When the magnetic force originating from the ring-shaped magnets overcame the gravitational force, the magnetic field-levitated KB tumor cells adhered to the surface area of magnetic iron oxide (Fe(3)O(4))-encapsulated nano/microparticles and concentrated clusters of levitated cells, ultimately developing tumor cells to tumor spheroids. These simple cell culture models may prove useful for the screening of anticancer drugs and their formulations. Copyright © 2011 Elsevier B.V. All rights reserved.

92 Years of the Ising Model: A High Resolution Monte Carlo Study

NASA Astrophysics Data System (ADS)

Xu, Jiahao; Ferrenberg, Alan M.; Landau, David P.

2018-04-01

Using extensive Monte Carlo simulations that employ the Wolff cluster flipping and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising model with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, we obtained the critical inverse temperature K c = 0.221 654 626(5) and the critical exponent of the correlation length ν = 0.629 912(86) with precision that improves upon previous Monte Carlo estimates.

Strain rates, stress markers and earthquake clustering (Invited)

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Boundaries Control Collective Dynamics of Inertial Self-Propelled Robots.

PubMed

Deblais, A; Barois, T; Guerin, T; Delville, P H; Vaudaine, R; Lintuvuori, J S; Boudet, J F; Baret, J C; Kellay, H

2018-05-04

Simple ingredients, such as well-defined interactions and couplings for the velocity and orientation of self-propelled objects, are sufficient to produce complex collective behavior in assemblies of such entities. Here, we use assemblies of rodlike robots made motile through self-vibration. When confined in circular arenas, dilute assemblies of these rods act as a gas. Increasing the surface fraction leads to a collective behavior near the boundaries: polar clusters emerge while, in the bulk, gaslike behavior is retained. The coexistence between a gas and surface clusters is a direct consequence of inertial effects as shown by our simulations. A theoretical model, based on surface mediated transport accounts for this coexistence and illustrates the exact role of the boundaries. Our study paves the way towards the control of collective behavior: By using deformable but free to move arenas, we demonstrate that the surface induced clusters can lead to directed motion, while the topology of the surface states can be controlled by biasing the motility of the particles.

A uniform approach for programming distributed heterogeneous computing systems

PubMed Central

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-01-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations. PMID:25844015

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

The void spectrum in two-dimensional numerical simulations of gravitational clustering

NASA Technical Reports Server (NTRS)

Kauffmann, Guinevere; Melott, Adrian L.

1992-01-01

An algorithm for deriving a spectrum of void sizes from two-dimensional high-resolution numerical simulations of gravitational clustering is tested, and it is verified that it produces the correct results where those results can be anticipated. The method is used to study the growth of voids as clustering proceeds. It is found that the most stable indicator of the characteristic void 'size' in the simulations is the mean fractional area covered by voids of diameter d, in a density field smoothed at its correlation length. Very accurate scaling behavior is found in power-law numerical models as they evolve. Eventually, this scaling breaks down as the nonlinearity reaches larger scales. It is shown that this breakdown is a manifestation of the undesirable effect of boundary conditions on simulations, even with the very large dynamic range possible here. A simple criterion is suggested for deciding when simulations with modest large-scale power may systematically underestimate the frequency of larger voids.

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

PubMed

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

2013-09-01

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

A uniform approach for programming distributed heterogeneous computing systems.

PubMed

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-12-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater's performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.

Boundaries Control Collective Dynamics of Inertial Self-Propelled Robots

NASA Astrophysics Data System (ADS)

Deblais, A.; Barois, T.; Guerin, T.; Delville, P. H.; Vaudaine, R.; Lintuvuori, J. S.; Boudet, J. F.; Baret, J. C.; Kellay, H.

2018-05-01

Simple ingredients, such as well-defined interactions and couplings for the velocity and orientation of self-propelled objects, are sufficient to produce complex collective behavior in assemblies of such entities. Here, we use assemblies of rodlike robots made motile through self-vibration. When confined in circular arenas, dilute assemblies of these rods act as a gas. Increasing the surface fraction leads to a collective behavior near the boundaries: polar clusters emerge while, in the bulk, gaslike behavior is retained. The coexistence between a gas and surface clusters is a direct consequence of inertial effects as shown by our simulations. A theoretical model, based on surface mediated transport accounts for this coexistence and illustrates the exact role of the boundaries. Our study paves the way towards the control of collective behavior: By using deformable but free to move arenas, we demonstrate that the surface induced clusters can lead to directed motion, while the topology of the surface states can be controlled by biasing the motility of the particles.

Not-so-simple stellar populations in the intermediate-age Large Magellanic Cloud star clusters NGC 1831 and NGC 1868

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

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

2014-04-01

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

Effects of Cluster Environment on Chemical Abundances in Virgo Cluster Spirals

NASA Astrophysics Data System (ADS)

Kennicutt, R. C.; Skillman, E. D.; Shields, G. A.; Zaritsky, D.

1995-12-01

We have obtained new chemical abundance measurements of HII regions in Virgo cluster spiral galaxies, in order to test whether the cluster environment has significantly influenced the gas-phase abundances and chemical evolution of spiral disks. The sample of 9 Virgo spirals covers a narrow range of morphological type (Sbc - Sc) but shows broad ranges in HI deficiencies and radii in the cluster. This allows us to compare the Virgo sample as a whole to field spirals, using a large sample from Zaritsky, Kennicutt, & Huchra, and to test for systematic trends with HI content and location within the cluster. The Virgo spirals show a wide dispersion in mean disk abundances and abundance gradients. Strongly HI deficient spirals closest to the cluster core show anomalously high oxygen abundances (by 0.3 to 0.5 dex), while outlying spirals with normal HI content show abundances similar to those of field spirals. The most HI depleted spirals also show weaker abundance gradients on average, but the formal significance of this trend is marginal. We find a strong correlation between mean abundance and HI/optical diameter ratio that is quite distinct from the behavior seen in field galaxies. This suggests that dynamical processes associated with the cluster environment are more important than cluster membership in determining the evolution of chemical abundances and stellar populations in spiral galaxies. Simple chemical evolution models are calculated to predict the magnitude of the abundance enhancement expected if ram-pressure stripping or curtailment of infall is responsible for the gas deficiencies. The increased abundances of the spirals in the cluster core may have significant effects on their use as cosmological standard candles.

An Iterative Local Updating Ensemble Smoother for Estimation and Uncertainty Assessment of Hydrologic Model Parameters With Multimodal Distributions

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Lin, Guang; Li, Weixuan; Wu, Laosheng; Zeng, Lingzao

2018-03-01

Ensemble smoother (ES) has been widely used in inverse modeling of hydrologic systems. However, for problems where the distribution of model parameters is multimodal, using ES directly would be problematic. One popular solution is to use a clustering algorithm to identify each mode and update the clusters with ES separately. However, this strategy may not be very efficient when the dimension of parameter space is high or the number of modes is large. Alternatively, we propose in this paper a very simple and efficient algorithm, i.e., the iterative local updating ensemble smoother (ILUES), to explore multimodal distributions of model parameters in nonlinear hydrologic systems. The ILUES algorithm works by updating local ensembles of each sample with ES to explore possible multimodal distributions. To achieve satisfactory data matches in nonlinear problems, we adopt an iterative form of ES to assimilate the measurements multiple times. Numerical cases involving nonlinearity and multimodality are tested to illustrate the performance of the proposed method. It is shown that overall the ILUES algorithm can well quantify the parametric uncertainties of complex hydrologic models, no matter whether the multimodal distribution exists.

The dynamics of superclusters - Initial determination of the mass density of the universe at large scales

NASA Technical Reports Server (NTRS)

Ford, H. C.; Ciardullo, R.; Harms, R. J.; Bartko, F.

1981-01-01

The radial velocities of cluster members of two rich, large superclusters have been measured in order to probe the supercluster mass densities, and simple evolutionary models have been computed to place limits upon the mass density within each supercluster. These superclusters represent true physical associations of size of about 100 Mpc seen presently at an early stage of evolution. One supercluster is weakly bound, the other probably barely bound, but possibly marginally unbound. Gravity has noticeably slowed the Hubble expansion of both superclusters. Galaxy surface-density counts and the density enhancement of Abell clusters within each supercluster were used to derive the ratio of mass densities of the superclusters to the mean field mass density. The results strongly exclude a closed universe.

AN EMPIRICAL METHOD FOR IMPROVING THE QUALITY OF RXTE HEXTE SPECTRA

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

Garcia, Javier A.; Steiner, James F.; McClintock, Jeffrey E.

2016-03-01

We have developed a correction tool to improve the quality of Rossi X-ray Timing Explorer (RXTE) High Energy X-ray Timing Experiment (HEXTE) spectra by employing the same method we used earlier to improve the quality of RXTE Proportional Counter Array (PCA) spectra. We fit all of the hundreds of HEXTE spectra of the Crab individually to a simple power-law model, some 37 million counts in total for Cluster A and 39 million counts for Cluster B, and we create for each cluster a combined spectrum of residuals. We find that the residual spectrum of Cluster A is free of instrumental artifacts while that of Clustermore » B contains significant features with amplitudes ∼1%; the most prominent is in the energy range 30–50 keV, which coincides with the iodine K edge. Starting with the residual spectrum for Cluster B, via an iterative procedure we created the calibration tool hexBcorr for correcting any Cluster B spectrum of interest. We demonstrate the efficacy of the tool by applying it to Cluster B spectra of two bright black holes, which contain several million counts apiece. For these spectra, application of the tool significantly improves the goodness of fit, while affecting only slightly the broadband fit parameters. The tool may be important for the study of spectral features, such as cyclotron lines, a topic that is beyond the scope of this paper.« less

Ecological symmetry breaking can favour the evolution of altruism in an action-response game.

PubMed

Di Paolo, E A

2000-03-21

The evolution of altruistic behaviour is studied in a simple action-response game with a tunable degree of conflict of interest. It is shown that for the continuous, mixed-medium approach no stable polymorphism favours altruism. Ecological dynamics are explored with the addition of a spatial dimension and a local energy variable. A continuous spatial model with finite local range does not introduce any substantial difference in the results with respect to the level of altruism. However, the model illustrates how ecological coupling may lead to the formation of stable spatial patterns in the form of discrete and isolated clusters of players as a consequence of inverse density dependence. A discrete, individual-based model is built in which local interactions are also modelled as occurring within a finite neighbourhood of each individual and spatial positions are not restricted as in lattice models. This model shows substantially different results. A high level of altruism is observed for low (but positive) degrees of conflict and this level decreases linearly for higher degrees of conflict. The evolution of altruism is explained by studying the broken symmetries introduced by the spatial clusters themselves, mainly between their central and peripheral regions which, in combination with the discrete and the stochastic nature of the model, result in the stabilization of strategies in which players behave altruistically towards the same type. As a consequence of the activity of the players, energy resources at the centre of an altruistic cluster are very depleted; so much so that, for low conflict, fitter non-altruistic mutants may initially invade only to become locally extinct due to their less efficient use of energy as their numbers increase. In peripheral regions invader may subsist; however, for geometrical reasons long-lasting genealogies tend to originate only at the centre of a cluster. Copyright 2000 Academic Press.

Using Star Clusters as Tracers of Star Formation and Chemical Evolution: The Chemical Enrichment History of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Chilingarian, Igor V.; Asa’d, Randa

2018-05-01

The star formation (SFH) and chemical enrichment (CEH) histories of Local Group galaxies are traditionally studied by analyzing their resolved stellar populations in a form of color–magnitude diagrams obtained with the Hubble Space Telescope. Star clusters can be studied in integrated light using ground-based telescopes to much larger distances. They represent snapshots of the chemical evolution of their host galaxy at different ages. Here we present a simple theoretical framework for the chemical evolution based on the instantaneous recycling approximation (IRA) model. We infer a CEH from an SFH and vice versa using observational data. We also present a more advanced model for the evolution of individual chemical elements that takes into account the contribution of supernovae type Ia. We demonstrate that ages, iron, and α-element abundances of 15 star clusters derived from the fitting of their integrated optical spectra reliably trace the CEH of the Large Magellanic Cloud obtained from resolved stellar populations in the age range 40 Myr < t < 3.5 Gyr. The CEH predicted by our model from the global SFH of the LMC agrees remarkably well with the observed cluster age–metallicity relation. Moreover, the present-day total gas mass of the LMC estimated by the IRA model (6.2× {10}8 {M}ȯ ) matches within uncertainties the observed H I mass corrected for the presence of molecular gas (5.8+/- 0.5× {10}8 {M}ȯ ). We briefly discuss how our approach can be used to study SFHs of galaxies as distant as 10 Mpc at the level of detail that is currently available only in a handful of nearby Milky Way satellites. .

The Role of Deep Creep in the Timing of Large Earthquakes

NASA Astrophysics Data System (ADS)

Sammis, C. G.; Smith, S. W.

2012-12-01

The observed temporal clustering of the world's largest earthquakes has been largely discounted for two reasons: a) it is consistent with Poisson clustering, and b) no physical mechanism leading to such clustering has been proposed. This lack of a mechanism arises primarily because the static stress transfer mechanism, commonly used to explain aftershocks and the clustering of large events on localized fault networks, does not work at global distances. However, there is recent observational evidence that the surface waves from large earthquakes trigger non-volcanic tremor at the base of distant fault zones at global distances. Based on these observations, we develop a simple non-linear coupled oscillator model that shows how the triggering of such tremor can lead to the synchronization of large earthquakes on a global scale. A basic assumption of the model is that induced tremor is a proxy for deep creep that advances the seismic cycle of the fault. We support this hypothesis by demonstrating that the 2010 Maule Chile and the 2011 Fukushima Japan earthquakes, which have been shown to induce tremor on the Parkfield segment of the San Andreas Fault, also produce changes in off-fault seismicity that are spatially and temporally consistent with episodes of deep creep on the fault. The observed spatial pattern can be simulated using an Okada dislocation model for deep creep (below 20 km) on the fault plane in which the slip rate decreases from North to South consistent with surface creep measurements and deepens south of the "Parkfield asperity" as indicated by recent tremor locations. The model predicts the off-fault events should have reverse mechanism consistent with observed topography.

Characterization and analysis of a transcriptome from the boreal spider crab Hyas araneus.

PubMed

Harms, Lars; Frickenhaus, Stephan; Schiffer, Melanie; Mark, Felix C; Storch, Daniela; Pörtner, Hans-Otto; Held, Christoph; Lucassen, Magnus

2013-12-01

Research investigating the genetic basis of physiological responses has significantly broadened our understanding of the mechanisms underlying organismic response to environmental change. However, genomic data are currently available for few taxa only, thus excluding physiological model species from this approach. In this study we report the transcriptome of the model organism Hyas araneus from Spitsbergen (Arctic). We generated 20,479 transcripts, using the 454 GS FLX sequencing technology in combination with an Illumina HiSeq sequencing approach. Annotation by Blastx revealed 7159 blast hits in the NCBI non-redundant protein database. The comparison between the spider crab H. araneus transcriptome and EST libraries of the European lobster Homarus americanus and the porcelain crab Petrolisthes cinctipes yielded 3229/2581 sequences with a significant hit, respectively. The clustering by the Markov Clustering Algorithm (MCL) revealed a common core of 1710 clusters present in all three species and 5903 unique clusters for H. araneus. The combined sequencing approaches generated transcripts that will greatly expand the limited genomic data available for crustaceans. We introduce the MCL clustering for transcriptome comparisons as a simple approach to estimate similarities between transcriptomic libraries of different size and quality and to analyze homologies within the selected group of species. In particular, we identified a large variety of reverse transcriptase (RT) sequences not only in the H. araneus transcriptome and other decapod crustaceans, but also sea urchin, supporting the hypothesis of a heritable, anti-viral immunity and the proposed viral fragment integration by host-derived RTs in marine invertebrates. © 2013.

Planck intermediate results. XL. The Sunyaev-Zeldovich signal from the Virgo cluster

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Virgo cluster is the largest Sunyaev-Zeldovich (SZ) source in the sky, both in terms of angular size and total integrated flux. Planck's wide angular scale and frequency coverage, together with its high sensitivity, enable a detailed study of this big object through the SZ effect. Virgo is well resolved by Planck, showing an elongated structure that correlates well with the morphology observed from X-rays, but extends beyond the observed X-ray signal. We find good agreement between the SZ signal (or Compton parameter, yc) observed by Planck and the expected signal inferred from X-ray observations and simple analytical models. Owing to its proximity to us, the gas beyond the virial radius in Virgo can be studied with unprecedented sensitivity by integrating the SZ signal over tens of square degrees. We study the signal in the outskirts of Virgo and compare it with analytical models and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surround Virgo, out to twice the virial radius. We find the SZ signal in the outskirts of Virgo to be consistent with a simple model that extrapolates the inferred pressure at lower radii, while assuming that the temperature stays in the keV range beyond the virial radius. The observed signal is also consistent with simulations and points to a shallow pressure profile in the outskirts of the cluster. This reservoir of gas at large radii can be linked with the hottest phase of the elusivewarm/hot intergalactic medium. Taking the lack of symmetry of Virgo into account, we find that a prolate model is favoured by the combination of SZ and X-ray data, in agreement with predictions. Finally, based on the combination of the same SZ and X-ray data, we constrain the total amount of gas in Virgo. Under the hypothesis that the abundance of baryons in Virgo is representative of the cosmic average, we also infer a distance for Virgo of approximately 18 Mpc, in good agreement with previous estimates.

Planck intermediate results: XL. The Sunyaev-Zeldovich signal from the Virgo cluster

DOE PAGES

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

2016-12-12

The Virgo cluster is the largest Sunyaev-Zeldovich (SZ) source in the sky, both in terms of angular size and total integrated flux. Planck’s wide angular scale and frequency coverage, together with its high sensitivity, enable a detailed study of this big object through the SZ effect. Virgo is well resolved by Planck, showing an elongated structure that correlates well with the morphology observed from X-rays, but extends beyond the observed X-ray signal. We find good agreement between the SZ signal (or Compton parameter, y c) observed by Planck and the expected signal inferred from X-ray observations and simple analytical models.more » Owing to its proximity to us, the gas beyond the virial radius in Virgo can be studied with unprecedented sensitivity by integrating the SZ signal over tens of square degrees. In this paper, we study the signal in the outskirts of Virgo and compare it with analytical models and a constrained simulation of the environment of Virgo. Planck data suggest that significant amounts of low-density plasma surround Virgo, out to twice the virial radius. We find the SZ signal in the outskirts of Virgo to be consistent with a simple model that extrapolates the inferred pressure at lower radii, while assuming that the temperature stays in the keV range beyond the virial radius. The observed signal is also consistent with simulations and points to a shallow pressure profile in the outskirts of the cluster. This reservoir of gas at large radii can be linked with the hottest phase of the elusivewarm/hot intergalactic medium. Taking the lack of symmetry of Virgo into account, we find that a prolate model is favoured by the combination of SZ and X-ray data, in agreement with predictions. In conclusion, based on the combination of the same SZ and X-ray data, we constrain the total amount of gas in Virgo. Under the hypothesis that the abundance of baryons in Virgo is representative of the cosmic average, we also infer a distance for Virgo of approximately 18 Mpc, in good agreement with previous estimates.« less

Development of a Two-fluid Drag Law for Clustered Particles using Direct Numerical Simulation and Validation through Experiments

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

Gokaltun, Seckin; Munroe, Norman; Subramaniam, Shankar

2014-12-31

This study presents a new drag model, based on the cohesive inter-particle forces, implemented in the MFIX code. This new drag model combines an existing standard model in MFIX with a particle-based drag model based on a switching principle. Switches between the models in the computational domain occur where strong particle-to-particle cohesion potential is detected. Three versions of the new model were obtained by using one standard drag model in each version. Later, performance of each version was compared against available experimental data for a fluidized bed, published in the literature and used extensively by other researchers for validation purposes.more » In our analysis of the results, we first observed that standard models used in this research were incapable of producing closely matching results. Then, we showed for a simple case that a threshold is needed to be set on the solid volume fraction. This modification was applied to avoid non-physical results for the clustering predictions, when governing equation of the solid granular temperate was solved. Later, we used our hybrid technique and observed the capability of our approach in improving the numerical results significantly; however, improvement of the results depended on the threshold of the cohesive index, which was used in the switching procedure. Our results showed that small values of the threshold for the cohesive index could result in significant reduction of the computational error for all the versions of the proposed drag model. In addition, we redesigned an existing circulating fluidized bed (CFB) test facility in order to create validation cases for clustering regime of Geldart A type particles.« less

Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968

New Parameterizations for Neutral and Ion-Induced Sulfuric Acid-Water Particle Formation in Nucleation and Kinetic Regimes

NASA Astrophysics Data System (ADS)

Määttänen, Anni; Merikanto, Joonas; Henschel, Henning; Duplissy, Jonathan; Makkonen, Risto; Ortega, Ismael K.; Vehkamäki, Hanna

2018-01-01

We have developed new parameterizations of electrically neutral homogeneous and ion-induced sulfuric acid-water particle formation for large ranges of environmental conditions, based on an improved model that has been validated against a particle formation rate data set produced by Cosmics Leaving OUtdoor Droplets (CLOUD) experiments at European Organization for Nuclear Research (CERN). The model uses a thermodynamically consistent version of the Classical Nucleation Theory normalized using quantum chemical data. Unlike the earlier parameterizations for H2SO4-H2O nucleation, the model is applicable to extreme dry conditions where the one-component sulfuric acid limit is approached. Parameterizations are presented for the critical cluster sulfuric acid mole fraction, the critical cluster radius, the total number of molecules in the critical cluster, and the particle formation rate. If the critical cluster contains only one sulfuric acid molecule, a simple formula for kinetic particle formation can be used: this threshold has also been parameterized. The parameterization for electrically neutral particle formation is valid for the following ranges: temperatures 165-400 K, sulfuric acid concentrations 104-1013 cm-3, and relative humidities 0.001-100%. The ion-induced particle formation parameterization is valid for temperatures 195-400 K, sulfuric acid concentrations 104-1016 cm-3, and relative humidities 10-5-100%. The new parameterizations are thus applicable for the full range of conditions in the Earth's atmosphere relevant for binary sulfuric acid-water particle formation, including both tropospheric and stratospheric conditions. They are also suitable for describing particle formation in the atmosphere of Venus.

Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Theoretical characterization on the size-dependent electron and hole trapping activity of chloride-passivated CdSe nanoclusters

NASA Astrophysics Data System (ADS)

Cui, Yingqi; Cui, Xianhui; Zhang, Li; Xie, Yujuan; Yang, Mingli

2018-04-01

Ligand passivation is often used to suppress the surface trap states of semiconductor quantum dots (QDs) for their continuous photoluminescence output. The suppression process is related to the electrophilic/nucleophilic activity of surface atoms that varies with the structure and size of QD and the electron donating/accepting nature of ligand. Based on first-principles-based descriptors and cluster models, the electrophilic/nucleophilic activities of bare and chloride-coated CdSe clusters were studied to reveal the suppression mechanism of Cl-passivated QDs and compared to experimental observations. The surface atoms of bare clusters have higher activity than inner atoms and their activity decreases with cluster size. In the ligand-coated clusters, the Cd atom remains as the electrophilic site, while the nucleophilic site of Se atoms is replaced by Cl atoms. The activities of Cd and Cl atoms in the coated clusters are, however, remarkably weaker than those in bare clusters. Cluster size, dangling atoms, ligand coverage, electronegativity of ligand atoms, and solvent (water) were found to have considerable influence on the activity of surface atoms. The suppression of surface trap states in Cl-passivated QDs was attributed to the reduction of electrophilic/nucleophilic activity of Cd/Se/Cl atoms. Both saturation to under-coordinated surface atoms and proper selection for the electron donating/accepting strength of ligands are crucial for eliminating the charge carrier traps. Our calculations predicted a similar suppressing effect of chloride ligands with experiments and provided a simple but effective approach to assess the charge carrier trapping behaviors of semiconductor QDs.

Radio Selection of the Most Distant Galaxy Clusters

NASA Astrophysics Data System (ADS)

Daddi, E.; Jin, S.; Strazzullo, V.; Sargent, M. T.; Wang, T.; Ferrari, C.; Schinnerer, E.; Smolčić, V.; Calabró, A.; Coogan, R.; Delhaize, J.; Delvecchio, I.; Elbaz, D.; Gobat, R.; Gu, Q.; Liu, D.; Novak, M.; Valentino, F.

2017-09-01

We show that the most distant X-ray-detected cluster known to date, Cl J1001 at {z}{spec}=2.506, hosts a strong overdensity of radio sources. Six of them are individually detected (within 10\\prime\\prime ) in deep 0\\buildrel{\\prime\\prime}\\over{.} 75 resolution VLA 3 GHz imaging, with {S}3{GHz}> 8 μ {Jy}. Of the six, an active galactic nucleus (AGN) likely affects the radio emission in two galaxies, while star formation is the dominant source powering the remaining four. We searched for cluster candidates over the full COSMOS 2 deg2 field using radio-detected 3 GHz sources and looking for peaks in {{{Σ }}}5 density maps. Cl J1001 is the strongest overdensity by far with > 10σ , with a simple {z}{phot}> 1.5 preselection. A cruder photometric rejection of z< 1 radio foregrounds leaves Cl J1001 as the second strongest overdensity, while even using all radio sources Cl J1001 remains among the four strongest projected overdensities. We conclude that there are great prospects for future deep and wide-area radio surveys to discover large samples of the first generation of forming galaxy clusters. In these remarkable structures, widespread star formation and AGN activity of massive galaxy cluster members, residing within the inner cluster core, will ultimately lead to radio continuum as one of the most effective means for their identification, with detection rates expected in the ballpark of 0.1-1 per square degree at z≳ 2.5. Samples of hundreds such high-redshift clusters could potentially constrain cosmological parameters and test cluster and galaxy formation models.

Free cooling of the one-dimensional wet granular gas.

PubMed

Zaburdaev, V Yu; Brinkmann, M; Herminghaus, S

2006-07-07

The free cooling behavior of a wet granular gas is studied in one dimension. We employ a particularly simple model system in which the interaction of wet grains is characterized by a fixed energy loss assigned to each collision. Macroscopic laws of energy dissipation and cluster formation are studied on the basis of numerical simulations and mean-field analytical calculations. We find a number of remarkable scaling properties which may shed light on earlier unexplained results for related systems.

Theory of Force Regulation by Nascent Adhesion Sites

PubMed Central

Bruinsma, Robijn

2005-01-01

The mechanical coupling of a cell with the extracellular matrix relies on adhesion sites, clusters of membrane-associated proteins that communicate forces generated along the F-Actin filaments of the cytoskeleton to connecting tissue. Nascent adhesion sites have been shown to regulate these forces in response to tissue rigidity. Force-regulation by substrate rigidity of adhesion sites with fixed area is not possible for stationary adhesion sites, according to elasticity theory. A simple model is presented to describe force regulation by dynamical adhesion sites. PMID:15849245

Galaxy Formation from the Primordial Black Holes

NASA Astrophysics Data System (ADS)

Morikawa, Masahiro

2017-12-01

Supermassive black hole (SMBH) of size MBH = 106-10M⊙ is common in the Universe and it defines the center of the galaxy. A galaxy and the SMBH are generally thought to have co-evolved. However, the SMBH cannot evolve so fast as commonly observed even at redshift z > 6. Therefore, we explore a natural hypothesis that the SMBH has been already formed mature at z ⪆ 10 before stars and galaxies. The SMBH forms energetic jets and out-flows which trigger massive star formation in the ambient gas. They eventually construct globular clusters and classical bulge as well as the body of elliptical galaxies. We propose simple models which implement these processes. We point out that the globular clusters and classical bulges have a common origin but are in different phases. The same is true for the elliptical and spiral galaxies. Physics behind these phase division is the runaway star formation process with strong feedback to SMBH. This is similar to the forest-fire model that displays self-organized criticality.

Experiences modeling ocean circulation problems on a 30 node commodity cluster with 3840 GPU processor cores.

NASA Astrophysics Data System (ADS)

Hill, C.

2008-12-01

Low cost graphic cards today use many, relatively simple, compute cores to deliver support for memory bandwidth of more than 100GB/s and theoretical floating point performance of more than 500 GFlop/s. Right now this performance is, however, only accessible to highly parallel algorithm implementations that, (i) can use a hundred or more, 32-bit floating point, concurrently executing cores, (ii) can work with graphics memory that resides on the graphics card side of the graphics bus and (iii) can be partially expressed in a language that can be compiled by a graphics programming tool. In this talk we describe our experiences implementing a complete, but relatively simple, time dependent shallow-water equations simulation targeting a cluster of 30 computers each hosting one graphics card. The implementation takes into account the considerations (i), (ii) and (iii) listed previously. We code our algorithm as a series of numerical kernels. Each kernel is designed to be executed by multiple threads of a single process. Kernels are passed memory blocks to compute over which can be persistent blocks of memory on a graphics card. Each kernel is individually implemented using the NVidia CUDA language but driven from a higher level supervisory code that is almost identical to a standard model driver. The supervisory code controls the overall simulation timestepping, but is written to minimize data transfer between main memory and graphics memory (a massive performance bottle-neck on current systems). Using the recipe outlined we can boost the performance of our cluster by nearly an order of magnitude, relative to the same algorithm executing only on the cluster CPU's. Achieving this performance boost requires that many threads are available to each graphics processor for execution within each numerical kernel and that the simulations working set of data can fit into the graphics card memory. As we describe, this puts interesting upper and lower bounds on the problem sizes for which this technology is currently most useful. However, many interesting problems fit within this envelope. Looking forward, we extrapolate our experience to estimate full-scale ocean model performance and applicability. Finally we describe preliminary hybrid mixed 32-bit and 64-bit experiments with graphics cards that support 64-bit arithmetic, albeit at a lower performance.

Morphological and Inter Simple Sequence Repeat (ISSR) markers analyses of Corynespora cassiicola isolates from rubber plantations in Malaysia.

PubMed

Nghia, Nguyen Anh; Kadir, Jugah; Sunderasan, E; Puad Abdullah, Mohd; Malik, Adam; Napis, Suhaimi

2008-10-01

Morphological features and Inter Simple Sequence Repeat (ISSR) polymorphism were employed to analyse 21 Corynespora cassiicola isolates obtained from a number of Hevea clones grown in rubber plantations in Malaysia. The C. cassiicola isolates used in this study were collected from several states in Malaysia from 1998 to 2005. The morphology of the isolates was characteristic of that previously described for C. cassiicola. Variations in colony and conidial morphology were observed not only among isolates but also within a single isolate with no inclination to either clonal or geographical origin of the isolates. ISSR analysis delineated the isolates into two distinct clusters. The dendrogram created from UPGMA analysis based on Nei and Li's coefficient (calculated from the binary matrix data of 106 amplified DNA bands generated from 8 ISSR primers) showed that cluster 1 encompasses 12 isolates from the states of Johor and Selangor (this cluster was further split into 2 sub clusters (1A, 1B), sub cluster 1B consists of a unique isolate, CKT05D); while cluster 2 comprises of 9 isolates that were obtained from the other states. Detached leaf assay performed on selected Hevea clones showed that the pathogenicity of representative isolates from cluster 1 (with the exception of CKT05D) resembled that of race 1; and isolates in cluster 2 showed pathogenicity similar to race 2 of the fungus that was previously identified in Malaysia. The isolate CKT05D from sub cluster 1B showed pathogenicity dissimilar to either race 1 or race 2.

Effect of video server topology on contingency capacity requirements

NASA Astrophysics Data System (ADS)

Kienzle, Martin G.; Dan, Asit; Sitaram, Dinkar; Tetzlaff, William H.

1996-03-01

Video servers need to assign a fixed set of resources to each video stream in order to guarantee on-time delivery of the video data. If a server has insufficient resources to guarantee the delivery, it must reject the stream request rather than slowing down all existing streams. Large scale video servers are being built as clusters of smaller components, so as to be economical, scalable, and highly available. This paper uses a blocking model developed for telephone systems to evaluate video server cluster topologies. The goal is to achieve high utilization of the components and low per-stream cost combined with low blocking probability and high user satisfaction. The analysis shows substantial economies of scale achieved by larger server images. Simple distributed server architectures can result in partitioning of resources with low achievable resource utilization. By comparing achievable resource utilization of partitioned and monolithic servers, we quantify the cost of partitioning. Next, we present an architecture for a distributed server system that avoids resource partitioning and results in highly efficient server clusters. Finally, we show how, in these server clusters, further optimizations can be achieved through caching and batching of video streams.

Data Analytics for Smart Parking Applications.

PubMed

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-09-23

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset.

Data Analytics for Smart Parking Applications

PubMed Central

Piovesan, Nicola; Turi, Leo; Toigo, Enrico; Martinez, Borja; Rossi, Michele

2016-01-01

We consider real-life smart parking systems where parking lot occupancy data are collected from field sensor devices and sent to backend servers for further processing and usage for applications. Our objective is to make these data useful to end users, such as parking managers, and, ultimately, to citizens. To this end, we concoct and validate an automated classification algorithm having two objectives: (1) outlier detection: to detect sensors with anomalous behavioral patterns, i.e., outliers; and (2) clustering: to group the parking sensors exhibiting similar patterns into distinct clusters. We first analyze the statistics of real parking data, obtaining suitable simulation models for parking traces. We then consider a simple classification algorithm based on the empirical complementary distribution function of occupancy times and show its limitations. Hence, we design a more sophisticated algorithm exploiting unsupervised learning techniques (self-organizing maps). These are tuned following a supervised approach using our trace generator and are compared against other clustering schemes, namely expectation maximization, k-means clustering and DBSCAN, considering six months of data from a real sensor deployment. Our approach is found to be superior in terms of classification accuracy, while also being capable of identifying all of the outliers in the dataset. PMID:27669259

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

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

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

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

DOE PAGES

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

2017-11-27

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

Unresolved versus resolved: testing the validity of young simple stellar population models with VLT/MUSE observations of NGC 3603

NASA Astrophysics Data System (ADS)

Kuncarayakti, H.; Galbany, L.; Anderson, J. P.; Krühler, T.; Hamuy, M.

2016-09-01

Context. Stellar populations are the building blocks of galaxies, including the Milky Way. The majority, if not all, extragalactic studies are entangled with the use of stellar population models given the unresolved nature of their observation. Extragalactic systems contain multiple stellar populations with complex star formation histories. However, studies of these systems are mainly based upon the principles of simple stellar populations (SSP). Hence, it is critical to examine the validity of SSP models. Aims: This work aims to empirically test the validity of SSP models. This is done by comparing SSP models against observations of spatially resolved young stellar population in the determination of its physical properties, that is, age and metallicity. Methods: Integral field spectroscopy of a young stellar cluster in the Milky Way, NGC 3603, was used to study the properties of the cluster as both a resolved and unresolved stellar population. The unresolved stellar population was analysed using the Hα equivalent width as an age indicator and the ratio of strong emission lines to infer metallicity. In addition, spectral energy distribution (SED) fitting using STARLIGHT was used to infer these properties from the integrated spectrum. Independently, the resolved stellar population was analysed using the colour-magnitude diagram (CMD) to determine age and metallicity. As the SSP model represents the unresolved stellar population, the derived age and metallicity were tested to determine whether they agree with those derived from resolved stars. Results: The age and metallicity estimate of NGC 3603 derived from integrated spectroscopy are confirmed to be within the range of those derived from the CMD of the resolved stellar population, including other estimates found in the literature. The result from this pilot study supports the reliability of SSP models for studying unresolved young stellar populations. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programme 60.A-9344.

Hydrostatic Chandra X-ray analysis of SPT-selected galaxy clusters - I. Evolution of profiles and core properties

NASA Astrophysics Data System (ADS)

Sanders, J. S.; Fabian, A. C.; Russell, H. R.; Walker, S. A.

2018-02-01

We analyse Chandra X-ray Observatory observations of a set of galaxy clusters selected by the South Pole Telescope using a new publicly available forward-modelling projection code, MBPROJ2, assuming hydrostatic equilibrium. By fitting a power law plus constant entropy model we find no evidence for a central entropy floor in the lowest entropy systems. A model of the underlying central entropy distribution shows a narrow peak close to zero entropy which accounts for 60 per cent of the systems, and a second broader peak around 130 keV cm2. We look for evolution over the 0.28-1.2 redshift range of the sample in density, pressure, entropy and cooling time at 0.015R500 and at 10 kpc radius. By modelling the evolution of the central quantities with a simple model, we find no evidence for a non-zero slope with redshift. In addition, a non-parametric sliding median shows no significant change. The fraction of cool-core clusters with central cooling times below 2 Gyr is consistent above and below z = 0.6 (˜30-40 per cent). Both by comparing the median thermodynamic profiles, centrally biased towards cool cores, in two redshift bins, and by modelling the evolution of the unbiased average profile as a function of redshift, we find no significant evolution beyond self-similar scaling in any of our examined quantities. Our average modelled radial density, entropy and cooling-time profiles appear as power laws with breaks around 0.2R500. The dispersion in these quantities rises inwards of this radius to around 0.4 dex, although some of this scatter can be fitted by a bimodal model.

Towards an Autonomic Cluster Management System (ACMS) with Reflex Autonomicity

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Hinchey, Mike; Sterritt, Roy

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of providing a fault-tolerant environment and achieving significant computational capabilities for high-performance computing applications. However, the task of manually managing and configuring a cluster quickly becomes daunting as the cluster grows in size. Autonomic computing, with its vision to provide self-management, can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Autonomic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management and its evolution to include reflex reactions via pulse monitoring.

Multiple stellar populations in Magellanic Cloud clusters - III. The first evidence of an extended main sequence turn-off in a young cluster: NGC 1856

NASA Astrophysics Data System (ADS)

Milone, A. P.; Bedin, L. R.; Piotto, G.; Marino, A. F.; Cassisi, S.; Bellini, A.; Jerjen, H.; Pietrinferni, A.; Aparicio, A.; Rich, R. M.

2015-07-01

Recent studies have shown that the extended main-sequence turn-off (eMSTO) is a common feature of intermediate-age star clusters in the Magellanic Clouds (MCs). The most simple explanation is that these stellar systems harbour multiple generations of stars with an age difference of a few hundred million years. However, while an eMSTO has been detected in a large number of clusters with ages between ˜1-2 Gyr, several studies of young clusters in both MCs and in nearby galaxies do not find any evidence for a prolonged star formation history, i. e. for multiple stellar generations. These results have suggested alternative interpretation of the eMSTOs observed in intermediate-age star clusters. The eMSTO could be due to stellar rotation mimicking an age spread or to interacting binaries. In these scenarios, intermediate-age MC clusters would be simple stellar populations, in close analogy with younger clusters. Here, we provide the first evidence for an eMSTO in a young stellar cluster. We exploit multiband Hubble Space Telescope photometry to study the ˜300-Myr old star cluster NGC 1856 in the Large Magellanic Cloud and detected a broadened MSTO that is consistent with a prolonged star formation which had a duration of about 150 Myr. Below the turn-off, the main sequence (MS) of NGC 1856 is split into a red and blue component, hosting 33 ± 5 and 67 ± 5 per cent of the total number of MS stars, respectively. We discuss these findings in the context of multiple-stellar-generation, stellar-rotation, and interacting-binary hypotheses.

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.

Pattern recognition analysis and classification modeling of selenium-producing areas

USGS Publications Warehouse

Naftz, D.L.

1996-01-01

Established chemometric and geochemical techniques were applied to water quality data from 23 National Irrigation Water Quality Program (NIWQP) study areas in the Western United States. These techniques were applied to the NIWQP data set to identify common geochemical processes responsible for mobilization of selenium and to develop a classification model that uses major-ion concentrations to identify areas that contain elevated selenium concentrations in water that could pose a hazard to water fowl. Pattern recognition modeling of the simple-salt data computed with the SNORM geochemical program indicate three principal components that explain 95% of the total variance. A three-dimensional plot of PC 1, 2 and 3 scores shows three distinct clusters that correspond to distinct hydrochemical facies denoted as facies 1, 2 and 3. Facies 1 samples are distinguished by water samples without the CaCO3 simple salt and elevated concentrations of NaCl, CaSO4, MgSO4 and Na2SO4 simple salts relative to water samples in facies 2 and 3. Water samples in facies 2 are distinguished from facies 1 by the absence of the MgSO4 simple salt and the presence of the CaCO3 simple salt. Water samples in facies 3 are similar to samples in facies 2, with the absence of both MgSO4 and CaSO4 simple salts. Water samples in facies 1 have the largest selenium concentration (10 ??gl-1), compared to a median concentration of 2.0 ??gl-1 and less than 1.0 ??gl-1 for samples in facies 2 and 3. A classification model using the soft independent modeling by class analogy (SIMCA) algorithm was constructed with data from the NIWQP study areas. The classification model was successful in identifying water samples with a selenium concentration that is hazardous to some species of water-fowl from a test data set comprised of 2,060 water samples from throughout Utah and Wyoming. Application of chemometric and geochemical techniques during data synthesis analysis of multivariate environmental databases from other national-scale environmental programs such as the NIWQP could also provide useful insights for addressing 'real world' environmental problems.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Preparation and Luminescence Thermochromism of Tetranuclear Copper(I)-Pyridine-Iodide Clusters

ERIC Educational Resources Information Center

Parmeggiani, Fabio; Sacchetti, Alessandro

2012-01-01

A simple and straightforward synthesis of a tetranuclear copper(I)-pyridine-iodide cluster is described as a laboratory experiment for advanced inorganic chemistry undergraduate students. The product is used to demonstrate the fascinating and visually impressive phenomenon of luminescence thermochromism: exposed to long-wave UV light, the…

Using routine surveillance data to estimate the epidemic potential of emerging zoonoses: application to the emergence of US swine origin influenza A H3N2v virus.

PubMed

Cauchemez, Simon; Epperson, Scott; Biggerstaff, Matthew; Swerdlow, David; Finelli, Lyn; Ferguson, Neil M

2013-01-01

Prior to emergence in human populations, zoonoses such as SARS cause occasional infections in human populations exposed to reservoir species. The risk of widespread epidemics in humans can be assessed by monitoring the reproduction number R (average number of persons infected by a human case). However, until now, estimating R required detailed outbreak investigations of human clusters, for which resources and expertise are not always available. Additionally, existing methods do not correct for important selection and under-ascertainment biases. Here, we present simple estimation methods that overcome many of these limitations. Our approach is based on a parsimonious mathematical model of disease transmission and only requires data collected through routine surveillance and standard case investigations. We apply it to assess the transmissibility of swine-origin influenza A H3N2v-M virus in the US, Nipah virus in Malaysia and Bangladesh, and also present a non-zoonotic example (cholera in the Dominican Republic). Estimation is based on two simple summary statistics, the proportion infected by the natural reservoir among detected cases (G) and among the subset of the first detected cases in each cluster (F). If detection of a case does not affect detection of other cases from the same cluster, we find that R can be estimated by 1-G; otherwise R can be estimated by 1-F when the case detection rate is low. In more general cases, bounds on R can still be derived. We have developed a simple approach with limited data requirements that enables robust assessment of the risks posed by emerging zoonoses. We illustrate this by deriving transmissibility estimates for the H3N2v-M virus, an important step in evaluating the possible pandemic threat posed by this virus. Please see later in the article for the Editors' Summary.

A General Precipitation-limited L X–T–R Relation among Early-type Galaxies

NASA Astrophysics Data System (ADS)

Voit, G. Mark; Ma, C. P.; Greene, J.; Goulding, A.; Pandya, V.; Donahue, M.; Sun, M.

2018-01-01

The relation between X-ray luminosity (L X) and ambient gas temperature (T) among massive galactic systems is an important cornerstone of both observational cosmology and galaxy-evolution modeling. In the most massive galaxy clusters, the relation is determined primarily by cosmological structure formation. In less massive systems, it primarily reflects the feedback response to radiative cooling of circumgalactic gas. Here we present a simple but powerful model for the L X–T relation as a function of physical aperture R within which those measurements are made. The model is based on the precipitation framework for AGN feedback and assumes that the circumgalactic medium is precipitation-regulated at small radii and limited by cosmological structure formation at large radii. We compare this model with many different data sets and show that it successfully reproduces the slope and upper envelope of the L X–T–R relation over the temperature range from ∼0.2 keV through ≳ 10 {keV}. Our findings strongly suggest that the feedback mechanisms responsible for regulating star formation in individual massive galaxies have much in common with the precipitation-triggered feedback that appears to regulate galaxy-cluster cores.

The Globular Cluster NGC 2419: A Crucible for Theories of Gravity

NASA Astrophysics Data System (ADS)

Ibata, R.; Sollima, A.; Nipoti, C.; Bellazzini, M.; Chapman, S. C.; Dalessandro, E.

2011-09-01

We present the analysis of a kinematic data set of stars in the globular cluster NGC 2419, taken with the DEep Imaging Multi-Object Spectrograph at the Keck II telescope. Combined with a reanalysis of deep Hubble Space Telescope and Subaru Telescope imaging data, which provide an accurate luminosity profile of the cluster, we investigate the validity of a large set of dynamical models of the system, which are checked for stability via N-body simulations. We find that isotropic models in either Newtonian or Modified Newtonian Dynamics (MOND) are ruled out with extremely high confidence. However, a simple Michie model in Newtonian gravity with anisotropic velocity dispersion provides an excellent representation of the luminosity profile and kinematics of the cluster. The anisotropy profiles of these models ensure an isotropic center to the cluster, which progresses to extreme radial anisotropy toward the outskirts. In contrast, with MOND we find that Michie models that reproduce the luminosity profile either overpredict the velocity dispersion on the outskirts of the cluster if the mass-to-light ratio (M/L) is kept at astrophysically motivated values or else they underpredict the central velocity dispersion if the M/L is taken to be very small. We find that the best Michie model in MOND is a factor of ~104 less likely than the Newtonian model that best fits the system. A likelihood ratio of 350 is found when we investigate more general models by solving the Jeans equation with a Markov Chain Monte Carlo scheme. We verified with N-body simulations that these results are not significantly different when the MOND external field effect is accounted for. If the assumptions that the cluster is in dynamical equilibrium, spherical, not on a peculiar orbit, and possesses a single dynamical tracer population of constant M/L are correct, we conclude that the present observations provide a very severe challenge for MOND. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. This paper was also based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institute National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii.

Appplication of statistical mechanical methods to the modeling of social networks

NASA Astrophysics Data System (ADS)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Collective firm bankruptcies and phase transition in rating dynamics

NASA Astrophysics Data System (ADS)

Sieczka, P.; Hołyst, J. A.

2009-10-01

We present a simple model of firm rating evolution. We consider two sources of defaults: individual dynamics of economic development and Potts-like interactions between firms. We show that such a defined model leads to phase transition, which results in collective defaults. The existence of the collective phase depends on the mean interaction strength. For small interaction strength parameters, there are many independent bankruptcies of individual companies. For large parameters, there are giant collective defaults of firm clusters. In the case when the individual firm dynamics favors dumping of rating changes, there is an optimal strength of the firm's interactions from the systemic risk point of view. in here

Counts-in-cylinders in the Sloan Digital Sky Survey with Comparisons to N-body Simulations

NASA Astrophysics Data System (ADS)

Berrier, Heather D.; Barton, Elizabeth J.; Berrier, Joel C.; Bullock, James S.; Zentner, Andrew R.; Wechsler, Risa H.

2011-01-01

Environmental statistics provide a necessary means of comparing the properties of galaxies in different environments, and a vital test of models of galaxy formation within the prevailing hierarchical cosmological model. We explore counts-in-cylinders, a common statistic defined as the number of companions of a particular galaxy found within a given projected radius and redshift interval. Galaxy distributions with the same two-point correlation functions do not necessarily have the same companion count distributions. We use this statistic to examine the environments of galaxies in the Sloan Digital Sky Survey Data Release 4 (SDSS DR4). We also make preliminary comparisons to four models for the spatial distributions of galaxies, based on N-body simulations and data from SDSS DR4, to study the utility of the counts-in-cylinders statistic. There is a very large scatter between the number of companions a galaxy has and the mass of its parent dark matter halo and the halo occupation, limiting the utility of this statistic for certain kinds of environmental studies. We also show that prevalent empirical models of galaxy clustering, that match observed two- and three-point clustering statistics well, fail to reproduce some aspects of the observed distribution of counts-in-cylinders on 1, 3, and 6 h -1 Mpc scales. All models that we explore underpredict the fraction of galaxies with few or no companions in 3 and 6 h -1 Mpc cylinders. Roughly 7% of galaxies in the real universe are significantly more isolated within a 6 h -1 Mpc cylinder than the galaxies in any of the models we use. Simple phenomenological models that map galaxies to dark matter halos fail to reproduce high-order clustering statistics in low-density environments.

Influence of the geometrical detail in the description of DNA and the scoring method of ionization clustering on nanodosimetric parameters of track structure: a Monte Carlo study using Geant4-DNA

NASA Astrophysics Data System (ADS)

Bueno, M.; Schulte, R.; Meylan, S.; Villagrasa, C.

2015-11-01

The aim of this study was to evaluate the influence of the geometrical detail of the DNA on nanodosimetric parameters of track structure induced by protons and alpha particles of different energies (LET values ranging from 1 to 162.5~\\text{keV}~μ {{\\text{m}}-1} ) as calculated by Geant4-DNA Monte Carlo simulations. The first geometry considered consisted of a well-structured placement of a realistic description of the DNA double helix wrapped around cylindrical histones (GeomHist) forming a 18 kbp-long chromatin fiber. In the second geometry considered, the DNA was modeled as a total of 1800 ten bp-long homogeneous cylinders (2.3 nm diameter and 3.4 nm height) placed in random positions and orientations (GeomCyl). As for GeomHist, GeomCyl contained a DNA material equivalent to 18 kbp. Geant4-DNA track structure simulations were performed and ionizations were counted in the scoring volumes. For GeomCyl, clusters were defined as the number of ionizations (ν) scored in each 10 bp-long cylinder. For GeomHist, clusters of ionizations scored in the sugar-phosphate groups of the double-helix were revealed by the DBSCAN clustering algorithm according to a proximity criteria among ionizations separated by less than 10 bp. The topology of the ionization clusters formed using GeomHist and GeomCyl geometries were compared in terms of biologically relevant nanodosimetric quantities. The discontinuous modeling of the DNA for GeomCyl led to smaller cluster sizes than for GeomHist. The continuous modeling of the DNA molecule for GeomHist allowed the merging of ionization points by the DBSCAN algorithm giving rise to larger clusters, which were not detectable within the GeomCyl geometry. Mean cluster size (m1) was found to be of the order of 10% higher for GeomHist compared to GeomCyl for LET <15~\\text{keV}~μ {{\\text{m}}-1} . For higher LETs, the difference increased with LET similarly for protons and alpha particles. Both geometries showed the same relationship between m1 and the cumulative relative frequency of clusters with ν ≥slant 3 (f3) within statistical variations, independently of particle type. In order to obtain ionization cluster size distributions relevant for biological DNA lesions, the complex DNA geometry and a scoring method without fixed boundaries should be preferred to the simple cylindrical geometry with a fixed scoring volume.

Using Massive Star Clusters in Merger Remnants To Provide Reference Colors of Intermediate-Age Stellar Populations

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2009-07-01

Much current research in cosmology and galaxy formation relies on an accurate interpretation of colors of galaxies in terms of their evolutionary state, i.e., in terms of ages and metallicities. One particularly important topic is the ability to identify early-type galaxies at "intermediate" ages { 500 Myr - 5 Gyr}, i.e., the period between the end of star formation and half the age of the universe. Currently, integrated-light studies must rely on population synthesis models which rest upon spectral libraries of stars in the solar neighborhood. These models have a difficult time correctly incorporating short-lived evolutionary phases such as thermally pulsing AGB stars, which produce up to 80% of the flux in the near-IR in this age range. Furthermore, intermediate-age star clusters in the Local Group do not represent proper templates against which to calibrate population synthesis models in this age range, because their masses are too low to render the effect of stochastic fluctuations due to the number of bright RGB and AGB stars negligible. As a consequence, current population synthesis models have trouble reconciling the evolutionary state of high-redshift galaxies from optical versus near-IR colors. We propose a simple and effective solution to this issue, namely obtaining high-quality EMPIRICAL colors of massive globular clusters in galaxy merger remnants which span this important age range. These colors should serve as relevant references, both to identify intermediate-age objects in the local and distant universe and as calibrators for population synthesis modellers.

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.

New approaches to model and study social networks

NASA Astrophysics Data System (ADS)

Lind, P. G.; Herrmann, H. J.

2007-07-01

We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features, we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbours which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped about.

Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

2016-04-01

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

New Constraints on a Complex Relation between Globular Cluster Colors and Environment

NASA Astrophysics Data System (ADS)

Powalka, Mathieu; Puzia, Thomas H.; Lançon, Ariane; Peng, Eric W.; Schönebeck, Frederik; Alamo-Martínez, Karla; Ángel, Simón; Blakeslee, John P.; Côté, Patrick; Cuillandre, Jean-Charles; Duc, Pierre-Alain; Durrell, Patrick; Ferrarese, Laura; Grebel, Eva K.; Guhathakurta, Puragra; Gwyn, S. D. J.; Kuntschner, Harald; Lim, Sungsoon; Liu, Chengze; Lyubenova, Mariya; Mihos, J. Christopher; Muñoz, Roberto P.; Ordenes-Briceño, Yasna; Roediger, Joel; Sánchez-Janssen, Rubén; Spengler, Chelsea; Toloba, Elisa; Zhang, Hongxin

2016-09-01

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color-color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color-color space. While the average photometric colors become bluer with increasing radial distance to the cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color-color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.

Sampling procedures for throughfall monitoring: A simulation study

NASA Astrophysics Data System (ADS)

Zimmermann, Beate; Zimmermann, Alexander; Lark, Richard Murray; Elsenbeer, Helmut

2010-01-01

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

A simple model for DNA bridging proteins and bacterial or human genomes: bridging-induced attraction and genome compaction

NASA Astrophysics Data System (ADS)

Johnson, J.; Brackley, C. A.; Cook, P. R.; Marenduzzo, D.

2015-02-01

We present computer simulations of the phase behaviour of an ensemble of proteins interacting with a polymer, mimicking non-specific binding to a piece of bacterial DNA or eukaryotic chromatin. The proteins can simultaneously bind to the polymer in two or more places to create protein bridges. Despite the lack of any explicit interaction between the proteins or between DNA segments, our simulations confirm previous results showing that when the protein-polymer interaction is sufficiently strong, the proteins come together to form clusters. Furthermore, a sufficiently large concentration of bridging proteins leads to the compaction of the swollen polymer into a globular phase. Here we characterise both the formation of protein clusters and the polymer collapse as a function of protein concentration, protein-polymer affinity and fibre flexibility.

[Advances in application of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 system in stem cells research].

PubMed

Sun, S J; Huo, J H; Geng, Z J; Sun, X Y; Fu, X B

2018-04-20

Gene engineering has attracted worldwide attention because of its ability of precise location of disease mutations in genome. As a new gene editing technology, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system is simple, fast, and accurate to operate at a specific gene site. It overcomes the long-standing problem of conventional operation. At the same time, stem cells are a good foundation for establishing disease model in vitro. Therefore, it has great significance to combine stem cells with the rapidly developing gene manipulation techniques. In this review, we mainly focus on the mechanism of CRISPR/Cas9 technology and its application in stem cell genomic editing, so as to pave the way for promoting rapid application and development of CRISPR/Cas9 technology.

Mean Occupation Function of High-redshift Quasars from the Planck Cluster Catalog

NASA Astrophysics Data System (ADS)

Chakraborty, Priyanka; Chatterjee, Suchetana; Dutta, Alankar; Myers, Adam D.

2018-06-01

We characterize the distribution of quasars within dark matter halos using a direct measurement technique for the first time at redshifts as high as z ∼ 1. Using the Planck Sunyaev-Zeldovich (SZ) catalog for galaxy groups and the Sloan Digital Sky Survey (SDSS) DR12 quasar data set, we assign host clusters/groups to the quasars and make a measurement of the mean number of quasars within dark matter halos as a function of halo mass. We find that a simple power-law fit of {log}< N> =(2.11+/- 0.01) {log}(M)-(32.77+/- 0.11) can be used to model the quasar fraction in dark matter halos. This suggests that the quasar fraction increases monotonically as a function of halo mass even to redshifts as high as z ∼ 1.

Jellyfish: the origin and distribution of extreme ram-pressure stripping events in massive galaxy clusters

NASA Astrophysics Data System (ADS)

McPartland, Conor; Ebeling, Harald; Roediger, Elke; Blumenthal, Kelly

2016-01-01

We investigate the observational signatures and physical origin of ram-pressure stripping (RPS) in 63 massive galaxy clusters at z = 0.3-0.7, based on images obtained with the Hubble Space Telescope. Using a training set of a dozen `jellyfish' galaxies identified earlier in the same imaging data, we define morphological criteria to select 211 additional, less obvious cases of RPS. Spectroscopic follow-up observations of 124 candidates so far confirmed 53 as cluster members. For the brightest and most favourably aligned systems, we visually derive estimates of the projected direction of motion based on the orientation of apparent compression shocks and debris trails. Our findings suggest that the onset of these events occurs primarily at large distances from the cluster core (>400 kpc), and that the trajectories of the affected galaxies feature high-impact parameters. Simple models show that such trajectories are highly improbable for galaxy infall along filaments but common for infall at high velocities, even after observational biases are accounted for, provided the duration of the resulting RPS events is ≲500 Myr. We thus tentatively conclude that extreme RPS events are preferentially triggered by cluster mergers, an interpretation that is supported by the disturbed dynamical state of many of the host clusters. This hypothesis implies that extreme RPS might occur also near the cores of merging poor clusters or even merging groups of galaxies. Finally, we present nine additional `jellyfish" galaxies at z > 0.3 discovered by us, thereby doubling the number of such systems known at intermediate redshift.

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

PubMed

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

2017-01-09

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

Autonomic Cluster Management System (ACMS): A Demonstration of Autonomic Principles at Work

NASA Technical Reports Server (NTRS)

Baldassari, James D.; Kopec, Christopher L.; Leshay, Eric S.; Truszkowski, Walt; Finkel, David

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of achieving significant computational capabilities for high-performance computing applications, while simultaneously affording the ability to. increase that capability simply by adding more (inexpensive) processors. However, the task of manually managing and con.guring a cluster quickly becomes impossible as the cluster grows in size. Autonomic computing is a relatively new approach to managing complex systems that can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Automatic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management.

Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank.

PubMed

Muñoz, María; Pong-Wong, Ricardo; Canela-Xandri, Oriol; Rawlik, Konrad; Haley, Chris S; Tenesa, Albert

2016-09-01

Genome-wide association studies have detected many loci underlying susceptibility to disease, but most of the genetic factors that contribute to disease susceptibility remain unknown. Here we provide evidence that part of the 'missing heritability' can be explained by an overestimation of heritability. We estimated the heritability of 12 complex human diseases using family history of disease in 1,555,906 individuals of white ancestry from the UK Biobank. Estimates using simple family-based statistical models were inflated on average by ∼47% when compared with those from structural equation modeling (SEM), which specifically accounted for shared familial environmental factors. In addition, heritabilities estimated using SNP data explained an average of 44.2% of the simple family-based estimates across diseases and an average of 57.3% of the SEM-estimated heritabilities, accounting for almost all of the SEM heritability for hypertension. Our results show that both genetics and familial environment make substantial contributions to familial clustering of disease.

Genetic diversity studies in pea (Pisum sativum L.) using simple sequence repeat markers.

PubMed

Kumari, P; Basal, N; Singh, A K; Rai, V P; Srivastava, C P; Singh, P K

2013-03-13

The genetic diversity among 28 pea (Pisum sativum L.) genotypes was analyzed using 32 simple sequence repeat markers. A total of 44 polymorphic bands, with an average of 2.1 bands per primer, were obtained. The polymorphism information content ranged from 0.657 to 0.309 with an average of 0.493. The variation in genetic diversity among these cultivars ranged from 0.11 to 0.73. Cluster analysis based on Jaccard's similarity coefficient using the unweighted pair-group method with arithmetic mean (UPGMA) revealed 2 distinct clusters, I and II, comprising 6 and 22 genotypes, respectively. Cluster II was further differentiated into 2 subclusters, IIA and IIB, with 12 and 10 genotypes, respectively. Principal component (PC) analysis revealed results similar to those of UPGMA. The first, second, and third PCs contributed 21.6, 16.1, and 14.0% of the variation, respectively; cumulative variation of the first 3 PCs was 51.7%.

Centre-excised X-ray luminosity as an efficient mass proxy for future galaxy cluster surveys

DOE PAGES

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn; ...

2017-10-02

The cosmological constraining power of modern galaxy cluster catalogues can be improved by obtaining low-scatter mass proxy measurements for even a small fraction of sources. In the context of large upcoming surveys that will reveal the cluster population down to the group scale and out to high redshifts, efficient strategies for obtaining such mass proxies will be valuable. Here in this work, we use high-quality weak-lensing and X-ray mass estimates for massive clusters in current X-ray-selected catalogues to revisit the scaling relations of the projected, centre-excised X-ray luminosity (L ce), which previous work suggests correlates tightly with total mass. Ourmore » data confirm that this is the case with Lce having an intrinsic scatter at fixed mass comparable to that of gas mass, temperature or YX. Compared to the other proxies, however, Lce is less susceptible to systematic uncertainties due to background modelling, and can be measured precisely with shorter exposures. This opens up the possibility of using L ce to estimate masses for large numbers of clusters discovered by new X-ray surveys (e.g. eROSITA) directly from the survey data, as well as for clusters discovered at other wavelengths with relatively short follow-up observations. We describe a simple procedure for making such estimates from X-ray surface brightness data, and comment on the spatial resolution required to apply this method as a function of cluster mass and redshift. Lastly, we also explore the potential impact of Chandra and XMM–Newton follow-up observations over the next decade on dark energy constraints from new cluster surveys.« less

Centre-excised X-ray luminosity as an efficient mass proxy for future galaxy cluster surveys

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

Mantz, Adam B.; Allen, Steven W.; Morris, R. Glenn

The cosmological constraining power of modern galaxy cluster catalogues can be improved by obtaining low-scatter mass proxy measurements for even a small fraction of sources. In the context of large upcoming surveys that will reveal the cluster population down to the group scale and out to high redshifts, efficient strategies for obtaining such mass proxies will be valuable. Here in this work, we use high-quality weak-lensing and X-ray mass estimates for massive clusters in current X-ray-selected catalogues to revisit the scaling relations of the projected, centre-excised X-ray luminosity (L ce), which previous work suggests correlates tightly with total mass. Ourmore » data confirm that this is the case with Lce having an intrinsic scatter at fixed mass comparable to that of gas mass, temperature or YX. Compared to the other proxies, however, Lce is less susceptible to systematic uncertainties due to background modelling, and can be measured precisely with shorter exposures. This opens up the possibility of using L ce to estimate masses for large numbers of clusters discovered by new X-ray surveys (e.g. eROSITA) directly from the survey data, as well as for clusters discovered at other wavelengths with relatively short follow-up observations. We describe a simple procedure for making such estimates from X-ray surface brightness data, and comment on the spatial resolution required to apply this method as a function of cluster mass and redshift. Lastly, we also explore the potential impact of Chandra and XMM–Newton follow-up observations over the next decade on dark energy constraints from new cluster surveys.« less

Hot Gas Halos in Galaxies

NASA Astrophysics Data System (ADS)

Mulchaey, John

Most galaxy formation models predict that massive low-redshift disk galaxies are embedded in extended hot halos of externally accreted gas. Such gas appears necessary to maintain ongoing star formation in isolated spirals like the Milky Way. To explain the large population of red galaxies in rich groups and clusters, most galaxy evolution models assume that these hot gas halos are stripped completely when a galaxy enters a denser environment. This simple model has been remarkably successful at reproducing many observed properties of galaxies. Although theoretical arguments suggest hot gas halos are an important component in galaxies, we know very little about this gas from an observational standpoint. In fact, previous observations have failed to detect soft X-ray emission from such halos in disk galaxies. Furthermore, the assumption that hot gas halos are stripped completely when a galaxy enters a group or cluster has not been verified. We propose to combine proprietary and archival XMM-Newton observations of galaxies in the field, groups and clusters to study how hot gas halos are impacted by environment. Our proposed program has three components: 1) The deepest search to date for a hot gas halo in a quiescent spiral galaxy. A detection will confirm a basic tenet of disk galaxy formation models, whereas a non-detection will seriously challenge these models and impose new constraints on the growth mode and feedback history of disk galaxies. 2) A detailed study of the hot gas halos properties of field early-type galaxies. As environmental processes such as stripping are not expected to be important in the field, a study of hot gas halos in this environment will allow us to better understand how feedback and other internal processes impact hot gas halos. 3) A study of hot gas halos in the outskirts of groups and clusters. By comparing observations with our suite of simulations we can begin to understand what role the stripping of hot gas halos plays in galaxy evolution.

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

SLURM: Simplex Linux Utility for Resource Management

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

Jette, M; Grondona, M

2003-04-22

Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters of thousands of nodes. Components include machine status, partition management, job management, scheduling, and stream copy modules. This paper presents an overview of the SLURM architecture and functionality.

Construction Cluster Volume 5 [Electrical].

ERIC Educational Resources Information Center

Pennsylvania State Dept. of Justice, Harrisburg. Bureau of Correction.

The document is the fifth of a series, to be integrated with a G.E.D. program, containing instructional materials for the construction cluster. The volume focuses on electrical work and consists of 20 instructional units which require a month of study: (1) safety precautions and first aid for electrical workers; (2) planning a simple installation;…

A HYDRODYNAMICAL SOLUTION FOR THE ''TWIN-TAILED'' COLLIDING GALAXY CLUSTER ''EL GORDO''

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

Molnar, Sandor M.; Broadhurst, Tom, E-mail: sandor@phys.ntu.edu.tw

The distinctive cometary X-ray morphology of the recently discovered massive galaxy cluster ''El Gordo'' (ACT-CT J0102–4915; z = 0.87) indicates that an unusually high-speed collision is ongoing between two massive galaxy clusters. A bright X-ray ''bullet'' leads a ''twin-tailed'' wake, with the Sunyaev-Zel'dovich (SZ) centroid at the end of the northern tail. We show how the physical properties of this system can be determined using our FLASH-based, N-body/hydrodynamic model, constrained by detailed X-ray, SZ, and Hubble lensing and dynamical data. The X-ray morphology and the location of the two dark matter components and the SZ peak are accurately described by amore » simple binary collision viewed about 480 million years after the first core passage. We derive an impact parameter of ≅300 kpc, and a relative initial infall velocity of ≅2250 km s{sup –1} when separated by the sum of the two virial radii assuming an initial total mass of 2.15 × 10{sup 15} M {sub ☉} and a mass ratio of 1.9. Our model demonstrates that tidally stretched gas accounts for the northern X-ray tail along the collision axis between the mass peaks, and that the southern tail lies off axis, comprising compressed and shock heated gas generated as the less massive component plunges through the main cluster. The challenge for ΛCDM will be to find out if this physically extreme event can be plausibly accommodated when combined with the similarly massive, high-infall-velocity case of the Bullet cluster and other such cases being uncovered in new SZ based surveys.« less

Nano-jewellery: C5Au12--a gold-plated diamond at molecular level.

PubMed

Naumkin, F

2006-06-07

A mixed carbon-metal cluster is designed by combining the tetrahedral C(5) radical (with a central atom-the skeleton of the C(5)H(12) molecule) and the spherical Au(12) layer (the external atomic shell of the Au(13) cluster). The C(5)Au(12) cluster and its negative and positive ionic derivatives, C(5)Au(12)(+/-), are investigated ab initio (DFT) in terms of optimized structures and relative energies of a few spin-states, for the icosahedral-like and octahedral-like isomers. The cluster is predicted to be generally more stable in its octahedral shape (similar to C(5)H(12)) which prevails for the negative ion and may compete with the icosahedral shape for the neutral system and positive ion. Adiabatic ionization energies (AIE) and electron affinities (AEA) of C(5)Au(12), vertical electron-detachment (VDE) energies of C(5)Au(12)(-), and vertical ionization and electron-attachment energies (VIE, VEA) of C(5)Au(12) are calculated as well, and compared with those for the corresponding isomers of the Au(13) cluster. The AIE and VIE values are found to be close for the two systems, while the AEA and VDE values are significantly reduced for the radical-based species. A simple fragment-based model is proposed for the decomposition of the total interaction into carbon-gold and gold-gold components.

Optical signatures of molecular particles via mass-selected cluster spectroscopy

NASA Technical Reports Server (NTRS)

Duncan, Michael A.

1990-01-01

A new molecular beam apparatus was developed to study optical absorption in cold (less than 100 K) atomic clusters and complexes produced by their condensation with simple molecular gases. In this instrument, ionized clusters produced in a laser vaporization nozzle source are mass selected and studied with photodissociation spectroscopy at visible and ultraviolet wavelengths. This new approach can be applied to synthesize and characterize numerous particulates and weakly bound complexes expected in planetary atmospheres and in comets.

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.

Evaluating and comparing methods of sinkhole susceptibility mapping in the Ebro Valley evaporite karst (NE Spain)

NASA Astrophysics Data System (ADS)

Galve, J. P.; Gutiérrez, F.; Remondo, J.; Bonachea, J.; Lucha, P.; Cendrero, A.

2009-10-01

Multiple sinkhole susceptibility models have been generated in three study areas of the Ebro Valley evaporite karst (NE Spain) applying different methods (nearest neighbour distance, sinkhole density, heuristic scoring system and probabilistic analysis) for each sinkhole type separately (cover collapse sinkholes, cover and bedrock collapse sinkholes and cover and bedrock sagging sinkholes). The quantitative and independent evaluation of the predictive capability of the models reveals that: (1) The most reliable susceptibility models are those derived from the nearest neighbour distance and sinkhole density. These models can be generated in a simple and rapid way from detailed geomorphological maps. (2) The reliability of the nearest neighbour distance and density models is conditioned by the degree of clustering of the sinkholes. Consequently, the karst areas in which sinkholes show a higher clustering are a priori more favourable for predicting new occurrences. (3) The predictive capability of the best models obtained in this research is significantly higher (12.5-82.5%) than that of the heuristic sinkhole susceptibility model incorporated into the General Urban Plan for the municipality of Zaragoza. Although the probabilistic approach provides lower quality results than the methods based on sinkhole proximity and density, it helps to identify the most significant factors and select the most effective mitigation strategies and may be applied to model susceptibility in different future scenarios.

Non-Abelian Bremsstrahlung and Azimuthal Asymmetries in High Energy p+A Reactions

DOE PAGES

Gyulassy, Miklos; Vitev, Ivan Mateev; Levai, Peter; ...

2014-09-25

Here we apply the GLV reaction operator solution to the Vitev-Gunion-Bertsch (VGB) boundary conditions to compute the all-order in nuclear opacity non-abelian gluon bremsstrahlung of event- by-event uctuating beam jets in nuclear collisions. We evaluate analytically azimuthal Fourier moments of single gluon, vmore » $$M\\atop{n}$$ {1}, and even number 2ℓ gluon, v$$M\\atop{n}$$ {2ℓ} inclusive distributions in high energy p+A reactions as a function of harmonic $n$, target recoil cluster number, $M$, and gluon number, 2ℓ, at RHIC and LHC. Multiple resolved clusters of recoiling target beam jets together with the projectile beam jet form Color Scintillation Antenna (CSA) arrays that lead to character- istic boost non-invariant trapezoidal rapidity distributions in asymmetric B+A nuclear collisions. The scaling of intrinsically azimuthally anisotropic and long range in η nature of the non-Abelian bremsstrahlung leads to v n moments that are similar to results from hydrodynamic models, but due entirely to non-Abelian wave interference phenomena sourced by the fluctuating CSA. Our analytic non-flow solutions are similar to recent numerical saturation model predictions but differ by predicting a simple power-law hierarchy of both even and odd v n without invoking k T factorization. A test of CSA mechanism is the predicted nearly linear η rapidity dependence of the v n(k Tη). Non- Abelian beam jet bremsstrahlung may thus provide a simple analytic solution to Beam Energy Scan (BES) puzzle of the near $$\\sqrt{s}$$ independence of v n(pT) moments observed down to 10 AGeV where large-x valence quark beam jets dominate inelastic dynamics. Recoil bremsstrahlung from multiple independent CSA clusters could also provide a partial explanation for the unexpected similarity of v n in p(D) + A and non-central A + A at same dN=dη multiplicity as observed at RHIC and LHC.« less

The comparison of automated clustering algorithms for resampling representative conformer ensembles with RMSD matrix.

PubMed

Kim, Hyoungrae; Jang, Cheongyun; Yadav, Dharmendra K; Kim, Mi-Hyun

2017-03-23

The accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate enough conformers, however model building methods relies on explicit number of common conformers. In this work, we have attempted to make clustering algorithms, which could find reasonable number of representative conformer ensembles automatically with asymmetric dissimilarity matrix generated from openeye tool kit. RMSD was the important descriptor (variable) of each column of the N × N matrix considered as N variables describing the relationship (network) between the conformer (in a row) and the other N conformers. This approach used to evaluate the performance of the well-known clustering algorithms by comparison in terms of generating representative conformer ensembles and test them over different matrix transformation functions considering the stability. In the network, the representative conformer group could be resampled for four kinds of algorithms with implicit parameters. The directed dissimilarity matrix becomes the only input to the clustering algorithms. Dunn index, Davies-Bouldin index, Eta-squared values and omega-squared values were used to evaluate the clustering algorithms with respect to the compactness and the explanatory power. The evaluation includes the reduction (abstraction) rate of the data, correlation between the sizes of the population and the samples, the computational complexity and the memory usage as well. Every algorithm could find representative conformers automatically without any user intervention, and they reduced the data to 14-19% of the original values within 1.13 s per sample at the most. The clustering methods are simple and practical as they are fast and do not ask for any explicit parameters. RCDTC presented the maximum Dunn and omega-squared values of the four algorithms in addition to consistent reduction rate between the population size and the sample size. The performance of the clustering algorithms was consistent over different transformation functions. Moreover, the clustering method can also be applied to molecular dynamics sampling simulation results.

Accuracy assessment of a net radiation and temperature index snowmelt model using ground observations of snow water equivalent in an alpine basin

NASA Astrophysics Data System (ADS)

Molotch, N. P.; Painter, T. H.; Bales, R. C.; Dozier, J.

2003-04-01

In this study, an accumulated net radiation / accumulated degree-day index snowmelt model was coupled with remotely sensed snow covered area (SCA) data to simulate snow cover depletion and reconstruct maximum snow water equivalent (SWE) in the 19.1-km2 Tokopah Basin of the Sierra Nevada, California. Simple net radiation snowmelt models are attractive for operational snowmelt runoff forecasts as they are computationally inexpensive and have low input requirements relative to physically based energy balance models. The objective of this research was to assess the accuracy of a simple net radiation snowmelt model in a topographically heterogeneous alpine environment. Previous applications of net radiation / temperature index snowmelt models have not been evaluated in alpine terrain with intensive field observations of SWE. Solar radiation data from two meteorological stations were distributed using the topographic radiation model TOPORAD. Relative humidity and temperature data were distributed based on the lapse rate calculated between three meteorological stations within the basin. Fractional SCA data from the Landsat Enhanced Thematic Mapper (5 acquisitions) and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) (2 acquisitions) were used to derive daily SCA using a linear regression between acquisition dates. Grain size data from AVIRIS (4 acquisitions) were used to infer snow surface albedo and interpolated linearly with time to derive daily albedo values. Modeled daily snowmelt rates for each 30-m pixel were scaled by the SCA and integrated over the snowmelt season to obtain estimates of maximum SWE accumulation. Snow surveys consisting of an average of 335 depth measurements and 53 density measurements during April, May and June, 1997 were interpolated using a regression tree / co-krig model, with independent variables of average incoming solar radiation, elevation, slope and maximum upwind slope. The basin was clustered into 7 elevation / average-solar-radiation zones for SWE accuracy assessment. Model simulations did a poor job at estimating the spatial distribution of SWE. Basin clusters where the solar radiative flux dominated the melt flux were simulated more accurately than those dominated by the turbulent fluxes or the longwave radiative flux.

Protoplanetary disc `isochrones' and the evolution of discs in the M˙-Md plane

NASA Astrophysics Data System (ADS)

Lodato, Giuseppe; Scardoni, Chiara E.; Manara, Carlo F.; Testi, Leonardo

2017-12-01

In this paper, we compare simple viscous diffusion models for the disc evolution with the results of recent surveys of the properties of young protoplanetary discs. We introduce the useful concept of 'disc isochrones' in the accretion rate-disc mass plane and explore a set of Monte Carlo realization of disc initial conditions. We find that such simple viscous models can provide a remarkable agreement with the available data in the Lupus star forming region, with the key requirement that the average viscous evolutionary time-scale of the discs is comparable to the cluster age. Our models produce naturally a correlation between mass accretion rate and disc mass that is shallower than linear, contrary to previous results and in agreement with observations. We also predict that a linear correlation, with a tighter scatter, should be found for more evolved disc populations. Finally, we find that such viscous models can reproduce the observations in the Lupus region only in the assumption that the efficiency of angular momentum transport is a growing function of radius, thus putting interesting constraints on the nature of the microscopic processes that lead to disc accretion.

Revisiting the Electronic Structure of FeS Monomers Using ab Initio Ligand Field Theory and the Angular Overlap Model.

PubMed

Chilkuri, Vijay Gopal; DeBeer, Serena; Neese, Frank

2017-09-05

Iron-sulfur (FeS) proteins are universally found in nature with actives sites ranging in complexity from simple monomers to multinuclear sites from two up to eight iron atoms. These sites include mononuclear (rubredoxins), dinuclear (ferredoxins and Rieske proteins), trinuclear (e.g., hydrogenases), and tetranuclear (various ferredoxins and high-potential iron-sulfur proteins). The electronic structure of the higher-nuclearity clusters is inherently extremely complex. Hence, it is reasonable to take a bottom-up approach in which clusters of increasing nuclearity are analyzed in terms of the properties of their lower nuclearity constituents. In the present study, the first step is taken by an in-depth analysis of mononuclear FeS systems. Two different FeS molecules with phenylthiolate and methylthiolate as ligands are studied in their oxidized and reduced forms using modern wave function-based ab initio methods. The ab initio electronic spectra and wave function are presented and analyzed in detail. The very intricate electronic structure-geometry relationship in these systems is analyzed using ab initio ligand field theory (AILFT) in conjunction with the angular overlap model (AOM) parametrization scheme. The simple AOM model is used to explain the effect of geometric variations on the electronic structure. Through a comparison of the ab initio computed UV-vis absorption spectra and the available experimental spectra, the low-energy part of the many-particle spectrum is carefully analyzed. We show ab initio calculated magnetic circular dichroism spectra and present a comparison with the experimental spectrum. Finally, AILFT parameters and the ab initio spectra are compared with those obtained experimentally to understand the effect of the increased covalency of the thiolate ligands on the electronic structure of FeS monomers.

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

Diffuse Optical Light in Galaxy Clusters. I. Abell 3888

NASA Astrophysics Data System (ADS)

Krick, J. E.; Bernstein, R. A.; Pimbblet, K. A.

2006-01-01

We are undertaking a program to measure the characteristics of the intracluster light (ICL; total flux, profile, color, and substructure) in a sample of 10 galaxy clusters with a range of cluster mass, morphology, and redshift. We present here the methods and results for the first cluster in that sample, A3888. We have identified an ICL component in A3888 in V and r that contains 13%+/-5% of the total cluster light and extends to 700 h-170 kpc (~0.3r200) from the center of the cluster. The ICL color in our smallest radial bin is V-r=0.3+/-0.1, similar to the central cluster elliptical galaxies. The ICL is redder than the galaxies at 400 h-170 kpc1) with a high-metallicity (1.0 Zsolar

Characterization of the reactive and dissociative behavior of transition metal oxide cluster ions in the gas phase.

PubMed

Maleknia, S; Brodbelt, J; Pope, K

1991-05-01

The reactive and dissociative behavior of molybdenum and tungsten oxide cluster ions has been studied in the gas phase using a triple quadrupole mass spectrometer. Cluster ions (MO3) n (-) were formed via a simple thermal desorption/electron capture negative ionization method, and their structures were characterized by collision-activated dissociation (CAD). Typically, the clusters fragment by losses of neutral (MO3) units. Reactions of the oxide cluster ions with ethylene oxide, cyclohexene oxide, ethylene sulfide cyclohexene sulfide, 2,3-butanedione, and 2,4-pentanedione were examined, and product ions were characterized by CAD. The clusters react with ethylene oxide by addition of ethylene oxide or net addition of oxygen, whereas the clusters react with ethylene sulfide via net addition of one or two sulfur atoms. Reactions of the clusters with the diones result in addition of one or two dione units, in some cases with dehydration.

Atomic scale simulations of vapor cooled carbon clusters

NASA Astrophysics Data System (ADS)

Bogana, M. P.; Colombo, L.

2007-03-01

By means of atomistic simulations we observed the formation of many topologically non-equivalent carbon clusters formed by the condensation of liquid droplets, including: (i) standard fullerenes and onion-like structures, (ii) clusters showing extremely complex surfaces with both positive and negative curvatures and (iii) complex endohedral structures. In this work we offer a thorough structural characterization of the above systems, as well as an attempt to correlate the resulting structure to the actual protocol of growth. The IR and Raman responses of some exotic linear carbon structures have been further investigated, finding good agreement with experimental evidence of carbinoid structures in cluster-assembled films. Towards the aim of fully understanding the process of cluster-to-cluster coalescence dynamics, we further simulated an aerosol of amorphous carbon clusters at controlled temperatures. Various annealing temperatures and times have been observed, identifying different pathways for cluster ripening, ranging from simple coalescence to extensive reconstruction.

Lithium cluster anions: photoelectron spectroscopy and ab initio calculations.

PubMed

Alexandrova, Anastassia N; Boldyrev, Alexander I; Li, Xiang; Sarkas, Harry W; Hendricks, Jay H; Arnold, Susan T; Bowen, Kit H

2011-01-28

Structural and energetic properties of small, deceptively simple anionic clusters of lithium, Li(n)(-), n = 3-7, were determined using a combination of anion photoelectron spectroscopy and ab initio calculations. The most stable isomers of each of these anions, the ones most likely to contribute to the photoelectron spectra, were found using the gradient embedded genetic algorithm program. Subsequently, state-of-the-art ab initio techniques, including time-dependent density functional theory, coupled cluster, and multireference configurational interactions methods, were employed to interpret the experimental spectra.

A fuzzy clustering algorithm to detect planar and quadric shapes

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Frigui, Hichem; Nasraoui, Olfa

1992-01-01

In this paper, we introduce a new fuzzy clustering algorithm to detect an unknown number of planar and quadric shapes in noisy data. The proposed algorithm is computationally and implementationally simple, and it overcomes many of the drawbacks of the existing algorithms that have been proposed for similar tasks. Since the clustering is performed in the original image space, and since no features need to be computed, this approach is particularly suited for sparse data. The algorithm may also be used in pattern recognition applications.

Wrapping up BLAST and other applications for use on Unix clusters.

PubMed

Hokamp, Karsten; Shields, Denis C; Wolfe, Kenneth H; Caffrey, Daniel R

2003-02-12

We have developed two programs that speed up common bioinformatic applications by spreading them across a UNIX cluster.(1) BLAST.pm, a new module for the 'MOLLUSC' package. (2) WRAPID, a simple tool for parallelizing large numbers of small instances of programs such as BLAST, FASTA and CLUSTALW. The packages were developed in Perl on a 20-node Linux cluster and are provided together with a configuration script and documentation. They can be freely downloaded from http://wolfe.gen.tcd.ie/wrapper.

Time dependent density functional calculation of plasmon response in clusters

NASA Astrophysics Data System (ADS)

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

2003-02-01

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

Collective behavior in two-dimensional biological systems: Receptor clustering and beta-sheet aggregation

NASA Astrophysics Data System (ADS)

Guo, Chinlin

We studied two particular biomedical systems which exhibit collective molecular behavior. One is clustering of tumor necrosis factor receptor I (TNFR1), and another is β-sheet folding and aggregation. Receptor clustering has been shown to be a crucial step in many signaling events but its biological meaning has not been adequately addressed. Here, via a simple lattice model, we show how cells use this clustering machinery to enhance sensitivity as well as robustness. On the other hand, intracellular deposition of aggregated protein rich in β-sheet is a prominent cytopathological feature of most neurodegenerative diseases. How this aggregation occurs and how it responds to therapy is not completely understood. Here, we started from a reconstruction of the H-bond potential and carry out a full investigation of β-sheet thermodynamics as well as kinetics. We show that β-sheet aggregation is most likely due to molecular stacking and found that the minimal length of an aggregate mutant polymer corresponds well with the number observed in adult Huntington's disease. We have also shown that molecular agents such as dendrimers might fail at high-dose therapy; instead, a potential therapy strategy is to block β-turn formation. Our predictions can be used for future experimental tests and clinical trials.

Resolved magnetic dynamo action in the simulated intracluster medium

NASA Astrophysics Data System (ADS)

Vazza, F.; Brunetti, G.; Brüggen, M.; Bonafede, A.

2018-02-01

Faraday rotation and synchrotron emission from extragalactic radio sources give evidence for the presence of magnetic fields extending over ˜ Mpc scales. However, the origin of these fields remains elusive. With new high-resolution grid simulations, we studied the growth of magnetic fields in a massive galaxy cluster that in several aspects is similar to the Coma cluster. We investigated models in which magnetic fields originate from primordial seed fields with comoving strengths of 0.1 nG at redshift z = 30. The simulations show evidence of significant magnetic field amplification. At the best spatial resolution (3.95 kpc), we are able to resolve the scale where magnetic tension balances the bending of magnetic lines by turbulence. This allows us to observe the final growth stage of the small-scale dynamo. To our knowledge, this is the first time that this is seen in cosmological simulations of the intracluster medium. Our mock observations of Faraday rotation provide a good match to observations of the Coma cluster. However, the distribution of magnetic fields shows strong departures from a simple Maxwellian distribution, suggesting that the three-dimensional structure of magnetic fields in real clusters may be significantly different than what is usually assumed when inferring magnetic field values from rotation measure observations.

How supernovae launch galactic winds?

NASA Astrophysics Data System (ADS)

Fielding, Drummond; Quataert, Eliot; Martizzi, Davide; Faucher-Giguère, Claude-André

2017-09-01

We use idealized three-dimensional hydrodynamic simulations of global galactic discs to study the launching of galactic winds by supernovae (SNe). The simulations resolve the cooling radii of the majority of supernova remnants (SNRs) and thus self-consistently capture how SNe drive galactic winds. We find that SNe launch highly supersonic winds with properties that agree reasonably well with expectations from analytic models. The energy loading (η _E= \\dot{E}_wind/ \\dot{E}_SN) of the winds in our simulations are well converged with spatial resolution while the wind mass loading (η _M= \\dot{M}_wind/\\dot{M}_\\star) decreases with resolution at the resolutions we achieve. We present a simple analytic model based on the concept that SNRs with cooling radii greater than the local scaleheight break out of the disc and power the wind. This model successfully explains the dependence (or lack thereof) of ηE (and by extension ηM) on the gas surface density, star formation efficiency, disc radius and the clustering of SNe. The winds our simulations are weaker than expected in reality, likely due to the fact that we seed SNe preferentially at density peaks. Clustering SNe in time and space substantially increases the wind power.

Spatial memory in foraging games.

PubMed

Kerster, Bryan E; Rhodes, Theo; Kello, Christopher T

2016-03-01

Foraging and foraging-like processes are found in spatial navigation, memory, visual search, and many other search functions in human cognition and behavior. Foraging is commonly theorized using either random or correlated movements based on Lévy walks, or a series of decisions to remain or leave proximal areas known as "patches". Neither class of model makes use of spatial memory, but search performance may be enhanced when information about searched and unsearched locations is encoded. A video game was developed to test the role of human spatial memory in a canonical foraging task. Analyses of search trajectories from over 2000 human players yielded evidence that foraging movements were inherently clustered, and that clustering was facilitated by spatial memory cues and influenced by memory for spatial locations of targets found. A simple foraging model is presented in which spatial memory is used to integrate aspects of Lévy-based and patch-based foraging theories to perform a kind of area-restricted search, and thereby enhance performance as search unfolds. Using only two free parameters, the model accounts for a variety of findings that individually support competing theories, but together they argue for the integration of spatial memory into theories of foraging. Copyright © 2015 Elsevier B.V. All rights reserved.

Search for ternary fission of chromium-48

NASA Astrophysics Data System (ADS)

Dummer, Andrew K.

1999-07-01

Both alpha cluster model calculations and macroscopic energy calculations that allow for a double-neck shape of the compound nucleus suggest the possibility of a novel three 16O, chain-like configuration in 48 Cr. Such a configuration might lead to an enhanced cross section for three-16O breakup. To explore this possibility, the three-body exit channels for the 36Ar + 12C reaction at a beam energy of 210 MeV have been studied. The cross section for 16O + 16O + 16O breakup has been deduced and has been found to be in excess of what would be expected to result from a sequential binary fission process. However, the observation of a similarly enhanced 12C + 16O + 20Ne breakup cross section suggests that the observed 16O + 16O + 16O yields might still be associated with a statistical fission process. The results are discussed in the context of the fission of light nuclear systems and a simple cluster model calculation. This latter, ``Harvey model'' calculation suggests a possible inhibition of the formation of a three- 16O chain configuration from the 36Ar + 12C entrance channel. A further measurement using the 20Ne + 28Si-entrance channel is suggested.

Effect of nanoconfinement on the sputter yield in ultrathin polymeric films: Experiments and model

NASA Astrophysics Data System (ADS)

Cristaudo, Vanina; Poleunis, Claude; Delcorte, Arnaud

2018-06-01

This fundamental contribution on secondary ion mass spectrometry (SIMS) polymer depth-profiling by large argon clusters investigates the dependence of the sputter yield volume (Y) on the thickness (d) of ultrathin films as a function of the substrate nature, i.e. hard vs soft. For this purpose, thin films of polystyrene (PS) oligomers (∼4,000 amu) are spin-coated, respectively, onto silicon and poly (methyl methacrylate) supports and, then, bombarded by 10 keV Ar3000+ ions. The investigated thickness ranges from 15 to 230 nm. Additionally, the influence of the polymer molecular weight on Y(d) for PS thin films on Si is explored. The sputtering efficiency is found to be strongly dependent on the overlayer thickness, only in the case of the silicon substrate. A simple phenomenological model is proposed for the description of the thickness influence on the sputtering yield. Molecular dynamics (MD) simulations conducted on amorphous films of polyethylene-like oligomers of increasing thickness (from 2 to 20 nm), under comparable cluster bombardment conditions, predict a significant increase of the sputtering yield for ultrathin layers on hard substrates, induced by energy confinement in the polymer, and support our phenomenological model.

Spread of information and infection on finite random networks

NASA Astrophysics Data System (ADS)

Isham, Valerie; Kaczmarska, Joanna; Nekovee, Maziar

2011-04-01

The modeling of epidemic-like processes on random networks has received considerable attention in recent years. While these processes are inherently stochastic, most previous work has been focused on deterministic models that ignore important fluctuations that may persist even in the infinite network size limit. In a previous paper, for a class of epidemic and rumor processes, we derived approximate models for the full probability distribution of the final size of the epidemic, as opposed to only mean values. In this paper we examine via direct simulations the adequacy of the approximate model to describe stochastic epidemics and rumors on several random network topologies: homogeneous networks, Erdös-Rényi (ER) random graphs, Barabasi-Albert scale-free networks, and random geometric graphs. We find that the approximate model is reasonably accurate in predicting the probability of spread. However, the position of the threshold and the conditional mean of the final size for processes near the threshold are not well described by the approximate model even in the case of homogeneous networks. We attribute this failure to the presence of other structural properties beyond degree-degree correlations, and in particular clustering, which are present in any finite network but are not incorporated in the approximate model. In order to test this “hypothesis” we perform additional simulations on a set of ER random graphs where degree-degree correlations and clustering are separately and independently introduced using recently proposed algorithms from the literature. Our results show that even strong degree-degree correlations have only weak effects on the position of the threshold and the conditional mean of the final size. On the other hand, the introduction of clustering greatly affects both the position of the threshold and the conditional mean. Similar analysis for the Barabasi-Albert scale-free network confirms the significance of clustering on the dynamics of rumor spread. For this network, though, with its highly skewed degree distribution, the addition of positive correlation had a much stronger effect on the final size distribution than was found for the simple random graph.

Quantify spatial relations to discover handwritten graphical symbols

NASA Astrophysics Data System (ADS)

Li, Jinpeng; Mouchère, Harold; Viard-Gaudin, Christian

2012-01-01

To model a handwritten graphical language, spatial relations describe how the strokes are positioned in the 2-dimensional space. Most of existing handwriting recognition systems make use of some predefined spatial relations. However, considering a complex graphical language, it is hard to express manually all the spatial relations. Another possibility would be to use a clustering technique to discover the spatial relations. In this paper, we discuss how to create a relational graph between strokes (nodes) labeled with graphemes in a graphical language. Then we vectorize spatial relations (edges) for clustering and quantization. As the targeted application, we extract the repetitive sub-graphs (graphical symbols) composed of graphemes and learned spatial relations. On two handwriting databases, a simple mathematical expression database and a complex flowchart database, the unsupervised spatial relations outperform the predefined spatial relations. In addition, we visualize the frequent patterns on two text-lines containing Chinese characters.

Radiation-induced gene expression in the nematode Caenorhabditis elegans

NASA Technical Reports Server (NTRS)

Nelson, Gregory A.; Jones, Tamako A.; Chesnut, Aaron; Smith, Anna L.

2002-01-01

We used the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation in a simple animal model emphasizing the unique effects of charged particle radiation. Here we demonstrate by RT-PCR differential display and whole genome microarray hybridization experiments that gamma rays, accelerated protons and iron ions at the same physical dose lead to unique transcription profiles. 599 of 17871 genes analyzed (3.4%) showed differential expression 3 hrs after exposure to 3 Gy of radiation. 193 were up-regulated, 406 were down-regulated and 90% were affected only by a single species of radiation. A novel statistical clustering technique identified the regulatory relationships between the radiation-modulated genes and showed that genes affected by each radiation species were associated with unique regulatory clusters. This suggests that independent homeostatic mechanisms are activated in response to radiation exposure as a function of track structure or ionization density.

Nanostructural characterization of amorphous diamondlike carbon films

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

SIEGAL,MICHAEL P.; TALLANT,DAVID R.; MARTINEZ-MIRANDA,L.J.

2000-01-27

Nanostructural characterization of amorphous diamondlike carbon (a-C) films grown on silicon using pulsed-laser deposition (PLD) is correlated to both growth energetic and film thickness. Raman spectroscopy and x-ray reflectivity probe both the topological nature of 3- and 4-fold coordinated carbon atom bonding and the topographical clustering of their distributions within a given film. In general, increasing the energetic of PLD growth results in films becoming more ``diamondlike'', i.e. increasing mass density and decreasing optical absorbance. However, these same properties decrease appreciably with thickness. The topology of carbon atom bonding is different for material near the substrate interface compared to materialmore » within the bulk portion of an a-C film. A simple model balancing the energy of residual stress and the free energies of resulting carbon topologies is proposed to provide an explanation of the evolution of topographical bonding clusters in a growing a-C film.« less

An Intercomparison Between Radar Reflectivity and the IR Cloud Classification Technique for the TOGA-COARE Area

NASA Technical Reports Server (NTRS)

Carvalho, L. M. V.; Rickenbach, T.

1999-01-01

Satellite infrared (IR) and visible (VIS) images from the Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) experiment are investigated through the use of Clustering Analysis. The clusters are obtained from the values of IR and VIS counts and the local variance for both channels. The clustering procedure is based on the standardized histogram of each variable obtained from 179 pairs of images. A new approach to classify high clouds using only IR and the clustering technique is proposed. This method allows the separation of the enhanced convection in two main classes: convective tops, more closely related to the most active core of the storm, and convective systems, which produce regions of merged, thick anvil clouds. The resulting classification of different portions of cloudiness is compared to the radar reflectivity field for intensive events. Convective Systems and Convective Tops are followed during their life cycle using the IR clustering method. The areal coverage of precipitation and features related to convective and stratiform rain is obtained from the radar for each stage of the evolving Mesoscale Convective Systems (MCS). In order to compare the IR clustering method with a simple threshold technique, two IR thresholds (Tir) were used to identify different portions of cloudiness, Tir=240K which roughly defines the extent of all cloudiness associated with the MCS, and Tir=220K which indicates the presence of deep convection. It is shown that the IR clustering technique can be used as a simple alternative to identify the actual portion of convective and stratiform rainfall.

The Evolution of Globular Cluster Systems In Early-Type Galaxies

NASA Astrophysics Data System (ADS)

Grillmair, Carl

1999-07-01

We will measure structural parameters {core radii and concentrations} of globular clusters in three early-type galaxies using deep, four-point dithered observations. We have chosen globular cluster systems which have young, medium-age and old cluster populations, as indicated by cluster colors and luminosities. Our primary goal is to test the hypothesis that globular cluster luminosity functions evolve towards a ``universal'' form. Previous observations have shown that young cluster systems have exponential luminosity functions rather than the characteristic log-normal luminosity function of old cluster systems. We will test to see whether such young system exhibits a wider range of structural parameters than an old systems, and whether and at what rate plausible disruption mechanisms will cause the luminosity function to evolve towards a log-normal form. A simple observational comparison of structural parameters between different age cluster populations and between diff er ent sub-populations within the same galaxy will also provide clues concerning both the formation and destruction mechanisms of star clusters, the distinction between open and globular clusters, and the advisability of using globular cluster luminosity functions as distance indicators.

Herding, minority game, market clearing and efficient markets in a simple spin model framework

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav; Vosvrda, Miloslav

2018-01-01

We present a novel approach towards the financial Ising model. Most studies utilize the model to find settings which generate returns closely mimicking the financial stylized facts such as fat tails, volatility clustering and persistence, and others. We tackle the model utility from the other side and look for the combination of parameters which yields return dynamics of the efficient market in the view of the efficient market hypothesis. Working with the Ising model, we are able to present nicely interpretable results as the model is based on only two parameters. Apart from showing the results of our simulation study, we offer a new interpretation of the Ising model parameters via inverse temperature and entropy. We show that in fact market frictions (to a certain level) and herding behavior of the market participants do not go against market efficiency but what is more, they are needed for the markets to be efficient.

SLURM: Simple Linux Utility for Resource Management

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

Jette, M; Dunlap, C; Garlick, J

2002-04-24

Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters of thousands of nodes. Components include machine status, partition management, job management, and scheduling modules. The design also includes a scalable, general-purpose communication infrastructure. Development will take place in four phases: Phase I results in a solid infrastructure; Phase II produces a functional but limited interactive job initiation capability without use of the interconnect/switch; Phase III provides switch support and documentation; Phase IV provides job status, fault-tolerance, and job queuing and control through Livermore's Distributed Productionmore » Control System (DPCS), a meta-batch and resource management system.« less

Benchmark fragment-based 1H, 13C, 15N and 17O chemical shift predictions in molecular crystals†

PubMed Central

Hartman, Joshua D.; Kudla, Ryan A.; Day, Graeme M.; Mueller, Leonard J.; Beran, Gregory J. O.

2016-01-01

The performance of fragment-based ab initio 1H, 13C, 15N and 17O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. 1H, 13C, 15N, and 17O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same 1H, 13C, 15N, and 17O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tertbutyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2. PMID:27431490

Benchmark fragment-based (1)H, (13)C, (15)N and (17)O chemical shift predictions in molecular crystals.

PubMed

Hartman, Joshua D; Kudla, Ryan A; Day, Graeme M; Mueller, Leonard J; Beran, Gregory J O

2016-08-21

The performance of fragment-based ab initio(1)H, (13)C, (15)N and (17)O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. (1)H, (13)C, (15)N, and (17)O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same (1)H, (13)C, (15)N, and (17)O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tert-butyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2.

Simulation studies for surfaces and materials strength

NASA Technical Reports Server (NTRS)

Halicioglu, T.

1986-01-01

During this reporting period three investigations were carried out. The first area of research concerned the analysis of the structure-energy relationship in small clusters. This study is very closely related to the improvement of the potential energy functions which are suitable and simple enough to be used in atomistic simulation studies. Parameters obtained from ab initio calculations for dimers and trimers of Al were used to estimate energetics and global minimum energy structures of clusters continuing up to 15 Al atoms. The second research topic addressed modeling of the collision process for atoms impinging on surfaces. In this simulation study qualitative aspects of the O atom collision with a graphite surface were analyzed. Four different O/graphite systems were considered and the aftermath of the impact was analyzed. The final area of investigation was related to the simulation of thin amorphous Si films on crystalline Si substrates. Parameters obtained in an earlier study were used to model an exposed amorphous Si surface and an a-Si/c-Si interface. Structural details for various film thicknesses were investigated at an atomistic level.

A real-frequency solver for the Anderson impurity model based on bath optimization and cluster perturbation theory

NASA Astrophysics Data System (ADS)

Zingl, Manuel; Nuss, Martin; Bauernfeind, Daniel; Aichhorn, Markus

2018-05-01

Recently solvers for the Anderson impurity model (AIM) working directly on the real-frequency axis have gained much interest. A simple and yet frequently used impurity solver is exact diagonalization (ED), which is based on a discretization of the AIM bath degrees of freedom. Usually, the bath parameters cannot be obtained directly on the real-frequency axis, but have to be determined by a fit procedure on the Matsubara axis. In this work we present an approach where the bath degrees of freedom are first discretized directly on the real-frequency axis using a large number of bath sites (≈ 50). Then, the bath is optimized by unitary transformations such that it separates into two parts that are weakly coupled. One part contains the impurity site and its interacting Green's functions can be determined with ED. The other (larger) part is a non-interacting system containing all the remaining bath sites. Finally, the Green's function of the full AIM is calculated via coupling these two parts with cluster perturbation theory.

Structure of the X-ray source in the Virgo cluster of galaxies

NASA Technical Reports Server (NTRS)

Gorenstein, P.; Fabricant, D.; Topka, K.; Tucker, W.; Harnden, F. R., Jr.

1977-01-01

High-angular-resolution observations in the 0.15-1.5-keV band with an imaging X-ray telescope shows the extended X-ray source in the Virgo cluster of galaxies to be a diffuse halo of about 15 arcmin core radius surrounding M87. The angular structure of the surface brightness is marginally consistent with either of two simple models: (1) an isothermal (or adiabatic or hydrostatic) sphere plus a point source at M87 accounting for 12% of the total 0.5-1.5-keV intensity or (2) a power-law function without a discrete point source. No evidence for a point source is seen in the 0.15-0.28-keV band, which is consistent with self-absorption by about 10 to the 21st power per sq cm of matter having a cosmic abundance. The power-law models are motivated by the idea that radiation losses regulate the accretion of matter onto M87 and can account for the observed difference in the size of the X-ray source as seen in the present measurements and at higher energies.

Searching for 300, 000 Degree Gas in the Core of the Phoenix Cluster with HST-COS

NASA Astrophysics Data System (ADS)

McDonald, Michael

2013-10-01

The high central density of the intracluster medium in some galaxy clusters suggests that the hot 10,000,000K gas should cool completely in less than a Hubble time. In these clusters, simple cooling models predict 100-1000 solar masses per year of cooling gas should fuel massive starbursts in the central galaxy. The fact that the typical central cluster galaxy is a massive, "red and dead" elliptical galaxy, with little evidence for a cool ISM, has led to the realization of the "cooling flow problem". It is now thought that mechanical feedback from the central supermassive blackhole, in the form of radio-blown bubbles, is offsetting cooling, leading to an exceptionally precise {residuals of less than 10 percent} balance between cooling and feedback in nearly every galaxy cluster in the local Universe. In the recently-discovered Phoenix cluster, where z=0.596, we observe an 800 solar mass per year starburst within the central galaxy which accounts for about 30 percent of the classical cooling prediction for this system. We speculate that this may represent the first "true" cooling flow, with the factor of 3 difference between cooling and star formation being attributed to star formation efficiency, rather than a problem with cooling. In order to test these predictions, we propose far-UV spectroscopic observations of the OVI 1032A emission line, which probes 10^5.5K gas, in the central galaxy of the Phoenix cluster. If detected at the expected levels, this would provide compelling evidence that the starburst is, indeed, fueled by runaway cooling of the intracluster medium, confirming the presence of the first, bonafide cooling flow.

Electron impact ionization cross sections of beryllium-tungsten clusters*

NASA Astrophysics Data System (ADS)

Sukuba, Ivan; Kaiser, Alexander; Huber, Stefan E.; Urban, Jan; Probst, Michael

2016-01-01

We report calculated electron impact ionization cross sections (EICSs) of beryllium-tungsten clusters, BenW with n = 1,...,12, from the ionization threshold to 10 keV using the Deutsch-Märk (DM) and the binary-encounter-Bethe (BEB) formalisms. The positions of the maxima of DM and BEB cross sections are mostly close to each other. The DM cross sections are more sensitive with respect to the cluster size. For the clusters smaller than Be4W they yield smaller cross sections than BEB and vice versa larger cross sections than BEB for clusters larger than Be6W. The maximum cross section values for the singlet-spin groundstate clusters range from 7.0 × 10-16 cm2 at 28 eV (BeW) to 54.2 × 10-16 cm2 at 43 eV (Be12W) for the DM cross sections and from 13.5 × 10-16 cm2 at 43 eV (BeW) to 38.9 × 10-16 cm2 at 43 eV (Be12W) for the BEB cross sections. Differences of the EICSs in different isomers and between singlet and triplet states are also explored. Both the DM and BEB cross sections could be fitted perfectly to a simple expression used in modeling and simulation codes in the framework of nuclear fusion research. Contribution to the Topical Issue "Atomic Cluster Collisions (7th International Symposium)", edited by Gerardo Delgado Barrio, Andrey Solov'Yov, Pablo Villarreal, Rita Prosmiti.Supplementary material in the form of one pdf file available from the Journal web page at http://dx.doi.org/10.1140/epjd/e2015-60583-7

TURBULENT COSMIC-RAY REACCELERATION AT RADIO RELICS AND HALOS IN CLUSTERS OF GALAXIES

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

Fujita, Yutaka; Takizawa, Motokazu; Yamazaki, Ryo

Radio relics are synchrotron emission found on the periphery of galaxy clusters. From the position and the morphology, it is often believed that the relics are generated by cosmic-ray (CR) electrons accelerated at shocks through a diffusive shock acceleration (DSA) mechanism. However, some radio relics have harder spectra than the prediction of the standard DSA model. One example is observed in the cluster 1RXS J0603.3+4214, which is often called the “Toothbrush Cluster.” Interestingly, the position of the relic is shifted from that of a possible shock. In this study, we show that these discrepancies in the spectrum and the positionmore » can be solved if turbulent (re)acceleration is very effective behind the shock. This means that for some relics turbulent reacceleration may be the main mechanism to produce high-energy electrons, contrary to the common belief that it is the DSA. Moreover, we show that for efficient reacceleration, the effective mean free path of the electrons has to be much smaller than their Coulomb mean free path. We also study the merging cluster 1E 0657−56, or the “Bullet Cluster,” in which a radio relic has not been found at the position of the prominent shock ahead of the bullet. We indicate that a possible relic at the shock is obscured by the observed large radio halo that is generated by strong turbulence behind the shock. We propose a simple explanation of the morphological differences of radio emission among the Toothbrush, the Bullet, and the Sausage (CIZA J2242.8+5301) Clusters.« less

NEW CONSTRAINTS ON A COMPLEX RELATION BETWEEN GLOBULAR CLUSTER COLORS AND ENVIRONMENT

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

Powalka, Mathieu; Lançon, Ariane; Puzia, Thomas H.

We present an analysis of high-quality photometry for globular clusters (GCs) in the Virgo cluster core region, based on data from the Next Generation Virgo Cluster Survey (NGVS) pilot field, and in the Milky Way (MW), based on Very Large Telescope/X-Shooter spectrophotometry. We find significant discrepancies in color–color diagrams between sub-samples from different environments, confirming that the environment has a strong influence on the integrated colors of GCs. GC color distributions along a single color are not sufficient to capture the differences we observe in color–color space. While the average photometric colors become bluer with increasing radial distance to themore » cD galaxy M87, we also find a relation between the environment and the slope and intercept of the color–color relations. A denser environment seems to produce a larger dynamic range in certain color indices. We argue that these results are not due solely to differential extinction, Initial Mass Function variations, calibration uncertainties, or overall age/metallicity variations. We therefore suggest that the relation between the environment and GC colors is, at least in part, due to chemical abundance variations, which affect stellar spectra and stellar evolution tracks. Our results demonstrate that stellar population diagnostics derived from model predictions which are calibrated on one particular sample of GCs may not be appropriate for all extragalactic GCs. These results advocate a more complex model of the assembly history of GC systems in massive galaxies that goes beyond the simple bimodality found in previous decades.« less

Rotationally invariant clustering of diffusion MRI data using spherical harmonics

NASA Astrophysics Data System (ADS)

Liptrot, Matthew; Lauze, François

2016-03-01

We present a simple approach to the voxelwise classification of brain tissue acquired with diffusion weighted MRI (DWI). The approach leverages the power of spherical harmonics to summarise the diffusion information, sampled at many points over a sphere, using only a handful of coefficients. We use simple features that are invariant to the rotation of the highly orientational diffusion data. This provides a way to directly classify voxels whose diffusion characteristics are similar yet whose primary diffusion orientations differ. Subsequent application of machine-learning to the spherical harmonic coefficients therefore may permit classification of DWI voxels according to their inferred underlying fibre properties, whilst ignoring the specifics of orientation. After smoothing apparent diffusion coefficients volumes, we apply a spherical harmonic transform, which models the multi-directional diffusion data as a collection of spherical basis functions. We use the derived coefficients as voxelwise feature vectors for classification. Using a simple Gaussian mixture model, we examined the classification performance for a range of sub-classes (3-20). The results were compared against existing alternatives for tissue classification e.g. fractional anisotropy (FA) or the standard model used by Camino.1 The approach was implemented on both two publicly-available datasets: an ex-vivo pig brain and in-vivo human brain from the Human Connectome Project (HCP). We have demonstrated how a robust classification of DWI data can be performed without the need for a model reconstruction step. This avoids the potential confounds and uncertainty that such models may impose, and has the benefit of being computable directly from the DWI volumes. As such, the method could prove useful in subsequent pre-processing stages, such as model fitting, where it could inform about individual voxel complexities and improve model parameter choice.

Large-area measurements of CIB power spectra with Planck HFI maps

NASA Astrophysics Data System (ADS)

Mak, D. S. Y.; Challinor, A.; Efstathiou, G.; Lagache, G.

We present new measurements of the power spectra of the cosmic infrared background (CIB) anisotropies using the Planck 2015 full-mission HFI data at 353, 545, and 857 GHz over 20 000 square degrees. Unlike previous Planck measurements of the CIB power spectra, we do not rely on external HI data to remove Galactic dust emission from the Planck maps. Instead, we model the Galactic emission at the level of the power spectra, using templates constructed directly from the Planck data by exploiting the statistical isotropy of all extragalactic emission components. This allows us to work at the full resolution of Planck over large sky areas. We construct a likelihood based on the measured spectra (for multipoles 50 <= l <= 2500) using analytic covariance matrices that account for masking and the realistic instrumental noise properties. The results of an MCMC exploration of this likelihood are presented, based on simple parameterised models of the CIB power that arises from clustering of infrared galaxies. We explore simultaneously the parameters describing the clustered power, the Poisson power levels, and the amplitudes of the Galactic power spectrum templates across the six frequency (cross-)spectra. The best-fit model provides a good fit to all spectra. As an example, Fig. 1 compares the measured auto spectra at 353, 545, and 857 GHz over 40% of the sky to the power in the best-fit model. We find that the power in the CIB anisotropies from galaxy clustering is roughly equal to the Poisson power at multipoles l =2000 (the clustered power dominates on larger scales), and that our dust-cleaned CIB spectra are in good agreement with previous Planck and Herschel measurements. A key feature of our analysis is that it allows one to make many internal consistency tests. We show that our results are stable to data selection and choice of survey area, demonstrating both our ability to remove Galactic dust power to high accuracy and the statistical isotropy of the CIB signal.

The most massive galaxies in clusters are already fully grown at z ˜ 0.5

NASA Astrophysics Data System (ADS)

Oldham, L. J.; Houghton, R. C. W.; Davies, Roger L.

2017-02-01

By constructing scaling relations for galaxies in the massive cluster MACSJ0717.5 at z = 0.545 and comparing with those of Coma, we model the luminosity evolution of the stellar populations and the structural evolution of the galaxies. We calculate magnitudes, surface brightnesses and effective radii using Hubble Space Telescope (HST)/ACS images and velocity dispersions using Gemini/GMOS spectra, and present a catalogue of our measurements for 17 galaxies. We also generate photometric catalogues for ˜3000 galaxies from the HST imaging. With these, we construct the colour-magnitude relation, the Fundamental Plane, the mass-to-light versus mass relation, the mass-size relation and the mass-velocity dispersion relation for both clusters. We present a new, coherent way of modelling these scaling relations simultaneously using a simple physical model in order to infer the evolution in luminosity, size and velocity dispersion as a function of redshift, and show that the data can be fully accounted for with this model. We find that (a) the evolution in size and velocity dispersion undergone by these galaxies between z ˜ 0.5 and z ˜ 0 is mild, with Re(z) ˜ (1 + z)-0.40 ± 0.32 and σ(z) ˜ (1 + z)0.09 ± 0.27, and (b) the stellar populations are old, ˜10 Gyr, with a ˜3 Gyr dispersion in age, and are consistent with evolving purely passively since z ˜ 0.5 with Δ log M/L_B = -0.55_{-0.07}^{+0.15} z. The implication is that these galaxies formed their stars early and subsequently grew dissipationlessly so as to have their mass already in place by z ˜ 0.5, and suggests a dominant role for dry mergers, which may have accelerated the growth in these high-density cluster environments.

Collisional model for granular impact dynamics.

PubMed

Clark, Abram H; Petersen, Alec J; Behringer, Robert P

2014-01-01

When an intruder strikes a granular material from above, the grains exert a stopping force which decelerates and stops the intruder. Many previous studies have used a macroscopic force law, including a drag force which is quadratic in velocity, to characterize the decelerating force on the intruder. However, the microscopic origins of the force-law terms are still a subject of debate. Here, drawing from previous experiments with photoelastic particles, we present a model which describes the velocity-squared force in terms of repeated collisions with clusters of grains. From our high speed photoelastic data, we infer that "clusters" correspond to segments of the strong force network that are excited by the advancing intruder. The model predicts a scaling relation for the velocity-squared drag force that accounts for the intruder shape. Additionally, we show that the collisional model predicts an instability to rotations, which depends on the intruder shape. To test this model, we perform a comprehensive experimental study of the dynamics of two-dimensional granular impacts on beds of photoelastic disks, with different profiles for the leading edge of the intruder. We particularly focus on a simple and useful case for testing shape effects by using triangular-nosed intruders. We show that the collisional model effectively captures the dynamics of intruder deceleration and rotation; i.e., these two dynamical effects can be described as two different manifestations of the same grain-scale physical processes.

The Monitor project: searching for occultations in young open clusters

NASA Astrophysics Data System (ADS)

Aigrain, S.; Hodgkin, S.; Irwin, J.; Hebb, L.; Irwin, M.; Favata, F.; Moraux, E.; Pont, F.

2007-02-01

The Monitor project is a photometric monitoring survey of nine young (1-200Myr) clusters in the solar neighbourhood to search for eclipses by very low mass stars and brown dwarfs and for planetary transits in the light curves of cluster members. It began in the autumn of 2004 and uses several 2- to 4-m telescopes worldwide. We aim to calibrate the relation between age, mass, radius and where possible luminosity, from the K dwarf to the planet regime, in an age range where constraints on evolutionary models are currently very scarce. Any detection of an exoplanet in one of our youngest targets (<~10Myr) would also provide important constraints on planet formation and migration time-scales and their relation to protoplanetary disc lifetimes. Finally, we will use the light curves of cluster members to study rotation and flaring in low-mass pre-main-sequence stars. The present paper details the motivation, science goals and observing strategy of the survey. We present a method to estimate the sensitivity and number of detections expected in each cluster, using a simple semi-analytic approach which takes into account the characteristics of the cluster and photometric observations, using (tunable) best-guess assumptions for the incidence and parameter distribution of putative companions, and we incorporate the limits imposed by radial velocity follow-up from medium and large telescopes. We use these calculations to show that the survey as a whole can be expected to detect over 100 young low and very low mass eclipsing binaries, and ~3 transiting planets with radial velocity signatures detectable with currently available facilities.

Universal dynamical properties preclude standard clustering in a large class of biochemical data.

PubMed

Gomez, Florian; Stoop, Ralph L; Stoop, Ruedi

2014-09-01

Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

MYStIX: Dynamical evolution of young clusters

NASA Astrophysics Data System (ADS)

Kuhn, Michael A.

2014-08-01

The spatial structure of young stellar clusters in Galactic star-forming regions provides insight into these clusters’ dynamical evolution---a topic with implications for open questions in star-formation and cluster survival. The Massive Young Star-Forming Complex Study in Infrared and X-ray (MYStIX) provides a sample of >30,000 young stars in star-forming regions (d<3.6 kpc) that contain at least one O-type star. We use the finite mixture model analysis to identify subclusters of stars and determine their properties: including subcluster radii, intrinsic numbers of stars, central density, ellipticity, obscuration, and age. In 17 MYStIX regions we find 142 subclusters, with a diverse radii and densities and age spreads of up to ~1 Myr in a region. There is a strong negative correlation between subcluster radius and density, which indicates that embedded subclusters expand but also gain stars as they age. Subcluster expansion is also shown by a positive radius--age correlation, which indicates that subclusters are expanding at <1 km/s. The subcluster ellipticity distribution and number--density relation show signs of a hierarchical merger scenario, whereby young stellar clusters are built up through mergers of smaller clumps, causing evolution from a clumpy spatial distribution of stars (seen in some regions) to a simpler distribution of stars (seen in other regions). Many of the simple young stellar clusters show signs of dynamically relaxation, even though they are not old enough for this to have occurred through two-body interactions. However, this apparent contradiction might be explained if small subcluster, which have shorter dynamical relaxation times, can produce dynamically relaxed clusters through hierarchical mergers.

Galaxy Clusters: A Novel Look at Diffuse Baryons Withstanding Dark Matter Gravity

NASA Astrophysics Data System (ADS)

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

2009-06-01

In galaxy clusters, the equilibria of the intracluster plasma (ICP) and of the gravitationally dominant dark matter (DM) are governed by the hydrostatic equation and by the Jeans equation, respectively; in either case gravity is withstood by the corresponding, entropy-modulated pressure. Jeans, with the DM "entropy" set to K vprop r α and α ≈ 1.25-1.3 applying from groups to rich clusters, yields our radial α-profiles these, compared to the empirical Navarro-Frenk-White distribution, are flatter at the center and steeper in the outskirts as required by recent gravitational lensing data. In the ICP, on the other hand, the entropy run k(r) is mainly shaped by shocks, as steadily set by supersonic accretion of gas at the cluster boundary, and intermittently driven from the center by merging events or by active galactic nuclei (AGNs); the resulting equilibrium is described by the exact yet simple formalism constituting our ICP Supermodel. With two parameters, this accurately represents the runs of density n(r) and temperature T(r) as required by up-to-date X-ray data on surface brightness and spectroscopy for both cool core (CC) and non-cool core (NCC) clusters; the former are marked by a middle temperature peak, whose location is predicted from rich clusters to groups. The Supermodel inversely links the inner runs of n(r) and T(r), and highlights their central scaling with entropy nc vprop k -1 c and Tc vprop k 0.35 c , to yield radiative cooling times tc ≈ 0.3(kc /15 keV cm2)1.2 Gyr. We discuss the stability of the central values so focused: against radiative erosion of kc in the cool dense conditions of CC clusters, that triggers recurrent AGN activities resetting it back; or against energy inputs from AGNs and mergers whose effects are saturated by the hot central conditions of NCC clusters. From the Supermodel, we also derive as limiting cases the classic polytropic β-models, and the "mirror" model with T(r) vprop σ2(r) suitable for NCC and CC clusters, respectively; these limiting cases highlight how the ICP temperature T(r) strives to mirror the DM velocity dispersion σ2(r) away from energy and entropy injections. Finally, we discuss how the Supermodel connects information derived from X-ray and gravitational lensing observations.

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

A QUANTITATIVE ANALYSIS OF DISTANT OPEN CLUSTERS

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

Janes, Kenneth A.; Hoq, Sadia

2011-03-15

The oldest open star clusters are important for tracing the history of the Galactic disk, but many of the more distant clusters are heavily reddened and projected against the rich stellar background of the Galaxy. We have undertaken an investigation of several distant clusters (Berkeley 19, Berkeley 44, King 25, NGC 6802, NGC 6827, Berkeley 52, Berkeley 56, NGC 7142, NGC 7245, and King 9) to develop procedures for separating probable cluster members from the background field. We next created a simple quantitative approach for finding approximate cluster distances, reddenings, and ages. We first conclude that with the possible exceptionmore » of King 25 they are probably all physical clusters. We also find that for these distant clusters our typical errors are about {+-}0.07 in E(B - V), {+-}0.15 in log(age), and {+-}0.25 in (m - M){sub o}. The clusters range in age from 470 Myr to 7 Gyr and range from 7.1 to 16.4 kpc from the Galactic center.« less

Preoptimised VB: a fast method for the ground and excited states of ionic clusters I. Localised preoptimisation for (ArCO) +, (ArN 2) + and N 4+

NASA Astrophysics Data System (ADS)

Langenberg, J. H.; Bucur, I. B.; Archirel, P.

1997-09-01

We show that in the simple case of van der Waals ionic clusters, the optimisation of orbitals within VB can be easily simulated with the help of pseudopotentials. The procedure yields the ground and the first excited states of the cluster simultaneously. This makes the calculation of potential energy surfaces for tri- and tetraatomic clusters possible, with very acceptable computation times. We give potential curves for (ArCO) +, (ArN 2) + and N 4+. An application to the simulation of the SCF method is shown for Na +H 2O.

A simple algorithm for the identification of clinical COPD phenotypes.

PubMed

Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim; Piquet, Jacques; Ter Riet, Gerben; Garcia-Aymerich, Judith; Cosio, Borja; Bakke, Per; Puhan, Milo A; Langhammer, Arnulf; Alfageme, Inmaculada; Almagro, Pere; Ancochea, Julio; Celli, Bartolome R; Casanova, Ciro; de-Torres, Juan P; Decramer, Marc; Echazarreta, Andrés; Esteban, Cristobal; Gomez Punter, Rosa Mar; Han, MeiLan K; Johannessen, Ane; Kaiser, Bernhard; Lamprecht, Bernd; Lange, Peter; Leivseth, Linda; Marin, Jose M; Martin, Francis; Martinez-Camblor, Pablo; Miravitlles, Marc; Oga, Toru; Sofia Ramírez, Ana; Sin, Don D; Sobradillo, Patricia; Soler-Cataluña, Juan J; Turner, Alice M; Verdu Rivera, Francisco Javier; Soriano, Joan B; Roche, Nicolas

2017-11-01

This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV 1 , dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV 1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes. Copyright ©ERS 2017.

An explicitly spin-free compact open-shell coupled cluster theory using a multireference combinatoric exponential ansatz: formal development and pilot applications.

PubMed

Datta, Dipayan; Mukherjee, Debashis

2009-07-28

In this paper, we present a comprehensive account of an explicitly spin-free compact state-universal multireference coupled cluster (CC) formalism for computing the state energies of simple open-shell systems, e.g., doublets and biradicals, where the target open-shell states can be described by a few configuration state functions spanning a model space. The cluster operators in this formalism are defined in terms of the spin-free unitary generators with respect to the common closed-shell component of all model functions (core) as vacuum. The spin-free cluster operators are either closed-shell-like n hole-n particle excitations (denoted by T(mu)) or involve excitations from the doubly occupied (nonvalence) orbitals to the singly occupied (valence) orbitals (denoted by S(e)(mu)). In addition, there are cluster operators with exchange spectator scatterings involving the valence orbitals (denoted by S(re)(mu)). We propose a new multireference cluster expansion ansatz for the wave operator with the above generally noncommuting cluster operators which essentially has the same physical content as the Jeziorski-Monkhorst ansatz with the commuting cluster operators defined in the spin-orbital basis. The T(mu) operators in our ansatz are taken to commute with all other operators, while the S(e)(mu) and S(re)(mu) operators are allowed to contract among themselves through the spectator valence orbitals. An important innovation of this ansatz is the choice of an appropriate automorphic factor accompanying each contracted composite of cluster operators in order to ensure that each distinct excitation generated by this composite appears only once in the wave operator. The resulting CC equations consist of two types of terms: a "direct" term and a "normalization" term containing the effective Hamiltonian operator. It is emphasized that the direct term is almost quartic in the cluster amplitudes, barring only a handful of terms and termination of the normalization term depends on the valence rank of the effective Hamiltonian operator and the excitation rank of the cluster operators at which the theory is truncated. Illustrative applications are presented by computing the state energies of neutral doublet radicals and doublet molecular cations and ionization energies of neutral molecules and comparing our results with the other open-shell CC theories, benchmark full CI results (when available) in the same basis, and the experimental results. Highly encouraging results show the efficacy of the method.

60 micron luminosity evolution of rich clusters of galaxies

NASA Technical Reports Server (NTRS)

Kelly, Douglas M.; Rieke, George H.

1990-01-01

The average 60-micron flux has been determined for a collection of optically selected galaxy clusters at redshifts ranging from 0.30 to 0.92. The result, 26 mJy per cluster, represents the faintest flux determination known of using the IRAS data base. The flux from this set of clusters has been compared to the 60-micron flux from a sample of nearby galaxy clusters. It is found that the far-infrared luminosity evolution in cluster galaxies can be no more than a factor of 1.7 from z = 0.4 to the present epoch. This upper limit is close to the evolution predicted for simple aging of the stellar populations. Additional processes such as mergers, cannibalism, or enhanced rates of starbursts appear to occur at a low enough level that they have little influence on the far-infrared emission from clusters over this redshift range.

Unsupervised Structure Detection in Biomedical Data.

PubMed

Vogt, Julia E

2015-01-01

A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood comparisons that detects structure in unsupervised data. The method is based on ordering objects in terms of similarity and on the mutual overlap of nearest neighbors. This basic framework was originally introduced in the field of social network analysis to detect actor communities. We demonstrate that the same ideas can successfully be applied to biomedical data sets in order to reveal complex underlying structure. The algorithm is very efficient and works on distance data directly without requiring a vectorial embedding of data. Comprehensive experiments demonstrate the validity of this approach. Comparisons with state-of-the-art clustering methods show that the presented method outperforms hierarchical methods as well as density based clustering methods and model-based clustering. A further advantage of the method is that it simultaneously provides a visualization of the data. Especially in biomedical applications, the visualization of data can be used as a first pre-processing step when analyzing real world data sets to get an intuition of the underlying data structure. We apply this model to synthetic data as well as to various biomedical data sets which demonstrate the high quality and usefulness of the inferred structure.

Role of design complexity in technology improvement.

PubMed

McNerney, James; Farmer, J Doyne; Redner, Sidney; Trancik, Jessika E

2011-05-31

We study a simple model for the evolution of the cost (or more generally the performance) of a technology or production process. The technology can be decomposed into n components, each of which interacts with a cluster of d - 1 other components. Innovation occurs through a series of trial-and-error events, each of which consists of randomly changing the cost of each component in a cluster, and accepting the changes only if the total cost of the cluster is lowered. We show that the relationship between the cost of the whole technology and the number of innovation attempts is asymptotically a power law, matching the functional form often observed for empirical data. The exponent α of the power law depends on the intrinsic difficulty of finding better components, and on what we term the design complexity: the more complex the design, the slower the rate of improvement. Letting d as defined above be the connectivity, in the special case in which the connectivity is constant, the design complexity is simply the connectivity. When the connectivity varies, bottlenecks can arise in which a few components limit progress. In this case the design complexity depends on the details of the design. The number of bottlenecks also determines whether progress is steady, or whether there are periods of stasis punctuated by occasional large changes. Our model connects the engineering properties of a design to historical studies of technology improvement.

Electronic shell structure in Ga12 icosahedra and the relation to the bulk forms of gallium.

PubMed

Schebarchov, D; Gaston, N

2012-07-28

The electronic structure of known cluster compounds with a cage-like icosahedral Ga(12) centre is studied by first-principles theoretical methods, based on density functional theory. We consider these hollow metalloid nanostructures in the context of the polymorphism of the bulk, and identify a close relation to the α phase of gallium. This previously unrecognised connection is established using the electron localisation function, which reveals the ubiquitous presence of radially-pointing covalent bonds around the Ga(12) centre--analogous to the covalent bonds between buckled deltahedral planes in α-Ga. Furthermore, we find prominent superatom shell structure in these clusters, despite their hollow icosahedral motif and the presence of covalent bonds. The exact nature of the electronic shell structure is contrasted with simple electron shell models based on jellium, and we demonstrate how the interplay between gallium dimerisation, ligand- and crystal-field effects can alter the splitting of the partially filled 1F shell. Finally, in the unique compound where the Ga(12) centre is bridged by six phosphorus ligands, the electronic structure most closely resembles that of δ-Ga and there are no well-defined superatom orbitals. The results of this comprehensive study bring new insights into the nature of chemical bonding in metalloid gallium compounds and the relation to bulk gallium metal, and they may also guide the development of more general models for ligand-protected clusters.

Refinement of the probability density function model for preferential concentration of aerosol particles in isotropic turbulence

NASA Astrophysics Data System (ADS)

Zaichik, Leonid I.; Alipchenkov, Vladimir M.

2007-11-01

The purposes of the paper are threefold: (i) to refine the statistical model of preferential particle concentration in isotropic turbulence that was previously proposed by Zaichik and Alipchenkov [Phys. Fluids 15, 1776 (2003)], (ii) to investigate the effect of clustering of low-inertia particles using the refined model, and (iii) to advance a simple model for predicting the collision rate of aerosol particles. The model developed is based on a kinetic equation for the two-point probability density function of the relative velocity distribution of particle pairs. Improvements in predicting the preferential concentration of low-inertia particles are attained due to refining the description of the turbulent velocity field of the carrier fluid by including a difference between the time scales of the of strain and rotation rate correlations. The refined model results in a better agreement with direct numerical simulations for aerosol particles.

Helix-packing motifs in membrane proteins.

PubMed

Walters, R F S; DeGrado, W F

2006-09-12

The fold of a helical membrane protein is largely determined by interactions between membrane-imbedded helices. To elucidate recurring helix-helix interaction motifs, we dissected the crystallographic structures of membrane proteins into a library of interacting helical pairs. The pairs were clustered according to their three-dimensional similarity (rmsd

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

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

Luo, R; Wang, J; Zhong, H

2016-06-15

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB.more » Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10{sup −7}, χ{sup 2} test) and nonlinear correction (p=5.98 * 10{sup −7}, χ{sup 2} test), which is similar to the cluster result of CT data (p=4.52 * 10{sup −8}, χ{sup 2} test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.« less

CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

NASA Astrophysics Data System (ADS)

Komura, Yukihiro; Okabe, Yutaka

2014-03-01

We present sample CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm. We deal with the classical spin models; the Ising model, the q-state Potts model, and the classical XY model. As for the lattice, both the 2D (square) lattice and the 3D (simple cubic) lattice are treated. We already reported the idea of the GPU implementation for 2D models (Komura and Okabe, 2012). We here explain the details of sample programs, and discuss the performance of the present GPU implementation for the 3D Ising and XY models. We also show the calculated results of the moment ratio for these models, and discuss phase transitions. Catalogue identifier: AERM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERM_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5632 No. of bytes in distributed program, including test data, etc.: 14688 Distribution format: tar.gz Programming language: C, CUDA. Computer: System with an NVIDIA CUDA enabled GPU. Operating system: System with an NVIDIA CUDA enabled GPU. Classification: 23. External routines: NVIDIA CUDA Toolkit 3.0 or newer Nature of problem: Monte Carlo simulation of classical spin systems. Ising, q-state Potts model, and the classical XY model are treated for both two-dimensional and three-dimensional lattices. Solution method: GPU-based Swendsen-Wang multi-cluster spin flip Monte Carlo method. The CUDA implementation for the cluster-labeling is based on the work by Hawick et al. [1] and that by Kalentev et al. [2]. Restrictions: The system size is limited depending on the memory of a GPU. Running time: For the parameters used in the sample programs, it takes about a minute for each program. Of course, it depends on the system size, the number of Monte Carlo steps, etc. References: [1] K.A. Hawick, A. Leist, and D. P. Playne, Parallel Computing 36 (2010) 655-678 [2] O. Kalentev, A. Rai, S. Kemnitzb, and R. Schneider, J. Parallel Distrib. Comput. 71 (2011) 615-620

Ajmaline blocks INa and IKr without eliciting differences between Brugada syndrome patient and control human pluripotent stem cell-derived cardiac clusters.

PubMed

Miller, Duncan C; Harmer, Stephen C; Poliandri, Ariel; Nobles, Muriel; Edwards, Elizabeth C; Ware, James S; Sharp, Tyson V; McKay, Tristan R; Dunkel, Leo; Lambiase, Pier D; Tinker, Andrew

2017-12-01

The class Ia anti-arrhythmic drug ajmaline is used clinically to unmask latent type I ECG in Brugada syndrome (BrS) patients, although its mode of action is poorly characterised. Our aims were to identify ajmaline's mode of action in human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs), and establish a simple BrS hiPSC platform to test whether differences in ajmaline response could be determined between BrS patients and controls. Control hiPSCs were differentiated into spontaneously contracting cardiac clusters. It was found using multi electrode array (MEA) that ajmaline treatment significantly lengthened cluster activation-recovery interval. Patch clamping of single CMs isolated from clusters revealed that ajmaline can block both I Na and I Kr . Following generation of hiPSC lines from BrS patients (absent of pathogenic SCN5A sodium channel mutations), analysis of hiPSC-CMs from patients and controls revealed that differentiation and action potential parameters were similar. Comparison of cardiac clusters by MEA showed that ajmaline lengthened activation-recovery interval consistently across all lines. We conclude that ajmaline can block both depolarisation and repolarisation of hiPSC-CMs at the cellular level, but that a more refined integrated tissue model may be necessary to elicit differences in its effect between BrS patients and controls. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Globular cluster systems as tracers of environmental effects on Virgo early-type dwarfs

NASA Astrophysics Data System (ADS)

Sánchez-Janssen, R.; Aguerri, J. A. L.

2012-08-01

Early-type dwarfs (dEs) are by far the most abundant galaxy population in nearby clusters. Whether these objects are primordial, or the recent end products of the different physical mechanisms that can transform galaxies once they enter these high-density environments, is still a matter of debate. Here we present a novel approach to test these scenarios by comparing the properties of the globular cluster systems (GCSs) of Virgo dEs and their potential progenitors with simple predictions from gravitational and hydrodynamical interaction models. We show that low-mass (M★ ≲ 2 × 108 M⊙) dEs have GCSs consistent with the descendants of gas-stripped late-type dwarfs. On the other hand, higher mass dEs have properties - including the high mass specific frequencies of their GCSs and their concentrated spatial distribution within Virgo - incompatible with a recent, environmentally driven evolution. They mostly comprise nucleated systems, but also dEs with recent star formation and/or disc features. Bright, nucleated dEs appear to be a population that has long resided within the cluster potential well, but have surprisingly managed to retain very rich and spatially extended GCSs - possibly an indication of high total masses. Our analysis does not favour violent evolutionary mechanisms that result in significant stellar mass-losses, but more gentle processes involving gas removal by a combination of internal and external factors, and highlights the relevant role of initial conditions. Additionally, we briefly comment on the origin of luminous cluster S0 galaxies.

minimega

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

David Fritz, John Floren

2013-08-27

Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.

Analysis of Salmonella enterica Serovar Typhimurium Variable-Number Tandem-Repeat Data for Public Health Investigation Based on Measured Mutation Rates and Whole-Genome Sequence Comparisons

PubMed Central

Dimovski, Karolina; Cao, Hanwei; Wijburg, Odilia L. C.; Strugnell, Richard A.; Mantena, Radha K.; Whipp, Margaret; Hogg, Geoff

2014-01-01

Variable-number tandem repeats (VNTRs) mutate rapidly and can be useful markers for genotyping. While multilocus VNTR analysis (MLVA) is increasingly used in the detection and investigation of food-borne outbreaks caused by Salmonella enterica serovar Typhimurium (S. Typhimurium) and other bacterial pathogens, MLVA data analysis usually relies on simple clustering approaches that may lead to incorrect interpretations. Here, we estimated the rates of copy number change at each of the five loci commonly used for S. Typhimurium MLVA, during in vitro and in vivo passage. We found that loci STTR5, STTR6, and STTR10 changed during passage but STTR3 and STTR9 did not. Relative rates of change were consistent across in vitro and in vivo growth and could be accurately estimated from diversity measures of natural variation observed during large outbreaks. Using a set of 203 isolates from a series of linked outbreaks and whole-genome sequencing of 12 representative isolates, we assessed the accuracy and utility of several alternative methods for analyzing and interpreting S. Typhimurium MLVA data. We show that eBURST analysis was accurate and informative. For construction of MLVA-based trees, a novel distance metric, based on the geometric model of VNTR evolution coupled with locus-specific weights, performed better than the commonly used simple or categorical distance metrics. The data suggest that, for the purpose of identifying potential transmission clusters for further investigation, isolates whose profiles differ at one of the rapidly changing STTR5, STTR6, and STTR10 loci should be collapsed into the same cluster. PMID:24957617

Accurate calculation and modeling of the adiabatic connection in density functional theory

NASA Astrophysics Data System (ADS)

Teale, A. M.; Coriani, S.; Helgaker, T.

2010-04-01

Using a recently implemented technique for the calculation of the adiabatic connection (AC) of density functional theory (DFT) based on Lieb maximization with respect to the external potential, the AC is studied for atoms and molecules containing up to ten electrons: the helium isoelectronic series, the hydrogen molecule, the beryllium isoelectronic series, the neon atom, and the water molecule. The calculation of AC curves by Lieb maximization at various levels of electronic-structure theory is discussed. For each system, the AC curve is calculated using Hartree-Fock (HF) theory, second-order Møller-Plesset (MP2) theory, coupled-cluster singles-and-doubles (CCSD) theory, and coupled-cluster singles-doubles-perturbative-triples [CCSD(T)] theory, expanding the molecular orbitals and the effective external potential in large Gaussian basis sets. The HF AC curve includes a small correlation-energy contribution in the context of DFT, arising from orbital relaxation as the electron-electron interaction is switched on under the constraint that the wave function is always a single determinant. The MP2 and CCSD AC curves recover the bulk of the dynamical correlation energy and their shapes can be understood in terms of a simple energy model constructed from a consideration of the doubles-energy expression at different interaction strengths. Differentiation of this energy expression with respect to the interaction strength leads to a simple two-parameter doubles model (AC-D) for the AC integrand (and hence the correlation energy of DFT) as a function of the interaction strength. The structure of the triples-energy contribution is considered in a similar fashion, leading to a quadratic model for the triples correction to the AC curve (AC-T). From a consideration of the structure of a two-level configuration-interaction (CI) energy expression of the hydrogen molecule, a simple two-parameter CI model (AC-CI) is proposed to account for the effects of static correlation on the AC. When parametrized in terms of the same input data, the AC-CI model offers improved performance over the corresponding AC-D model, which is shown to be the lowest-order contribution to the AC-CI model. The utility of the accurately calculated AC curves for the analysis of standard density functionals is demonstrated for the BLYP exchange-correlation functional and the interaction-strength-interpolation (ISI) model AC integrand. From the results of this analysis, we investigate the performance of our proposed two-parameter AC-D and AC-CI models when a simple density functional for the AC at infinite interaction strength is employed in place of information at the fully interacting point. The resulting two-parameter correlation functionals offer a qualitatively correct behavior of the AC integrand with much improved accuracy over previous attempts. The AC integrands in the present work are recommended as a basis for further work, generating functionals that avoid spurious error cancellations between exchange and correlation energies and give good accuracy for the range of densities and types of correlation contained in the systems studied here.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the Northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

NASA Astrophysics Data System (ADS)

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

2013-09-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Formation of Twisted Elephant Trunks in the Rosette Nebula

NASA Astrophysics Data System (ADS)

Carlqvist, P.; Gahm, G. F.; Kristen, H.

New observations show that dark elephant trunks in the Rosette nebula are often built up by thin filaments. In several of the trunks the filaments seem to form a twisted pattern. This pattern is hard to reconcile with current theory. We propose a new model for the formation of twisted elephant trunks in which electromagnetic forces play an important role. The model considers the behaviour of a twisted magnetic filament in a molecular cloud, where a cluster of hot stars has been recently born. As a result of stellar winds, and radiation pressure, electromagnetic forces, and inertia forces part of the filament can develop into a double helix pointing towards the stars. The double helix represents the twisted elephant trunk. A simple analogy experiment visualizes and supports the trunk model.

Simple Linux Utility for Resource Management

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

Jette, M.

2009-09-09

SLURM is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small computer clusters. As a cluster resource manager, SLURM has three key functions. First, it allocates exclusive and/or non exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allciated nodes. Finally, it arbitrates conflicting requests for resouces by managing a queue of pending work.

Patterning C. elegans: homeotic cluster genes, cell fates and cell migrations.

PubMed

Salser, S J; Kenyon, C

1994-05-01

Despite its simple body form, the nematode C. elegans expresses homeotic cluster genes similar to those of insects and vertebrates in the patterning of many cell types and tissues along the anteroposterior axis. In the ventral nerve cord, these genes program spatial patterns of cell death, fusion, division and neurotransmitter production; in migrating cells they regulate the direction and extent of movement. Nematode development permits an analysis at the cellular level of how homeotic cluster genes interact to specify cell fates, and how cell behavior can be regulated to assemble an organism.

Close-packed floating clusters: granular hydrodynamics beyond the freezing point?

PubMed

Meerson, Baruch; Pöschel, Thorsten; Bromberg, Yaron

2003-07-11

Monodisperse granular flows often develop regions with hexagonal close packing of particles. We investigate this effect in a system of inelastic hard spheres driven from below by a "thermal" plate. Molecular dynamics simulations show, in a wide range of parameters, a close-packed cluster supported by a low-density region. Surprisingly, the steady-state density profile, including the close-packed cluster part, is well described by a variant of Navier-Stokes granular hydrodynamics (NSGH). We suggest a simple explanation for the success of NSGH beyond the freezing point.

SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

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

Kumar, S.; Gezari, S.; Heinis, S.

2015-03-20

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g {sub P1}, r {sub P1}, i {sub P1}, and z {sub P1}. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and anmore » analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.« less

Peculiarities in velocity dispersion and surface density profiles of star clusters

NASA Astrophysics Data System (ADS)

Küpper, Andreas H. W.; Kroupa, Pavel; Baumgardt, Holger; Heggie, Douglas C.

2010-10-01

Based on our recent work on tidal tails of star clusters we investigate star clusters of a few 104Msolar by means of velocity dispersion profiles and surface density profiles. We use a comprehensive set of N-body computations of star clusters on various orbits within a realistic tidal field to study the evolution of these profiles with time, and ongoing cluster dissolution. From the velocity dispersion profiles we find that the population of potential escapers, i.e. energetically unbound stars inside the Jacobi radius, dominates clusters at radii above about 50 per cent of the Jacobi radius. Beyond 70 per cent of the Jacobi radius nearly all stars are energetically unbound. The velocity dispersion therefore significantly deviates from the predictions of simple equilibrium models in this regime. We furthermore argue that for this reason this part of a cluster cannot be used to detect a dark matter halo or deviations from the Newtonian gravity. By fitting templates to about 104 computed surface density profiles we estimate the accuracy which can be achieved in reconstructing the Jacobi radius of a cluster in this way. We find that the template of King works well for extended clusters on nearly circular orbits, but shows significant flaws in the case of eccentric cluster orbits. This we fix by extending this template with three more free parameters. Our template can reconstruct the tidal radius over all fitted ranges with an accuracy of about 10 per cent, and is especially useful in the case of cluster data with a wide radial coverage and for clusters showing significant extra-tidal stellar populations. No other template that we have tried can yield comparable results over this range of cluster conditions. All templates fail to reconstruct tidal parameters of concentrated clusters, however. Moreover, we find that the bulk of a cluster adjusts to the mean tidal field which it experiences and not to the tidal field at perigalacticon as has often been assumed in other investigations, i.e. a fitted tidal radius is a cluster's time average mean tidal radius and not its perigalactic one. Furthermore, we study the tidal debris in the vicinity of the clusters and find it to be well represented by a power law with a slope of -4 to -5. This steep slope we ascribe to the epicyclic motion of escaped stars in the tidal tails. Star clusters close to apogalacticon show a significantly shallower slope of up to -1, however. We suggest that clusters at apogalacticon can be identified by measuring this slope.

A Starburst in the Core of a Galaxy Cluster: the Dwarf Irregular NGC 1427A in Fornax

NASA Astrophysics Data System (ADS)

Mora, Marcelo D.; Chanamé, Julio; Puzia, Thomas H.

2015-09-01

Gas-rich galaxies in dense environments such as galaxy clusters and massive groups are affected by a number of possible types of interactions with the cluster environment, which make their evolution radically different than that of field galaxies. The dwarf irregular galaxy NGC 1427A, presently infalling toward the core of the Fornax galaxy cluster for the first time, offers a unique opportunity to study those processes at a level of detail not possible to achieve for galaxies at higher redshifts, when galaxy-scale interactions were more common. Using the spatial resolution of the Hubble Space Telescope/Advanced Camera for Surveys and auxiliary Very Large Telescope/FORS1 ground-based observations, we study the properties of the most recent episodes of star formation in this gas-rich galaxy, the only one of its type near the core of the Fornax cluster. We study the structural and photometric properties of young star cluster complexes in NGC 1427A, identifying 12 bright such complexes with exceptionally blue colors. The comparison of our broadband near-UV/optical photometry with simple stellar population models yields ages below ˜ 4× {10}6 years and stellar masses from a few 1000 up to ˜ 3× {10}4{M}⊙ , slightly dependent on the assumption of cluster metallicity and initial mass function. Their grouping is consistent with hierarchical and fractal star cluster formation. We use deep Hα imaging data to determine the current star formation rate in NGC 1427A and estimate the ratio, Γ, of star formation occurring in these star cluster complexes to that in the entire galaxy. We find Γ to be among the largest such values available in the literature, consistent with starburst galaxies. Thus a large fraction of the current star formation in NGC 1427A is occurring in star clusters, with the peculiar spatial arrangement of such complexes strongly hinting at the possibility that the starburst is being triggered by the passage of the galaxy through the cluster environment. Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 70.B-0695.

Stabilizing ultrasmall Au clusters for enhanced photoredox catalysis.

PubMed

Weng, Bo; Lu, Kang-Qiang; Tang, Zichao; Chen, Hao Ming; Xu, Yi-Jun

2018-04-18

Recently, loading ligand-protected gold (Au) clusters as visible light photosensitizers onto various supports for photoredox catalysis has attracted considerable attention. However, the efficient control of long-term photostability of Au clusters on the metal-support interface remains challenging. Herein, we report a simple and efficient method for enhancing the photostability of glutathione-protected Au clusters (Au GSH clusters) loaded on the surface of SiO 2 sphere by utilizing multifunctional branched poly-ethylenimine (BPEI) as a surface charge modifying, reducing and stabilizing agent. The sequential coating of thickness controlled TiO 2 shells can further significantly improve the photocatalytic efficiency, while such structurally designed core-shell SiO 2 -Au GSH clusters-BPEI@TiO 2 composites maintain high photostability during longtime light illumination conditions. This joint strategy via interfacial modification and composition engineering provides a facile guideline for stabilizing ultrasmall Au clusters and rational design of Au clusters-based composites with improved activity toward targeting applications in photoredox catalysis.

Infrared spectra of seeded hydrogen clusters: (para-H2)N-N2O and (ortho-H2)N-N2O, N = 2-13.

PubMed

Tang, Jian; McKellar, A R W

2005-09-15

High-resolution infrared spectra of clusters containing para-H2 and/or ortho-H2 and a single nitrous oxide molecule are studied in the 2225-cm(-1) region of the upsilon1 fundamental band of N2O. The clusters are formed in pulsed supersonic jet expansions from a cooled nozzle and probed using a tunable infrared diode laser spectrometer. The simple symmetric rotor-type spectra generally show no resolved K structure, with prominent Q-branch features for ortho-H2 but not para-H2 clusters. The observed vibrational shifts and rotational constants are reported. There is no obvious indication of superfluid effects for para-H2 clusters up to N=13. Sharp transitions due to even larger clusters are observed, but no definite assignments are possible. Mixed (para-H2)N-(ortho-H2)M-N2O cluster line positions can be well predicted by linear interpolation between the corresponding transitions of the pure clusters.

New tools for characterizing swarming systems: A comparison of minimal models

NASA Astrophysics Data System (ADS)

Huepe, Cristián; Aldana, Maximino

2008-05-01

We compare three simple models that reproduce qualitatively the emergent swarming behavior of bird flocks, fish schools, and other groups of self-propelled agents by using a new set of diagnosis tools related to the agents’ spatial distribution. Two of these correspond in fact to different implementations of the same model, which had been previously confused in the literature. All models appear to undergo a very similar order-to-disorder phase transition as the noise level is increased if we only compare the standard order parameter, which measures the degree of agent alignment. When considering our novel quantities, however, their properties are clearly distinguished, unveiling previously unreported qualitative characteristics that help determine which model best captures the main features of realistic swarms. Additionally, we analyze the agent clustering in space, finding that the distribution of cluster sizes is typically exponential at high noise, and approaches a power-law as the noise level is reduced. This trend is sometimes reversed at noise levels close to the phase transition, suggesting a non-trivial critical behavior that could be verified experimentally. Finally, we study a bi-stable regime that develops under certain conditions in large systems. By computing the probability distributions of our new quantities, we distinguish the properties of each of the coexisting metastable states. Our study suggests new experimental analyses that could be carried out to characterize real biological swarms.

Methods for Generating Complex Networks with Selected Structural Properties for Simulations: A Review and Tutorial for Neuroscientists

PubMed Central

Prettejohn, Brenton J.; Berryman, Matthew J.; McDonnell, Mark D.

2011-01-01

Many simulations of networks in computational neuroscience assume completely homogenous random networks of the Erdös–Rényi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the “scale-free” and “small-world” properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length, and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks. PMID:21441986

Genetic diversity studies and identification of SSR markers associated with Fusarium wilt (Fusarium udum) resistance in cultivated pigeonpea (Cajanus cajan).

PubMed

Singh, A K; Rai, V P; Chand, R; Singh, R P; Singh, M N

2013-01-01

Genetic diversity and identification of simple sequence repeat markers correlated with Fusarium wilt resistance was performed in a set of 36 elite cultivated pigeonpea genotypes differing in levels of resistance to Fusarium wilt. Twenty-four polymorphic sequence repeat markers were screened across these genotypes, and amplified a total of 59 alleles with an average high polymorphic information content value of 0.52. Cluster analysis, done by UPGMA and PCA, grouped the 36 pigeonpea genotypes into two main clusters according to their Fusarium wilt reaction. Based on the Kruskal-Wallis ANOVA and simple regression analysis, six simple sequence repeat markers were found to be significantly associated with Fusarium wilt resistance. The phenotypic variation explained by these markers ranged from 23.7 to 56.4%. The present study helps in finding out feasibility of prescreened SSR markers to be used in genetic diversity analysis and their potential association with disease resistance.

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.

K-means clustering for support construction in diffractive imaging.

PubMed

Hattanda, Shunsuke; Shioya, Hiroyuki; Maehara, Yosuke; Gohara, Kazutoshi

2014-03-01

A method for constructing an object support based on K-means clustering of the object-intensity distribution is newly presented in diffractive imaging. This releases the adjustment of unknown parameters in the support construction, and it is well incorporated with the Gerchberg and Saxton diagram. A simple numerical simulation reveals that the proposed method is effective for dynamically constructing the support without an initial prior support.

Simple Rules Govern the Patterns of Arctic Sea Ice Melt Ponds

NASA Astrophysics Data System (ADS)

Popović, Predrag; Cael, B. B.; Silber, Mary; Abbot, Dorian S.

2018-04-01

Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming.

Simple Rules Govern the Patterns of Arctic Sea Ice Melt Ponds.

PubMed

Popović, Predrag; Cael, B B; Silber, Mary; Abbot, Dorian S

2018-04-06

Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming.

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

USGS Publications Warehouse

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

2017-01-01

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

Measurements and simulations of MAPS (Monolithic Active Pixel Sensors) response to charged particles - a study towards a vertex detector at the ILC

NASA Astrophysics Data System (ADS)

Maczewski, Lukasz

2010-05-01

The International Linear Collider (ILC) is a project of an electron-positron (e+e-) linear collider with the centre-of-mass energy of 200-500 GeV. Monolithic Active Pixel Sensors (MAPS) are one of the proposed silicon pixel detector concepts for the ILC vertex detector (VTX). Basic characteristics of two MAPS pixel matrices MIMOSA-5 (17 μm pixel pitch) and MIMOSA-18 (10 μm pixel pitch) are studied and compared (pedestals, noises, calibration of the ADC-to-electron conversion gain, detector efficiency and charge collection properties). The e+e- collisions at the ILC will be accompanied by intense beamsstrahlung background of electrons and positrons hitting inner planes of the vertex detector. Tracks of this origin leave elongated clusters contrary to those of secondary hadrons. Cluster characteristics and orientation with respect to the pixels netting are studied for perpendicular and inclined tracks. Elongation and precision of determining the cluster orientation as a function of the angle of incidence were measured. A simple model of signal formation (based on charge diffusion) is proposed and tested using the collected data.

Gas-generated thermal oxidation of a coordination cluster for an anion-doped mesoporous metal oxide.

PubMed

Hirai, Kenji; Isobe, Shigehito; Sada, Kazuki

2015-12-18

Central in material design of metal oxides is the increase of surface area and control of intrinsic electronic and optical properties, because of potential applications for energy storage, photocatalysis and photovoltaics. Here, we disclose a facile method, inspired by geochemical process, which gives rise to mesoporous anion-doped metal oxides. As a model system, we demonstrate that simple calcination of a multinuclear coordination cluster results in synchronic chemical reactions: thermal oxidation of Ti8O10(4-aminobenzoate)12 and generation of gases including amino-group fragments. The gas generation during the thermal oxidation of Ti8O10(4-aminobenzoate)12 creates mesoporosity in TiO2. Concurrently, nitrogen atoms contained in the gases are doped into TiO2, thus leading to the formation of mesoporous N-doped TiO2. The mesoporous N-doped TiO2 can be easily synthesized by calcination of the multinuclear coordination cluster, but shows better photocatalytic activity than the one prepared by a conventional sol-gel method. Owing to an intrinsic designability of coordination compounds, this facile synthetic will be applicable to a wide range of metal oxides and anion dopants.

A comparative study on the interaction of acridine and synthetic bis-acridine with G-quadruplex structure.

PubMed

Nagesh, Narayana; Krishnaiah, Abburi

2003-07-31

DNA from the telomeres contains a stretch of simple tandemly repeated sequences in which clusters of G residues alternate with clusters of T/A sequences along one DNA strand. Model telomeric G-clusters form four-stranded structures in presence of Na(I), K(I) and NH(4)(I) ions. Electrophoretic and spectroscopic studies were made with the telomeric related sequences d(T6G16) or d(G4T2G4T2G4T2G4). It was noticed earlier that G-quadruplex may either be inter-molecular, or intra-molecular, or a mixture of both. CD spectral characteristics of various G-quadruplex DNA suggests that the CD maximum at 293 nm corresponds to that of an intra-molecular G-quadruplex structure or hairpin dimers. Fluorescence titration studies also show that acridine and the bis-acridine are interacting with G-quadruplex DNA and destabilize the K(I)-quadruplex structure more efficiently than the quadruplex formed by NH(4)(I) ion. Among the two drugs studied, acridine is more capable of breaking the G-quadruplex structure than bis-acridine. This result is further confirmed by the CD experiments.

Cooperativity of self-organized Brownian motors pulling on soft cargoes.

PubMed

Orlandi, Javier G; Blanch-Mercader, Carles; Brugués, Jan; Casademunt, Jaume

2010-12-01

We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state noise-driven ratchet formulation and study analytically and numerically the collective velocity-force and efficiency-force curves resulting from mutual interactions, mostly hard-core repulsion and weak (nonbinding) attraction. We analyze different parameter regimes including the limits of weak noise, mean-field behavior, rigid coupling, and large numbers of motors, for the different interactions. We present a general framework to classify and quantify cooperativity. We show that asymmetric loading leads generically to enhanced cooperativity beyond the simple superposition of the effects of individual motors. For weakly attracting interactions, the cooperativity is mostly enhanced, including highly coordinated motion of motors and complex nonmonotonic velocity-force curves, leading to self-regulated clusters. The dynamical scenario is enriched by resonances associated to commensurability of different length scales. Large clusters exhibit synchronized dynamics and bidirectional motion. Biological implications are discussed.

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.

Multiconfiguration resonating-group theory of the seven-nucleon system with realistic cluster wave functions

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

Fujiwara, Y.; Tang, Y.C.

1985-02-01

The properties of the seven-nucleon system are examined with a multiconfiguration and multi- channel resonating-group calculation. The cluster internal functions employed explain the charge-form-factor data over a wide range of q/sup 2/ and satisfy the variational stability condition quite well. The model space used is spanned by /sup 3/H+..cap alpha.., n+ /sup 6/Li, n+ /sup 6/Li(, and d+ /sup 5/He cluster configurations. The result shows that the specific distortion of the /sup 3/H+..cap alpha.. system is quite significant. With our multiconfiguration calculation, the ground-state energy is improved by more than 1 MeV. The calculated level spectrum agrees well with themore » level spectrum empirically determined. The energy positions of both natural-parity and unnatural-parity levels are reasonably explained. In addition, we find that, because of centrifugal-barrier effects, the aligned configuration generally makes the most sig- nificant contribution. The characteristics of nucleon-exchange terms are also briefly examined. Here it is found that, at sufficiently high energies where sharp resonance levels do not exist, the essential properties of these terms can already be learned by performing relatively simple single-configuration calculations.« less

Cooperativity of self-organized Brownian motors pulling on soft cargoes

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Blanch-Mercader, Carles; Brugués, Jan; Casademunt, Jaume

2010-12-01

We study the cooperative dynamics of Brownian motors moving along a one-dimensional track when an external load is applied to the leading motor, mimicking molecular motors pulling on membrane-bound cargoes in intracellular traffic. Due to the asymmetric loading, self-organized motor clusters form spontaneously. We model the motors with a two-state noise-driven ratchet formulation and study analytically and numerically the collective velocity-force and efficiency-force curves resulting from mutual interactions, mostly hard-core repulsion and weak (nonbinding) attraction. We analyze different parameter regimes including the limits of weak noise, mean-field behavior, rigid coupling, and large numbers of motors, for the different interactions. We present a general framework to classify and quantify cooperativity. We show that asymmetric loading leads generically to enhanced cooperativity beyond the simple superposition of the effects of individual motors. For weakly attracting interactions, the cooperativity is mostly enhanced, including highly coordinated motion of motors and complex nonmonotonic velocity-force curves, leading to self-regulated clusters. The dynamical scenario is enriched by resonances associated to commensurability of different length scales. Large clusters exhibit synchronized dynamics and bidirectional motion. Biological implications are discussed.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model.

PubMed

Pulawski, Wojciech; Jamroz, Michal; Kolinski, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2016-11-28

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

A Large Stellar Evolution Database for Population Synthesis Studies. I. Scaled Solar Models and Isochrones

NASA Astrophysics Data System (ADS)

Pietrinferni, Adriano; Cassisi, Santi; Salaris, Maurizio; Castelli, Fiorella

2004-09-01

We present a large and updated stellar evolution database for low-, intermediate-, and high-mass stars in a wide metallicity range, suitable for studying Galactic and extragalactic simple and composite stellar populations using population synthesis techniques. The stellar mass range is between ~0.5 and 10 Msolar with a fine mass spacing. The metallicity [Fe/H] comprises 10 values ranging from -2.27 to 0.40, with a scaled solar metal distribution. The initial He mass fraction ranges from Y=0.245, for the more metal-poor composition, up to 0.303 for the more metal-rich one, with ΔY/ΔZ~1.4. For each adopted chemical composition, the evolutionary models have been computed without (canonical models) and with overshooting from the Schwarzschild boundary of the convective cores during the central H-burning phase. Semiconvection is included in the treatment of core convection during the He-burning phase. The whole set of evolutionary models can be used to compute isochrones in a wide age range, from ~30 Myr to ~15 Gyr. Both evolutionary models and isochrones are available in several observational planes, employing an updated set of bolometric corrections and color-Teff relations computed for this project. The number of points along the models and the resulting isochrones is selected in such a way that interpolation for intermediate metallicities not contained in the grid is straightforward; a simple quadratic interpolation produces results of sufficient accuracy for population synthesis applications.We compare our isochrones with results from a series of widely used stellar evolution databases and perform some empirical tests for the reliability of our models. Since this work is devoted to scaled solar chemical compositions, we focus our attention on the Galactic disk stellar populations, employing multicolor photometry of unevolved field main-sequence stars with precise Hipparcos parallaxes, well-studied open clusters, and one eclipsing binary system with precise measurements of masses, radii, and [Fe/H] of both components. We find that the predicted metallicity dependence of the location of the lower, unevolved main sequence in the color magnitude diagram (CMD) appears in satisfactory agreement with empirical data. When comparing our models with CMDs of selected, well-studied, open clusters, once again we were able to properly match the whole observed evolutionary sequences by assuming cluster distance and reddening estimates in satisfactory agreement with empirical evaluations of these quantities. In general, models including overshooting during the H-burning phase provide a better match to the observations, at least for ages below ~4 Gyr. At [Fe/H] around solar and higher ages (i.e., smaller convective cores) before the onset of radiative cores, the selected efficiency of core overshooting may be too high in our model, as well as in various other models in the literature. Since we also provide canonical models, the reader is strongly encouraged to always compare the results from both sets in this critical age range.

Direct observation of lifetime killing defects in 4H SiC epitaxial layers through spin dependent recombination in bipolar junction transistors

NASA Astrophysics Data System (ADS)

Cochrane, C. J.; Lenahan, P. M.; Lelis, A. J.

2009-03-01

We have identified a magnetic resonance spectrum associated with minority carrier lifetime killing defects in device quality 4H SiC through magnetic resonance measurements in bipolar junction transistors using spin dependent recombination (SDR). The SDR spectrum has nine distinguishable lines; it is, within experimental error, essentially isotropic with four distinguishable pairs of side peaks symmetric about the strong center line. The line shape is, within experimental error, independent of bias voltage and recombination current. The large amplitude and spacing of the inner pair of side peaks and three more widely separated pairs of side peaks are not consistent with either a simple silicon or carbon vacancy or a carbon or silicon antisite. This indicates that the lifetime killing defect is not a simple defect but a defect aggregate. The spectrum is consistent with a multidefect cluster with an electron spin S =1/2. (The observed spectrum has not been reported previously in the magnetic resonance literature on SiC.) A fairly strong argument can be made in terms of a first order model linking the SDR spectrum to a divacancy or possibly a vacancy/antisite pair. The SDR amplitude versus gate voltage is semiquantitatively consistent with a very simple model in which the defect is uniformly distributed within the depletion region of the base/collector junction and is also the dominating recombination center. The large relative amplitude of the SDR response is more nearly consistent with a Kaplan-Solomon-Mott-like model for spin dependent recombination than the Lepine model.

A simple phenomenological model for grain clustering in turbulence

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.

2016-01-01

We propose a simple model for density fluctuations of aerodynamic grains, embedded in a turbulent, gravitating gas disc. The model combines a calculation for the behaviour of a group of grains encountering a single turbulent eddy, with a hierarchical approximation of the eddy statistics. This makes analytic predictions for a range of quantities including: distributions of grain densities, power spectra and correlation functions of fluctuations, and maximum grain densities reached. We predict how these scale as a function of grain drag time ts, spatial scale, grain-to-gas mass ratio tilde{ρ }, strength of turbulence α, and detailed disc properties. We test these against numerical simulations with various turbulence-driving mechanisms. The simulations agree well with the predictions, spanning ts Ω ˜ 10-4-10, tilde{ρ }˜ 0{-}3, α ˜ 10-10-10-2. Results from `turbulent concentration' simulations and laboratory experiments are also predicted as a special case. Vortices on a wide range of scales disperse and concentrate grains hierarchically. For small grains this is most efficient in eddies with turnover time comparable to the stopping time, but fluctuations are also damped by local gas-grain drift. For large grains, shear and gravity lead to a much broader range of eddy scales driving fluctuations, with most power on the largest scales. The grain density distribution has a log-Poisson shape, with fluctuations for large grains up to factors ≳1000. We provide simple analytic expressions for the predictions, and discuss implications for planetesimal formation, grain growth, and the structure of turbulence.

Adaptive fuzzy leader clustering of complex data sets in pattern recognition

NASA Technical Reports Server (NTRS)

Newton, Scott C.; Pemmaraju, Surya; Mitra, Sunanda

1992-01-01

A modular, unsupervised neural network architecture for clustering and classification of complex data sets is presented. The adaptive fuzzy leader clustering (AFLC) architecture is a hybrid neural-fuzzy system that learns on-line in a stable and efficient manner. The initial classification is performed in two stages: a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from fuzzy C-means system equations for the centroids and the membership values. The AFLC algorithm is applied to the Anderson Iris data and laser-luminescent fingerprint image data. It is concluded that the AFLC algorithm successfully classifies features extracted from real data, discrete or continuous.

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

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

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

Chiu, I.; et al.

2017-11-02

We estimate total mass (more » $$M_{500}$$), intracluster medium (ICM) mass ($$M_{\\mathrm{ICM}}$$) and stellar mass ($$M_{\\star}$$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $$M_{500}\\gtrsim2.5\\times10^{14}M_{\\odot}$$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $$M_{500}$$ are estimated from the SZE observable, the ICM masses $$M_{\\mathrm{ICM}}$$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $$M_{\\star}$$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $$\\approx9$$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.« less

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

DOE PAGES

Chiu, I.; Mohr, J. J.; McDonald, M.; ...

2018-05-16

Here, we estimate total mass (more » $$M_{500}$$), intracluster medium (ICM) mass ($$M_{\\mathrm{ICM}}$$) and stellar mass ($$M_{\\star}$$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $$M_{500}\\gtrsim2.5\\times10^{14}M_{\\odot}$$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $$M_{500}$$ are estimated from the SZE observable, the ICM masses $$M_{\\mathrm{ICM}}$$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $$M_{\\star}$$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $$\\approx9$$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.« less

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

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

Chiu, I.; et al.

2017-11-02

We estimate total mass (more » $$M_{500}$$), intracluster medium (ICM) mass ($$M_{\\mathrm{ICM}}$$) and stellar mass ($$M_{\\star}$$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $$M_{500}\\gtrsim2.5\\times10^{14}M_{\\odot}$$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $$M_{500}$$ are estimated from the SZE observable, the ICM masses $$M_{\\mathrm{ICM}}$$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $$M_{\\star}$$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $$\\approx9$$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the strong mass and weak redshift trends in the stellar mass scaling relation suggest a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called 'missing baryons' outside cluster virial regions.« less

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

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

Chiu, I.; Mohr, J. J.; McDonald, M.

Here, we estimate total mass (more » $$M_{500}$$), intracluster medium (ICM) mass ($$M_{\\mathrm{ICM}}$$) and stellar mass ($$M_{\\star}$$) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses $$M_{500}\\gtrsim2.5\\times10^{14}M_{\\odot}$$ and redshift $0.2 < z < 1.25$ from the 2500 deg$^2$ South Pole Telescope SPT-SZ survey. The total masses $$M_{500}$$ are estimated from the SZE observable, the ICM masses $$M_{\\mathrm{ICM}}$$ are obtained from the analysis of $Chandra$ X-ray observations, and the stellar masses $$M_{\\star}$$ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) $griz$ optical photometry and $WISE$ or $Spitzer$ near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past $$\\approx9$$ Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.« less

Baryon Content in a Sample of 91 Galaxy Clusters Selected by the South Pole Telescope at 0.2 < z < 1.25

NASA Astrophysics Data System (ADS)

Chiu, I.; Mohr, J. J.; McDonald, M.; Bocquet, S.; Desai, S.; Klein, M.; Israel, H.; Ashby, M. L. N.; Stanford, A.; Benson, B. A.; Brodwin, M.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Annis, J.; Bayliss, M.; Benoit-Lévy, A.; Bertin, E.; Bleem, L.; Brooks, D.; Buckley-Geer, E.; Bulbul, E.; Capasso, R.; Carlstrom, J. E.; Rosell, A. Carnero; Carretero, J.; Castander, F. J.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Davis, C.; Diehl, H. T.; Dietrich, J. P.; Doel, P.; Drlica-Wagner, A.; Eifler, T. F.; Evrard, A. E.; Flaugher, B.; García-Bellido, J.; Garmire, G.; Gaztanaga, E.; Gerdes, D. W.; Gonzalez, A.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gupta, N.; Gutierrez, G.; Hlavacek-L, J.; Honscheid, K.; James, D. J.; Jeltema, T.; Kraft, R.; Krause, E.; Kuehn, K.; Kuhlmann, S.; Kuropatkin, N.; Lahav, O.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Melchior, P.; Menanteau, F.; Miquel, R.; Murray, S.; Nord, B.; Ogando, R. L. C.; Plazas, A. A.; Rapetti, D.; Reichardt, C. L.; Romer, A. K.; Roodman, A.; Sanchez, E.; Saro, A.; Scarpine, V.; Schindler, R.; Schubnell, M.; Sharon, K.; Smith, R. C.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Stalder, B.; Stern, C.; Strazzullo, V.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Vikram, V.; Walker, A. R.; Weller, J.; Zhang, Y.

2018-05-01

We estimate total mass (M500), intracluster medium (ICM) mass (MICM) and stellar mass (M⋆) in a Sunyaev-Zel'dovich effect (SZE) selected sample of 91 galaxy clusters with masses M500 ≳ 2.5 × 1014M⊙ and redshift 0.2 < z < 1.25 from the 2500 ° ^2 South Pole Telescope SPT-SZ survey. The total masses M500 are estimated from the SZE observable, the ICM masses MICM are obtained from the analysis of Chandra X-ray observations, and the stellar masses M⋆ are derived by fitting spectral energy distribution templates to Dark Energy Survey (DES) griz optical photometry and WISE or Spitzer near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass and the cold baryonic fraction with cluster halo mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past ≈9 Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low density environment or field surrounding the parent halos, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called "missing baryons" outside cluster virial regions.

Molecular characterization and population structure study of cambuci: strategy for conservation and genetic improvement.

PubMed

Santos, D N; Nunes, C F; Setotaw, T A; Pio, R; Pasqual, M; Cançado, G M A

2016-12-19

Cambuci (Campomanesia phaea) belongs to the Myrtaceae family and is native to the Atlantic Forest of Brazil. It has ecological and social appeal but is exposed to problems associated with environmental degradation and expansion of agricultural activities in the region. Comprehensive studies on this species are rare, making its conservation and genetic improvement difficult. Thus, it is important to develop research activities to understand the current situation of the species as well as to make recommendations for its conservation and use. This study was performed to characterize the cambuci accessions found in the germplasm bank of Coordenadoria de Assistência Técnica Integral using inter-simple sequence repeat markers, with the goal of understanding the plant's population structure. The results showed the existence of some level of genetic diversity among the cambuci accessions that could be exploited for the genetic improvement of the species. Principal coordinate analysis and discriminant analysis clustered the 80 accessions into three groups, whereas Bayesian model-based clustering analysis clustered them into two groups. The formation of two cluster groups and the high membership coefficients within the groups pointed out the importance of further collection to cover more areas and more genetic variability within the species. The study also showed the lack of conservation activities; therefore, more attention from the appropriate organizations is needed to plan and implement natural and ex situ conservation activities.

New method for estimating clustering of DNA lesions induced by physical/chemical mutagens using fluorescence anisotropy.

PubMed

Akamatsu, Ken; Shikazono, Naoya; Saito, Takeshi

2017-11-01

We have developed a new method for estimating the localization of DNA damage such as apurinic/apyrimidinic sites (APs) on DNA using fluorescence anisotropy. This method is aimed at characterizing clustered DNA damage produced by DNA-damaging agents such as ionizing radiation and genotoxic chemicals. A fluorescent probe with an aminooxy group (AlexaFluor488) was used to label APs. We prepared a pUC19 plasmid with APs by heating under acidic conditions as a model for damaged DNA, and subsequently labeled the APs. We found that the observed fluorescence anisotropy (r obs ) decreases as averaged AP density (λ AP : number of APs per base pair) increases due to homo-FRET, and that the APs were randomly distributed. We applied this method to three DNA-damaging agents, 60 Co γ-rays, methyl methanesulfonate (MMS), and neocarzinostatin (NCS). We found that r obs -λ AP relationships differed significantly between MMS and NCS. At low AP density (λ AP  < 0.001), the APs induced by MMS seemed to not be closely distributed, whereas those induced by NCS were remarkably clustered. In contrast, the AP clustering induced by 60 Co γ-rays was similar to, but potentially more likely to occur than, random distribution. This simple method can be used to estimate mutagenicity of ionizing radiation and genotoxic chemicals. Copyright © 2017 Elsevier Inc. All rights reserved.

Ion-neutral Clustering of Bile Acids in Electrospray Ionization Across UPLC Flow Regimes

NASA Astrophysics Data System (ADS)

Brophy, Patrick; Broeckling, Corey D.; Murphy, James; Prenni, Jessica E.

2018-02-01

Bile acid authentic standards were used as model compounds to quantitatively evaluate complex in-source phenomenon on a UPLC-ESI-TOF-MS operated in the negative mode. Three different diameter columns and a ceramic-based microfluidic separation device were utilized, allowing for detailed descriptions of bile acid behavior across a wide range of flow regimes and instantaneous concentrations. A custom processing algorithm based on correlation analysis was developed to group together all ion signals arising from a single compound; these grouped signals produce verified compound spectra for each bile acid at each on-column mass loading. Significant adduction was observed for all bile acids investigated under all flow regimes and across a wide range of bile acid concentrations. The distribution of bile acid containing clusters was found to depend on the specific bile acid species, solvent flow rate, and bile acid concentration. Relative abundancies of each cluster changed non-linearly with concentration. It was found that summing all MS level (low collisional energy) ions and ion-neutral adducts arising from a single compound improves linearity across the concentration range (0.125-5 ng on column) and increases the sensitivity of MS level quantification. The behavior of each cluster roughly follows simple equilibrium processes consistent with our understanding of electrospray ionization mechanisms and ion transport processes occurring in atmospheric pressure interfaces. [Figure not available: see fulltext.