The cluster-cluster correlation function. [of galaxies
NASA Technical Reports Server (NTRS)
Postman, M.; Geller, M. J.; Huchra, J. P.
1986-01-01
The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.
Galaxy clusters and cold dark matter - A low-density unbiased universe?
NASA Technical Reports Server (NTRS)
Bahcall, Neta A.; Cen, Renyue
1992-01-01
Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.
Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.
Dornas, João V; Braun, Jochen
2018-01-15
Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morse, David C.
2006-10-15
Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules,more » and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of binary homopolymer blends and diblock copolymer melts.« less
Uncertainties in the cluster-cluster correlation function
NASA Astrophysics Data System (ADS)
Ling, E. N.; Frenk, C. S.; Barrow, J. D.
1986-12-01
The bootstrap resampling technique is applied to estimate sampling errors and significance levels of the two-point correlation functions determined for a subset of the CfA redshift survey of galaxies and a redshift sample of 104 Abell clusters. The angular correlation function for a sample of 1664 Abell clusters is also calculated. The standard errors in xi(r) for the Abell data are found to be considerably larger than quoted 'Poisson errors'. The best estimate for the ratio of the correlation length of Abell clusters (richness class R greater than or equal to 1, distance class D less than or equal to 4) to that of CfA galaxies is 4.2 + 1.4 or - 1.0 (68 percentile error). The enhancement of cluster clustering over galaxy clustering is statistically significant in the presence of resampling errors. The uncertainties found do not include the effects of possible systematic biases in the galaxy and cluster catalogs and could be regarded as lower bounds on the true uncertainty range.
NASA Astrophysics Data System (ADS)
Paust, Nathaniel E. Q.; Reid, I. Neill; Piotto, Giampaolo; Aparicio, Antonio; Anderson, Jay; Sarajedini, Ata; Bedin, Luigi R.; Chaboyer, Brian; Dotter, Aaron; Hempel, Maren; Majewski, Steven; Marín-Franch, A.; Milone, Antonino; Rosenberg, Alfred; Siegel, Michael
2010-02-01
We have used observations obtained as part of the Hubble Space Telescope/ACS Survey of Galactic Globular Clusters to construct global present-day mass functions for 17 globular clusters utilizing multi-mass King models to extrapolate from our observations to the global cluster behavior. The global present-day mass functions for these clusters are well matched by power laws from the turnoff, ≈0.8 M sun, to 0.2-0.3 M sun on the lower main sequence. The slopes of those power-law fits, α, have been correlated with an extensive set of intrinsic and extrinsic cluster properties to investigate which parameters may influence the form of the present-day mass function. We do not confirm previous suggestions of correlations between α and either metallicity or Galactic location. However, we do find a strong statistical correlation with the related parameters central surface brightness, μ V , and inferred central density, ρ0. The correlation is such that clusters with denser cores (stronger binding energy) tend to have steeper mass functions (a higher proportion of low-mass stars), suggesting that dynamical evolution due to external interactions may have played a key role in determining α. Thus, the present-day mass function may owe more to nurture than to nature. Detailed modeling of external dynamical effects is therefore a requisite for determining the initial mass function for Galactic globular clusters.
Clustering Coefficients for Correlation Networks.
Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu
2018-01-01
Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.
Clustering Coefficients for Correlation Networks
Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu
2018-01-01
Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714
Diametrical clustering for identifying anti-correlated gene clusters.
Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman
2003-09-01
Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.
Statistical indicators of collective behavior and functional clusters in gene networks of yeast
NASA Astrophysics Data System (ADS)
Živković, J.; Tadić, B.; Wick, N.; Thurner, S.
2006-03-01
We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.
The Correlation Function of Galaxy Clusters and Detection of Baryon Acoustic Oscillations
NASA Astrophysics Data System (ADS)
Hong, T.; Han, J. L.; Wen, Z. L.; Sun, L.; Zhan, H.
2012-04-01
We calculate the correlation function of 13,904 galaxy clusters of z <= 0.4 selected from the cluster catalog of Wen et al. The correlation function can be fitted with a power-law model ξ(r) = (r/R 0)-γ on the scales of 10 h -1 Mpc <= r <= 50 h -1 Mpc, with a larger correlation length of R 0 = 18.84 ± 0.27 h -1 Mpc for clusters with a richness of R >= 15 and a smaller length of R 0 = 16.15 ± 0.13 h -1 Mpc for clusters with a richness of R >= 5. The power-law index of γ = 2.1 is found to be almost the same for all cluster subsamples. A pronounced baryon acoustic oscillations (BAO) peak is detected at r ~ 110 h -1 Mpc with a significance of ~1.9σ. By analyzing the correlation function in the range of 20 h -1 Mpc <= r <= 200 h -1 Mpc, we find that the constraints on distance parameters are Dv (zm = 0.276) = 1077 ± 55(1σ) Mpc and h = 0.73 ± 0.039(1σ), which are consistent with the cosmology derived from Wilkinson Microwave Anisotropy Probe (WMAP) seven-year data. However, the BAO signal from the cluster sample is stronger than expected and leads to a rather low matter density Ω m h 2 = 0.093 ± 0.0077(1σ), which deviates from the WMAP7 result by more than 3σ. The correlation function of the GMBCG cluster sample is also calculated and our detection of the BAO feature is confirmed.
NASA Technical Reports Server (NTRS)
Ramella, Massimo; Geller, Margaret J.; Huchra, John P.
1990-01-01
The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.
Multi-particle correlations in transverse momenta from statistical clusters
NASA Astrophysics Data System (ADS)
Bialas, Andrzej; Bzdak, Adam
2016-09-01
We evaluate n-particle (n = 2 , 3 , 4 , 5) transverse momentum correlations for pions and kaons following from the decay of statistical clusters. These correlation functions could provide strong constraints on a possible existence of thermal clusters in the process of particle production.
On hierarchical solutions to the BBGKY hierarchy
NASA Technical Reports Server (NTRS)
Hamilton, A. J. S.
1988-01-01
It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.
NASA Technical Reports Server (NTRS)
Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.
1985-01-01
The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.
Higher order correlations of IRAS galaxies
NASA Technical Reports Server (NTRS)
Meiksin, Avery; Szapudi, Istvan; Szalay, Alexander
1992-01-01
The higher order irreducible angular correlation functions are derived up to the eight-point function, for a sample of 4654 IRAS galaxies, flux-limited at 1.2 Jy in the 60 microns band. The correlations are generally found to be somewhat weaker than those for the optically selected galaxies, consistent with the visual impression of looser clusters in the IRAS sample. It is found that the N-point correlation functions can be expressed as the symmetric sum of products of N - 1 two-point functions, although the correlations above the four-point function are consistent with zero. The coefficients are consistent with the hierarchical clustering scenario as modeled by Hamilton and by Schaeffer.
NASA Astrophysics Data System (ADS)
Baumgardt, H.; Hilker, M.
2018-05-01
We have determined masses, stellar mass functions and structural parameters of 112 Milky Way globular clusters by fitting a large set of N-body simulations to their velocity dispersion and surface density profiles. The velocity dispersion profiles were calculated based on a combination of more than 15,000 high-precision radial velocities which we derived from archival ESO/VLT and Keck spectra together with ˜20, 000 published radial velocities from the literature. Our fits also include the stellar mass functions of the globular clusters, which are available for 47 clusters in our sample, allowing us to self-consistently take the effects of mass segregation and ongoing cluster dissolution into account. We confirm the strong correlation between the global mass functions of globular clusters and their relaxation times recently found by Sollima & Baumgardt (2017). We also find a correlation of the escape velocity from the centre of a globular cluster and the fraction of first generation stars (FG) in the cluster recently derived for 57 globular clusters by Milone et al. (2017), but no correlation between the FG star fraction and the global mass function of a globular cluster. This could indicate that the ability of a globular cluster to keep the wind ejecta from the polluting star(s) is the crucial parameter determining the presence and fraction of second generation stars and not its later dynamical mass loss.
NASA Astrophysics Data System (ADS)
Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel
2018-05-01
We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.
NASA Astrophysics Data System (ADS)
Sridhar, Srivatsan; Maurogordato, Sophie; Benoist, Christophe; Cappi, Alberto; Marulli, Federico
2017-04-01
Context. The next generation of galaxy surveys will provide cluster catalogues probing an unprecedented range of scales, redshifts, and masses with large statistics. Their analysis should therefore enable us to probe the spatial distribution of clusters with high accuracy and derive tighter constraints on the cosmological parameters and the dark energy equation of state. However, for the majority of these surveys, redshifts of individual galaxies will be mostly estimated by multiband photometry which implies non-negligible errors in redshift resulting in potential difficulties in recovering the real-space clustering. Aims: We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to detect and measure the redshift and mass evolution of the correlation length r0 and of the bias parameter b(M,z) as a function of the uncertainty on the cluster redshift estimate. Methods: We calculate the correlation function for cluster sub-samples covering various mass and redshift bins selected from a 500 deg2 light-cone limited to H < 24. In order to simulate the distribution of clusters in photometric redshift space, we assign to each cluster a redshift randomly extracted from a Gaussian distribution having a mean equal to the cluster cosmological redshift and a dispersion equal to σz. The dispersion is varied in the range σ(z=0)=\\frac{σz{1+z_c} = 0.005,0.010,0.030} and 0.050, in order to cover the typical values expected in forthcoming surveys. The correlation function in real-space is then computed through estimation and deprojection of wp(rp). Four mass ranges (from Mhalo > 2 × 1013h-1M⊙ to Mhalo > 2 × 1014h-1M⊙) and six redshift slices covering the redshift range [0, 2] are investigated, first using cosmological redshifts and then for the four photometric redshift configurations. Results: From the analysis of the light-cone in cosmological redshifts we find a clear increase of the correlation amplitude as a function of redshift and mass. The evolution of the derived bias parameter b(M,z) is in fair agreement with theoretical expectations. We calculate the r0-d relation up to our highest mass, highest redshift sample tested (z = 2,Mhalo > 2 × 1014h-1M⊙). From our pilot sample limited to Mhalo > 5 × 1013h-1M⊙(0.4 < z < 0.7), we find that the real-space correlation function can be recovered by deprojection of wp(rp) within an accuracy of 5% for σz = 0.001 × (1 + zc) and within 10% for σz = 0.03 × (1 + zc). For higher dispersions (besides σz > 0.05 × (1 + zc)), the recovery becomes noisy and difficult. The evolution of the correlation in redshift and mass is clearly detected for all σz tested, but requires a large binning in redshift to be detected significantly between individual redshift slices when increasing σz. The best-fit parameters (r0 and γ) as well as the bias obtained from the deprojection method for all σz are within the 1σ uncertainty of the zc sample.
From Head to Sword: The Clustering Properties of Stars in Orion
NASA Astrophysics Data System (ADS)
Gomez, Mercedes; Lada, Charles J.
1998-04-01
We investigate the structure in the spatial distributions of optically selected samples of young stars in the Head (lambda Orionis) and in the Sword (Orion A) regions of the constellation of Orion with the aid of stellar surface density maps and the two-point angular correlation function. The distributions of young stars in both regions are found to be nonrandom and highly clustered. Stellar surface density maps reveal three distinct clusters in the lambda Ori region. The two-point correlation function displays significant features at angular scales that correspond to the radii and separations of the three clusters identified in the surface density maps. Most young stars in the lambda Ori region (~80%) are presently found within these three clusters, consistent with the idea that the majority of young stars in this region were formed in dense protostellar clusters that have significantly expanded since their formation. Over a scale of ~0.05d-0.5d the correlation function is well described by a single power law that increases smoothly with decreasing angular scale. This suggests that, within the clusters, the stars either are themselves hierarchically clustered or have a volume density distribution that falls steeply with radius. The relative lack of Hα emission-line stars in the one cluster in this region that contains OB stars suggests a timescale for emission-line activity of less than 4 Myr around late-type stars in the cluster and may indicate that the lifetimes of protoplanetary disks around young stellar objects are reduced in clusters containing O stars. The spatial distribution of young stars in the Orion A region is considerably more complex. The angular correlation function of the OB stars (which are mostly foreground to the Orion A molecular cloud) is very similar to that of the Hα stars (which are located mostly within the molecular cloud) and significantly different from that of the young stars in the lambda Ori region. This suggests that, although spatially separated, both populations in the Orion A region may have originated from a similar fragmentation process. Stellar surface density maps and modeling of the angular correlation function suggest that somewhat less than half of the OB and Hα stars in the Orion A cloud are presently within well-defined stellar clusters. Although all the OB stars could have originated in rich clusters, a significant fraction of the Hα stars appear to have formed outside such clusters in a more spatially dispersed manner. The close similarity of the angular correlation functions of the OB and Hα stars toward the molecular cloud, in conjunction with the earlier indications of a relatively high star formation rate and high gas pressure in this cloud, is consistent with the idea that older, foreground OB stars triggered the current episode of star formation in the Orion A cloud. One of the OB clusters (Upper Sword) that is foreground to the cloud does not appear to be associated with any of the clusterings of emission-line stars, again suggesting a timescale (<4 Myr) for emission-line activity and disk lifetimes around late-type stars born in OB clusters.
Veatch, Sarah L.; Machta, Benjamin B.; Shelby, Sarah A.; Chiang, Ethan N.; Holowka, David A.; Baird, Barbara A.
2012-01-01
We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins. PMID:22384026
Peculiar velocity effect on galaxy correlation functions in nonlinear clustering regime
NASA Astrophysics Data System (ADS)
Matsubara, Takahiko
1994-03-01
We studied the distortion of the apparent distribution of galaxies in redshift space contaminated by the peculiar velocity effect. Specifically we obtained the expressions for N-point correlation functions in redshift space with given functional form for velocity distribution f(v) and evaluated two- and three-point correlation functions quantitatively. The effect of velocity correlations is also discussed. When the two-point correlation function in real space has a power-law form, Xir(r) is proportional to r(-gamma), the redshift-space counterpart on small scales also has a power-law form but with an increased power-law index: Xis(s) is proportional to s(1-gamma). When the three-point correlation function has the hierarchical form and the two-point correlation function has the power-law form in real space, the hierarchical form of the three-point correlation function is almost preserved in redshift space. The above analytic results are compared with the direct analysis based on N-body simulation data for cold dark matter models. Implications on the hierarchical clustering ansatz are discussed in detail.
NASA Technical Reports Server (NTRS)
Mcclelland, J.; Silk, J.
1978-01-01
Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.
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…
Brain structure and function correlates of cognitive subtypes in schizophrenia.
Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan
2015-10-30
Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.
2017-01-01
Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422
Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S
2017-04-01
Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.
Micro-heterogeneity versus clustering in binary mixtures of ethanol with water or alkanes.
Požar, Martina; Lovrinčević, Bernarda; Zoranić, Larisa; Primorać, Tomislav; Sokolić, Franjo; Perera, Aurélien
2016-08-24
Ethanol is a hydrogen bonding liquid. When mixed in small concentrations with water or alkanes, it forms aggregate structures reminiscent of, respectively, the direct and inverse micellar aggregates found in emulsions, albeit at much smaller sizes. At higher concentrations, micro-heterogeneous mixing with segregated domains is found. We examine how different statistical methods, namely correlation function analysis, structure factor analysis and cluster distribution analysis, can describe efficiently these morphological changes in these mixtures. In particular, we explain how the neat alcohol pre-peak of the structure factor evolves into the domain pre-peak under mixing conditions, and how this evolution differs whether the co-solvent is water or alkane. This study clearly establishes the heuristic superiority of the correlation function/structure factor analysis to study the micro-heterogeneity, since cluster distribution analysis is insensitive to domain segregation. Correlation functions detect the domains, with a clear structure factor pre-peak signature, while the cluster techniques detect the cluster hierarchy within domains. The main conclusion is that, in micro-segregated mixtures, the domain structure is a more fundamental statistical entity than the underlying cluster structures. These findings could help better understand comparatively the radiation scattering experiments, which are sensitive to domains, versus the spectroscopy-NMR experiments, which are sensitive to clusters.
Clustering in the SDSS Redshift Survey
NASA Astrophysics Data System (ADS)
Zehavi, I.; Blanton, M. R.; Frieman, J. A.; Weinberg, D. H.; SDSS Collaboration
2002-05-01
We present measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our current sample consists of roughly 80,000 galaxies with redshifts in the range 0.02 < z < 0.2, covering about 1200 square degrees. We measure the clustering in redshift space and in real space. The two-dimensional correlation function ξ (rp,π ) shows clear signatures of redshift distortions, both the small-scale ``fingers-of-God'' effect and the large-scale compression. The inferred real-space correlation function is well described by a power law. The SDSS is especially suitable for investigating the dependence of clustering on galaxy properties, due to the wealth of information in the photometric survey. We focus on the dependence of clustering on color and on luminosity.
Derivation of the density functional theory from the cluster expansion.
Hsu, J Y
2003-09-26
The density functional theory is derived from a cluster expansion by truncating the higher-order correlations in one and only one term in the kinetic energy. The formulation allows self-consistent calculation of the exchange correlation effect without imposing additional assumptions to generalize the local density approximation. The pair correlation is described as a two-body collision of bound-state electrons, and modifies the electron- electron interaction energy as well as the kinetic energy. The theory admits excited states, and has no self-interaction energy.
RNA Polymerase II cluster dynamics predict mRNA output in living cells
Cho, Won-Ki; Jayanth, Namrata; English, Brian P; Inoue, Takuma; Andrews, J Owen; Conway, William; Grimm, Jonathan B; Spille, Jan-Hendrik; Lavis, Luke D; Lionnet, Timothée; Cisse, Ibrahim I
2016-01-01
Protein clustering is a hallmark of genome regulation in mammalian cells. However, the dynamic molecular processes involved make it difficult to correlate clustering with functional consequences in vivo. We developed a live-cell super-resolution approach to uncover the correlation between mRNA synthesis and the dynamics of RNA Polymerase II (Pol II) clusters at a gene locus. For endogenous β-actin genes in mouse embryonic fibroblasts, we observe that short-lived (~8 s) Pol II clusters correlate with basal mRNA output. During serum stimulation, a stereotyped increase in Pol II cluster lifetime correlates with a proportionate increase in the number of mRNAs synthesized. Our findings suggest that transient clustering of Pol II may constitute a pre-transcriptional regulatory event that predictably modulates nascent mRNA output. DOI: http://dx.doi.org/10.7554/eLife.13617.001 PMID:27138339
Krause, Kathrin; Kopp, Benjamin T; Tazi, Mia F; Caution, Kyle; Hamilton, Kaitlin; Badr, Asmaa; Shrestha, Chandra; Tumin, Dmitry; Hayes, Don; Robledo-Avila, Frank; Hall-Stoodley, Luanne; Klamer, Brett G; Zhang, Xiaoli; Partida-Sanchez, Santiago; Parinandi, Narasimham L; Kirkby, Stephen E; Dakhlallah, Duaa; McCoy, Karen S; Cormet-Boyaka, Estelle; Amer, Amal O
2018-07-01
Cystic fibrosis (CF) is a multi-organ disorder characterized by chronic sino-pulmonary infections and inflammation. Many patients with CF suffer from repeated pulmonary exacerbations that are predictors of worsened long-term morbidity and mortality. There are no reliable markers that associate with the onset or progression of an exacerbation or pulmonary deterioration. Previously, we found that the Mirc1/Mir17-92a cluster which is comprised of 6 microRNAs (Mirs) is highly expressed in CF mice and negatively regulates autophagy which in turn improves CF transmembrane conductance regulator (CFTR) function. Therefore, here we sought to examine the expression of individual Mirs within the Mirc1/Mir17-92 cluster in human cells and biological fluids and determine their role as biomarkers of pulmonary exacerbations and response to treatment. Mirc1/Mir17-92 cluster expression was measured in human CF and non-CF plasma, blood-derived neutrophils, and sputum samples. Values were correlated with pulmonary function, exacerbations and use of CFTR modulators. Mirc1/Mir17-92 cluster expression was not significantly elevated in CF neutrophils nor plasma when compared to the non-CF cohort. Cluster expression in CF sputum was significantly higher than its expression in plasma. Elevated CF sputum Mirc1/Mir17-92 cluster expression positively correlated with pulmonary exacerbations and negatively correlated with lung function. Patients with CF undergoing treatment with the CFTR modulator Ivacaftor/Lumacaftor did not demonstrate significant change in the expression Mirc1/Mir17-92 cluster after six months of treatment. Mirc1/Mir17-92 cluster expression is a promising biomarker of respiratory status in patients with CF including pulmonary exacerbation. Published by Elsevier B.V.
NASA Astrophysics Data System (ADS)
Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias
2007-11-01
The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Møller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.
Santra, Biswajit; Michaelides, Angelos; Scheffler, Matthias
2007-11-14
The ability of several density-functional theory (DFT) exchange-correlation functionals to describe hydrogen bonds in small water clusters (dimer to pentamer) in their global minimum energy structures is evaluated with reference to second order Moller-Plesset perturbation theory (MP2). Errors from basis set incompleteness have been minimized in both the MP2 reference data and the DFT calculations, thus enabling a consistent systematic evaluation of the true performance of the tested functionals. Among all the functionals considered, the hybrid X3LYP and PBE0 functionals offer the best performance and among the nonhybrid generalized gradient approximation functionals, mPWLYP and PBE1W perform best. The popular BLYP and B3LYP functionals consistently underbind and PBE and PW91 display rather variable performance with cluster size.
Symptom clusters in patients with high-grade glioma.
Fox, Sherry W; Lyon, Debra; Farace, Elana
2007-01-01
To describe the co-occurring symptoms (depression, fatigue, pain, sleep disturbance, and cognitive impairment), quality of life (QoL), and functional status in patients with high-grade glioma. Correlational, descriptive study of 73 participants with high-grade glioma in the U.S. Nine brief measures were obtained with a mailed survey. Participants were recruited from the online message board of The Healing Exchange BRAIN TRUST, a nonprofit organization dedicated to improving quality of life for people with brain tumors. Two symptom cluster models were examined. Four co-occurring symptoms were significantly correlated with each other and explained 29% of the variance in QoL: depression, fatigue, sleep disturbance, and cognitive impairment. Depression, fatigue, sleep disturbance, cognitive impairment, and pain were significantly correlated with each other and explained 62% of the variance in functional status. The interrelationships of the symptoms examined in this study and their relationships with QoL and functional status meet the criteria for defining a symptom cluster. The differences in the models of QoL and functional status indicates that symptom clusters may have unique characteristics in patients with gliomas.
Long-Range Near-Side Angular Correlations in Proton-Proton Interactions in CMS.
None
2017-12-09
The CMS Collaboration Results on two-particle angular correlations for charged particles emitted in proton-proton collisions at center of mass energies of 0.9, 2.36 and 7TeV over a broad range of pseudorapidity (?) and azimuthal angle (f) are presented using data collected with the CMS detector at the LHC. Short-range correlations in ??, which are studied in minimum bias events, are characterized using a simple independent cluster parameterization in order to quantify their strength (cluster size) and their extent in ? (cluster decay width). Long-range azimuthal correlations are studied more differentially as a function of charged particle multiplicity and particle transverse momentum using a 980nb-1 data set at 7TeV. In high multiplicity events, a pronounced structure emerges in the two-dimensional correlation function for particles in intermediate pTâs of 1-3GeV/c, 2.0< |??|<4.8 and ?fË0. This is the ?rst observation of such a ridge-like feature in two-particle correlation functions in pp or p-pbar collisions. EVO Universe, password "seminar"; Phone Bridge ID: 2330444 Password: 5142
Microscopic Electron Variations Measured Simultaneously By The Cluster Spacecraft
NASA Astrophysics Data System (ADS)
Buckley, A. M.; Carozzi, T. D.; Gough, M. P.; Beloff, N.
Data is used from the Particle Correlator experiments running on each of the four Cluster spacecraft so as to determine common microscopic behaviour in the elec- tron population observed over the macroscopic Cluster separations. The Cluster par- ticle correlator experiments operate by forming on board Auto Correlation Functions (ACFs) generated from short time series of electron counts obtained, as a function of electron energy, from the PEACE HEEA sensor. The information on the microscopic variation of the electron flux covers the frequency range DC up to 41 kHz (encom- passing typical electron plasma frequencies and electron gyro frequencies and their harmonics), the electron energy range is that covered by the PEACE HEEA sensor (within the range 1 eV to 26 keV). Results are presented of coherent electron struc- tures observed simultaneously by the four spacecraft in the differing plasma interac- tion regions and boundaries encountered by Cluster. As an aid to understanding the plasma interactions, use is made of numerical simulations which model both the un- derlying statistical properties of the electrons and also the manner in which particle correlator experiments operate.
NASA Astrophysics Data System (ADS)
Koitz, Ralph; Soini, Thomas M.; Genest, Alexander; Trickey, S. B.; Rösch, Notker
2012-07-01
The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pdn with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Aun (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.
NASA Technical Reports Server (NTRS)
Mushotzky, R. F.; Serlemitsos, P. J.; Smith, B. W.; Boldt, E. A.; Holt, S. S.
1978-01-01
OSO-8 X-ray spectra from 2 to 20 keV were analyzed for 26 clusters of galaxies. Temperature, emission integrals, iron abundances, and low energy absorption measurements are given. Eight clusters have positive iron emission line detections at the 90% confidence level, and all twenty cluster spectra are consistent with Fe/H=0.000014 by number with the possible exception of Virgo. Physical correlations between X-ray spectral parameters and other cluster properties are examined. It is found that: (1) the X-ray temperature is approximately proportional to the square of the velocity dispersion of the galaxies; (2) the emission integral and therefore the bolometric X-ray luminosity is a strong function of the X-ray temperature; (3) the X-ray temperature and emission integral are better correlated with cluster central galaxy density than with richness; (4) temperature and emission integral are separately correlated with Rood-Sastry type; and (5) the fraction of galaxies which are spirals is correlated with the observed ram pressure in the cluster core.
Dispersion- and Exchange-Corrected Density Functional Theory for Sodium Ion Hydration.
Soniat, Marielle; Rogers, David M; Rempe, Susan B
2015-07-14
A challenge in density functional theory is developing functionals that simultaneously describe intermolecular electron correlation and electron delocalization. Recent exchange-correlation functionals address those two issues by adding corrections important at long ranges: an atom-centered pairwise dispersion term to account for correlation and a modified long-range component of the electron exchange term to correct for delocalization. Here we investigate how those corrections influence the accuracy of binding free energy predictions for sodium-water clusters. We find that the dual-corrected ωB97X-D functional gives cluster binding energies closest to high-level ab initio methods (CCSD(T)). Binding energy decomposition shows that the ωB97X-D functional predicts the smallest ion-water (pairwise) interaction energy and larger multibody contributions for a four-water cluster than most other functionals - a trend consistent with CCSD(T) results. Also, ωB97X-D produces the smallest amounts of charge transfer and the least polarizable waters of the density functionals studied, which mimics the lower polarizability of CCSD. When compared with experimental binding free energies, however, the exchange-corrected CAM-B3LYP functional performs best (error <1 kcal/mol), possibly because of its parametrization to experimental formation enthalpies. For clusters containing more than four waters, "split-shell" coordination must be considered to obtain accurate free energies in comparison with experiment.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.
Perhaps the most important approximations to the electronic structure problem in quantum chemistry are those based on coupled cluster and density functional theories. Coupled cluster theory has been called the ``gold standard'' of quantum chemistry due to the high accuracy that it achieves for weakly correlated systems. Kohn-Sham density functionals based on semilocal approximations are, without a doubt, the most widely used methods in chemistry and material science because of their high accuracy/cost ratio. The root of the success of coupled cluster and density functionals is their ability to efficiently describe the dynamic part of the electron correlation. However, both traditional coupled cluster and density functional approximations may fail catastrophically when substantial static correlation is present. This severely limits the applicability of these methods to a plethora of important chemical and physical problems such as, e.g., the description of bond breaking, transition states, transition metal-, lanthanide- and actinide-containing compounds, and superconductivity. In an attempt to tackle this problem, nonstandard (single-reference) coupled cluster-based techniques that aim to describe static correlation have been recently developed: pair coupled cluster doubles (pCCD) and singlet-paired coupled cluster doubles (CCD0). The ability to describe static correlation in pCCD and CCD0 comes, however, at the expense of important amounts of dynamic correlation so that the high accuracy of standard coupled cluster becomes unattainable. Thus, the reliable and efficient description of static and dynamic correlation in a simultaneous manner remains an open problem for quantum chemistry and many-body theory in general. In this thesis, different ways to combine pCCD and CCD0 with density functionals in order to describe static and dynamic correlation simultaneously (and efficiently) are explored. The combination of wavefunction and density functional methods has a long history in quantum chemistry (practical implementations have appeared in the literature since the 1970s). However, this kind of techniques have not achieved widespread use due to problems such as double counting of correlation and the symmetry dilemma--the fact that wavefunction methods respect the symmetries of Hamiltonian, while modern functionals are designed to work with broken symmetry densities. Here, particular mathematical features of pCCD and CCD0 are exploited to avoid these problems in an efficient manner. The two resulting families of approximations, denoted as pCCD+DFT and CCD0+DFT, are shown to be able to describe static and dynamic correlation in standard benchmark calculations. Furthermore, it is also shown that CCD0+DFT lends itself to combination with correlation from the direct random phase approximation (dRPA). Inclusion of dRPA in the long-range via the technique of range-separation allows for the description of dispersion correlation, the remaining part of the correlation. Thus, when combined with the dRPA, CCD0+DFT can account for all three-types of electron correlation that are necessary to accurately describe molecular systems. Lastly, applications of CCD0+DFT to actinide chemistry are considered in this work. The accuracy of CCD0+DFT for predicting equilibrium geometries and vibrational frequencies of actinide molecules and ions is assessed and compared to that of well-established quantum chemical methods. For this purpose, the f0 actinyl series (UO2 2+, NpO 23+, PuO24+, the isoelectronic NUN, and Thorium (ThO, ThO2+) and Nobelium (NoO, NoO2) oxides are studied. It is shown that the CCD0+DFT description of these species agrees with available experimental data and is comparable with the results given by the highest-level calculations that are possible for such heavy compounds while being, at least, an order of magnitude lower in computational cost.
NASA Astrophysics Data System (ADS)
Hincks, Adam D.; Hajian, Amir; Addison, Graeme E.
2013-05-01
We cross-correlate the 100 μm Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40σ. The cross-spectrum, which arises from the spatial correlation between unresolved dusty galaxies that make up the cosmic infrared background (CIB) in the IRIS map and the galaxy clusters, is well-fit by a single power law with an index of -1.28±0.12, similar to the clustering of unresolved galaxies from cross-correlating far-infrared and submillimetre maps at longer wavelengths. Using a recent, phenomenological model for the spectral and clustering properties of the IRIS galaxies, we constrain the large-scale bias of the maxBCG clusters to be 2.6±1.4, consistent with existing analyses of the real-space cluster correlation function. The success of our method suggests that future CIB-optical cross-correlations using Planck and Herschel data will significantly improve our understanding of the clustering and redshift distribution of the faint CIB sources.
Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure
Skvortsova, Elena B.; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779
Universal spatial correlation functions for describing and reconstructing soil microstructure.
Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.
Spectral analysis of pair-correlation bandwidth: application to cell biology images.
Binder, Benjamin J; Simpson, Matthew J
2015-02-01
Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.
Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.
Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino
2017-01-10
In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.
Bose--Einstein Correlations and Thermal Cluster Formation in High-energy Collisions
NASA Astrophysics Data System (ADS)
Bialas, A.; Florkowski, W.; Zalewski, K.
The blast wave model is generalized to include the production of thermal clusters, as suggested by the apparent success of the statistical model of particle production at high energies. The formulae for the HBT correlation functions and the corresponding HBT radii are derived.
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.
Evidence for biasing in the CfA survey
NASA Technical Reports Server (NTRS)
Hamilton, A. J. S.
1988-01-01
Intrinsically bright galaxies appear systematically more correlated than faint galaxies in the Center for Astrophysics redshift survey. The amplification of the two-point correlation function behaves exponentially with luminosity, being essentially flat up to the knee of the luminosity function, then increasing markedly. The amplification reaches a factor of 3.5e + or - 0.4 in the very brightest galaxies. The effect is dominated by spirals rather than ellipticals, so that the correlation function of bright spirals becomes comparable to that of normal ellipticals. Similar results are obtained whether the correlation function is measured in two or three dimensions. The effect persists to separations of a correlation length or more, and is not confined to the cores of the Virgo, Coma, and Abell 1367 clusters, suggesting that the effect is caused by biasing, that is, galaxies kindle preferentially in more clustered regions, rather than by gravitational relaxation.
Thermodynamically accessible titanium clusters TiN, N = 2-32.
Lazauskas, Tomas; Sokol, Alexey A; Buckeridge, John; Catlow, C Richard A; Escher, Susanne G E T; Farrow, Matthew R; Mora-Fonz, David; Blum, Volker W; Phaahla, Tshegofatso M; Chauke, Hasani R; Ngoepe, Phuti E; Woodley, Scott M
2018-05-10
We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area. The results suggest a growth mechanism that is based on forming coordination centres by interpenetrating icosahedra, icositetrahedra and Frank-Kasper polyhedra. We identify centres of coordination, which act as centres of bulk nucleation in medium sized clusters and determine the morphological features of the cluster.
R package to estimate intracluster correlation coefficient with confidence interval for binary data.
Chakraborty, Hrishikesh; Hossain, Akhtar
2018-03-01
The Intracluster Correlation Coefficient (ICC) is a major parameter of interest in cluster randomized trials that measures the degree to which responses within the same cluster are correlated. There are several types of ICC estimators and its confidence intervals (CI) suggested in the literature for binary data. Studies have compared relative weaknesses and advantages of ICC estimators as well as its CI for binary data and suggested situations where one is advantageous in practical research. The commonly used statistical computing systems currently facilitate estimation of only a very few variants of ICC and its CI. To address the limitations of current statistical packages, we developed an R package, ICCbin, to facilitate estimating ICC and its CI for binary responses using different methods. The ICCbin package is designed to provide estimates of ICC in 16 different ways including analysis of variance methods, moments based estimation, direct probabilistic methods, correlation based estimation, and resampling method. CI of ICC is estimated using 5 different methods. It also generates cluster binary data using exchangeable correlation structure. ICCbin package provides two functions for users. The function rcbin() generates cluster binary data and the function iccbin() estimates ICC and it's CI. The users can choose appropriate ICC and its CI estimate from the wide selection of estimates from the outputs. The R package ICCbin presents very flexible and easy to use ways to generate cluster binary data and to estimate ICC and it's CI for binary response using different methods. The package ICCbin is freely available for use with R from the CRAN repository (https://cran.r-project.org/package=ICCbin). We believe that this package can be a very useful tool for researchers to design cluster randomized trials with binary outcome. Copyright © 2017 Elsevier B.V. All rights reserved.
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.
Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J
2008-06-18
Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Campa, Julia; Estrada, Juan; Flaugher, Brenna
2017-02-03
The knowledge of the scatter in the mass-observable relation is a key ingredient for a cosmological analysis based on galaxy clusters in a photometric survey. We demonstrate here how the linear bias measured in the correlation function for clusters can be used to determine the value of the scatter. The new method is tested in simulations of a 5.000 square degrees optical survey up to z~1, similar to the ongoing Dark Energy Survey. The results indicate that the scatter can be measured with a precision of 5% using this technique.
NASA Technical Reports Server (NTRS)
Hamilton, A. J. S.; Matthews, Alex; Kumar, P.; Lu, Edward
1991-01-01
It was discovered that the nonlinear evolution of the two point correlation function in N-body experiments of galaxy clustering with Omega = 1 appears to be described to good approximation by a simple general formula. The underlying form of the formula is physically motivated, but its detailed representation is obtained empirically by fitting to N-body experiments. In this paper, the formula is presented along with an inverse formula which converts a final, nonlinear correlation function into the initial linear correlation function. The inverse formula is applied to observational data from the CfA, IRAs, and APM galaxy surveys, and the initial spectrum of fluctuations of the universe, if Omega = 1.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Papastergis, Emmanouil; Giovanelli, Riccardo; Haynes, Martha P.
We use a sample of ≈6000 galaxies detected by the Arecibo Legacy Fast ALFA (ALFALFA) 21 cm survey to measure the clustering properties of H I-selected galaxies. We find no convincing evidence for a dependence of clustering on galactic atomic hydrogen (H I) mass, over the range M{sub H{sub I}} ≈ 10{sup 8.5}-10{sup 10.5} M{sub ☉}. We show that previously reported results of weaker clustering for low H I mass galaxies are probably due to finite-volume effects. In addition, we compare the clustering of ALFALFA galaxies with optically selected samples drawn from the Sloan Digital Sky Survey (SDSS). We findmore » that H I-selected galaxies cluster more weakly than even relatively optically faint galaxies, when no color selection is applied. Conversely, when SDSS galaxies are split based on their color, we find that the correlation function of blue optical galaxies is practically indistinguishable from that of H I-selected galaxies. At the same time, SDSS galaxies with red colors are found to cluster significantly more than H I-selected galaxies, a fact that is evident in both the projected as well as the full two-dimensional correlation function. A cross-correlation analysis further reveals that gas-rich galaxies 'avoid' being located within ≈3 Mpc of optical galaxies with red colors. Next, we consider the clustering properties of halo samples selected from the Bolshoi ΛCDM simulation. A comparison with the clustering of ALFALFA galaxies suggests that galactic H I mass is not tightly related to host halo mass and that a sizable fraction of subhalos do not host H I galaxies. Lastly, we find that we can recover fairly well the correlation function of H I galaxies by just excluding halos with low spin parameter. This finding lends support to the hypothesis that halo spin plays a key role in determining the gas content of galaxies.« less
Kesler, Shelli R; Adams, Marjorie; Packer, Melissa; Rao, Vikram; Henneghan, Ashley M; Blayney, Douglas W; Palesh, Oxana
2017-03-01
Several previous studies have demonstrated that cancer chemotherapy is associated with brain injury and cognitive dysfunction. However, evidence suggests that cancer pathogenesis alone may play a role, even in non-CNS cancers. Using a multimodal neuroimaging approach, we measured structural and functional connectome topology as well as functional network dynamics in newly diagnosed patients with breast cancer. Our study involved a novel, pretreatment assessment that occurred prior to the initiation of any cancer therapies, including surgery with anesthesia. We enrolled 74 patients with breast cancer age 29-65 and 50 frequency-matched healthy female controls who underwent anatomic and resting-state functional MRI as well as cognitive testing. Compared to controls, patients with breast cancer demonstrated significantly lower functional network dynamics ( p = .046) and cognitive functioning ( p < .02, corrected). The breast cancer group also showed subtle alterations in structural local clustering and functional local clustering ( p < .05, uncorrected) as well as significantly increased correlation between structural global clustering and functional global clustering compared to controls ( p = .03). This hyper-correlation between structural and functional topologies was significantly associated with cognitive dysfunction ( p = .005). Our findings could not be accounted for by psychological distress and suggest that non-CNS cancer may directly and/or indirectly affect the brain via mechanisms such as tumor-induced neurogenesis, inflammation, and/or vascular changes, for example. Our results also have broader implications concerning the importance of the balance between structural and functional connectome properties as a potential biomarker of general neurologic deficit.
Investigation of the 9B nucleus and its cluster-nucleon correlations
NASA Astrophysics Data System (ADS)
Zhao, Qing; Ren, Zhongzhou; Lyu, Mengjiao; Horiuchi, Hisashi; Funaki, Yasuro; Röpke, Gerd; Schuck, Peter; Tohsaki, Akihiro; Xu, Chang; Yamada, Taiichi; Zhou, Bo
2018-05-01
In order to study the correlations between clusters and nucleons in light nuclei, we formulate a new superposed Tohsaki-Horiuchi-Schuck-Röpke (THSR) wave function which describes both spatially large spreading and cluster-correlated dynamics of valence nucleons. Using this new THSR wave function, the binding energy of 9B is significantly improved in comparison with our previous studies. We calculate the excited states of 9B and obtain an energy spectrum of 9B which is consistent with the experimental results. This includes the prediction of the first 1 /2+ excited state of 9B which is not yet fixed experimentally. We study the proton dynamics in 9B and find that the cluster-proton correlation plays an essential role for the proton dynamics in the ground state of 9B. Furthermore, we discuss the density distribution of the valence proton with special attention to its tail structure. Finally, the resonance nature of excited states of 9B is illustrated comparing root-mean-square radii between the ground and excited states.
Halo correlations in nonlinear cosmic density fields
NASA Astrophysics Data System (ADS)
Bernardeau, F.; Schaeffer, R.
1999-09-01
The question we address in this paper is the determination of the correlation properties of the dark matter halos appearing in cosmic density fields once they underwent a strongly nonlinear evolution induced by gravitational dynamics. A series of previous works have given indications that kind of non-Gaussian features are induced by nonlinear evolution in term of the high-order correlation functions. Assuming such patterns for the matter field, i.e. that the high-order correlation functions behave as products of two-body correlation functions, we derive the correlation properties of the halos, that are assumed to represent the correlation properties of galaxies or clusters. The hierarchical pattern originally induced by gravity is shown to be conserved for the halos. The strength of their correlations at any order varies, however, but is found to depend only on their internal properties, namely on the parameter x~ m/r(3-gamma ) where m is the mass of the halo, r its size and gamma is the power law index of the two-body correlation function. This internal parameter is seen to be close to the depth of the internal potential well of virialized objects. We were able to derive the explicit form of the generating function of the moments of the halo counts probability distribution function. In particular we show explicitly that, generically, S_P(x)-> P(P-2) in the rare halo limit. Various illustrations of our general results are presented. As a function of the properties of the underlying matter field, we construct the count probabilities for halos and in particular discuss the halo void probability. We evaluate the dependence of the halo mass function on the environment: within clusters, hierarchical clustering implies the higher masses are favored. These properties solely arise from what is a natural bias (ie, naturally induced by gravity) between the observed objects and the unseen matter field, and how it manifests itself depending on which selection effects are imposed.
NASA Astrophysics Data System (ADS)
Świetoń, Agnieszka; Pollo, Agnieszka; VVDS Team
2014-12-01
We discuss the dependence of galaxy clustering according to their colours up to z˜ 1.2. For that purpose we used one of the wide fields (F22) from the VIMOS-VLT Deep Survey (VVDS). For galaxies with absolute luminosities close to the characteristic Schechter luminosities M^* at a given redshift, we measured the projected two-point correlation function w_{p}(r_{p}) and we estimated the best-fit parameters for a single power-law model: ξ(r) = (r/r_0)^{-γ} , where r_0 is the correlation length and γ is the slope of correlation function. Our results show that red galaxies exhibit the strongest clustering in all epochs up to z˜ 1.2. Green valley represents the "intermediate" population and blue cloud shows the weakest clustering strength. We also compared the shape of w_p(r_p) for different galaxy populations. All three populations have different clustering properties on the small scales, similarly to the behaviour observed in the local catalogues.
Herschel-ATLAS: The Angular Correlation Function of Submillimetre Galaxies at High and Low Redshift
NASA Technical Reports Server (NTRS)
Maddox, S. J.; Dunne, L.; Rigby, E.; Eales, S.; Cooray, A.; Scott, D.; Peacock, J. A.; Negrello, M.; Smith, D. J. B.; Benford, D.;
2010-01-01
We present measurements of the angular correlation function of galaxies selected from the first field of the H-ATLAS survey. Careful removal of the background from galactic cirrus is essential, and currently dominates the uncertainty in our measurements. For our 250 micrometer-selected sample we detect no significant clustering, consistent with the expectation that the 250 pm-selected sources are mostly normal galaxies at z < or equal to 1. For our 350 micrometer and 500 micrometer-selected samples we detect relatively strong clustering with correlation amplitudes A of 0.2 and 1.2 at 1', but with relatively large uncertainties. For samples which preferentially select high redshift galaxies at z approx. 2-3 we detect significant strong clustering, leading to an estimate of r(0) approx. 7-11/h Mpc. The slope of our clustering measurements is very steep. delta approx. 2. The measurements are consistent with the idea that sub-mm sources consist of a low redshift population of normal galaxies and a high redshift population of highly clustered star-bursting galaxies.
Low-luminosity stellar mass functions in globular clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richer, H.B.; Fahlman, G.G.; Buonanno, R.
New data are presented on cluster luminosity functions and mass functions for selected fields in the globular clusters M13 and M71, extending down the main sequence to at least 0.2 solar mass. In this experiment, CCD photometry data were obtained at the prime focus of the CFHT on the cluster fields that were far from the cluster center. Luminosity functions were constructed, using the ADDSTAR routine to correct for the background, and mass functions were derived using the available models. The mass functions obtained for M13 and M71 were compared to existing data for NGC 6397. Results show that (1)more » all three globular clusters display a marked change in slope at about 0.4 solar mass, with the slopes becoming considerably steeper toward lower masses; (2) there is no correlation between the slope of the mass function and metallicity; and (3) the low-mass slope of the mass function for M13 is much steeper than for NGC 6397 and M71. 22 refs.« less
NASA Technical Reports Server (NTRS)
Mushotzky, R. F.; Serlemitsos, P. J.; Boldt, E. A.; Holt, S. S.; Smith, B. W.
1978-01-01
OSO 8 X-ray spectra from 2 to 20 keV have been analyzed for 26 clusters of galaxies. For 20 clusters temperatures, emission integrals, iron abundances, and low-energy absorption measurements are presented. The data give, in general, better fits to thermal bremsstrahlung than to power-law models. Eight clusters have positive iron emission-line detections at the 90% confidence level, and all 20 cluster spectra are consistent with Fe/H = 0.000014 by number with the possible exception of Virgo. Thus it is confirmed that X-ray emission in this energy band is predominantly thermal radiation from hot intracluster gas rather than inverse Compton radiation. Physical correlations between X-ray spectral parameters and other cluster properties are examined. It is found that (1) the X-ray temperature is approximately proportional to the square of the velocity dispersion of the galaxies; (2) the emission integral is a strong function of the X-ray temperature; (3) the X-ray temperature and emission integral are better correlated with cluster central-galaxy density than with richness; and (4) the fraction of galaxies which are spirals is correlated with the observed ram pressure in the cluster core.
Brain correlates of the intrinsic subjective cost of effort in sedentary volunteers.
Bernacer, J; Martinez-Valbuena, I; Martinez, M; Pujol, N; Luis, E; Ramirez-Castillo, D; Pastor, M A
2016-01-01
One key aspect of motivation is the ability of agents to overcome excessive weighting of intrinsic subjective costs. This contribution aims to analyze the subjective cost of effort and assess its neural correlates in sedentary volunteers. We recruited a sample of 57 subjects who underwent a decision-making task using a prospective, moderate, and sustained physical effort as devaluating factor. Effort discounting followed a hyperbolic function, and individual discounting constants correlated with an indicator of sedentary lifestyle (global physical activity questionnaire; R=-0.302, P=0.033). A subsample of 24 sedentary volunteers received a functional magnetic resonance imaging scan while performing a similar effort-discounting task. BOLD signal of a cluster located in the dorsomedial prefrontal cortex correlated with the subjective value of the pair of options under consideration (Z>2.3, P<0.05; cluster corrected for multiple comparisons for the whole brain). Furthermore, effort-related discounting of reward correlated with the signal of a cluster in the ventrolateral prefrontal cortex (Z>2.3, P<0.05; small volume cluster corrected for a region of interest including the ventral prefrontal cortex and striatum). This study offers empirical data about the intrinsic subjective cost of effort and its neural correlates in sedentary individuals. © 2016 Elsevier B.V. All rights reserved.
Course 4: Density Functional Theory, Methods, Techniques, and Applications
NASA Astrophysics Data System (ADS)
Chrétien, S.; Salahub, D. R.
Contents 1 Introduction 2 Density functional theory 2.1 Hohenberg and Kohn theorems 2.2 Levy's constrained search 2.3 Kohn-Sham method 3 Density matrices and pair correlation functions 4 Adiabatic connection or coupling strength integration 5 Comparing and constrasting KS-DFT and HF-CI 6 Preparing new functionals 7 Approximate exchange and correlation functionals 7.1 The Local Spin Density Approximation (LSDA) 7.2 Gradient Expansion Approximation (GEA) 7.3 Generalized Gradient Approximation (GGA) 7.4 meta-Generalized Gradient Approximation (meta-GGA) 7.5 Hybrid functionals 7.6 The Optimized Effective Potential method (OEP) 7.7 Comparison between various approximate functionals 8 LAP correlation functional 9 Solving the Kohn-Sham equations 9.1 The Kohn-Sham orbitals 9.2 Coulomb potential 9.3 Exchange-correlation potential 9.4 Core potential 9.5 Other choices and sources of error 9.6 Functionality 10 Applications 10.1 Ab initio molecular dynamics for an alanine dipeptide model 10.2 Transition metal clusters: The ecstasy, and the agony... 10.3 The conversion of acetylene to benzene on Fe clusters 11 Conclusions
NASA Astrophysics Data System (ADS)
Yoo, Soohaeng; Shao, Nan; Zeng, X. C.
2009-10-01
We report improved results of lowest-lying silicon clusters Si 30-Si 38. A large population of low-energy clusters are collected from previous searches by several research groups and the binding energies of these clusters are computed using density-functional theory (DFT) methods. Best candidates (isomers with high binding energies) are identified from the screening calculations. Additional constrained search is then performed for the best candidates using the basin-hopping method combined with DFT geometry optimization. The obtained low-lying clusters are classified according to binding energies computed using either the Perdew-Burke-Ernzerhof (PBE) functional or the Becke exchange and Lee-Yang-Parr correlation (BLYP) functional. We propose to rank low-lying clusters according to the mean PBE/BLYP binding energies in view that the PBE functional tends to give greater binding energies for more compact clusters whereas the BLYP functional tends to give greater binding energies for less compact clusters or clusters composed of small-sized magic-number clusters. Except for Si 30, the new search confirms again that medium-size silicon clusters Si 31-Si 38 constructed with proper fullerene cage motifs are most promising to be the lowest-energy structures.
First results from the IllustrisTNG simulations: matter and galaxy clustering
NASA Astrophysics Data System (ADS)
Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill
2018-03-01
Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.
The evolution of active galactic nuclei in clusters of galaxies from the Dark Energy Survey
Bufanda, E.; Hollowood, D.; Jeltema, T. E.; ...
2016-12-13
The correlation between active galactic nuclei (AGN) and environment provides important clues to AGN fueling and the relationship of black hole growth to galaxy evolution. Here, we analyze the fraction of galaxies in clusters hosting AGN as a function of redshift and cluster richness for X-ray detected AGN associated with clusters of galaxies in Dark Energy Survey (DES) Science Verification data. The present sample includes 33 AGN with L_X > 10 43 ergs s -1 in non-central, host galaxies with luminosity greater than 0.5 L* from a total sample of 432 clusters in the redshift range of 0.10.7. Our resultmore » is in good agreement with previous work and parallels the increase in star formation in cluster galaxies over the same redshift range. But, the AGN fraction in clusters is observed to have no significant correlation with cluster mass. Future analyses with DES Year 1 through Year 3 data will be able to clarify whether AGN activity is correlated to cluster mass and will tightly constrain the relationship between cluster AGN populations and redshift.« less
New trial wave function for the nuclear cluster structure of nuclei
NASA Astrophysics Data System (ADS)
Zhou, Bo
2018-04-01
A new trial wave function is proposed for nuclear cluster physics, in which an exact solution to the long-standing center-of-mass problem is given. In the new approach, the widths of the single-nucleon Gaussian wave packets and the widths of the relative Gaussian wave functions describing correlations of nucleons or clusters are treated as variables in the explicit intrinsic wave function of the nuclear system. As an example, this new wave function was applied to study the typical {^{20}Ne} (α+{{^{16}}O}) cluster system. By removing exactly the spurious center-of-mass effect in a very simple way, the energy curve of {^{20}Ne} was obtained by variational calculations with the width of the α cluster, the width of the {{^{16}}O} cluster, and the size parameter of the nucleus. These are considered the three crucial variational variables in describing the {^{20}Ne} (α+{{^{16}}O}) cluster system. This shows that the new wave function can be a very interesting new tool for studying many-body and cluster effects in nuclear physics.
Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S
2010-02-01
Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.
The correlation function for density perturbations in an expanding universe. II - Nonlinear theory
NASA Technical Reports Server (NTRS)
Mcclelland, J.; Silk, J.
1977-01-01
A formalism is developed to find the two-point and higher-order correlation functions for a given distribution of sizes and shapes of perturbations which are randomly placed in three-dimensional space. The perturbations are described by two parameters such as central density and size, and the two-point correlation function is explicitly related to the luminosity function of groups and clusters of galaxies
Galaxy Clustering Around Nearby Luminous Quasars
NASA Technical Reports Server (NTRS)
Fisher, Karl B.; Bahcall, John N.; Kirhakos, Sofia; Schneider, Donald P.
1996-01-01
We examine the clustering of galaxies around a sample of 20 luminous low redshift (z approx. less than 0.30) quasars observed with the Wide Field Camera-2 on the Hubble Space Telescope (HST). The HST resolution makes possible galaxy identification brighter than V = 24.5 and as close as 1 min or 2 min to the quasar. We find a significant enhancement of galaxies within a projected separation of approx. less than 100 1/h kpc of the quasars. If we model the QSO/galaxy correlation function as a power law with a slope given by the galaxy/galaxy correlation function, we find that the ratio of the QSO/galaxy to galaxy/galaxy correlation functions is 3.8 +/- 0.8. The galaxy counts within r less than 15 1/h kpc of the quasars are too high for the density profile to have an appreciable core radius (approx. greater than 100 1/h kpc). Our results reinforce the idea that low redshift quasars are located preferentially in groups of 10-20 galaxies rather than in rich clusters. We see no significant difference in the clustering amplitudes derived from radio-loud and radio-quiet subsamples.
Cheong, Ying; Saran, Mili; Hounslow, James William; Reading, Isabel Claire
2018-01-08
Chronic pelvic pain is a debilitating condition. It is unknown if there is a clinical phenotype for adhesive disorders. This study aimed to determine if the presence or absence, nature, severity and extent of adhesions correlated with demographic and patient reported clinical characteristics of women presenting with CPP. Women undergoing a laparoscopy for the investigation of chronic pelvic pain were recruited prospectively; their pain and phenotypic characteristics were entered into a hierarchical cluster analysis. The groups with differing baseline clinical and operative characteristics in terms of adhesions involvement were analyzed. Sixty two women were recruited where 37 had adhesions. A low correlation was found between women's reported current pain scores and that of most severe (r = 0.34) or average pain experienced (r = 0.44) in the last 6 months. Three main groups of women with CPP were identified: Cluster 1 (n = 35) had moderate severity of pain, with poor average and present pain intensity; Cluster 2 (n = 14) had a long duration of symptoms/diagnosis, the worst current pain and worst physical, emotional and social functions; Cluster 3 (n = 11) had the shortest duration of pain and showed the best evidence of coping with low (good) physical, social and emotional scores. This cluster also had the highest proportion of women with adhesions (82%) compared to 51% in Cluster 1 and 71% in Cluster 2. In this study, we found that there is little or no correlation between patient-reported pain, physical, emotional and functional characteristics scores with the presence or absence of intra-abdominal/pelvic adhesions found during investigative laparoscopy. Most women who had adhesions had the lowest reported current pain scores.
Abeykoon, A M Milinda; Donner, Wolfgang; Brunelli, Michela; Castro-Colin, Miguel; Jacobson, Allan J; Moss, Simon C
2009-09-23
The structure of Se particles in the approximately 13 A diameter alpha-cages of zeolite NdY has been determined by Rietveld refinement and pair distribution function (PDF) analysis of X-ray data. With the diffuse scattering subtracted an average structure comprised of an undistorted framework containing nanoclusters of 20 Se atoms is observed. The intracluster correlations and the cluster-framework correlations which give rise to diffuse scattering were modeled by using PDF analysis.
Strong Clustering of Lyman Break Galaxies around Luminous Quasars at Z ˜ 4
NASA Astrophysics Data System (ADS)
García-Vergara, Cristina; Hennawi, Joseph F.; Barrientos, L. Felipe; Rix, Hans-Walter
2017-10-01
In the standard picture of structure formation, the first massive galaxies are expected to form at the highest peaks of the density field, which constitute the cores of massive proto-clusters. Luminous quasars (QSOs) at z ˜ 4 are the most strongly clustered population known, and should thus reside in massive dark matter halos surrounded by large overdensities of galaxies, implying a strong QSO-galaxy cross-correlation function. We observed six z ˜ 4 QSO fields with VLT/FORS, exploiting a novel set of narrow-band filters custom designed to select Lyman Break Galaxies (LBGs) in a thin redshift slice of {{Δ }}z˜ 0.3, mitigating the projection effects that have limited the sensitivity of previous searches for galaxies around z≳ 4 QSOs. We find that LBGs are strongly clustered around QSOs, and present the first measurement of the QSO-LBG cross-correlation function at z ˜ 4, on scales of 0.1≲ R≲ 9 {h}-1 {Mpc} (comoving). Assuming a power-law form for the cross-correlation function ξ ={(r/{r}0{QG})}γ , we measure {r}0{QG}={8.83}-1.51+1.39 {h}-1 {Mpc} for a fixed slope of γ =2.0. This result is in agreement with the expected cross-correlation length deduced from measurements of the QSO and LBG auto-correlation function, and assuming a deterministic bias model. We also measure a strong auto-correlation of LBGs in our QSO fields, finding {r}0{GG}={21.59}-1.69+1.72 {h}-1 {Mpc} for a fixed slope of γ =1.5, which is ˜4 times larger than the LBG auto-correlation length in blank fields, providing further evidence that QSOs reside in overdensities of LBGs. Our results qualitatively support a picture where luminous QSOs inhabit exceptionally massive ({M}{halo}> {10}12 {M}⊙ ) dark matter halos at z ˜ 4.
Correlations and clustering in wholesale electricity markets
Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin
2017-11-24
We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.
Correlations and clustering in wholesale electricity markets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin
We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.
Correlations and clustering in wholesale electricity markets
NASA Astrophysics Data System (ADS)
Cui, Tianyu; Caravelli, Francesco; Ududec, Cozmin
2018-02-01
We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. This allows us to reconstruct aspects of the locational structure of the grid.
Statistical Issues in Galaxy Cluster Cosmology
NASA Technical Reports Server (NTRS)
Mantz, Adam
2013-01-01
The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.
Rissling, Anthony J.; Miyakoshi, Makoto; Sugar, Catherine A.; Braff, David L.; Makeig, Scott; Light, Gregory A.
2014-01-01
Although sensory processing abnormalities contribute to widespread cognitive and psychosocial impairments in schizophrenia (SZ) patients, scalp-channel measures of averaged event-related potentials (ERPs) mix contributions from distinct cortical source-area generators, diluting the functional relevance of channel-based ERP measures. SZ patients (n = 42) and non-psychiatric comparison subjects (n = 47) participated in a passive auditory duration oddball paradigm, eliciting a triphasic (Deviant−Standard) tone ERP difference complex, here termed the auditory deviance response (ADR), comprised of a mid-frontal mismatch negativity (MMN), P3a positivity, and re-orienting negativity (RON) peak sequence. To identify its cortical sources and to assess possible relationships between their response contributions and clinical SZ measures, we applied independent component analysis to the continuous 68-channel EEG data and clustered the resulting independent components (ICs) across subjects on spectral, ERP, and topographic similarities. Six IC clusters centered in right superior temporal, right inferior frontal, ventral mid-cingulate, anterior cingulate, medial orbitofrontal, and dorsal mid-cingulate cortex each made triphasic response contributions. Although correlations between measures of SZ clinical, cognitive, and psychosocial functioning and standard (Fz) scalp-channel ADR peak measures were weak or absent, for at least four IC clusters one or more significant correlations emerged. In particular, differences in MMN peak amplitude in the right superior temporal IC cluster accounted for 48% of the variance in SZ-subject performance on tasks necessary for real-world functioning and medial orbitofrontal cluster P3a amplitude accounted for 40%/54% of SZ-subject variance in positive/negative symptoms. Thus, source-resolved auditory deviance response measures including MMN may be highly sensitive to SZ clinical, cognitive, and functional characteristics. PMID:25379456
Ren, Hongyan; Tang, Ping; Zhao, Qinghua; Ren, Guosheng
2017-08-23
To identify symptom distress and clusters in patients 3 months after radical cystectomy and to explore their potential predictors. A cross-sectional design was used to investigate 99 bladder cancer patients 3 months after radical cystectomy. Data were collected by demographic and disease characteristic questionnaires, the symptom experience scale of the M.D. Anderson symptom inventory, two additional symptoms specific to radical cystectomy, and the functional assessment of cancer therapy questionnaire. A factor analysis, stepwise regression, and correlation analysis were applied. Three symptom clusters were identified: fatigue-malaise, gastrointestinal, and psycho-urinary. Age, complication severity, albumin post-surgery (negative), orthotropic neobladder reconstruction, adjuvant chemotherapy and American Society of Anesthesiologists (ASA) scores were significant predictors of fatigue-malaise. Adjuvant chemotherapy, orthotropic neobladder reconstruction, female gender, ASA scores and albumin (negative) were significant predictors of gastrointestinal symptoms. Being unmarried, having a higher educational level and complication severity were significant predictors of psycho-urinary symptoms. The correlations between clusters and for each cluster with quality of life were significant, with the highest correlation observed between the psycho-urinary cluster and quality of life. Bladder cancer patients experience concurrent symptoms that appear to cluster and are significantly correlated with quality of life. Moreover, symptom clusters may be predicted by certain demographic and clinical characteristics.
Property relationships of the physical infrastructure and the traffic flow networks
NASA Astrophysics Data System (ADS)
Zhou, Ta; Zou, Sheng-Rong; He, Da-Ren
2010-03-01
We studied both empirically and analytically the correlation between the degrees or the clustering coefficients, respectively, of the networks in the physical infrastructure and the traffic flow layers in three Chinese transportation systems. The systems are bus transportation systems in Beijing and Hangzhou, and the railway system in the mainland. It is found that the correlation between the degrees obey a linear function; while the correlation between the clustering coefficients obey a power law. A possible dynamic explanation on the rules is presented.
Gunina, Anastasia O.; Krylov, Anna I.
2016-11-14
We apply high-level ab initio methods to describe the electronic structure of small clusters of ammonia and dimethylether (DME) doped with sodium, which provide a model for solvated electrons. We investigate the effect of the solvent and cluster size on the electronic states. We consider both energies and properties, with a focus on the shape of the electronic wave function and the related experimental observables such as photoelectron angular distributions. The central quantity in modeling photoionization experiments is the Dyson orbital, which describes the difference between the initial N-electron and final (N-1)-electron states of a system. Dyson orbitals enter themore » expression of the photoelectron matrix element, which determines total and partial photoionization cross-sections. We compute Dyson orbitals for the Na(NH3)n and Na(DME)m clusters using correlated wave functions (obtained with equation-of-motion coupled-cluster model for electron attachment with single and double substitutions) and compare them with more approximate Hartree-Fock and Kohn-Sham orbitals. As a result, we also analyze the effect of correlation and basis sets on the shapes of Dyson orbitals and the experimental observables.« less
NASA Astrophysics Data System (ADS)
Gunawardhana, M. L. P.; Norberg, P.; Zehavi, I.; Farrow, D. J.; Loveday, J.; Hopkins, A. M.; Davies, L. J. M.; Wang, L.; Alpaslan, M.; Bland-Hawthorn, J.; Brough, S.; Holwerda, B. W.; Owers, M. S.; Wright, A. H.
2018-06-01
Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their interaction. In this study, we use two-point auto, cross and mark correlation functions to investigate the extent to which small-scale clustering properties of star forming galaxies can be used to gain physical insight into galaxy-galaxy interactions between galaxies of similar optical brightness and stellar mass. The Hα star formers, drawn from the highly spatially complete Galaxy And Mass Assembly (GAMA) survey, show an increase in clustering on small separations. Moreover, the clustering strength shows a strong dependence on optical brightness and stellar mass, where (1) the clustering amplitude of optically brighter galaxies at a given separation is larger than that of optically fainter systems, (2) the small scale clustering properties (e.g. the strength, the scale at which the signal relative to the fiducial power law plateaus) of star forming galaxies appear to differ as a function of increasing optical brightness of galaxies. According to cross and mark correlation analyses, the former result is largely driven by the increased dust content in optically bright star forming galaxies. The latter could be interpreted as evidence of a correlation between interaction-scale and optical brightness of galaxies, where physical evidence of interactions between optically bright star formers, likely hosted within relatively massive halos, persist over larger separations than those between optically faint star formers.
Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S
2015-09-01
The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.
Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S
2015-01-01
The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648
T7 RNA Polymerase Functions In Vitro without Clustering
Finan, Kieran; Torella, Joseph P.; Kapanidis, Achillefs N.; Cook, Peter R.
2012-01-01
Many nucleic acid polymerases function in clusters known as factories. We investigate whether the RNA polymerase (RNAP) of phage T7 also clusters when active. Using ‘pulldowns’ and fluorescence correlation spectroscopy we find that elongation complexes do not interact in vitro with a Kd<1 µM. Chromosome conformation capture also reveals that genes located 100 kb apart on the E. coli chromosome do not associate more frequently when transcribed by T7 RNAP. We conclude that if clustering does occur in vivo, it must be driven by weak interactions, or mediated by a phage-encoded protein. PMID:22768341
Clustering of galaxies with f(R) gravity
NASA Astrophysics Data System (ADS)
Capozziello, Salvatore; Faizal, Mir; Hameeda, Mir; Pourhassan, Behnam; Salzano, Vincenzo; Upadhyay, Sudhaker
2018-02-01
Based on thermodynamics, we discuss the galactic clustering of expanding Universe by assuming the gravitational interaction through the modified Newton's potential given by f(R) gravity. We compute the corrected N-particle partition function analytically. The corrected partition function leads to more exact equations of state of the system. By assuming that the system follows quasi-equilibrium, we derive the exact distribution function that exhibits the f(R) correction. Moreover, we evaluate the critical temperature and discuss the stability of the system. We observe the effects of correction of f(R) gravity on the power-law behaviour of particle-particle correlation function also. In order to check the feasibility of an f(R) gravity approach to the clustering of galaxies, we compare our results with an observational galaxy cluster catalogue.
The VLT LBG redshift survey - VI. Mapping H I in the proximity of z ˜ 3 LBGs with X-Shooter
NASA Astrophysics Data System (ADS)
Bielby, R. M.; Shanks, T.; Crighton, N. H. M.; Bornancini, C. G.; Infante, L.; Lambas, D. G.; Minniti, D.; Morris, S. L.; Tummuangpak, P.
2017-10-01
We present an analysis of the spatial distribution and dynamics of neutral hydrogen gas around galaxies using new X-Shooter observations of z ˜ 2.5-4 quasars. Adding the X-Shooter data to our existing data set of high-resolution quasar spectroscopy, we use a total sample of 29 quasars alongside ˜1700 Lyman Break Galaxies (LBGs) in the redshift range 2 ≲ z ≲ 3.5. We measure the Lyα forest auto-correlation function, finding a clustering length of s0 = 0.081 ± 0.006 h-1 Mpc, and the cross-correlation function with LBGs, finding a cross-clustering length of s0 = 0.27 ± 0.14 h-1 Mpc and power-law slope γ = 1.1 ± 0.2. Our results highlight the weakly clustered nature of neutral hydrogren systems in the Lyα forest. Building on this, we make a first analysis of the dependence of the clustering on absorber strength, finding a clear preference for stronger Lyα forest absorption features to be more strongly clustered around the galaxy population, suggesting that they trace on average higher mass haloes. Using the projected and 2-D cross-correlation functions, we constrain the dynamics of Lyα forest clouds around z ˜ 3 galaxies. We find a significant detection of large-scale infall of neutral hydrogen, with a constraint on the Lyα forest infall parameter of βF = 1.02 ± 0.22.
Real- and redshift-space halo clustering in f(R) cosmologies
NASA Astrophysics Data System (ADS)
Arnalte-Mur, Pablo; Hellwing, Wojciech A.; Norberg, Peder
2017-05-01
We present two-point correlation function statistics of the mass and the haloes in the chameleon f(R) modified gravity scenario using a series of large-volume N-body simulations. Three distinct variations of f(R) are considered (F4, F5 and F6) and compared to a fiducial Λ cold dark matter (ΛCDM) model in the redshift range z ∈ [0, 1]. We find that the matter clustering is indistinguishable for all models except for F4, which shows a significantly steeper slope. The ratio of the redshift- to real-space correlation function at scales >20 h-1 Mpc agrees with the linear General Relativity (GR) Kaiser formula for the viable f(R) models considered. We consider three halo populations characterized by spatial abundances comparable to that of luminous red galaxies and galaxy clusters. The redshift-space halo correlation functions of F4 and F5 deviate significantly from ΛCDM at intermediate and high redshift, as the f(R) halo bias is smaller than or equal to that of the ΛCDM case. Finally, we introduce a new model-independent clustering statistic to distinguish f(R) from GR: the relative halo clustering ratio - R. The sampling required to adequately reduce the scatter in R will be available with the advent of the next-generation galaxy redshift surveys. This will foster a prospective avenue to obtain largely model-independent cosmological constraints on this class of modified gravity models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wahlen-Strothman, J. M.; Henderson, T. H.; Hermes, M. R.
Coupled cluster and symmetry projected Hartree-Fock are two central paradigms in electronic structure theory. However, they are very different. Single reference coupled cluster is highly successful for treating weakly correlated systems, but fails under strong correlation unless one sacrifices good quantum numbers and works with broken-symmetry wave functions, which is unphysical for finite systems. Symmetry projection is effective for the treatment of strong correlation at the mean-field level through multireference non-orthogonal configuration interaction wavefunctions, but unlike coupled cluster, it is neither size extensive nor ideal for treating dynamic correlation. We here examine different scenarios for merging these two dissimilar theories.more » We carry out this exercise over the integrable Lipkin model Hamiltonian, which despite its simplicity, encompasses non-trivial physics for degenerate systems and can be solved via diagonalization for a very large number of particles. We show how symmetry projection and coupled cluster doubles individually fail in different correlation limits, whereas models that merge these two theories are highly successful over the entire phase diagram. Despite the simplicity of the Lipkin Hamiltonian, the lessons learned in this work will be useful for building an ab initio symmetry projected coupled cluster theory that we expect to be accurate in the weakly and strongly correlated limits, as well as the recoupling regime.« less
ON THE CLUSTERING OF SUBMILLIMETER GALAXIES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Williams, Christina C.; Giavalisco, Mauro; Yun, Min S.
2011-06-01
We measure the angular two-point correlation function of submillimeter galaxies (SMGs) from 1.1 mm imaging of the COSMOS field with the AzTEC camera and ASTE 10 m telescope. These data yield one of the largest contiguous samples of SMGs to date, covering an area of 0.72 deg{sup 2} down to a 1.26 mJy beam{sup -1} (1{sigma}) limit, including 189 (328) sources with S/N {>=}3.5 (3). We can only set upper limits to the correlation length r{sub 0}, modeling the correlation function as a power law with pre-assigned slope. Assuming existing redshift distributions, we derive 68.3% confidence level upper limits ofmore » r{sub 0} {approx}< 6-8h{sup -1} Mpc at 3.7 mJy and r{sub 0} {approx}< 11-12 h{sup -1} Mpc at 4.2 mJy. Although consistent with most previous estimates, these upper limits imply that the real r{sub 0} is likely smaller. This casts doubts on the robustness of claims that SMGs are characterized by significantly stronger spatial clustering (and thus larger mass) than differently selected galaxies at high redshift. Using Monte Carlo simulations we show that even strongly clustered distributions of galaxies can appear unclustered when sampled with limited sensitivity and coarse angular resolution common to current submillimeter surveys. The simulations, however, also show that unclustered distributions can appear strongly clustered under these circumstances. From the simulations, we predict that at our survey depth, a mapped area of 2 deg{sup 2} is needed to reconstruct the correlation function, assuming smaller beam sizes of future surveys (e.g., the Large Millimeter Telescope's 6'' beam size). At present, robust measures of the clustering strength of bright SMGs appear to be below the reach of most observations.« less
Wavelet-based clustering of resting state MRI data in the rat.
Medda, Alessio; Hoffmann, Lukas; Magnuson, Matthew; Thompson, Garth; Pan, Wen-Ju; Keilholz, Shella
2016-01-01
While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas. Copyright © 2015 Elsevier Inc. All rights reserved.
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.
The JCMT Gould Belt Survey: Dense Core Clusters in Orion B
NASA Astrophysics Data System (ADS)
Kirk, H.; Johnstone, D.; Di Francesco, J.; Lane, J.; Buckle, J.; Berry, D. S.; Broekhoven-Fiene, H.; Currie, M. J.; Fich, M.; Hatchell, J.; Jenness, T.; Mottram, J. C.; Nutter, D.; Pattle, K.; Pineda, J. E.; Quinn, C.; Salji, C.; Tisi, S.; Hogerheijde, M. R.; Ward-Thompson, D.; The JCMT Gould Belt Survey Team
2016-04-01
The James Clerk Maxwell Telescope Gould Belt Legacy Survey obtained SCUBA-2 observations of dense cores within three sub-regions of Orion B: LDN 1622, NGC 2023/2024, and NGC 2068/2071, all of which contain clusters of cores. We present an analysis of the clustering properties of these cores, including the two-point correlation function and Cartwright’s Q parameter. We identify individual clusters of dense cores across all three regions using a minimal spanning tree technique, and find that in each cluster, the most massive cores tend to be centrally located. We also apply the independent M-Σ technique and find a strong correlation between core mass and the local surface density of cores. These two lines of evidence jointly suggest that some amount of mass segregation in clusters has happened already at the dense core stage.
Computational study of AuSi{sub n} (n=1-9) nanoalloy clusters invoking DFT based descriptors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ranjan, Prabhat; Kumar, Ajay; Chakraborty, Tanmoy, E-mail: tanmoy.chakraborty@jaipur.manipal.edu, E-mail: tanmoychem@gmail.com
2016-04-13
Nanoalloy clusters formed between Au and Si are topics of great interest today from both scientific and technological point of view. Due to its remarkable catalytic, electronic, mechanical and magnetic properties Au-Si nanoalloy clusters have extensive applications in the field of microelectronics, catalysis, biomedicine, and jewelry industry. Density Functional Theory (DFT) is a new paradigm of quantum mechanics, which is very much popular to study the electronic properties of materials. Conceptual DFT based descriptors have been invoked to correlate the experimental properties of nanoalloy clusters. In this venture, we have systematically investigated AuSi{sub n} (n=1-9) nanoalloy clusters in the theoreticalmore » frame of the B3LYP exchange correlation. The experimental properties of AuSi{sub n} (n=1-9) nanoalloy clusters are correlated in terms of DFT based descriptors viz. HOMO-LUMO gap, Electronegativity (χ), Global Hardness (η), Global Softness (S) and Electrophilicity Index (ω). The calculated HOMO-LUMO gap exhibits interesting odd-even alteration behaviour, indicating that even numbered clusters possess higher stability as compare to their neighbour odd numbered clusters. This study also reflects a very well agreement between experimental bond length and computed data.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Byrd, Jason N., E-mail: byrd.jason@ensco.com; ENSCO, Inc., 4849 North Wickham Road, Melbourne, Florida 32940; Lutz, Jesse J., E-mail: jesse.lutz.ctr@afit.edu
The accurate determination of the preferred Si{sub 12}C{sub 12} isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC{sub 3} to Si{sub 12}C{sub 12}. It is found that post-MBPT(2) correlation energy plays a significant rolemore » in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si{sub 12}C{sub 12} isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.« less
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.; Sousa Alencar, Ana G.; Scuseria, Gustavo E.
2015-12-01
Singlet-paired coupled cluster doubles (CCD0) is a simplification of CCD that relinquishes a fraction of dynamic correlation in order to be able to describe static correlation. Combinations of CCD0 with density functionals that recover specifically the dynamic correlation missing in the former have also been developed recently. Here, we assess the accuracy of CCD0 and CCD0+DFT (and variants of these using Brueckner orbitals) as compared to well-established quantum chemical methods for describing ground-state properties of singlet actinide molecules. The f0 actinyl series (UO22+, NpO23+, PuO24+), the isoelectronic NUN, and thorium (ThO, ThO2+) and nobelium (NoO, NoO2) oxides are studied.
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.
NASA Technical Reports Server (NTRS)
Croft, R. A. C.; Dalton, G. B.; Efstathiou, G.; Sutherland, W. J.; Maddox, S. J.
1997-01-01
We analyze the spatial clustering properties of a new catalog of very rich galaxy clusters selected from the APM Galaxy Survey. These clusters are of comparable richness and space density to Abell Richness Class greater than or equal to 1 clusters, but selected using an objective algorithm from a catalog demonstrably free of artificial inhomogeneities. Evaluation of the two-point correlation function xi(sub cc)(r) for the full sample and for richer subsamples reveals that the correlation amplitude is consistent with that measured for lower richness APM clusters and X-ray selected clusters. We apply a maximum likelihood estimator to find the best fitting slope and amplitude of a power law fit to x(sub cc)(r), and to estimate the correlation length r(sub 0) (the value of r at which xi(sub cc)(r) is equal to unity). For clusters with a mean space density of 1.6 x 10(exp -6) h(exp 3) MpC(exp -3) (equivalent to the space density of Abell Richness greater than or equal to 2 clusters), we find r(sub 0) = 21.3(+11.1/-9.3) h(exp -1) Mpc (95% confidence limits). This is consistent with the weak richness dependence of xi(sub cc)(r) expected in Gaussian models of structure formation. In particular, the amplitude of xi(sub cc)(r) at all richnesses matches that of xi(sub cc)(r) for clusters selected in N-Body simulations of a low density Cold Dark Matter model.
NASA Astrophysics Data System (ADS)
Garza, Alejandro J.; Bulik, Ireneusz W.; Alencar, Ana G. Sousa; Sun, Jianwei; Perdew, John P.; Scuseria, Gustavo E.
2016-04-01
Contrary to standard coupled cluster doubles (CCD) and Brueckner doubles (BD), singlet-paired analogues of CCD and BD (denoted here as CCD0 and BD0) do not break down when static correlation is present, but neglect substantial amounts of dynamic correlation. In fact, CCD0 and BD0 do not account for any contributions from multielectron excitations involving only same-spin electrons at all. We exploit this feature to add - without introducing double counting, self-interaction, or increase in cost - the missing correlation to these methods via meta-GGA (generalised gradient approximation) density functionals (Tao-Perdew-Staroverov-Scuseria and strongly constrained and appropriately normed). Furthermore, we improve upon these CCD0+DFT blends by invoking range separation: the short- and long-range correlations absent in CCD0/BD0 are evaluated with density functional theory and the direct random phase approximation, respectively. This corrects the description of long-range van der Waals forces. Comprehensive benchmarking shows that the combinations presented here are very accurate for weakly correlated systems, while also providing a reasonable description of strongly correlated problems without resorting to symmetry breaking.
NASA Astrophysics Data System (ADS)
Rodríguez-Torres, Sergio A.; Chuang, Chia-Hsun; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Behroozi, Peter; Hahn, Chang Hoon; Comparat, Johan; Yepes, Gustavo; Montero-Dorta, Antonio D.; Brownstein, Joel R.; Maraston, Claudia; McBride, Cameron K.; Tinker, Jeremy; Gottlöber, Stefan; Favole, Ginevra; Shu, Yiping; Kitaura, Francisco-Shu; Bolton, Adam; Scoccimarro, Román; Samushia, Lado; Schlegel, David; Schneider, Donald P.; Thomas, Daniel
2016-08-01
We present a study of the clustering and halo occupation distribution of Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies in the redshift range 0.43 < z < 0.7 drawn from the Final SDSS-III Data Release. We compare the BOSS results with the predictions of a halo abundance matching (HAM) clustering model that assigns galaxies to dark matter haloes selected from the large BigMultiDark N-body simulation of a flat Λ cold dark matter Planck cosmology. We compare the observational data with the simulated ones on a light cone constructed from 20 subsequent outputs of the simulation. Observational effects such as incompleteness, geometry, veto masks and fibre collisions are included in the model, which reproduces within 1σ errors the observed monopole of the two-point correlation function at all relevant scales: from the smallest scales, 0.5 h-1 Mpc, up to scales beyond the baryon acoustic oscillation feature. This model also agrees remarkably well with the BOSS galaxy power spectrum (up to k ˜ 1 h Mpc-1), and the three-point correlation function. The quadrupole of the correlation function presents some tensions with observations. We discuss possible causes that can explain this disagreement, including target selection effects. Overall, the standard HAM model describes remarkably well the clustering statistics of the CMASS sample. We compare the stellar-to-halo mass relation for the CMASS sample measured using weak lensing in the Canada-France-Hawaii Telescope Stripe 82 Survey with the prediction of our clustering model, and find a good agreement within 1σ. The BigMD-BOSS light cone including properties of BOSS galaxies and halo properties is made publicly available.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Degroote, M.; Henderson, T. M.; Zhao, J.
We present a similarity transformation theory based on a polynomial form of a particle-hole pair excitation operator. In the weakly correlated limit, this polynomial becomes an exponential, leading to coupled cluster doubles. In the opposite strongly correlated limit, the polynomial becomes an extended Bessel expansion and yields the projected BCS wavefunction. In between, we interpolate using a single parameter. The e ective Hamiltonian is non-hermitian and this Polynomial Similarity Transformation Theory follows the philosophy of traditional coupled cluster, left projecting the transformed Hamiltonian onto subspaces of the Hilbert space in which the wave function variance is forced to be zero.more » Similarly, the interpolation parameter is obtained through minimizing the next residual in the projective hierarchy. We rationalize and demonstrate how and why coupled cluster doubles is ill suited to the strongly correlated limit whereas the Bessel expansion remains well behaved. The model provides accurate wave functions with energy errors that in its best variant are smaller than 1% across all interaction stengths. The numerical cost is polynomial in system size and the theory can be straightforwardly applied to any realistic Hamiltonian.« less
Effect of Coulomb Correlation on the Magnetic Properties of Mn Clusters.
Huang, Chengxi; Zhou, Jian; Deng, Kaiming; Kan, Erjun; Jena, Puru
2018-05-03
In spite of decades of research, a fundamental understanding of the unusual magnetic behavior of small Mn clusters remains a challenge. Experiments show that Mn 2 is antiferromagnetic while small clusters containing up to five Mn atoms are ferromagnetic with magnetic moments of 5 μ B /atom and become ferrimagnetic as they grow further. Theoretical studies based on density functional theory (DFT), however, find Mn 2 to be ferromagnetic, with ferrimagnetic order setting in at different sizes that depend upon the computational methods used. While quantum chemical techniques correctly account for the antiferromagnetic ground state of Mn 2 , they are computationally too demanding to treat larger clusters, making it difficult to understand the evolution of magnetism. These studies clearly point to the importance of correlation and the need to find ways to treat it effectively for larger clusters and nanostructures. Here, we show that the DFT+ U method can be used to account for strong correlation. We determine the on-site Coulomb correlation, Hubbard U self-consistently by using the linear response theory and study its effect on the magnetic coupling of Mn clusters containing up to five atoms. With a calculated U value of 4.8 eV, we show that the ground state of Mn 2 is antiferromagnetic with a Mn-Mn distance of 3.34 Å, which agrees well with the electron spin resonance experiment. Equally important, we show that on-site Coulomb correlation also plays an important role in the evolution of magnetic coupling in larger clusters, as the results differ significantly from standard DFT calculations. We conclude that for a proper understanding of magnetism of Mn nanostructures (clusters, chains, and layers) one must take into account the effect of strong correlation.
A diagnostic for determining the quality of single-reference electron correlation methods
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Taylor, Peter R.
1989-01-01
It was recently proposed that the Euclidian norm of the t(sub 1) vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appopriate. This diagnostic, T(sub 1) is defined for use with self-consistent-field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T(sub 1) is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of non-dynamical electron correlation and is far superior to C(sub 0) from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T(sub 1) (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
A diagnostic for determining the quality of single-reference electron correlation methods
NASA Technical Reports Server (NTRS)
Lee, Timothy J.; Taylor, Peter R.
1989-01-01
It was recently proposed that the Euclidian norm of the t sub 1 vector of the coupled cluster wave function (normalized by the number of electrons included in the correlation procedure) could be used to determine whether a single-reference-based electron correlation procedure is appropriate. This diagnostic, T sub 1, is defined for use with self consistent field molecular orbitals and is invariant to the same orbital rotations as the coupled cluster energy. T sub 1 is investigated for several different chemical systems which exhibit a range of multireference behavior, and is shown to be an excellent measure of the importance of nondynamical electron correlation and is far superior to C sub 0 from a singles and doubles configuration interaction wave function. It is further suggested that when the aim is to recover a large fraction of the dynamical electron correlation energy, a large T sub 1 (i.e., greater than 0.02) probably indicates the need for a multireference electron correlation procedure.
Wobbled electronic properties of lithium clusters: Deterministic approach through first principles
NASA Astrophysics Data System (ADS)
Kushwaha, Anoop Kumar; Nayak, Saroj Kumar
2018-03-01
The innate tendency to form dendritic growth promoted through cluster formation leading to the failure of a Li-ion battery system have drawn significant attention of the researchers towards the effective destabilization of the cluster growth through selective implementation of electrolytic media such as acetonitrile (MeCN). In the present work, using first principles density functional theory and continuum dielectric model, we have investigated the origin of oscillatory nature of binding energy per atom of Lin (n ≤ 8) under the influence of MeCN. In the gas phase, we found that static mean polarizability is strongly correlated with binding energy and shows oscillatory nature with cluster size due to the open shell of Lin cluster. However, in acetonitrile medium, the binding energy has been correlated with electrostatic Lin -MeCN interaction and it has been found that both of them possess wobbled behavior characterized by the cluster size.
The X-CLASS-redMaPPer galaxy cluster comparison. I. Identification procedures
NASA Astrophysics Data System (ADS)
Sadibekova, T.; Pierre, M.; Clerc, N.; Faccioli, L.; Gastaud, R.; Le Fevre, J.-P.; Rozo, E.; Rykoff, E.
2014-11-01
Context. This paper is the first in a series undertaking a comprehensive correlation analysis between optically selected and X-ray-selected cluster catalogues. The rationale of the project is to develop a holistic picture of galaxy clusters utilising optical and X-ray-cluster-selected catalogues with well-understood selection functions. Aims: Unlike most of the X-ray/optical cluster correlations to date, the present paper focuses on the non-matching objects in either waveband. We investigate how the differences observed between the optical and X-ray catalogues may stem from (1) a shortcoming of the detection algorithms; (2) dispersion in the X-ray/optical scaling relations; or (3) substantial intrinsic differences between the cluster populations probed in the X-ray and optical bands. The aim is to inventory and elucidate these effects in order to account for selection biases in the further determination of X-ray/optical cluster scaling relations. Methods: We correlated the X-CLASS serendipitous cluster catalogue extracted from the XMM archive with the redMaPPer optical cluster catalogue derived from the Sloan Digital Sky Survey (DR8). We performed a detailed and, in large part, interactive analysis of the matching output from the correlation. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters, respectively. X-ray cluster matching rates were analysed as a function of optical richness. In the second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10-15 erg s-1 cm-2 in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Results: We find that all rich (λ ≥ 80) clusters are detected in X-rays out to z = 0.6. Below this redshift, the richness threshold for X-ray detection steadily decreases with redshift. Likewise, all X-ray bright clusters are detected by redMaPPer. After correcting for obvious pipeline shortcomings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centres. The fraction of clusters totally dominated by AGN-type emission appears to be a few percent. Conversely, ~40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the X-CLASS sample extending further out than redMaPPer (z< 1.5 vs. z< 0.6), but extending the correlation down to a richness of 5 raises the matching rate to ~65%. Conclusions: This state-of-the-art study involving two well-validated cluster catalogues has shown itself to be complex, and it points to a number of issues inherent to blind cross-matching, owing both to pipeline shortcomings and cluster peculiar properties. These can only been accounted for after a manual check. The combined X-ray and optical scaling relations will be presented in a subsequent article.
NASA Astrophysics Data System (ADS)
Núñez, Sara; López, José M.; Aguado, Andrés
2012-09-01
We report the putative Global Minimum (GM) structures and electronic properties of GaN+, GaN and GaN- clusters with N = 13-37 atoms, obtained from first-principles density functional theory structural optimizations. The calculations include spin polarization and employ an exchange-correlation functional which accounts for van der Waals dispersion interactions (vdW-DFT). We find a wide diversity of structural motifs within the located GM, including decahedral, polyicosahedral, polytetrahedral and layered structures. The GM structures are also extremely sensitive to the number of electrons in the cluster, so that the structures of neutral and charged clusters differ for most sizes. The main magic numbers (clusters with an enhanced stability) are identified and interpreted in terms of electronic and geometric shell closings. The theoretical results are consistent with experimental abundance mass spectra of GaN+ and with photoelectron spectra of GaN-. The size dependence of the latent heats of melting, the shape of the heat capacity peaks, and the temperature dependence of the collision cross-sections, all measured for GaN+ clusters, are properly interpreted in terms of the calculated cohesive energies, spectra of configurational excitations, and cluster shapes, respectively. The transition from ``non-melter'' to ``magic-melter'' behaviour, experimentally observed between Ga30+ and Ga31+, is traced back to a strong geometry change. Finally, the higher-than-bulk melting temperatures of gallium clusters are correlated with a more typically metallic behaviour of the clusters as compared to the bulk, contrary to previous theoretical claims.We report the putative Global Minimum (GM) structures and electronic properties of GaN+, GaN and GaN- clusters with N = 13-37 atoms, obtained from first-principles density functional theory structural optimizations. The calculations include spin polarization and employ an exchange-correlation functional which accounts for van der Waals dispersion interactions (vdW-DFT). We find a wide diversity of structural motifs within the located GM, including decahedral, polyicosahedral, polytetrahedral and layered structures. The GM structures are also extremely sensitive to the number of electrons in the cluster, so that the structures of neutral and charged clusters differ for most sizes. The main magic numbers (clusters with an enhanced stability) are identified and interpreted in terms of electronic and geometric shell closings. The theoretical results are consistent with experimental abundance mass spectra of GaN+ and with photoelectron spectra of GaN-. The size dependence of the latent heats of melting, the shape of the heat capacity peaks, and the temperature dependence of the collision cross-sections, all measured for GaN+ clusters, are properly interpreted in terms of the calculated cohesive energies, spectra of configurational excitations, and cluster shapes, respectively. The transition from ``non-melter'' to ``magic-melter'' behaviour, experimentally observed between Ga30+ and Ga31+, is traced back to a strong geometry change. Finally, the higher-than-bulk melting temperatures of gallium clusters are correlated with a more typically metallic behaviour of the clusters as compared to the bulk, contrary to previous theoretical claims. Electronic supplementary information (ESI) available: Atomic coordinates (in xyz format and Å units) and point group symmetries for the global minimum structures reported in this paper. See DOI: 10.1039/c2nr31222k
H. Li; X. Deng; Andy Dolloff; E. P. Smith
2015-01-01
A novel clustering method for bivariate functional data is proposed to group streams based on their waterâair temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...
Liu, L L; Liu, M J; Ma, M
2015-09-28
The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.
NASA Astrophysics Data System (ADS)
Bowers, Ariel; Whitmore, B. C.; Chandar, R.; Larsen, S. S.
2014-01-01
Luminosity functions have been determined for star cluster populations in 20 nearby (4 - 30 Mpc), star-forming galaxies based on ACS source lists generated by the Hubble Legacy Archive (http://hla.stsci.edu). These cluster catalogs provide one of the largest sets of uniform, automatically-generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster luminosity function can be approximated by a power-law, dN/dL ∝ Lα, with an average value for α of -2.37 and rms scatter = 0.18. A comparison of fitting results based on methods which use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum-likelihood) method to give slightly more negative values of α for galaxies with steper luminosity functions. Our uniform database results in a small scatter (0.5 magnitude) in the correlation between the magnitude of the brightest cluster (Mbrightest) and Log of the number of clusters brighter than MI = -9 (Log N). We also examine the magnitude of the brightest cluster vs. Log SFR for a sample including LIRGS and ULIRGS.
Summability of Connected Correlation Functions of Coupled Lattice Fields
NASA Astrophysics Data System (ADS)
Lukkarinen, Jani; Marcozzi, Matteo; Nota, Alessia
2018-04-01
We consider two nonindependent random fields ψ and φ defined on a countable set Z. For instance, Z=Z^d or Z=Z^d× I, where I denotes a finite set of possible "internal degrees of freedom" such as spin. We prove that, if the cumulants of ψ and φ enjoy a certain decay property, then all joint cumulants between ψ and φ are ℓ _2-summable in the precise sense described in the text. The decay assumption for the cumulants of ψ and φ is a restricted ℓ _1 summability condition called ℓ _1-clustering property. One immediate application of the results is given by a stochastic process ψ _t(x) whose state is ℓ _1-clustering at any time t: then the above estimates can be applied with ψ =ψ _t and φ =ψ _0 and we obtain uniform in t estimates for the summability of time-correlations of the field. The above clustering assumption is obviously satisfied by any ℓ _1-clustering stationary state of the process, and our original motivation for the control of the summability of time-correlations comes from a quest for a rigorous control of the Green-Kubo correlation function in such a system. A key role in the proof is played by the properties of non-Gaussian Wick polynomials and their connection to cumulants
The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies
NASA Astrophysics Data System (ADS)
Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Messa, M.; Pellerin, A.; Ryon, J. E.; Smith, L. J.; Shabani, F.; Thilker, D.; Ubeda, L.
2017-05-01
We present a study of the hierarchical clustering of the young stellar clusters in six local (3-15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ˜40-60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.
Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George
2013-01-01
Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853
Spatial correlations, clustering and percolation-like transitions in homicide crimes
NASA Astrophysics Data System (ADS)
Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.
2015-07-01
The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fransson, Thomas; Norman, Patrick; Coriani, Sonia
2013-03-28
Near carbon K-edge X-ray absorption fine structure spectra of a series of fluorine-substituted ethenes and acetone have been studied using coupled cluster and density functional theory (DFT) polarization propagator methods, as well as the static-exchange (STEX) approach. With the complex polarization propagator (CPP) implemented in coupled cluster theory, relaxation effects following the excitation of core electrons are accounted for in terms of electron correlation, enabling a systematic convergence of these effects with respect to electron excitations in the cluster operator. Coupled cluster results have been used as benchmarks for the assessment of propagator methods in DFT as well as themore » state-specific static-exchange approach. Calculations on ethene and 1,1-difluoroethene illustrate the possibility of using nonrelativistic coupled cluster singles and doubles (CCSD) with additional effects of electron correlation and relativity added as scalar shifts in energetics. It has been demonstrated that CPP spectra obtained with coupled cluster singles and approximate doubles (CC2), CCSD, and DFT (with a Coulomb attenuated exchange-correlation functional) yield excellent predictions of chemical shifts for vinylfluoride, 1,1-difluoroethene, trifluoroethene, as well as good spectral features for acetone in the case of CCSD and DFT. Following this, CPP-DFT is considered to be a viable option for the calculation of X-ray absorption spectra of larger {pi}-conjugated systems, and CC2 is deemed applicable for chemical shifts but not for studies of fine structure features. The CCSD method as well as the more approximate CC2 method are shown to yield spectral features relating to {pi}*-resonances in good agreement with experiment, not only for the aforementioned molecules but also for ethene, cis-1,2-difluoroethene, and tetrafluoroethene. The STEX approach is shown to underestimate {pi}*-peak separations due to spectral compressions, a characteristic which is inherent to this method.« less
Fransson, Thomas; Coriani, Sonia; Christiansen, Ove; Norman, Patrick
2013-03-28
Near carbon K-edge X-ray absorption fine structure spectra of a series of fluorine-substituted ethenes and acetone have been studied using coupled cluster and density functional theory (DFT) polarization propagator methods, as well as the static-exchange (STEX) approach. With the complex polarization propagator (CPP) implemented in coupled cluster theory, relaxation effects following the excitation of core electrons are accounted for in terms of electron correlation, enabling a systematic convergence of these effects with respect to electron excitations in the cluster operator. Coupled cluster results have been used as benchmarks for the assessment of propagator methods in DFT as well as the state-specific static-exchange approach. Calculations on ethene and 1,1-difluoroethene illustrate the possibility of using nonrelativistic coupled cluster singles and doubles (CCSD) with additional effects of electron correlation and relativity added as scalar shifts in energetics. It has been demonstrated that CPP spectra obtained with coupled cluster singles and approximate doubles (CC2), CCSD, and DFT (with a Coulomb attenuated exchange-correlation functional) yield excellent predictions of chemical shifts for vinylfluoride, 1,1-difluoroethene, trifluoroethene, as well as good spectral features for acetone in the case of CCSD and DFT. Following this, CPP-DFT is considered to be a viable option for the calculation of X-ray absorption spectra of larger π-conjugated systems, and CC2 is deemed applicable for chemical shifts but not for studies of fine structure features. The CCSD method as well as the more approximate CC2 method are shown to yield spectral features relating to π∗-resonances in good agreement with experiment, not only for the aforementioned molecules but also for ethene, cis-1,2-difluoroethene, and tetrafluoroethene. The STEX approach is shown to underestimate π∗-peak separations due to spectral compressions, a characteristic which is inherent to this method.
Cluster-cluster correlations and constraints on the correlation hierarchy
NASA Technical Reports Server (NTRS)
Hamilton, A. J. S.; Gott, J. R., III
1988-01-01
The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.
Spectral functions of strongly correlated extended systems via an exact quantum embedding
NASA Astrophysics Data System (ADS)
Booth, George H.; Chan, Garnet Kin-Lic
2015-04-01
Density matrix embedding theory (DMET) [Phys. Rev. Lett. 109, 186404 (2012), 10.1103/PhysRevLett.109.186404], introduced an approach to quantum cluster embedding methods whereby the mapping of strongly correlated bulk problems to an impurity with finite set of bath states was rigorously formulated to exactly reproduce the entanglement of the ground state. The formalism provided similar physics to dynamical mean-field theory at a tiny fraction of the cost but was inherently limited by the construction of a bath designed to reproduce ground-state, static properties. Here, we generalize the concept of quantum embedding to dynamic properties and demonstrate accurate bulk spectral functions at similarly small computational cost. The proposed spectral DMET utilizes the Schmidt decomposition of a response vector, mapping the bulk dynamic correlation functions to that of a quantum impurity cluster coupled to a set of frequency-dependent bath states. The resultant spectral functions are obtained on the real-frequency axis, without bath discretization error, and allows for the construction of arbitrary dynamic correlation functions. We demonstrate the method on the one- (1D) and two-dimensional (2D) Hubbard model, where we obtain zero temperature and thermodynamic limit spectral functions, and show the trivial extension to two-particle Green's functions. This advance therefore extends the scope and applicability of DMET in condensed-matter problems as a computationally tractable route to correlated spectral functions of extended systems and provides a competitive alternative to dynamical mean-field theory for dynamic quantities.
The cluster model of a hot dense vapor
NASA Astrophysics Data System (ADS)
Zhukhovitskii, D. I.
2015-04-01
We explore thermodynamic properties of a vapor in the range of state parameters where the contribution to thermodynamic functions from bound states of atoms (clusters) dominates over the interaction between the components of the vapor in free states. The clusters are assumed to be light and sufficiently "hot" for the number of bonds to be minimized. We use the technique of calculation of the cluster partition function for the cluster with a minimum number of interatomic bonds to calculate the caloric properties (heat capacity and velocity of sound) for an ideal mixture of the lightest clusters. The problem proves to be exactly solvable and resulting formulas are functions solely of the equilibrium constant of the dimer formation. These formulas ensure a satisfactory correlation with the reference data for the vapors of cesium, mercury, and argon up to moderate densities in both the sub- and supercritical regions. For cesium, we extend the model to the densities close to the critical one by inclusion of the clusters of arbitrary size. Knowledge of the cluster composition of the cesium vapor makes it possible to treat nonequilibrium phenomena such as nucleation of the supersaturated vapor, for which the effect of the cluster structural transition is likely to be significant.
PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1
DOE Office of Scientific and Technical Information (OSTI.GOV)
Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.
2014-04-01
We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1more » Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.« less
PRIMUS: Galaxy Clustering as a Function of Luminosity and Color at 0.2 < z < 1
NASA Astrophysics Data System (ADS)
Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Moustakas, John; Aird, James; Blanton, Michael R.; Bray, Aaron D.; Cool, Richard J.; Eisenstein, Daniel J.; Mendez, Alexander J.; Wong, Kenneth C.; Zhu, Guangtun
2014-04-01
We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(rp , π) and wp (rp ), using volume-limited samples constructed from a parent sample of over ~130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg2 of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h -1 < rp < 1 Mpc h -1) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b gal ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ~ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that "cosmic variance" can be a significant source of uncertainty for high-redshift clustering measurements.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics
NASA Astrophysics Data System (ADS)
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.
2018-02-01
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L
2018-02-07
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Theoretical study on the spectroscopic properties of CO3(*-).nH2O clusters: extrapolation to bulk.
Pathak, Arup K; Mukherjee, Tulsi; Maity, Dilip K
2008-10-24
Vertical detachment energies (VDE) and UV/Vis absorption spectra of hydrated carbonate radical anion clusters, CO(3)(*-).nH(2)O (n=1-8), are determined by means of ab initio electronic structure theory. The VDE values of the hydrated clusters are calculated with second-order Moller-Plesset perturbation (MP2) and coupled cluster theory using the 6-311++G(d,p) set of basis functions. The bulk VDE value of an aqueous carbonate radical anion solution is predicted to be 10.6 eV from the calculated weighted average VDE values of the CO(3)(*-).nH(2)O clusters. UV/Vis absorption spectra of the hydrated clusters are calculated by means of time-dependent density functional theory using the Becke three-parameter nonlocal exchange and the Lee-Yang-Parr nonlocal correlation functional (B3LYP). The simulated UV/Vis spectrum of the CO(3)(*-).8H(2)O cluster is in excellent agreement with the reported experimental spectrum for CO(3)(*-) (aq), obtained based on pulse radiolysis experiments.
Testing light-traces-mass in Hubble Frontier Fields Cluster MACS-J0416.1-2403
Sebesta, Kevin; Williams, Liliya L. R.; Mohammed, Irshad; ...
2016-06-17
Here, we reconstruct the projected mass distribution of a massive merging Hubble Frontier Fields cluster MACSJ0416 using the genetic algorithm based free-form technique called Grale. The reconstructions are constrained by 149 lensed images identified by Jauzac et al. using HFF data. No information about cluster galaxies or light is used, which makes our reconstruction unique in this regard. Using visual inspection of the maps, as well as galaxy-mass correlation functions we conclude that overall light does follow mass. Furthermore, the fact that brighter galaxies are more strongly clustered with mass is an important confirmation of the standard biasing scenario inmore » galaxy clusters. On the smallest scales, approximately less than a few arcseconds, the resolution afforded by 149 images is still not sufficient to confirm or rule out galaxy-mass offsets of the kind observed in ACO 3827. We also compare the mass maps of MACSJ0416 obtained by three different groups: Grale, and two parametric Lenstool reconstructions from the CATS and Sharon/Johnson teams. Overall, the three agree well; one interesting discrepancy between Grale and Lenstool galaxy-mass correlation functions occurs on scales of tens of kpc and may suggest that cluster galaxies are more biased tracers of mass than parametric methods generally assume.« less
Testing light-traces-mass in Hubble Frontier Fields Cluster MACS-J0416.1-2403
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sebesta, Kevin; Williams, Liliya L. R.; Mohammed, Irshad
Here, we reconstruct the projected mass distribution of a massive merging Hubble Frontier Fields cluster MACSJ0416 using the genetic algorithm based free-form technique called Grale. The reconstructions are constrained by 149 lensed images identified by Jauzac et al. using HFF data. No information about cluster galaxies or light is used, which makes our reconstruction unique in this regard. Using visual inspection of the maps, as well as galaxy-mass correlation functions we conclude that overall light does follow mass. Furthermore, the fact that brighter galaxies are more strongly clustered with mass is an important confirmation of the standard biasing scenario inmore » galaxy clusters. On the smallest scales, approximately less than a few arcseconds, the resolution afforded by 149 images is still not sufficient to confirm or rule out galaxy-mass offsets of the kind observed in ACO 3827. We also compare the mass maps of MACSJ0416 obtained by three different groups: Grale, and two parametric Lenstool reconstructions from the CATS and Sharon/Johnson teams. Overall, the three agree well; one interesting discrepancy between Grale and Lenstool galaxy-mass correlation functions occurs on scales of tens of kpc and may suggest that cluster galaxies are more biased tracers of mass than parametric methods generally assume.« less
Significance tests for functional data with complex dependence structure.
Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J
2015-01-01
We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.
THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.
The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less
Evolution of Clustering of Starburst Galaxies in the COSMOS Field
NASA Astrophysics Data System (ADS)
Tribiano, S. M.; Paglione, T. A. D.; Shopbell, P. L.; Capek, P.; Liu, C.; Tyson, N. D.; COSMOS Team
2005-12-01
We measure the angular and spatial correlation function, ω (θ ) on scales of θ = 3" - 300" and ξ (r) on scales of 1-25 h-1 Mpc of 18,801 starburst galaxies (SBGs) with 20 < i+AB < 25 in the COSMOS Field and compare to the correlation functions of the full galaxy sample (180,451 objects) over 0 < z ≤ 2.4. We find in all redshift slices of thickness dz = 0.4, except 0.8 < z ≤ 1.2 for ω (θ ) only, that the amplitude of the clustering of SBGs is greater than that of the full galaxy sample. We report results of fits to a power law profile, measured correlation lengths, and discuss implications for starburst environments. This work is supported by the CUNY Community College Collaborative Research Incentive Grant and the American Museum of Natural History.
High Level ab initio Predictions of the Energetics of mCO2•(H2O)n (n = 1-3, m = 1-12) Clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thanthiriwatte, Sahan; Duke, Jessica R.; Jackson, Virgil E.
Electronic structure calculations at the correlated molecular orbital theory and density functional theory levels have been used to generate a reliable set of clustering energies for up to three water molecules in carbon dioxide clusters up to n = 12. The structures and energetics are dominated by Lewis acid-base interactions with hydrogen bonding interactions playing a lesser energetic role. The actual binding energies are somewhat larger than might be expected. The correlated molecular orbital MP2 method and density functional theory with the ωB97X exchange-correlation functional provide good results for the energetics of the clusters but the B3LYP and ωB97X-D functionalsmore » do not. Seven CO2 molecules form the first solvent shell about a single H2O with four CO2 molecules interacting with the H2O via Lewis acid-base interactions, two CO2 interacting with the H2O by hydrogen bonds, and the seventh CO2 completing the shell. The Lewis acid-base and weak hydrogen bond interactions between the water molecules and the CO2 molecules are strong enough to disrupt the trimer ring configuration for as few as seven CO2 molecules. Calculated 13C NMR chemical shifts for mCO2•(H2O)n show little change with respect to the number of H2O or CO2 molecules in the cluster. The O-H stretching frequencies do exhibit shifts that can provide information about the interactions between water and CO2 molecules.« less
The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grasha, K.; Calzetti, D.; Adamo, A.
We present a study of the hierarchical clustering of the young stellar clusters in six local (3–15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. Themore » strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ∼40–60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.« less
Anatomical relationships between serotonin 5-HT2A and dopamine D2 receptors in living human brain.
Ishii, Tatsuya; Kimura, Yasuyuki; Ichise, Masanori; Takahata, Keisuke; Kitamura, Soichiro; Moriguchi, Sho; Kubota, Manabu; Zhang, Ming-Rong; Yamada, Makiko; Higuchi, Makoto; Okubo, Yoshinori; Suhara, Tetsuya
2017-01-01
Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.
Tanaka, Nao; Hasui, Chieko; Uji, Masayo; Hiramura, Hidetoshi; Chen, Zi; Shikai, Noriko; Kitamura, Toshinori
2008-02-01
To identify the psychosocial correlates of adolescents. Unmarried university students (n = 4226) aged 18-23 years were examined in a questionnaire survey. Four clusters of people (indifferent, secure, fearful, and preoccupied) identified by cluster analysis were plotted in 2-D using discriminant function analysis with the first function (father's and mother's Care, Cooperativeness, and family Cohesion on the positive end and Harm Avoidance and father's and mother's Overprotection on the negative end) representing the Self-model and the second function (Reward Dependence and experience of Peer Victimization on the positive end and Self-directedness on the negative end) representing the Other model. These findings partially support Bartholomew's notion that adult attachment is based on the good versus bad representations of the self and the other and that it is influenced by psychosocial environments experienced over the course of development.
Analysis of correlated mutations in HIV-1 protease using spectral clustering.
Liu, Ying; Eyal, Eran; Bahar, Ivet
2008-05-15
The ability of human immunodeficiency virus-1 (HIV-1) protease to develop mutations that confer multi-drug resistance (MDR) has been a major obstacle in designing rational therapies against HIV. Resistance is usually imparted by a cooperative mechanism that can be elucidated by a covariance analysis of sequence data. Identification of such correlated substitutions of amino acids may be obscured by evolutionary noise. HIV-1 protease sequences from patients subjected to different specific treatments (set 1), and from untreated patients (set 2) were subjected to sequence covariance analysis by evaluating the mutual information (MI) between all residue pairs. Spectral clustering of the resulting covariance matrices disclosed two distinctive clusters of correlated residues: the first, observed in set 1 but absent in set 2, contained residues involved in MDR acquisition; and the second, included those residues differentiated in the various HIV-1 protease subtypes, shortly referred to as the phylogenetic cluster. The MDR cluster occupies sites close to the central symmetry axis of the enzyme, which overlap with the global hinge region identified from coarse-grained normal-mode analysis of the enzyme structure. The phylogenetic cluster, on the other hand, occupies solvent-exposed and highly mobile regions. This study demonstrates (i) the possibility of distinguishing between the correlated substitutions resulting from neutral mutations and those induced by MDR upon appropriate clustering analysis of sequence covariance data and (ii) a connection between global dynamics and functional substitution of amino acids.
NASA Astrophysics Data System (ADS)
Champagne, Benoı̂t; Botek, Edith; Nakano, Masayoshi; Nitta, Tomoshige; Yamaguchi, Kizashi
2005-03-01
The basis set and electron correlation effects on the static polarizability (α) and second hyperpolarizability (γ) are investigated ab initio for two model open-shell π-conjugated systems, the C5H7 radical and the C6H8 radical cation in their doublet state. Basis set investigations evidence that the linear and nonlinear responses of the radical cation necessitate the use of a less extended basis set than its neutral analog. Indeed, double-zeta-type basis sets supplemented by a set of d polarization functions but no diffuse functions already provide accurate (hyper)polarizabilities for C6H8 whereas diffuse functions are compulsory for C5H7, in particular, p diffuse functions. In addition to the 6-31G*+pd basis set, basis sets resulting from removing not necessary diffuse functions from the augmented correlation consistent polarized valence double zeta basis set have been shown to provide (hyper)polarizability values of similar quality as more extended basis sets such as augmented correlation consistent polarized valence triple zeta and doubly augmented correlation consistent polarized valence double zeta. Using the selected atomic basis sets, the (hyper)polarizabilities of these two model compounds are calculated at different levels of approximation in order to assess the impact of including electron correlation. As a function of the method of calculation antiparallel and parallel variations have been demonstrated for α and γ of the two model compounds, respectively. For the polarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset methods bracket the reference value obtained at the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples level whereas the projected unrestricted second-order Møller-Plesset results are in much closer agreement with the unrestricted coupled cluster singles and doubles with a perturbative inclusion of the triples values than the projected unrestricted Hartree-Fock results. Moreover, the differences between the restricted open-shell Hartree-Fock and restricted open-shell second-order Møller-Plesset methods are small. In what concerns the second hyperpolarizability, the unrestricted Hartree-Fock and unrestricted second-order Møller-Plesset values remain of similar quality while using spin-projected schemes fails for the charged system but performs nicely for the neutral one. The restricted open-shell schemes, and especially the restricted open-shell second-order Møller-Plesset method, provide for both compounds γ values close to the results obtained at the unrestricted coupled cluster level including singles and doubles with a perturbative inclusion of the triples. Thus, to obtain well-converged α and γ values at low-order electron correlation levels, the removal of spin contamination is a necessary but not a sufficient condition. Density-functional theory calculations of α and γ have also been carried out using several exchange-correlation functionals. Those employing hybrid exchange-correlation functionals have been shown to reproduce fairly well the reference coupled cluster polarizability and second hyperpolarizability values. In addition, inclusion of Hartree-Fock exchange is of major importance for determining accurate polarizability whereas for the second hyperpolarizability the gradient corrections are large.
Exact hierarchical clustering in one dimension. [in universe
NASA Technical Reports Server (NTRS)
Williams, B. G.; Heavens, A. F.; Peacock, J. A.; Shandarin, S. F.
1991-01-01
The present adhesion model-based one-dimensional simulations of gravitational clustering have yielded bound-object catalogs applicable in tests of analytical approaches to cosmological structure formation. Attention is given to Press-Schechter (1974) type functions, as well as to their density peak-theory modifications and the two-point correlation function estimated from peak theory. The extent to which individual collapsed-object locations can be predicted by linear theory is significant only for objects of near-characteristic nonlinear mass.
Christakou, Anastasia; Halari, Rozmin; Smith, Anna B; Ifkovits, Eve; Brammer, Mick; Rubia, Katya
2009-10-15
Developmental functional imaging studies of cognitive control show progressive age-related increase in task-relevant fronto-striatal activation in male development from childhood to adulthood. Little is known, however, about how gender affects this functional development. In this study, we used event related functional magnetic resonance imaging to examine effects of sex, age, and their interaction on brain activation during attentional switching and interference inhibition, in 63 male and female adolescents and adults, aged 13 to 38. Linear age correlations were observed across all subjects in task-specific frontal, striatal and temporo-parietal activation. Gender analysis revealed increased activation in females relative to males in fronto-striatal areas during the Switch task, and laterality effects in the Simon task, with females showing increased left inferior prefrontal and temporal activation, and males showing increased right inferior prefrontal and parietal activation. Increased prefrontal activation clusters in females and increased parietal activation clusters in males furthermore overlapped with clusters that were age-correlated across the whole group, potentially reflecting more mature prefrontal brain activation patterns for females, and more mature parietal activation patterns for males. Gender by age interactions further supported this dissociation, revealing exclusive female-specific age correlations in inferior and medial prefrontal brain regions during both tasks, and exclusive male-specific age correlations in superior parietal (Switch task) and temporal regions (Simon task). These findings show increased recruitment of age-correlated prefrontal activation in females, and of age-correlated parietal activation in males, during tasks of cognitive control. Gender differences in frontal and parietal recruitment may thus be related to gender differences in the neurofunctional maturation of these brain regions.
Lewis, Scott M.; Christova, Peka; Jerde, Trenton A.; Georgopoulos, Apostolos P.
2012-01-01
We used hierarchical tree clustering to derive a functional organizational chart of 52 human cortical areas (26 per hemisphere) from zero-lag correlations calculated between single-voxel, prewhitened, resting-state BOLD fMRI time series in 18 subjects. No special “resting-state networks” were identified. There were four major features in the resulting tree (dendrogram). First, there was a strong clustering of homotopic, left-right hemispheric areas. Second, cortical areas were concatenated in multiple, partially overlapping clusters. Third, the arrangement of the areas revealed a layout that closely resembled the actual layout of the cerebral cortex, namely an orderly progression from anterior to posterior. And fourth, the layout of the cortical areas in the tree conformed to principles of efficient, compact layout of components proposed by Cherniak. Since the tree was derived on the basis of the strength of neural correlations, these results document an orderly relation between functional interactions and layout, i.e., between structure and function. PMID:22973198
NASA Astrophysics Data System (ADS)
Bordbar, G. H.; Hosseini, S.; Poostforush, A.
2017-05-01
Correlations in quantum fluids such as liquid 3He continue to be of high interest to scientists. Based on this prospect, the present work is devoted to study the effects of spin-spin correlation function on the thermodynamic properties of polarized liquid 3He such as pressure, velocity of sound, adiabatic index and adiabatic compressibility along different isentropic paths, using the Lennard-Jones potential and employing the variational approach based on cluster expansion of the energy functional. The inclusion of this correlation improves our previous calculations and leads to good agreements with experimental results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Niu, Shuqiang; Ichiye, Toshiko
A central issue in understanding redox properties of iron-sulfur proteins is determining the factors that tune the reduction potentials of the Fe-S clusters. Recently, Solomon and coworkers have shown that the Fe-S bond covalency of protein analogs measured by %L, the percent ligand character of the Fe 3d orbitals, from ligand K-edge X-ray absorption spectroscopy (XAS) correlates with the electrochemical redox potentials. Also, Wang and coworkers have measured electron detachment energies for iron-sulfur clusters without environmental perturbations by gas-phase photoelectron spectroscopy (PES). Here the correlations of the ligand character with redox energy and %L character are examined in [Fe₄S₄L₄]2⁻ clustersmore » with different ligands by broken symmetry density functional theory (BS-DFT) calculations using the B3LYP functional together with PES and XAS experimental results. These gas-phase studies assess ligand effects independently of environmental perturbations and thus provide essential information for computational studies of iron-sulfur proteins. The B3LYP oxidation energies agree well with PES data, and the %L character obtained from natural bond orbital analysis correlates with XAS values, although it systematically underestimates them because of basis set effects. The results show that stronger electron-donating terminal ligands increase %Lt, the percent ligand character from terminal ligands, but decrease %Sb, the percent ligand character from the bridging sulfurs. Because the oxidized orbital has significant Fe-Lt antibonding character, the oxidation energy correlates well with %Lt. However, because the reduced orbital has varying contributions of both Fe-Lt and Fe-Sb antibonding character, the reduction energy does not correlate with either %Lt or %Sb. Overall, BSDFT calculations together with XAS and PES experiments can unravel the complex underlying factors in the redox energy and chemical bonding of the [4Fe-4S] clusters in iron-sulfur proteins.« less
Gritsenko, Valeriya; Hardesty, Russell L; Boots, Mathew T; Yakovenko, Sergiy
2016-01-01
Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.
The cluster model of a hot dense vapor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhukhovitskii, D. I., E-mail: dmr@ihed.ras.ru
2015-04-28
We explore thermodynamic properties of a vapor in the range of state parameters where the contribution to thermodynamic functions from bound states of atoms (clusters) dominates over the interaction between the components of the vapor in free states. The clusters are assumed to be light and sufficiently “hot” for the number of bonds to be minimized. We use the technique of calculation of the cluster partition function for the cluster with a minimum number of interatomic bonds to calculate the caloric properties (heat capacity and velocity of sound) for an ideal mixture of the lightest clusters. The problem proves tomore » be exactly solvable and resulting formulas are functions solely of the equilibrium constant of the dimer formation. These formulas ensure a satisfactory correlation with the reference data for the vapors of cesium, mercury, and argon up to moderate densities in both the sub- and supercritical regions. For cesium, we extend the model to the densities close to the critical one by inclusion of the clusters of arbitrary size. Knowledge of the cluster composition of the cesium vapor makes it possible to treat nonequilibrium phenomena such as nucleation of the supersaturated vapor, for which the effect of the cluster structural transition is likely to be significant.« less
Symptom clusters in patients with nasopharyngeal carcinoma during radiotherapy.
Xiao, Wenli; Chan, Carmen W H; Fan, Yuying; Leung, Doris Y P; Xia, Weixiong; He, Yan; Tang, Linquan
2017-06-01
Despite the improvement in radiotherapy (RT) technology, patients with nasopharyngeal carcinoma (NPC) still suffer from numerous distressing symptoms simultaneously during RT. The purpose of the study was to investigate the symptom clusters experienced by NPC patients during RT. First-treated Chinese NPC patients (n = 130) undergoing late-period RT (from week 4 till the end) were recruited for this cross-sectional study. They completed a sociodemographic and clinical data questionnaire, the Chinese version of the M. D. Anderson Symptom Inventory - Head and Neck Module (MDASI-HN-C) and the Chinese version of the Functional Assessment of Cancer Therapy - Head and Neck Scale (FACT-H&N-C). Principal axis factor analysis with oblimin rotation, independent t-test, one-way analysis of variance (ANOVA) and Pearson product-moment correlation were used to analyze the data. Four symptom clusters were identified, and labelled general, gastrointestinal, nutrition impact and social interaction impact. Of these 4 types, the nutrition impact symptom cluster was the most severe. Statistically positive correlations were found between severity of all 4 symptom clusters and symptom interference, as well as weight loss. Statistically negative correlations were detected between the cluster severity and the QOL total score and 3 out of 5 subscale scores. The four clusters identified reveal the symptom patterns experienced by NPC patients during RT. Future intervention studies on managing these symptom clusters are warranted, especially for the nutrition impact symptom cluster. Copyright © 2017 Elsevier Ltd. All rights reserved.
Schramm-Loewner evolution and perimeter of percolation clusters of correlated random landscapes.
de Castro, C P; Luković, M; Pompanin, G; Andrade, R F S; Herrmann, H J
2018-03-27
Motivated by the fact that many physical landscapes are characterized by long-range height-height correlations that are quantified by the Hurst exponent H, we investigate the statistical properties of the iso-height lines of correlated surfaces in the framework of Schramm-Loewner evolution (SLE). We show numerically that in the continuum limit the external perimeter of a percolating cluster of correlated surfaces with H ∈ [-1, 0] is statistically equivalent to SLE curves. Our results suggest that the external perimeter also retains the Markovian properties, confirmed by the absence of time correlations in the driving function and the fact that the latter is Gaussian distributed for any specific time. We also confirm that for all H the variance of the winding angle grows logarithmically with size.
FAST TRACK COMMUNICATION A DFT + DMFT approach for nanosystems
NASA Astrophysics Data System (ADS)
Turkowski, Volodymyr; Kabir, Alamgir; Nayyar, Neha; Rahman, Talat S.
2010-11-01
We propose a combined density-functional-theory-dynamical-mean-field-theory (DFT + DMFT) approach for reliable inclusion of electron-electron correlation effects in nanosystems. Compared with the widely used DFT + U approach, this method has several advantages, the most important of which is that it takes into account dynamical correlation effects. The formalism is illustrated through different calculations of the magnetic properties of a set of small iron clusters (number of atoms 2 <= N <= 5). It is shown that the inclusion of dynamical effects leads to a reduction in the cluster magnetization (as compared to results from DFT + U) and that, even for such small clusters, the magnetization values agree well with experimental estimations. These results justify confidence in the ability of the method to accurately describe the magnetic properties of clusters of interest to nanoscience.
Competing risks regression for clustered data
Zhou, Bingqing; Fine, Jason; Latouche, Aurelien; Labopin, Myriam
2012-01-01
A population average regression model is proposed to assess the marginal effects of covariates on the cumulative incidence function when there is dependence across individuals within a cluster in the competing risks setting. This method extends the Fine–Gray proportional hazards model for the subdistribution to situations, where individuals within a cluster may be correlated due to unobserved shared factors. Estimators of the regression parameters in the marginal model are developed under an independence working assumption where the correlation across individuals within a cluster is completely unspecified. The estimators are consistent and asymptotically normal, and variance estimation may be achieved without specifying the form of the dependence across individuals. A simulation study evidences that the inferential procedures perform well with realistic sample sizes. The practical utility of the methods is illustrated with data from the European Bone Marrow Transplant Registry. PMID:22045910
NASA Astrophysics Data System (ADS)
Häberlen, Oliver D.; Chung, Sai-Cheong; Stener, Mauro; Rösch, Notker
1997-03-01
A series of gold clusters spanning the size range from Au6 through Au147 (with diameters from 0.7 to 1.7 nm) in icosahedral, octahedral, and cuboctahedral structure has been theoretically investigated by means of a scalar relativistic all-electron density functional method. One of the main objectives of this work was to analyze the convergence of cluster properties toward the corresponding bulk metal values and to compare the results obtained for the local density approximation (LDA) to those for a generalized gradient approximation (GGA) to the exchange-correlation functional. The average gold-gold distance in the clusters increases with their nuclearity and correlates essentially linearly with the average coordination number in the clusters. An extrapolation to the bulk coordination of 12 yields a gold-gold distance of 289 pm in LDA, very close to the experimental bulk value of 288 pm, while the extrapolated GGA gold-gold distance is 297 pm. The cluster cohesive energy varies linearly with the inverse of the calculated cluster radius, indicating that the surface-to-volume ratio is the primary determinant of the convergence of this quantity toward bulk. The extrapolated LDA binding energy per atom, 4.7 eV, overestimates the experimental bulk value of 3.8 eV, while the GGA value, 3.2 eV, underestimates the experiment by almost the same amount. The calculated ionization potentials and electron affinities of the clusters may be related to the metallic droplet model, although deviations due to the electronic shell structure are noticeable. The GGA extrapolation to bulk values yields 4.8 and 4.9 eV for the ionization potential and the electron affinity, respectively, remarkably close to the experimental polycrystalline work function of bulk gold, 5.1 eV. Gold 4f core level binding energies were calculated for sites with bulk coordination and for different surface sites. The core level shifts for the surface sites are all positive and distinguish among the corner, edge, and face-centered sites; sites in the first subsurface layer show still small positive shifts.
NASA Astrophysics Data System (ADS)
Hafizi, Roohollah; Hashemifar, S. Javad; Alaei, Mojtaba; Jangrouei, MohammadReza; Akbarzadeh, Hadi
2016-12-01
In this paper, we employ an evolutionary algorithm along with the full-potential density functional theory (DFT) computations to perform a comprehensive search for the stable structures of stoichiometric (WS2)n nano-clusters (n = 1 - 9), within three different exchange-correlation functionals. Our results suggest that n = 5 and 8 are possible candidates for the low temperature magic sizes of WS2 nano-clusters while at temperatures above 500 Kelvin, n = 7 exhibits a comparable relative stability with n = 8. The electronic properties and energy gap of the lowest energy isomers were computed within several schemes, including semilocal Perdew-Burke-Ernzerhof and Becke-Lee-Yang-Parr functionals, hybrid B3LYP functional, many body based DFT+GW approach, ΔSCF method, and time dependent DFT calculations. Vibrational spectra of the lowest lying isomers, computed by the force constant method, are used to address IR spectra and thermal free energy of the clusters. Time dependent density functional calculation in a real time domain is applied to determine the full absorption spectra and optical gap of the lowest energy isomers of the WS2 nano-clusters.
Doering, Stephan; Burgmer, Markus; Heuft, Gereon; Menke, Dina; Bäumer, Brigitta; Lübking, Margit; Feldmann, Marcus; Schneider, Gudrun
2014-01-01
The assessment of personality functioning has recently become a focus of psychiatric diagnostics. The interview-based Operationalized Psychodynamic Diagnosis (OPD-2) provides a 'structure axis' for the assessment of personality functioning. One hundred twenty-four psychiatric patients were diagnosed by means of the Structured Clinical Interviews for DSM-IV (SCID-I and SCID-II), underwent OPD-2 interviews, and completed 9 questionnaires. The OPD-2 structure axis shows good interrater reliability (intraclass correlation = 0.793). Correlations between the OPD-2 structure axis domains and a priori selected questionnaire scales were of medium size and significant. Patients with a personality disorder (PD) showed significantly worse personality functioning than those without. In cluster B PD, personality functioning was more severely impaired than in cluster C PD. The OPD-2 structure axis shows good reliability as well as concurrent and discriminant validity and can be recommended for clinical use and research purposes. © 2013 S. Karger AG, Basel.
Density-functional theory applied to d- and f-electron systems
NASA Astrophysics Data System (ADS)
Wu, Xueyuan
Density functional theory (DFT) has been applied to study the electronic and geometric structures of prototype d- and f-electron systems. For the d-electron system, all electron DFT with gradient corrections to the exchange and correlation functionals has been used to investigate the properties of small neutral and cationic vanadium clusters. Results are in good agreement with available experimental and other theoretical data. For the f-electron system, a hybrid DFT, namely, B3LYP (Becke's 3-parameter hybrid functional using the correlation functional of Lee, Yang and Parr) with relativistic effective core potentials and cluster models has been applied to investigate the nature of chemical bonding of both the bulk and the surfaces of plutonium monoxide and dioxide. Using periodic models, the electronic and geometric structures of PuO2 and its (110) surface, as well as water adsorption on this surface have also been investigated using DFT in both local density approximation (LDA) and generalized gradient approximation (GGA) formalisms.
Electronic and magnetic properties of small rhodium clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Soon, Yee Yeen; Yoon, Tiem Leong; Lim, Thong Leng
2015-04-24
We report a theoretical study of the electronic and magnetic properties of rhodium-atomic clusters. The lowest energy structures at the semi-empirical level of rhodium clusters are first obtained from a novel global-minimum search algorithm, known as PTMBHGA, where Gupta potential is used to describe the atomic interaction among the rhodium atoms. The structures are then re-optimized at the density functional theory (DFT) level with exchange-correlation energy approximated by Perdew-Burke-Ernzerhof generalized gradient approximation. For the purpose of calculating the magnetic moment of a given cluster, we calculate the optimized structure as a function of the spin multiplicity within the DFT framework.more » The resultant magnetic moments with the lowest energies so obtained allow us to work out the magnetic moment as a function of cluster size. Rhodium atomic clusters are found to display a unique variation in the magnetic moment as the cluster size varies. However, Rh{sub 4} and Rh{sub 6} are found to be nonmagnetic. Electronic structures of the magnetic ground-state structures are also investigated within the DFT framework. The results are compared against those based on different theoretical approaches available in the literature.« less
Assessment of the vision-specific quality of life using clustered visual field in glaucoma patients.
Sawada, Hideko; Yoshino, Takaiko; Fukuchi, Takeo; Abe, Haruki
2014-02-01
To investigate the significance of vision-specific quality of life (QOL) in glaucoma patients based on the location of visual field defects. We examined 336 eyes of 168 patients. The 25-item National Eye Institute Visual Function Questionnaire was used to evaluate patients' QOL. Visual field testing was performed using the Humphrey Field Analyzer; the visual field was divided into 10 clusters. We defined the eye with better mean deviation as the better eye and the fellow eye as the worse eye. A single linear regression analysis was applied to assess the significance of the relationship between QOL and the clustered visual field. The strongest correlation was observed in the lower paracentral visual field in the better eye. The lower peripheral visual field in the better eye also showed a good correlation. Correlation coefficients in the better eye were generally higher than those in the worse eye. For driving, the upper temporal visual field in the better eye was the most strongly correlated (r=0.509). For role limitation and peripheral vision, the lower peripheral visual field in the better eye had the highest correlation coefficients at 0.459 and 0.425, respectively. Overall, clusters in the lower hemifield in the better eye were more strongly correlated with QOL than those in the worse eye. In particular, the lower paracentral visual field in the better eye was correlated most strongly of all. Driving, however, strongly correlated with the upper hemifield in the better eye.
Grabowski, Ireneusz; Teale, Andrew M; Śmiga, Szymon; Bartlett, Rodney J
2011-09-21
The framework of ab initio density-functional theory (DFT) has been introduced as a way to provide a seamless connection between the Kohn-Sham (KS) formulation of DFT and wave-function based ab initio approaches [R. J. Bartlett, I. Grabowski, S. Hirata, and S. Ivanov, J. Chem. Phys. 122, 034104 (2005)]. Recently, an analysis of the impact of dynamical correlation effects on the density of the neon atom was presented [K. Jankowski, K. Nowakowski, I. Grabowski, and J. Wasilewski, J. Chem. Phys. 130, 164102 (2009)], contrasting the behaviour for a variety of standard density functionals with that of ab initio approaches based on second-order Møller-Plesset (MP2) and coupled cluster theories at the singles-doubles (CCSD) and singles-doubles perturbative triples [CCSD(T)] levels. In the present work, we consider ab initio density functionals based on second-order many-body perturbation theory and coupled cluster perturbation theory in a similar manner, for a range of small atomic and molecular systems. For comparison, we also consider results obtained from MP2, CCSD, and CCSD(T) calculations. In addition to this density based analysis, we determine the KS correlation potentials corresponding to these densities and compare them with those obtained for a range of ab initio density functionals via the optimized effective potential method. The correlation energies, densities, and potentials calculated using ab initio DFT display a similar systematic behaviour to those derived from electronic densities calculated using ab initio wave function theories. In contrast, typical explicit density functionals for the correlation energy, such as VWN5 and LYP, do not show behaviour consistent with this picture of dynamical correlation, although they may provide some degree of correction for already erroneous explicitly density-dependent exchange-only functionals. The results presented here using orbital dependent ab initio density functionals show that they provide a treatment of exchange and correlation contributions within the KS framework that is more consistent with traditional ab initio wave function based methods.
Monitoring Wetland Hydro-dynamics in the Prairie Pothole Region Using Landsat Time Series
NASA Astrophysics Data System (ADS)
Zhou, Q.; Rover, J.; Gallant, A.
2017-12-01
Wetlands provide a variety of ecosystem functions, while it is spatially and temporally dynamic. We mapped the dynamics of wetlands in the North Dakota Prairie Pothole Region using all available clear observations of Landsat sensor data from 1985 to 2014. We used a cluster analysis to group pixels exhibiting similar long-term spectral trends over seven Landsat bands, then applied the tasseled-cap transformation to evaluate the temporal characteristics of brightness, greenness, and wetness for each cluster. We tested relations between these three indices and hydrologic conditions, as represented by the Palmer Hydrological Drought Index (PHDI), using the cross-correlation analysis for each cluster performed over an eight-year moving window for the 30 years covered by the study. This temporal window size coincided with the timing of a major shift from a prolonged drought that occurred within the first eight years of the study period to wetter conditions that prevailed throughout the remaining years. The 20 cluster we produced represented a gradient from locations that continuously held water throughout the study period to locations that, at most, held water only for short periods in some years. The spatial distribution of the cluster groups reflected patterns of regional geologic and geomorphologic features. Comparisons of the PHDI to tasseled-cap wetness were the most straightforward to interpret among the results from the three indices. Wetness for most cluster groups had high positive correlations with PHDI during drought years, with the correlations reduced as the landscape entered a lengthy, wetter period; however, wetness generally remained highly and positively correlated with PHDI across all years for four cluster groups where the area exhibited two or more multi-year dry-wet cycles. These same four groups also had strong, generally negative correlations with tasseled-cap brightness. For other cluster groups, brightness often was strongly negatively correlated with the PHDI during the drought years, with the relation weakening for subsequent years of adequate or high moisture. Relations between tasseled-cap greenness and PHDI were highly variable among and within cluster groups. Results from this analysis support ongoing efforts to develop new products that characterize wetland dynamics.
Effects of cluster-shell competition and BCS-like pairing in 12C
NASA Astrophysics Data System (ADS)
Matsuno, H.; Itagaki, N.
2017-12-01
The antisymmetrized quasi-cluster model (AQCM) was proposed to describe α-cluster and jj-coupling shell models on the same footing. In this model, the cluster-shell transition is characterized by two parameters, R representing the distance between α clusters and Λ describing the breaking of α clusters, and the contribution of the spin-orbit interaction, very important in the jj-coupling shell model, can be taken into account starting with the α-cluster model wave function. Not only the closure configurations of the major shells but also the subclosure configurations of the jj-coupling shell model can be described starting with the α-cluster model wave functions; however, the particle-hole excitations of single particles have not been fully established yet. In this study we show that the framework of AQCM can be extended even to the states with the character of single-particle excitations. For ^{12}C, two-particle-two-hole (2p2h) excitations from the subclosure configuration of 0p_{3/2} corresponding to a BCS-like pairing are described, and these shell model states are coupled with the three α-cluster model wave functions. The correlation energy from the optimal configuration can be estimated not only in the cluster part but also in the shell model part. We try to pave the way to establish a generalized description of the nuclear structure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whitmore, Bradley C.; Bowers, Ariel S.; Lindsay, Kevin
2014-04-01
Luminosity functions (LFs) have been determined for star cluster populations in 20 nearby (4-30 Mpc), star-forming galaxies based on Advanced Camera for Surveys source lists generated by the Hubble Legacy Archive (HLA). These cluster catalogs provide one of the largest sets of uniform, automatically generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster LF can be approximated by a power law, dN/dL∝L {sup α}, with an average value for α ofmore » –2.37 and rms scatter = 0.18 when using the F814W ('I') band. A comparison of fitting results based on methods that use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum likelihood) method to give slightly more negative values of α for galaxies with steeper LFs. We find that galaxies with high rates of star formation (or equivalently, with the brightest or largest numbers of clusters) have a slight tendency to have shallower values of α. In particular, the Antennae galaxy (NGC 4038/39), a merging system with a relatively high star formation rate (SFR), has the second flattest LF in the sample. A tentative correlation may also be present between Hubble type and values of α, in the sense that later type galaxies (i.e., Sd and Sm) appear to have flatter LFs. Hence, while there do appear to be some weak correlations, the relative similarity in the values of α for a large number of star-forming galaxies suggests that, to first order, the LFs are fairly universal. We examine the bright end of the LFs and find evidence for a downturn, although it only pertains to about 1% of the clusters. Our uniform database results in a small scatter (≈0.4 to 0.5 mag) in the correlation between the magnitude of the brightest cluster (M {sub brightest}) and log of the number of clusters brighter than M{sub I} = –9 (log N). We also examine the magnitude of the brightest cluster versus log SFR for a sample including both dwarf galaxies and ULIRGs. This shows that the correlation extends over roughly six orders of magnitude but with scatter that is larger than for our spiral sample, probably because of the high levels of extinction in many of the LIRGs.« less
Reconciling mass functions with the star-forming main sequence via mergers
NASA Astrophysics Data System (ADS)
Steinhardt, Charles L.; Yurk, Dominic; Capak, Peter
2017-06-01
We combine star formation along the 'main sequence', quiescence and clustering and merging to produce an empirical model for the evolution of individual galaxies. Main-sequence star formation alone would significantly steepen the stellar mass function towards low redshift, in sharp conflict with observation. However, a combination of star formation and merging produces a consistent result for correct choice of the merger rate function. As a result, we are motivated to propose a model in which hierarchical merging is disconnected from environmentally independent star formation. This model can be tested via correlation functions and would produce new constraints on clustering and merging.
Automated modal parameter estimation using correlation analysis and bootstrap sampling
NASA Astrophysics Data System (ADS)
Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.
2018-02-01
The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to a three-dimensional feature space to assign a degree of physicalness to each cluster. The proposed algorithm is applied to two case studies: one with synthetic data and one with real test data obtained from a hammer impact test. The results indicate that the algorithm successfully clusters similar modes and gives a reasonable quantification of the extent to which each cluster is physical.
Dynamic evolution of nearby galaxy clusters
NASA Astrophysics Data System (ADS)
Biernacka, M.; Flin, P.
2011-06-01
A study of the evolution of 377 rich ACO clusters with redshift z<0.2 is presented. The data concerning galaxies in the investigated clusters were obtained using FOCAS packages applied to Digital Sky Survey I. The 377 galaxy clusters constitute a statistically uniform sample to which visual galaxy/star reclassifications were applied. Cluster shape within 2.0 h-1 Mpc from the adopted cluster centre (the mean and the median of all galaxy coordinates, the position of the brightest and of the third brightest galaxy in the cluster) was determined through its ellipticity calculated using two methods: the covariance ellipse method (hereafter CEM) and the method based on Minkowski functionals (hereafter MFM). We investigated ellipticity dependence on the radius of circular annuli, in which ellipticity was calculated. This was realized by varying the radius from 0.5 to 2 Mpc in steps of 0.25 Mpc. By performing Monte Carlo simulations, we generated clusters to which the two ellipticity methods were applied. We found that the covariance ellipse method works better than the method based on Minkowski functionals. We also found that ellipticity distributions are different for different methods used. Using the ellipticity-redshift relation, we investigated the possibility of cluster evolution in the low-redshift Universe. The correlation of cluster ellipticities with redshifts is undoubtly an indicator of structural evolution. Using the t-Student statistics, we found a statistically significant correlation between ellipticity and redshift at the significance level of α = 0.95. In one of the two shape determination methods we found that ellipticity grew with redshift, while the other method gave opposite results. Monte Carlo simulations showed that only ellipticities calculated at the distance of 1.5 Mpc from cluster centre in the Minkowski functional method are robust enough to be taken into account, but for that radius we did not find any relation between e and z. Since CEM pointed towards the existence of the e(z) relation, we conclude that such an effect is real though rather weak. A detailed study of the e(z) relation showed that the observed relation is nonlinear, and the number of elongated structures grows rapidly for z>0.14.
On basis set superposition error corrected stabilization energies for large n-body clusters.
Walczak, Katarzyna; Friedrich, Joachim; Dolg, Michael
2011-10-07
In this contribution, we propose an approximate basis set superposition error (BSSE) correction scheme for the site-site function counterpoise and for the Valiron-Mayer function counterpoise correction of second order to account for the basis set superposition error in clusters with a large number of subunits. The accuracy of the proposed scheme has been investigated for a water cluster series at the CCSD(T), CCSD, MP2, and self-consistent field levels of theory using Dunning's correlation consistent basis sets. The BSSE corrected stabilization energies for a series of water clusters are presented. A study regarding the possible savings with respect to computational resources has been carried out as well as a monitoring of the basis set dependence of the approximate BSSE corrections. © 2011 American Institute of Physics
Emergence of jams in the generalized totally asymmetric simple exclusion process
NASA Astrophysics Data System (ADS)
Derbyshev, A. E.; Povolotsky, A. M.; Priezzhev, V. B.
2015-02-01
The generalized totally asymmetric exclusion process (TASEP) [J. Stat. Mech. (2012) P05014, 10.1088/1742-5468/2012/05/P05014] is an integrable generalization of the TASEP equipped with an interaction, which enhances the clustering of particles. The process interpolates between two extremal cases: the TASEP with parallel update and the process with all particles irreversibly merging into a single cluster moving as an isolated particle. We are interested in the large time behavior of this process on a ring in the whole range of the parameter λ controlling the interaction. We study the stationary state correlations, the cluster size distribution, and the large-time fluctuations of integrated particle current. When λ is finite, we find the usual TASEP-like behavior: The correlation length is finite; there are only clusters of finite size in the stationary state and current fluctuations belong to the Kardar-Parisi-Zhang universality class. When λ grows with the system size, so does the correlation length. We find a nontrivial transition regime with clusters of all sizes on the lattice. We identify a crossover parameter and derive the large deviation function for particle current, which interpolates between the case considered by Derrida-Lebowitz and a single-particle diffusion.
A phase cell cluster expansion for Euclidean field theories
NASA Astrophysics Data System (ADS)
Battle, Guy A., III; Federbush, Paul
1982-08-01
We adapt the cluster expansion first used to treat infrared problems for lattice models (a mass zero cluster expansion) to the usual field theory situation. The field is expanded in terms of special block spin functions and the cluster expansion given in terms of the expansion coefficients (phase cell variables); the cluster expansion expresses correlation functions in terms of contributions from finite coupled subsets of these variables. Most of the present work is carried through in d space time dimensions (for φ24 the details of the cluster expansion are pursued and convergence is proven). Thus most of the results in the present work will apply to a treatment of φ34 to which we hope to return in a succeeding paper. Of particular interest in this paper is a substitute for the stability of the vacuum bound appropriate to this cluster expansion (for d = 2 and d = 3), and a new method for performing estimates with tree graphs. The phase cell cluster expansions have the renormalization group incorporated intimately into their structure. We hope they will be useful ultimately in treating four dimensional field theories.
2012-01-01
Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154
Pereiro, M; Baldomir, D; Arias, J E
2011-02-28
Optical excitation spectra of Ag(n) and Ag(n)@He(60) (n = 2, 8) clusters are investigated in the framework of the time-dependent density functional theory (TDDFT) within the linear response regime. We have performed the ab initio calculations for two different exact exchange functionals (GGA-exact and LDA-exact). The computed spectra of Ag(n)@He(60) clusters with the GGA-exact functional accounting for exchange-correlation effects are found to be generally in a relatively good agreement with the experiment. A strategy is proposed to obtain the ground-state structures of the Ag(n)@He(60) clusters and in the initial process of the geometry optimization, the He environment is simulated with buckyballs. A redshift of the silver clusters spectra is observed in the He environment with respect to the ones of bare silver clusters. This observation is discussed and explained in terms of a contraction of the Ag-He bonding length and a consequent confinement of the s valence electrons in silver clusters. Likewise, the Mie-Gans predictions combined with our TDDFT calculations also show that the dielectric effect produced by the He matrix is considerably less important in explaining the redshifting observed in the optical spectra of Ag(n)@He(60) clusters.
Holmes, Sean T; Iuliucci, Robbie J; Mueller, Karl T; Dybowski, Cecil
2015-11-10
Calculations of the principal components of magnetic-shielding tensors in crystalline solids require the inclusion of the effects of lattice structure on the local electronic environment to obtain significant agreement with experimental NMR measurements. We assess periodic (GIPAW) and GIAO/symmetry-adapted cluster (SAC) models for computing magnetic-shielding tensors by calculations on a test set containing 72 insulating molecular solids, with a total of 393 principal components of chemical-shift tensors from 13C, 15N, 19F, and 31P sites. When clusters are carefully designed to represent the local solid-state environment and when periodic calculations include sufficient variability, both methods predict magnetic-shielding tensors that agree well with experimental chemical-shift values, demonstrating the correspondence of the two computational techniques. At the basis-set limit, we find that the small differences in the computed values have no statistical significance for three of the four nuclides considered. Subsequently, we explore the effects of additional DFT methods available only with the GIAO/cluster approach, particularly the use of hybrid-GGA functionals, meta-GGA functionals, and hybrid meta-GGA functionals that demonstrate improved agreement in calculations on symmetry-adapted clusters. We demonstrate that meta-GGA functionals improve computed NMR parameters over those obtained by GGA functionals in all cases, and that hybrid functionals improve computed results over the respective pure DFT functional for all nuclides except 15N.
Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias
NASA Astrophysics Data System (ADS)
Medezinski, Elinor; Battaglia, Nicholas; Coupon, Jean; Cen, Renyue; Gaspari, Massimo; Strauss, Michael A.; Spergel, David N.
2017-02-01
There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (I.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determining their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.
Testing the Large-scale Environments of Cool-core and Non-cool-core Clusters with Clustering Bias
DOE Office of Scientific and Technical Information (OSTI.GOV)
Medezinski, Elinor; Battaglia, Nicholas; Cen, Renyue
2017-02-10
There are well-observed differences between cool-core (CC) and non-cool-core (NCC) clusters, but the origin of this distinction is still largely unknown. Competing theories can be divided into internal (inside-out), in which internal physical processes transform or maintain the NCC phase, and external (outside-in), in which the cluster type is determined by its initial conditions, which in turn leads to different formation histories (i.e., assembly bias). We propose a new method that uses the relative assembly bias of CC to NCC clusters, as determined via the two-point cluster-galaxy cross-correlation function (CCF), to test whether formation history plays a role in determiningmore » their nature. We apply our method to 48 ACCEPT clusters, which have well resolved central entropies, and cross-correlate with the SDSS-III/BOSS LOWZ galaxy catalog. We find that the relative bias of NCC over CC clusters is b = 1.42 ± 0.35 (1.6 σ different from unity). Our measurement is limited by the small number of clusters with core entropy information within the BOSS footprint, 14 CC and 34 NCC clusters. Future compilations of X-ray cluster samples, combined with deep all-sky redshift surveys, will be able to better constrain the relative assembly bias of CC and NCC clusters and determine the origin of the bimodality.« less
NASA Astrophysics Data System (ADS)
Christodoulou, L.; Eminian, C.; Loveday, J.; Norberg, P.; Baldry, I. K.; Hurley, P. D.; Driver, S. P.; Bamford, S. P.; Hopkins, A. M.; Liske, J.; Peacock, J. A.; Bland-Hawthorn, J.; Brough, S.; Cameron, E.; Conselice, C. J.; Croom, S. M.; Frenk, C. S.; Gunawardhana, M.; Jones, D. H.; Kelvin, L. S.; Kuijken, K.; Nichol, R. C.; Parkinson, H.; Pimbblet, K. A.; Popescu, C. C.; Prescott, M.; Robotham, A. S. G.; Sharp, R. G.; Sutherland, W. J.; Taylor, E. N.; Thomas, D.; Tuffs, R. J.; van Kampen, E.; Wijesinghe, D.
2012-09-01
We measure the two-point angular correlation function of a sample of 4289 223 galaxies with r < 19.4 mag from the Sloan Digital Sky Survey (SDSS) as a function of photometric redshift, absolute magnitude and colour down to Mr - 5 log h = -14 mag. Photometric redshifts are estimated from ugriz model magnitudes and two Petrosian radii using the artificial neural network package ANNz, taking advantage of the Galaxy And Mass Assembly (GAMA) spectroscopic sample as our training set. These photometric redshifts are then used to determine absolute magnitudes and colours. For all our samples, we estimate the underlying redshift and absolute magnitude distributions using Monte Carlo resampling. These redshift distributions are used in Limber's equation to obtain spatial correlation function parameters from power-law fits to the angular correlation function. We confirm an increase in clustering strength for sub-L* red galaxies compared with ˜L* red galaxies at small scales in all redshift bins, whereas for the blue population the correlation length is almost independent of luminosity for ˜L* galaxies and fainter. A linear relation between relative bias and log luminosity is found to hold down to luminosities L ˜ 0.03L*. We find that the redshift dependence of the bias of the L* population can be described by the passive evolution model of Tegmark & Peebles. A visual inspection of a random sample from our r < 19.4 sample of SDSS galaxies reveals that about 10 per cent are spurious, with a higher contamination rate towards very faint absolute magnitudes due to over-deblended nearby galaxies. We correct for this contamination in our clustering analysis.
Evaluation of cluster expansions and correlated one-body properties of nuclei
NASA Astrophysics Data System (ADS)
Moustakidis, Ch. C.; Massen, S. E.; Panos, C. P.; Grypeos, M. E.; Antonov, A. N.
2001-07-01
Three different cluster expansions for the evaluation of correlated one-body properties of s-p and s-d shell nuclei are compared. Harmonic oscillator wave functions and Jastrow-type correlations are used, while analytical expressions are obtained for the charge form factor, density distribution, and momentum distribution by truncating the expansions and using a standard Jastrow correlation function f. The harmonic oscillator parameter b and the correlation parameter β have been determined by a least-squares fit to the experimental charge form factors in each case. The information entropy of nuclei in position space (Sr) and momentum space (Sk) according to the three methods are also calculated. It is found that the larger the entropy sum, S=Sr+Sk (the net information content of the system), the smaller the values of χ2. This indicates that maximal S is a criterion of the quality of a given nuclear model, according to the maximum entropy principle. Only two exceptions to this rule, out of many cases examined, were found. Finally an analytic expression for the so-called ``healing'' or ``wound'' integrals is derived with the function f considered, for any state of the relative two-nucleon motion, and their values in certain cases are computed and compared.
On the universality of the two-point galaxy correlation function
NASA Technical Reports Server (NTRS)
Davis, Marc; Meiksin, Avery; Strauss, Michael A.; Da Costa, L. Nicolaci; Yahil, Amos
1988-01-01
The behavior of the two-point galaxy correlation function in volume-limited subsamples of three complete redshift surveys is investigated. The correlation length is shown to scale approximately as the square root of the distance limit in both the CfA and Southern Sky catalogs, but to be independent of the distance limit in the IRAS sample. This effect is found to be due to factors such as the large positive density fluctuations in the foreground of the optically selected catalogs biasing the correlation length estimate downward, and the brightest galaxies appearing to be more strongly clustered than the mean.
NASA Astrophysics Data System (ADS)
Ebeling, H.; Edge, A. C.; Bohringer, H.; Allen, S. W.; Crawford, C. S.; Fabian, A. C.; Voges, W.; Huchra, J. P.
1998-12-01
We present a 90 per cent flux-complete sample of the 201 X-ray-brightest clusters of galaxies in the northern hemisphere (delta>=0 deg), at high Galactic latitudes (|b|>=20 deg), with measured redshifts z<=0.3 and fluxes higher than 4.4x10^-12 erg cm^-2 s^-1 in the 0.1-2.4 keV band. The sample, called the ROSAT Brightest Cluster Sample (BCS), is selected from ROSAT All-Sky Survey data and is the largest X-ray-selected cluster sample compiled to date. In addition to Abell clusters, which form the bulk of the sample, the BCS also contains the X-ray-brightest Zwicky clusters and other clusters selected from their X-ray properties alone. Effort has been made to ensure the highest possible completeness of the sample and the smallest possible contamination by non-cluster X-ray sources. X-ray fluxes are computed using an algorithm tailored for the detection and characterization of X-ray emission from galaxy clusters. These fluxes are accurate to better than 15 per cent (mean 1sigma error). We find the cumulative logN-logS distribution of clusters to follow a power law kappa S^alpha with alpha=1.31^+0.06_-0.03 (errors are the 10th and 90th percentiles) down to fluxes of 2x10^-12 erg cm^-2 s^-1, i.e. considerably below the BCS flux limit. Although our best-fitting slope disagrees formally with the canonical value of -1.5 for a Euclidean distribution, the BCS logN-logS distribution is consistent with a non-evolving cluster population if cosmological effects are taken into account. Our sample will allow us to examine large-scale structure in the northern hemisphere, determine the spatial cluster-cluster correlation function, investigate correlations between the X-ray and optical properties of the clusters, establish the X-ray luminosity function for galaxy clusters, and discuss the implications of the results for cluster evolution.
Jung, Wi Hoon; Jang, Joon Hwan; Park, Jin Woo; Kim, Euitae; Goo, Eun-Hoe; Im, Oh-Soo; Kwon, Jun Soo
2014-01-01
As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders. PMID:25203441
Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data
Hu, Jianhua; Wang, Peng; Qu, Annie
2014-01-01
Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433
Pathak, Arup Kumar; Samanta, Alok Kumar; Maity, Dilip Kumar
2011-04-07
We report conformationally averaged VDEs (VDE(w)(n)) for different sizes of NO(3)(-)·nH(2)O clusters calculated by using uncorrelated HF, correlated hybrid density functional (B3LYP, BHHLYP) and correlated ab intio (MP2 and CCSD(T)) theory. It is observed that the VDE(w)(n) at the B3LYP/6-311++G(d,p), B3LYP/Aug-cc-Pvtz and CCSD(T)/6-311++G(d,p) levels is very close to the experimentally measured VDE. It is shown that the use of calculated results of the conformationally averaged VDE for small-sized solvated negatively-charged clusters and a microscopic theory-based general expression for the same provides a route to obtain the VDE for a wide range of cluster sizes, including bulk.
Marc G. Genton; David T. Butry; Marcia L. Gumpertz; Jeffrey P. Prestemon
2006-01-01
We analyse the spatio-temporal structure of wildfire ignitions in the St. Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning...
Percolation analyses of observed and simulated galaxy clustering
NASA Astrophysics Data System (ADS)
Bhavsar, S. P.; Barrow, J. D.
1983-11-01
A percolation cluster analysis is performed on equivalent regions of the CFA redshift survey of galaxies and the 4000 body simulations of gravitational clustering made by Aarseth, Gott and Turner (1979). The observed and simulated percolation properties are compared and, unlike correlation and multiplicity function analyses, favour high density (Omega = 1) models with n = - 1 initial data. The present results show that the three-dimensional data are consistent with the degree of filamentary structure present in isothermal models of galaxy formation at the level of percolation analysis. It is also found that the percolation structure of the CFA data is a function of depth. Percolation structure does not appear to be a sensitive probe of intrinsic filamentary structure.
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.
The clustering of primordial black holes
NASA Astrophysics Data System (ADS)
Chisholm, James R.
2005-12-01
We investigate the spatial clustering properties of primordial black holes (PBHs). With minimal assumptions, we show that PBHs are created highly clustered. They constitute an isocurvature perturbation that is non-linear upon horizon entry. Using the peak-background split model of bias, we compute the PBH two-point correlation function and power spectrum. A consequence of this is that PBHs cannot serve as the majority of dark matter in the universe. We show that this clustering leads to PBH mergers which spoil the mass-creation time relation. We examine the prospect of PBHs being the seeds of Supermassive Black Holes as well.
Quark cluster model for deep-inelastic lepton-deuteron scattering
NASA Astrophysics Data System (ADS)
Yen, G.; Vary, J. P.; Harindranath, A.; Pirner, H. J.
1990-10-01
We evaluate the contribution of quasifree nucleon knockout and of inelastic lepton-nucleon scattering in inclusive electron-deuteron reactions at large momentum transfer. We examine the degree of quantitative agreement with deuteron wave functions from the Reid soft-core and Bonn realistic nucleon-nucleon interactions. For the range of data available there is strong sensitivity to the tensor correlations which are distinctively different in these two deuteron models. At this stage of the analyses the Reid soft-core wave function provides a reasonable description of the data while the Bonn wave function does not. We then include a six-quark cluster component whose relative contribution is based on an overlap criterion and obtain a good description of all the data with both interactions. The critical separation at which overlap occurs (formation of six-quark clusters) is taken to be 1.0 fm and the six-quark cluster probability is 4.7% for Reid and 5.4% for Bonn. As a consequence the quark cluster model with either Reid or Bonn wave function describe the SLAC inclusive electron-deuteron scattering data equally well. We then show how additional data would be decisive in resolving which model is ultimately more correct.
NASA Astrophysics Data System (ADS)
Bialas, A.
2011-02-01
The idea of glue clusters, i.e., short-range correlations in the quark-gluon plasma close to freeze-out, is used to estimate the width of balance functions in momentum space. A good agreement is found with the recent measurements of the STAR Collaboration for central Au-Au collisions.
Fuzzy cluster analysis of high-field functional MRI data.
Windischberger, Christian; Barth, Markus; Lamm, Claus; Schroeder, Lee; Bauer, Herbert; Gur, Ruben C; Moser, Ewald
2003-11-01
Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.
Hyperextended Cosmological Perturbation Theory: Predicting Nonlinear Clustering Amplitudes
NASA Astrophysics Data System (ADS)
Scoccimarro, Román; Frieman, Joshua A.
1999-07-01
We consider the long-standing problem of predicting the hierarchical clustering amplitudes Sp in the strongly nonlinear regime of gravitational evolution. N-body results for the nonlinear evolution of the bispectrum (the Fourier transform of the three-point density correlation function) suggest a physically motivated Ansatz that yields the strongly nonlinear behavior of the skewness, S3, starting from leading-order perturbation theory. When generalized to higher order (p>3) polyspectra or correlation functions, this Ansatz leads to a good description of nonlinear amplitudes in the strongly nonlinear regime for both scale-free and cold dark matter models. Furthermore, these results allow us to provide a general fitting formula for the nonlinear evolution of the bispectrum that interpolates between the weakly and strongly nonlinear regimes, analogous to previous expressions for the power spectrum.
NASA Astrophysics Data System (ADS)
Marulli, F.; Bolzonella, M.; Branchini, E.; Davidzon, I.; de la Torre, S.; Granett, B. R.; Guzzo, L.; Iovino, A.; Moscardini, L.; Pollo, A.; Abbas, U.; Adami, C.; Arnouts, S.; Bel, J.; Bottini, D.; Cappi, A.; Coupon, J.; Cucciati, O.; De Lucia, G.; Fritz, A.; Franzetti, P.; Fumana, M.; Garilli, B.; Ilbert, O.; Krywult, J.; Le Brun, V.; Le Fèvre, O.; Maccagni, D.; Małek, K.; McCracken, H. J.; Paioro, L.; Polletta, M.; Schlagenhaufer, H.; Scodeggio, M.; Tasca, L. A. M.; Tojeiro, R.; Vergani, D.; Zanichelli, A.; Burden, A.; Di Porto, C.; Marchetti, A.; Marinoni, C.; Mellier, Y.; Nichol, R. C.; Peacock, J. A.; Percival, W. J.; Phleps, S.; Wolk, M.; Zamorani, G.
2013-09-01
Aims: We investigate the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 0.5 < z < 1.1, using the first ~ 55 000 redshifts from the VIMOS Public Extragalactic Redshift Survey (VIPERS). Methods: We measured the redshift-space two-point correlation functions (2PCF), ξ(s) and ξ(rp,π) , and the projected correlation function, wp(rp), in samples covering different ranges of B-band absolute magnitudes and stellar masses. We considered both threshold and binned galaxy samples, with median B-band absolute magnitudes - 21.6 ≲ MB - 5log (h) ≲ - 19.5 and median stellar masses 9.8 ≲ log (M⋆ [h-2 M⊙]) ≲ 10.7. We assessed the real-space clustering in the data from the projected correlation function, which we model as a power law in the range 0.2 < rp [h-1 Mpc ] < 20. Finally, we estimated the galaxy bias as a function of luminosity, stellar mass, and redshift, assuming a flat Λ cold dark matter model to derive the dark matter 2PCF. Results: We provide the best-fit parameters of the power-law model assumed for the real-space 2PCF - the correlation length, r0, and the slope, γ - as well as the linear bias parameter, as a function of the B-band absolute magnitude, stellar mass, and redshift. We confirm and provide the tightest constraints on the dependence of clustering on luminosity at 0.5 < z < 1.1. We prove the complexity of comparing the clustering dependence on stellar mass from samples that are originally flux-limited and discuss the possible origin of the observed discrepancies. Overall, our measurements provide stronger constraints on galaxy formation models, which are now required to match, in addition to local observations, the clustering evolution measured by VIPERS galaxies between z = 0.5 and z = 1.1 for a broad range of luminosities and stellar masses. Based on observations collected at the European Southern Observatory, Paranal, Chile, under programmes 182.A-0886 (LP) at the Very Large Telescope, and 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 Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at TERAPIX and the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS. The VIPERS web site is http://vipers.inaf.it/
Guan, Yongjun; Pazgier, Marzena; Sajadi, Mohammad M.; ...
2012-12-13
The HIV-1 envelope glycoprotein (Env) undergoes conformational transitions consequent to CD4 binding and coreceptor engagement during viral entry. The physical steps in this process are becoming defined, but less is known about their significance as targets of antibodies potentially protective against HIV-1 infection. Here we probe the functional significance of transitional epitope exposure by characterizing 41 human mAbs specific for epitopes exposed on trimeric Env after CD4 engagement. These mAbs recognize three epitope clusters: cluster A, the gp120 face occluded by gp41 in trimeric Env; cluster B, a region proximal to the coreceptor-binding site (CoRBS) and involving the V1/V2 domain;more » and cluster C, the coreceptor-binding site. The mAbs were evaluated functionally by antibody-dependent, cell-mediated cytotoxicity (ADCC) and for neutralization of Tiers 1 and 2 pseudoviruses. All three clusters included mAbs mediating ADCC. However, there was a strong potency bias for cluster A, which harbors at least three potent ADCC epitopes whose cognate mAbs have electropositive paratopes. Cluster A epitopes are functional ADCC targets during viral entry in an assay format using virion-sensitized target cells. In contrast, only cluster C contained epitopes that were recognized by neutralizing mAbs. There was significant diversity in breadth and potency that correlated with epitope fine specificity. In contrast, ADCC potency had no relationship with neutralization potency or breadth for any epitope cluster. In conclusion, Fc-mediated effector function and neutralization coselect with specificity in anti-Env antibody responses, but the nature of selection is distinct for these two antiviral activities.« less
Schelin, Lina; Tengman, Eva; Ryden, Patrik; Häger, Charlotte
2017-01-01
Clinical test batteries for evaluation of knee function after injury to the Anterior Cruciate Ligament (ACL) should be valid and feasible, while reliably capturing the outcome of rehabilitation. There is currently a lack of consensus as to which of the many available assessment tools for knee function that should be included. The present aim was to use a statistical approach to investigate the contribution of frequently used tests to avoid redundancy, and filter them down to a proposed comprehensive and yet feasible test battery for long-term evaluation after ACL injury. In total 48 outcome variables related to knee function, all potentially relevant for a long-term follow-up, were included from a cross-sectional study where 70 ACL-injured (17-28 years post injury) individuals were compared to 33 controls. Cluster analysis and logistic regression were used to group variables and identify an optimal test battery, from which a summarized estimator of knee function representing various functional aspects was derived. As expected, several variables were strongly correlated, and the variables also fell into logical clusters with higher within-correlation (max ρ = 0.61) than between clusters (max ρ = 0.19). An extracted test battery with just four variables assessing one-leg balance, isokinetic knee extension strength and hop performance (one-leg hop, side hop) were mathematically combined to an estimator of knee function, which acceptably classified ACL-injured individuals and controls. This estimator, derived from objective measures, correlated significantly with self-reported function, e.g. Lysholm score (ρ = 0.66; p<0.001). The proposed test battery, based on a solid statistical approach, includes assessments which are all clinically feasible, while also covering complementary aspects of knee function. Similar test batteries could be determined for earlier phases of ACL rehabilitation or to enable longitudinal monitoring. Such developments, established on a well-grounded consensus of measurements, would facilitate comparisons of studies and enable evidence-based rehabilitation.
Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I
2017-12-01
Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.
Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B
2017-01-01
Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.
Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L
2017-09-01
The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Xuefei; Zhang, Wenjing; Tang, Mingsheng
2015-05-12
Coupled-cluster (CC) methods have been extensively used as the high-level approach in quantum electronic structure theory to predict various properties of molecules when experimental results are unavailable. It is often assumed that CC methods, if they include at least up to connected-triple-excitation quasiperturbative corrections to a full treatment of single and double excitations (in particular, CCSD(T)), and a very large basis set, are more accurate than Kohn–Sham (KS) density functional theory (DFT). In the present work, we tested and compared the performance of standard CC and KS methods on bond energy calculations of 20 3d transition metal-containing diatomic molecules againstmore » the most reliable experimental data available, as collected in a database called 3dMLBE20. It is found that, although the CCSD(T) and higher levels CC methods have mean unsigned deviations from experiment that are smaller than most exchange-correlation functionals for metal–ligand bond energies of transition metals, the improvement is less than one standard deviation of the mean unsigned deviation. Furthermore, on average, almost half of the 42 exchange-correlation functionals that we tested are closer to experiment than CCSD(T) with the same extended basis set for the same molecule. The results show that, when both relativistic and core–valence correlation effects are considered, even the very high-level (expensive) CC method with single, double, triple, and perturbative quadruple cluster operators, namely, CCSDT(2)Q, averaged over 20 bond energies, gives a mean unsigned deviation (MUD(20) = 4.7 kcal/mol when one correlates only valence, 3p, and 3s electrons of transition metals and only valence electrons of ligands, or 4.6 kcal/mol when one correlates all core electrons except for 1s shells of transition metals, S, and Cl); and that is similar to some good xc functionals (e.g., B97-1 (MUD(20) = 4.5 kcal/mol) and PW6B95 (MUD(20) = 4.9 kcal/mol)) when the same basis set is used. We found that, for both coupled cluster calculations and KS calculations, the T1 diagnostics correlate the errors better than either the M diagnostics or the B1 DFT-based diagnostics. The potential use of practical standard CC methods as a benchmark theory is further confounded by the finding that CC and DFT methods usually have different signs of the error. We conclude that the available experimental data do not provide a justification for using conventional single-reference CC theory calculations to validate or test xc functionals for systems involving 3d transition metals.« less
Correlation Functions in Two-Dimensional Critical Systems with Conformal Symmetry
NASA Astrophysics Data System (ADS)
Flores, Steven Miguel
This thesis presents a study of certain conformal field theory (CFT) correlation functions that describe physical observables in conform ally invariant two-dimensional critical systems. These are typically continuum limits of critical lattice models in a domain within the complex plane and with a boundary. Certain clusters, called
Statistical mechanics of the cluster Ising model
NASA Astrophysics Data System (ADS)
Smacchia, Pietro; Amico, Luigi; Facchi, Paolo; Fazio, Rosario; Florio, Giuseppe; Pascazio, Saverio; Vedral, Vlatko
2011-08-01
We study a Hamiltonian system describing a three-spin-1/2 clusterlike interaction competing with an Ising-like antiferromagnetic interaction. We compute free energy, spin-correlation functions, and entanglement both in the ground and in thermal states. The model undergoes a quantum phase transition between an Ising phase with a nonvanishing magnetization and a cluster phase characterized by a string order. Any two-spin entanglement is found to vanish in both quantum phases because of a nontrivial correlation pattern. Nevertheless, the residual multipartite entanglement is maximal in the cluster phase and dependent on the magnetization in the Ising phase. We study the block entropy at the critical point and calculate the central charge of the system, showing that the criticality of the system is beyond the Ising universality class.
Galaxy clustering dependence on the [O II] emission line luminosity in the local Universe
NASA Astrophysics Data System (ADS)
Favole, Ginevra; Rodríguez-Torres, Sergio A.; Comparat, Johan; Prada, Francisco; Guo, Hong; Klypin, Anatoly; Montero-Dorta, Antonio D.
2017-11-01
We study the galaxy clustering dependence on the [O II] emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift z ∼ 0.1. We select volume-limited samples of galaxies with different [O II] luminosity thresholds and measure their projected, monopole and quadrupole two-point correlation functions. We model these observations using the 1 h-1 Gpc MultiDark-Planck cosmological simulation and generate light cones with the SUrvey GenerAtoR algorithm. To interpret our results, we adopt a modified (Sub)Halo Abundance Matching scheme, accounting for the stellar mass incompleteness of the emission line galaxies. The satellite fraction constitutes an extra parameter in this model and allows to optimize the clustering fit on both small and intermediate scales (i.e. rp ≲ 30 h-1 Mpc), with no need of any velocity bias correction. We find that, in the local Universe, the [O II] luminosity correlates with all the clustering statistics explored and with the galaxy bias. This latter quantity correlates more strongly with the SDSS r-band magnitude than [O II] luminosity. In conclusion, we propose a straightforward method to produce reliable clustering models, entirely built on the simulation products, which provides robust predictions of the typical ELG host halo masses and satellite fraction values. The SDSS galaxy data, MultiDark mock catalogues and clustering results are made publicly available.
Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Sathian, K
2018-02-01
In a recent study, Eklund et al. employed resting-state functional magnetic resonance imaging data as a surrogate for null functional magnetic resonance imaging (fMRI) datasets and posited that cluster-wise family-wise error (FWE) rate-corrected inferences made by using parametric statistical methods in fMRI studies over the past two decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; this was principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggested otherwise. Here, we show that accounting for non-Gaussian signal components such as those arising from resting-state neural activity as well as physiological responses and motion artifacts in the null fMRI datasets yields first- and second-level general linear model analysis residuals with nearly uniform and Gaussian sACF. Further comparison with nonparametric permutation tests indicates that cluster-based FWE corrected inferences made with Gaussian spatial noise approximations are valid.
Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko
2012-07-15
Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.
Veis, Libor; Antalík, Andrej; Brabec, Jiří; Neese, Frank; Legeza, Örs; Pittner, Jiří
2016-10-03
In the past decade, the quantum chemical version of the density matrix renormalization group (DMRG) method has established itself as the method of choice for calculations of strongly correlated molecular systems. Despite its favorable scaling, it is in practice not suitable for computations of dynamic correlation. We present a novel method for accurate "post-DMRG" treatment of dynamic correlation based on the tailored coupled cluster (CC) theory in which the DMRG method is responsible for the proper description of nondynamic correlation, whereas dynamic correlation is incorporated through the framework of the CC theory. We illustrate the potential of this method on prominent multireference systems, in particular, N 2 and Cr 2 molecules and also oxo-Mn(Salen), for which we have performed the first post-DMRG computations in order to shed light on the energy ordering of the lowest spin states.
Thermodynamics and proton activities of protic ionic liquids with quantum cluster equilibrium theory
NASA Astrophysics Data System (ADS)
Ingenmey, Johannes; von Domaros, Michael; Perlt, Eva; Verevkin, Sergey P.; Kirchner, Barbara
2018-05-01
We applied the binary Quantum Cluster Equilibrium (bQCE) method to a number of alkylammonium-based protic ionic liquids in order to predict boiling points, vaporization enthalpies, and proton activities. The theory combines statistical thermodynamics of van-der-Waals-type clusters with ab initio quantum chemistry and yields the partition functions (and associated thermodynamic potentials) of binary mixtures over a wide range of thermodynamic phase points. Unlike conventional cluster approaches that are limited to the prediction of thermodynamic properties, dissociation reactions can be effortlessly included into the bQCE formalism, giving access to ionicities, as well. The method is open to quantum chemical methods at any level of theory, but combination with low-cost composite density functional theory methods and the proposed systematic approach to generate cluster sets provides a computationally inexpensive and mostly parameter-free way to predict such properties at good-to-excellent accuracy. Boiling points can be predicted within an accuracy of 50 K, reaching excellent accuracy for ethylammonium nitrate. Vaporization enthalpies are predicted within an accuracy of 20 kJ mol-1 and can be systematically interpreted on a molecular level. We present the first theoretical approach to predict proton activities in protic ionic liquids, with results fitting well into the experimentally observed correlation. Furthermore, enthalpies of vaporization were measured experimentally for some alkylammonium nitrates and an excellent linear correlation with vaporization enthalpies of their respective parent amines is observed.
NGC 6273: Towards Defining A New Class of Galactic Globular Clusters?
NASA Astrophysics Data System (ADS)
Johnson, Christian I.; Rich, Robert Michael; Pilachowski, Catherine A.; Caldwell, Nelson; Mateo, Mario L.; Ira Bailey, John; Crane, Jeffrey D.
2016-01-01
A growing number of observations have found that several Galactic globular clusters exhibit abundance dispersions beyond the well-known light element (anti-)correlations. These clusters tend to be very massive, have >0.1 dex intrinsic metallicity dispersions, have complex sub-giant branch morphologies, and have correlated [Fe/H] and s-process element enhancements. Interestingly, nearly all of these clusters discovered so far have [Fe/H]~-1.7. In this context, we have examined the chemical composition of 18 red giant branch (RGB) stars in the massive, metal-poor Galactic bulge globular cluster NGC 6273 using high signal-to-noise, high resolution (R~27,000) spectra obtained with the Michigan/Magellan Fiber System (M2FS) and MSpec spectrograph mounted on the Magellan-Clay 6.5m telescope at Las Campanas Observatory. We find that the cluster exhibits a metallicity range from [Fe/H]=-1.80 to -1.30 and is composed of two dominant populations separated in [Fe/H] and [La/Fe] abundance. The increase in [La/Eu] as a function of [La/H] suggests that the increase in [La/Fe] with [Fe/H] is due to almost pure s-process enrichment. The most metal-rich star in our sample is not strongly La-enhanced, but is α-poor and may belong to a third "anomalous" stellar population. The two dominant populations exhibit the same [Na/Fe]-[Al/Fe] correlation found in other "normal" globular clusters. Therefore, NGC 6273 joins ω Centauri, M 22, M 2, and NGC 5286 as a possible new class of Galactic globular clusters.
Torres, Edmanuel; DiLabio, Gino A
2013-08-13
Large clusters of noncovalently bonded molecules can only be efficiently modeled by classical mechanics simulations. One prominent challenge associated with this approach is obtaining force-field parameters that accurately describe noncovalent interactions. High-level correlated wave function methods, such as CCSD(T), are capable of correctly predicting noncovalent interactions, and are widely used to produce reference data. However, high-level correlated methods are generally too computationally costly to generate the critical reference data required for good force-field parameter development. In this work we present an approach to generate Lennard-Jones force-field parameters to accurately account for noncovalent interactions. We propose the use of a computational step that is intermediate to CCSD(T) and classical molecular mechanics, that can bridge the accuracy and computational efficiency gap between them, and demonstrate the efficacy of our approach with methane clusters. On the basis of CCSD(T)-level binding energy data for a small set of methane clusters, we develop methane-specific, atom-centered, dispersion-correcting potentials (DCPs) for use with the PBE0 density-functional and 6-31+G(d,p) basis sets. We then use the PBE0-DCP approach to compute a detailed map of the interaction forces associated with the removal of a single methane molecule from a cluster of eight methane molecules and use this map to optimize the Lennard-Jones parameters for methane. The quality of the binding energies obtained by the Lennard-Jones parameters we obtained is assessed on a set of methane clusters containing from 2 to 40 molecules. Our Lennard-Jones parameters, used in combination with the intramolecular parameters of the CHARMM force field, are found to closely reproduce the results of our dispersion-corrected density-functional calculations. The approach outlined can be used to develop Lennard-Jones parameters for any kind of molecular system.
Comparative study of the LOCV and the FHNC approaches for the nucleonic matter problem
NASA Astrophysics Data System (ADS)
Tafrihi, Azar; Modarres, Majid
2016-03-01
The nucleonic matter problem is investigated by comparing the lowest order constrained variational (LOCV) method with the Fermi hypernetted chain (FHNC) theory, emphasizing the role of the LOCV correlation functions. In this way, the central correlation functions are used in the LOCV formalism, for the Bethe homework problem. It is shown that the LOCV computations reasonably agree with those of FHNC. Moreover, the FHNC calculations are performed with the LOCV correlation functions. It is found that, assuming the LOCV or the parametrized correlation functions, the FHNC computations do not change significantly. So, one may conclude that the mentioned consistencies refer to the choice of the LOCV correlation functions. Because, the contribution of the many-body cluster terms can be ignored, if the LOCV correlation functions satisfy the normalization constraint. Then, using the AV 18 interaction, the operator-dependent (OD) correlation functions are employed in the LOCV calculations. Note that the LOCV OD correlation functions are obtained by averaging over the states. It turns out that the overall behaviour of the LOCV OD correlation functions are similar to those of FHNC. Although, due to the many-body effects which are considered in the FHNC calculations, the LOCV results fairly differ from those of FHNC. Finally, it is worth mentioning that, unlike the recent FHNC calculations, the spin-orbit-dependent correlation functions are included in the LOCV approach.
Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins.
Kenn, Michael; Ribarics, Reiner; Ilieva, Nevena; Cibena, Michael; Karch, Rudolf; Schreiner, Wolfgang
2016-04-26
The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.
de Lara-Castells, María Pilar; Stoll, Hermann; Mitrushchenkov, Alexander O
2014-08-21
As a prototypical dispersion-dominated physisorption problem, we analyze here the performance of dispersionless and dispersion-accounting methodologies on the helium interaction with cluster models of the TiO2(110) surface. A special focus has been given to the dispersionless density functional dlDF and the dlDF+Das construction for the total interaction energy (K. Pernal, R. Podeswa, K. Patkowski, and K. Szalewicz, Phys. Rev. Lett. 2009, 109, 263201), where Das is an effective interatomic pairwise functional form for the dispersion. Likewise, the performance of symmetry-adapted perturbation theory (SAPT) method is evaluated, where the interacting monomers are described by density functional theory (DFT) with the dlDF, PBE, and PBE0 functionals. Our benchmarks include CCSD(T)-F12b calculations and comparative analysis on the nuclear bound states supported by the He-cluster potentials. Moreover, intra- and intermonomer correlation contributions to the physisorption interaction are analyzed through the method of increments (H. Stoll, J. Chem. Phys. 1992, 97, 8449) at the CCSD(T) level of theory. This method is further applied in conjunction with a partitioning of the Hartree-Fock interaction energy to estimate individual interaction energy components, comparing them with those obtained using the different SAPT(DFT) approaches. The cluster size evolution of dispersionless and dispersion-accounting energy components is then discussed, revealing the reduced role of the dispersionless interaction and intramonomer correlation when the extended nature of the surface is better accounted for. On the contrary, both post-Hartree-Fock and SAPT(DFT) results clearly demonstrate the high-transferability character of the effective pairwise dispersion interaction whatever the cluster model is. Our contribution also illustrates how the method of increments can be used as a valuable tool not only to achieve the accuracy of CCSD(T) calculations using large cluster models but also to evaluate the performance of SAPT(DFT) methods for the physically well-defined contributions to the total interaction energy. Overall, our work indicates the excellent performance of a dlDF+Das approach in which the parameters are optimized using the smallest cluster model of the target surface to treat van der Waals adsorbate-surface interactions.
Estimating Function Approaches for Spatial Point Processes
NASA Astrophysics Data System (ADS)
Deng, Chong
Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.
Spatial Correlation Function of the Chandra Selected Active Galactic Nuclei
NASA Technical Reports Server (NTRS)
Yang, Y.; Mushotzky, R. F.; Barger, A. J.; Cowie, L. L.
2006-01-01
We present the spatial correlation function analysis of non-stellar X-ray point sources in the Chandra Large Area Synoptic X-ray Survey of Lockman Hole Northwest (CLASXS). Our 9 ACIS-I fields cover a contiguous solid angle of 0.4 deg(exp 2) and reach a depth of 3 x 10(exp -15) erg/square cm/s in the 2-8 keV band. We supplement our analysis with data from the Chandra Deep Field North (CDFN). The addition of this field allows better probe of the correlation function at small scales. A total of 233 and 252 sources with spectroscopic information are used in the study of the CLASXS and CDFN fields respectively. We calculate both redshift-space and projected correlation functions in co-moving coordinates, averaged over the redshift range of 0.1 < z < 3.0, for both CLASXS and CDFN fields for a standard cosmology with Omega(sub Lambda) = 0.73,Omega(sub M) = 0.27, and h = 0.71 (H(sub 0) = 100h km/s Mpc(exp -1). The correlation function for the CLASXS field over scales of 3 Mpc< s < 200 Mpc can be modeled as a power-law of the form xi(s) = (S/SO)(exp - gamma), with gamma = 1.6(sup +0.4 sub -0.3) and S(sub o) = 8.0(sup +.14 sub -1.5) Mpc. The redshift-space correlation function for CDFN on scales of 1 Mpc< s < 100 Mpc is found to have a similar correlation length so = 8.55(sup +0.74 sub -0.74) Mpc, but a shallower slope (gamma = 1.3 +/- 0.1). The real-space correlation functions derived from the projected correlation functions, are found to be tau(sub 0 = 8.1(sup +1.2 sub -2.2) Mpc, and gamma = 2.1 +/- 0.5 for the CLASXS field, and tau(sub 0) = 5.8(sup +.1.0 sub -1.5) Mpc, gamma = 1.38(sup +0.12 sub -0.14 for the CDFN field. By comparing the real- and redshift-space correlation functions in the combined CLASXS and CDFN samples, we are able to estimate the redshift distortion parameter Beta = 0.4 +/- 0.2 at an effective redshift z = 0.94. We compare the correlation functions for hard and soft spectra sources in the CLASXS field and find no significant difference between the two groups. We have also found that the correlation between X-ray luminosity and clustering amplitude is weak, which, however, is fully consistent with the expectation using the simplest relations between X-ray luminosity, black hole mass, and dark halo mass. We study the evolution of the AGN clustering by dividing the samples into 4 redshift bins over 0.1 Mpc< z <3.0 Mpc. We find a very mild evolution in the clustering amplitude, which show the same evolution trend found in optically selected quasars in the 2dF survey. We estimate the evolution of the bias, and find that the bias increases rapidly with redshift (b(z = 0.45) = 0.95 +/- 0.15 and b(z = 2.07) = 3.03 +/- 0.83): The typical mass of the dark matter halo derived from the bias estimates show little change with redshift. The average halo mass is found to be log (M(sub halo)/M(sun))approximates 12.1. Subject headings: cosmology: observations - large-scale structure of the universe - x-rays: diffuse background - galaxies: nuclei
Local structure order in Pd 78Cu 6Si 16 liquid
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yue, G. Q.; Zhang, Y.; Sun, Y.
2015-02-05
The short-range order (SRO) in Pd 78Cu 6Si 16 liquid was studied by high energy x-ray diffraction and ab initio molecular dynamics (MD) simulations. The calculated pair correlation functions at different temperatures agree well with the experimental results. The partial pair correlation functions from ab intio MD simulations indicate that Si atoms prefer to be uniformly distributed while Cu atoms tend to aggregate. By performing structure analysis using Honeycutt-Andersen index, Voronoi tessellation, and atomic cluster alignment method, we show that the icosahedron and face-centered cubic SRO increase upon cooling. The dominant SRO is the Pd-centered Pd 9Si 2 motif, namelymore » the structure of which motif is similar to the structure of Pd-centered clusters in the Pd 9Si 2 crystal. The study further confirms the existence of trigonal prism capped with three half-octahedra that is reported as a structural unit in Pd-based amorphous alloys. The majority of Cu-centered clusters are icosahedra, suggesting that the presence of Cu is benefit to promote the glass forming ability.« less
Characterizing decision-making and reward processing in bipolar disorder: A cluster analysis.
Jiménez, E; Solé, B; Arias, B; Mitjans, M; Varo, C; Reinares, M; Bonnín, C M; Salagre, E; Ruíz, V; Torres, I; Tomioka, Y; Sáiz, P A; García-Portilla, M P; Burón, P; Bobes, J; Martínez-Arán, A; Torrent, C; Vieta, E; Benabarre, A
2018-05-25
The presence of abnormalities in emotional decision-making and reward processing among bipolar patients (BP) has been well rehearsed. These disturbances are not limited to acute phases and are common even during remission. In recent years, the existence of discrete cognitive profiles in this psychiatric population has been replicated. However, emotional decision making and reward processing domains have barely been studied. Therefore, our aim was to explore the existence of different profiles on the aforementioned cognitive dimensions in BP. The sample consisted of 126 euthymic BP. Main sociodemographic, clinical, functioning, and neurocognitive variables were gathered. A hierarchical-clustering technique was used to identify discrete neurocognitive profiles based on the performance in the Iowa Gambling Task. Afterward, the resulting clusters were compared using ANOVA or Chi-squared Test, as appropriate. Evidence for the existence of three different profiles was provided. Cluster 1 was mainly characterized by poor decision ability. Cluster 2 presented the lowest sensitivity to punishment. Finally, cluster 3 presented the best decision-making ability and the highest levels of punishment sensitivity. Comparison between the three clusters indicated that cluster 2 was the most functionally impaired group. The poorest outcomes in attention, executive function domains, and social cognition were also observed within the same group. In conclusion, similarly to that observed in "cold cognitive" domains, our results suggest the existence of three discrete cognitive profiles concerning emotional decision making and reward processing. Amongst all the indexes explored, low punishment sensitivity emerge as a potential correlate of poorer cognitive and functional outcomes in bipolar disorder. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.
Coupled-cluster based basis sets for valence correlation calculations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Claudino, Daniel; Bartlett, Rodney J., E-mail: bartlett@qtp.ufl.edu; Gargano, Ricardo
Novel basis sets are generated that target the description of valence correlation in atoms H through Ar. The new contraction coefficients are obtained according to the Atomic Natural Orbital (ANO) procedure from CCSD(T) (coupled-cluster singles and doubles with perturbative triples correction) density matrices starting from the primitive functions of Dunning et al. [J. Chem. Phys. 90, 1007 (1989); ibid. 98, 1358 (1993); ibid. 100, 2975 (1993)] (correlation consistent polarized valence X-tuple zeta, cc-pVXZ). The exponents of the primitive Gaussian functions are subject to uniform scaling in order to ensure satisfaction of the virial theorem for the corresponding atoms. These newmore » sets, named ANO-VT-XZ (Atomic Natural Orbital Virial Theorem X-tuple Zeta), have the same number of contracted functions as their cc-pVXZ counterparts in each subshell. The performance of these basis sets is assessed by the evaluation of the contraction errors in four distinct computations: correlation energies in atoms, probing the density in different regions of space via 〈r{sup n}〉 (−3 ≤ n ≤ 3) in atoms, correlation energies in diatomic molecules, and the quality of fitting potential energy curves as measured by spectroscopic constants. All energy calculations with ANO-VT-QZ have contraction errors within “chemical accuracy” of 1 kcal/mol, which is not true for cc-pVQZ, suggesting some improvement compared to the correlation consistent series of Dunning and co-workers.« less
Kyeong, Sunghyon; Kim, Eunjoo; Park, Hae-Jeong; Hwang, Dong-Uk
2014-08-05
Novelty seeking (NS) and harm avoidance (HA) are two major dimensions of temperament in Cloninger׳s neurobiological model of personality. Previous neurofunctional and biological studies on temperament dimensions of HA and NS suggested that the temperamental traits have significant correlations with cortical and subcortical brain regions. However, no study to date has investigated the functional network modular organization as a function of the temperament dimension. The temperament dimensions were originally proposed to be independent of one another. However, a meta-analysis based on 16 published articles found a significant negative correlation between HA and NS (Miettunen et al., 2008). Based on this negative correlation, the current study revealed the whole-brain connectivity modular architecture for two contrasting temperament groups. The k-means clustering algorithm, with the temperamental traits of HA and NS as an input, was applied to divide the 40 subjects into two temperament groups: 'high HA and low NS' versus 'low HA and high NS'. Using the graph theoretical framework, we found a functional segregation of whole brain network architectures derived from resting-state functional MRI. In the 'high HA and low NS' group, the regulatory brain regions, such as the prefrontal cortex (PFC), are clustered together with the limbic system. In the 'low HA and high NS' group, however, brain regions lying on the dopaminergic pathways, such as the PFC and basal ganglia, are partitioned together. These findings suggest that the neural basis of inhibited, passive, and inactive behaviors in the 'high HA and low NS' group was derived from the increased network associations between the PFC and limbic clusters. In addition, supporting evidence of topological differences between the two temperament groups was found by analyzing the functional connectivity density and gray matter volume, and by computing the relationships between the morphometry and function of the brain. Copyright © 2014 Elsevier B.V. All rights reserved.
Subspecialization in the human posterior medial cortex
Bzdok, Danilo; Heeger, Adrian; Langner, Robert; Laird, Angela R.; Fox, Peter T.; Palomero-Gallagher, Nicola; Vogt, Brent A.; Zilles, Karl; Eickhoff, Simon B.
2014-01-01
The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-constrained but not task-unconstrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications. PMID:25462801
Mars, Rogier B.; Jbabdi, Saad; Sallet, Jérôme; O’Reilly, Jill X.; Croxson, Paula L.; Olivier, Etienne; Noonan, MaryAnn P.; Bergmann, Caroline; Mitchell, Anna S.; Baxter, Mark G.; Behrens, Timothy E.J.; Johansen-Berg, Heidi; Tomassini, Valentina; Miller, Karla L.; Rushworth, Matthew F.S.
2011-01-01
Despite the prominence of parietal activity in human neuromaging investigations of sensorimotor and cognitive processes there remains uncertainty about basic aspects of parietal cortical anatomical organization. Descriptions of human parietal cortex draw heavily on anatomical schemes developed in other primate species but the validity of such comparisons has been questioned by claims that there are fundamental differences between the parietal cortex in humans and other primates. A scheme is presented for parcellation of human lateral parietal cortex into component regions on the basis of anatomical connectivity and the functional interactions of the resulting clusters with other brain regions. Anatomical connectivity was estimated using diffusion-weighted magnetic resonance image (MRI) based tractography and functional interactions were assessed by correlations in activity measured with functional MRI (fMRI) at rest. Resting state functional connectivity was also assessed directly in the rhesus macaque lateral parietal cortex in an additional experiment and the patterns found reflected known neuroanatomical connections. Cross-correlation in the tractography-based connectivity patterns of parietal voxels reliably parcellated human lateral parietal cortex into ten component clusters. The resting state functional connectivity of human superior parietal and intraparietal clusters with frontal and extrastriate cortex suggested correspondences with areas in macaque superior and intraparietal sulcus. Functional connectivity patterns with parahippocampal cortex and premotor cortex again suggested fundamental correspondences between inferior parietal cortex in humans and macaques. In contrast, the human parietal cortex differs in the strength of its interactions between the central inferior parietal lobule region and the anterior prefrontal cortex. PMID:21411650
Yu, Yang; Li, Chen; Yin, Bing; Li, Jian-Li; Huang, Yuan-He; Wen, Zhen-Yi; Jiang, Zhen-Yi
2013-08-07
The structures, relative stabilities, vertical electron detachment energies, and magnetic properties of a series of trinuclear clusters are explored via combined broken-symmetry density functional theory and ab initio study. Several exchange-correlation functionals are utilized to investigate the effects of different halogen elements and central atoms on the properties of the clusters. These clusters are shown to possess stronger superhalogen properties than previously reported dinuclear superhalogens. The calculated exchange coupling constants indicate the antiferromagnetic coupling between the transition metal ions. Spin density analysis demonstrates the importance of spin delocalization in determining the strengths of various couplings. Spin frustration is shown to occur in some of the trinuclear superhalogens. The coexistence of strong superhalogen properties and spin frustration implies the possibility of trinuclear superhalogens working as the building block of new materials of novel magnetic properties.
WGCNA: an R package for weighted correlation network analysis.
Langfelder, Peter; Horvath, Steve
2008-12-29
Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.
WGCNA: an R package for weighted correlation network analysis
Langfelder, Peter; Horvath, Steve
2008-01-01
Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008
NASA Astrophysics Data System (ADS)
Eftekharzadeh, S.; Myers, A. D.; Hennawi, J. F.; Djorgovski, S. G.; Richards, G. T.; Mahabal, A. A.; Graham, M. J.
2017-06-01
We present the most precise estimate to date of the clustering of quasars on very small scales, based on a sample of 47 binary quasars with magnitudes of g < 20.85 and proper transverse separations of ˜25 h-1 kpc. Our sample of binary quasars, which is about six times larger than any previous spectroscopically confirmed sample on these scales, is targeted using a kernel density estimation (KDE) technique applied to Sloan Digital Sky Survey (SDSS) imaging over most of the SDSS area. Our sample is 'complete' in that all of the KDE target pairs with 17.0 ≲ R ≲ 36.2 h-1 kpc in our area of interest have been spectroscopically confirmed from a combination of previous surveys and our own long-slit observational campaign. We catalogue 230 candidate quasar pairs with angular separations of <8 arcsec, from which our binary quasars were identified. We determine the projected correlation function of quasars (\\bar{W}_p) in four bins of proper transverse scale over the range 17.0 ≲ R ≲ 36.2 h-1 kpc. The implied small-scale quasar clustering amplitude from the projected correlation function, integrated across our entire redshift range, is A = 24.1 ± 3.6 at ˜26.6 h-1 kpc. Our sample is the first spectroscopically confirmed sample of quasar pairs that is sufficiently large to study how quasar clustering evolves with redshift at ˜25 h-1 kpc. We find that empirical descriptions of how quasar clustering evolves with redshift at ˜25 h-1 Mpc also adequately describe the evolution of quasar clustering at ˜25 h-1 kpc.
Complementary views on electron spectra: From fluctuation diagnostics to real-space correlations
NASA Astrophysics Data System (ADS)
Gunnarsson, O.; Merino, J.; Schäfer, T.; Sangiovanni, G.; Rohringer, G.; Toschi, A.
2018-03-01
We study the relation between the microscopic properties of a many-body system and the electron spectra, experimentally accessible by photoemission. In a recent paper [O. Gunnarsson et al., Phys. Rev. Lett. 114, 236402 (2015), 10.1103/PhysRevLett.114.236402], we introduced the "fluctuation diagnostics" approach to extract the dominant wave-vector-dependent bosonic fluctuations from the electronic self-energy. Here, we first reformulate the theory in terms of fermionic modes to render its connection with resonance valence bond (RVB) fluctuations more transparent. Second, by using a large-U expansion, where U is the Coulomb interaction, we relate the fluctuations to real-space correlations. Therefore, it becomes possible to study how electron spectra are related to charge, spin, superconductivity, and RVB-like real-space correlations, broadening the analysis of an earlier work [J. Merino and O. Gunnarsson, Phys. Rev. B 89, 245130 (2014), 10.1103/PhysRevB.89.245130]. This formalism is applied to the pseudogap physics of the two-dimensional Hubbard model, studied in the dynamical cluster approximation. We perform calculations for embedded clusters with up to 32 sites, having three inequivalent K points at the Fermi surface. We find that as U is increased, correlation functions gradually attain values consistent with an RVB state. This first happens for correlation functions involving the antinodal point and gradually spreads to the nodal point along the Fermi surface. Simultaneously, a pseudogap opens up along the Fermi surface. We relate this to a crossover from a Kondo-type state to an RVB-like localized cluster state and to the presence of RVB and spin fluctuations. These changes are caused by a strong momentum dependence in the cluster bath couplings along the Fermi surface. We also show, from a more algorithmic perspective, how the time-consuming calculations in fluctuation diagnostics can be drastically simplified.
Universal noise and Efimov physics
NASA Astrophysics Data System (ADS)
Nicholson, Amy N.
2016-03-01
Probability distributions for correlation functions of particles interacting via random-valued fields are discussed as a novel tool for determining the spectrum of a theory. In particular, this method is used to determine the energies of universal N-body clusters tied to Efimov trimers, for even N, by investigating the distribution of a correlation function of two particles at unitarity. Using numerical evidence that this distribution is log-normal, an analytical prediction for the N-dependence of the N-body binding energies is made.
Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe
2017-01-01
Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. PMID:29046391
Void statistics of the CfA redshift survey
NASA Technical Reports Server (NTRS)
Vogeley, Michael S.; Geller, Margaret J.; Huchra, John P.
1991-01-01
Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.
Void statistics of the CfA redshift survey
NASA Astrophysics Data System (ADS)
Vogeley, Michael S.; Geller, Margaret J.; Huchra, John P.
1991-11-01
Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.
Knox, Stephanie A; Chondros, Patty
2004-01-01
Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248
Assessment of interaction-strength interpolation formulas for gold and silver clusters
NASA Astrophysics Data System (ADS)
Giarrusso, Sara; Gori-Giorgi, Paola; Della Sala, Fabio; Fabiano, Eduardo
2018-04-01
The performance of functionals based on the idea of interpolating between the weak- and the strong-interaction limits the global adiabatic-connection integrand is carefully studied for the challenging case of noble-metal clusters. Different interpolation formulas are considered and various features of this approach are analyzed. It is found that these functionals, when used as a correlation correction to Hartree-Fock, are quite robust for the description of atomization energies, while performing less well for ionization potentials. Future directions that can be envisaged from this study and a previous one on main group chemistry are discussed.
Solvatochromic shifts from coupled-cluster theory embedded in density functional theory
NASA Astrophysics Data System (ADS)
Höfener, Sebastian; Gomes, André Severo Pereira; Visscher, Lucas
2013-09-01
Building on the framework recently reported for determining general response properties for frozen-density embedding [S. Höfener, A. S. P. Gomes, and L. Visscher, J. Chem. Phys. 136, 044104 (2012)], 10.1063/1.3675845, in this work we report a first implementation of an embedded coupled-cluster in density-functional theory (CC-in-DFT) scheme for electronic excitations, where only the response of the active subsystem is taken into account. The formalism is applied to the calculation of coupled-cluster excitation energies of water and uracil in aqueous solution. We find that the CC-in-DFT results are in good agreement with reference calculations and experimental results. The accuracy of calculations is mainly sensitive to factors influencing the correlation treatment (basis set quality, truncation of the cluster operator) and to the embedding treatment of the ground-state (choice of density functionals). This allows for efficient approximations at the excited state calculation step without compromising the accuracy. This approximate scheme makes it possible to use a first principles approach to investigate environment effects with specific interactions at coupled-cluster level of theory at a cost comparable to that of calculations of the individual subsystems in vacuum.
2010-01-01
Background The biological dimensions of genes are manifold. These include genomic properties, (e.g., X/autosomal linkage, recombination) and functional properties (e.g., expression level, tissue specificity). Multiple properties, each generally of subtle influence individually, may affect the evolution of genes or merely be (auto-)correlates. Results of multidimensional analyses may reveal the relative importance of these properties on the evolution of genes, and therefore help evaluate whether these properties should be considered during analyses. While numerous properties are now considered during studies, most work still assumes the stereotypical solitary gene as commonly depicted in textbooks. Here, we investigate the Drosophila melanogaster genome to determine whether deviations from the stereotypical gene architecture correlate with other properties of genes. Results Deviations from the stereotypical gene architecture were classified as the following gene constellations: Overlapping genes were defined as those that overlap in the 5-prime, exonic, or intronic regions. Chromatin co-clustering genes were defined as genes that co-clustered within 20 kb of transcriptional territories. If this scheme is applied the stereotypical gene emerges as a rare occurrence (7.5%), slightly varied schemes yielded between ~1%-50%. Moreover, when following our scheme, paired-overlapping genes and chromatin co-clustering genes accounted for 50.1 and 42.4% of the genes analyzed, respectively. Gene constellation was a correlate of a number of functional and evolutionary properties of genes, but its statistical effect was ~1-2 orders of magnitude lower than the effects of recombination, chromosome linkage and protein function. Analysis of datasets on male reproductive proteins showed these were biased in their representation of gene constellations and evolutionary rate Ka/Ks estimates, but these biases did not overwhelm the biologically meaningful observation of high evolutionary rates of male reproductive genes. Conclusion Given the rarity of the solitary stereotypical gene, and the abundance of gene constellations that deviate from it, the presence of gene constellations, while once thought to be exceptional in large Eukaryote genomes, might have broader relevance to the understanding and study of the genome. However, according to our definition, while gene constellations can be significant correlates of functional properties of genes, they generally are weak correlates of the evolution of genes. Thus, the need for their consideration would depend on the context of studies. PMID:20497561
Ultra-small Ag clusters in zeolite A4: Antibacterial and thermochromic applications
NASA Astrophysics Data System (ADS)
Horta-Fraijo, P.; Cortez-Valadez, M.; Flores-Lopez, N. S.; Britto Hurtado, R.; Vargas-Ortiz, R. A.; Perez-Rodriguez, A.; Flores-Acosta, M.
2018-03-01
The physical and chemical properties of metal clusters depend on their atomic structure, therefore, it is important to determine the lowest-energy structures of the clusters in order to understand and utilize their properties. In this work, we use the Density Functional Theory (DFT) at the generalized gradient approximation level Becke's three-parameter and the gradient corrected functional of Lee, Yang and Puar (B3LYP) in combination with the basis set LANL2DZ (the effective core potentials and associated double-zeta valence) to determine some of the structural, electronic and vibrational properties of the planar silver clusters (Agn clusters n = 2-24). Additionally, the study reports the experimental synthesis of small silver clusters in synthetic zeolite A4. The synthesis was possible using the ion exchange method with some precursors like silver nitrate (AgNO3) and synthetic zeolite A4. The silver clusters in zeolite powder underwent thermal treatment at 450 °C to release the remaining water or humidity on it. The morphology of the particles was determined by Transmission Electron microscopy. The nanomaterials obtained show thermochromic properties. The structural parameters were correlated theoretically and experimentally.
Fast Computation of the Two-Point Correlation Function in the Age of Big Data
NASA Astrophysics Data System (ADS)
Pellegrino, Andrew; Timlin, John
2018-01-01
We present a new code which quickly computes the two-point correlation function for large sets of astronomical data. This code combines the ease of use of Python with the speed of parallel shared libraries written in C. We include the capability to compute the auto- and cross-correlation statistics, and allow the user to calculate the three-dimensional and angular correlation functions. Additionally, the code automatically divides the user-provided sky masks into contiguous subsamples of similar size, using the HEALPix pixelization scheme, for the purpose of resampling. Errors are computed using jackknife and bootstrap resampling in a way that adds negligible extra runtime, even with many subsamples. We demonstrate comparable speed with other clustering codes, and code accuracy compared to known and analytic results.
NASA Astrophysics Data System (ADS)
Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.
2017-08-01
Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.
Luongo, Francisco J.; Zimmerman, Chris A.; Horn, Meryl E.
2016-01-01
Sequential patterns of prefrontal activity are believed to mediate important behaviors, e.g., working memory, but it remains unclear exactly how they are generated. In accordance with previous studies of cortical circuits, we found that prefrontal microcircuits in young adult mice spontaneously generate many more stereotyped sequences of activity than expected by chance. However, the key question of whether these sequences depend on a specific functional organization within the cortical microcircuit, or emerge simply as a by-product of random interactions between neurons, remains unanswered. We observed that correlations between prefrontal neurons do follow a specific functional organization—they have a small-world topology. However, until now it has not been possible to directly link small-world topologies to specific circuit functions, e.g., sequence generation. Therefore, we developed a novel analysis to address this issue. Specifically, we constructed surrogate data sets that have identical levels of network activity at every point in time but nevertheless represent various network topologies. We call this method shuffling activity to rearrange correlations (SHARC). We found that only surrogate data sets based on the actual small-world functional organization of prefrontal microcircuits were able to reproduce the levels of sequences observed in actual data. As expected, small-world data sets contained many more sequences than surrogate data sets with randomly arranged correlations. Surprisingly, small-world data sets also outperformed data sets in which correlations were maximally clustered. Thus the small-world functional organization of cortical microcircuits, which effectively balances the random and maximally clustered regimes, is optimal for producing stereotyped sequential patterns of activity. PMID:26888108
Galaxy Clustering in Early Sloan Digital Sky Survey Redshift Data
NASA Astrophysics Data System (ADS)
Zehavi, Idit; Blanton, Michael R.; Frieman, Joshua A.; Weinberg, David H.; Mo, Houjun J.; Strauss, Michael A.; Anderson, Scott F.; Annis, James; Bahcall, Neta A.; Bernardi, Mariangela; Briggs, John W.; Brinkmann, Jon; Burles, Scott; Carey, Larry; Castander, Francisco J.; Connolly, Andrew J.; Csabai, Istvan; Dalcanton, Julianne J.; Dodelson, Scott; Doi, Mamoru; Eisenstein, Daniel; Evans, Michael L.; Finkbeiner, Douglas P.; Friedman, Scott; Fukugita, Masataka; Gunn, James E.; Hennessy, Greg S.; Hindsley, Robert B.; Ivezić, Željko; Kent, Stephen; Knapp, Gillian R.; Kron, Richard; Kunszt, Peter; Lamb, Donald Q.; Leger, R. French; Long, Daniel C.; Loveday, Jon; Lupton, Robert H.; McKay, Timothy; Meiksin, Avery; Merrelli, Aronne; Munn, Jeffrey A.; Narayanan, Vijay; Newcomb, Matt; Nichol, Robert C.; Owen, Russell; Peoples, John; Pope, Adrian; Rockosi, Constance M.; Schlegel, David; Schneider, Donald P.; Scoccimarro, Roman; Sheth, Ravi K.; Siegmund, Walter; Smee, Stephen; Snir, Yehuda; Stebbins, Albert; Stoughton, Christopher; SubbaRao, Mark; Szalay, Alexander S.; Szapudi, Istvan; Tegmark, Max; Tucker, Douglas L.; Uomoto, Alan; Vanden Berk, Dan; Vogeley, Michael S.; Waddell, Patrick; Yanny, Brian; York, Donald G.
2002-05-01
We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5700kms-1<=cz<=39,000kms-1, distributed in several long but narrow (2.5d-5°) segments, covering 690 deg2. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 h-1 Mpc. The two-dimensional correlation function ξ(rp,π) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, ξ(r)=(r/6.1+/-0.2h-1Mpc)-1.75+/-0.03, for 0.1h-1Mpc<=r<=16h-1Mpc. The galaxy pairwise velocity dispersion is σ12~600+/-100kms-1 for projected separations 0.15h-1Mpc<=rp<=5h-1Mpc. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r<~10h-1Mpc: subsamples with absolute magnitude ranges centered on M*-1.5, M*, and M*+1.5 have real-space correlation functions that are parallel power laws of slope ~-1.8 with correlation lengths of approximately 7.4, 6.3, and 4.7 h-1 Mpc, respectively.
On the linearity of tracer bias around voids
NASA Astrophysics Data System (ADS)
Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro
2017-07-01
The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.
Structural study of gold clusters.
Xiao, Li; Tollberg, Bethany; Hu, Xiankui; Wang, Lichang
2006-03-21
Density functional theory (DFT) calculations were carried out to study gold clusters of up to 55 atoms. Between the linear and zigzag monoatomic Au nanowires, the zigzag nanowires were found to be more stable. Furthermore, the linear Au nanowires of up to 2 nm are formed by slightly stretched Au dimers. These suggest that a substantial Peierls distortion exists in those structures. Planar geometries of Au clusters were found to be the global minima till the cluster size of 13. A quantitative correlation is provided between various properties of Au clusters and the structure and size. The relative stability of selected clusters was also estimated by the Sutton-Chen potential, and the result disagrees with that obtained from the DFT calculations. This suggests that a modification of the Sutton-Chen potential has to be made, such as obtaining new parameters, in order to use it to search the global minima for bigger Au clusters.
The effect of clulstering of galaxies on the statistics of gravitational lenses
NASA Technical Reports Server (NTRS)
Anderson, N.; Alcock, C.
1986-01-01
It is examined whether clustering of galaxies can significantly alter the statistical properties of gravitational lenses? Only models of clustering that resemble the observed distribution of galaxies in the properties of the two-point correlation function are considered. Monte-Carlo simulations of the imaging process are described. It is found that the effect of clustering is too small to be significant, unless the mass of the deflectors is so large that gravitational lenses become common occurrences. A special model is described which was concocted to optimize the effect of clustering on gravitational lensing but still resemble the observed distribution of galaxies; even this simulation did not satisfactorily produce large numbers of wide-angle lenses.
NASA Technical Reports Server (NTRS)
Silk, J.; Wilson, M. L.
1979-01-01
The density profiles and Hubble flow deviations in the vicinities of rich galaxy clusters are derived for a variety of models of initial density and velocity perturbations at the recombination epoch. The galaxy correlation function, measured with respect to the Abell clusters, is used to normalize the theoretical models. The angular scales of the required primordial inhomogeneities are calculated. It is found that the resulting density profiles around rich clusters are surprisingly insensitive to the shape of the initial perturbations and also to the cosmological density parameter, Omega. However, it is shown that the distribution of galaxy radial velocities can provide a possible means of deriving Omega.
Scale-similar clustering of heavy particles in the inertial range of turbulence
NASA Astrophysics Data System (ADS)
Ariki, Taketo; Yoshida, Kyo; Matsuda, Keigo; Yoshimatsu, Katsunori
2018-03-01
Heavy particle clustering in turbulence is discussed from both phenomenological and analytical points of view, where the -4 /3 power law of the pair-correlation function is obtained in the inertial range. A closure theory explains the power law in terms of the balance between turbulence mixing and preferential-concentration mechanism. The obtained -4 /3 power law is supported by a direct numerical simulation of particle-laden turbulence.
Cluster redshifts in five suspected superclusters
NASA Technical Reports Server (NTRS)
Ciardullo, R.; Ford, H.; Harms, R.
1985-01-01
Redshift surveys for rich superclusters were carried out in five regions of the sky containing surface-density enhancements of Abell clusters. While several superclusters are identified, projection effects dominate each field, and no system contains more than five rich clusters. Two systems are found to be especially interesting. The first, field 0136 10, is shown to contain a superposition of at least four distinct superclusters, with the richest system possessing a small velocity dispersion. The second system, 2206 - 22, though a region of exceedingly high Abell cluster surface density, appears to be a remarkable superposition of 23 rich clusters almost uniformly distributed in redshift space between 0.08 and 0.24. The new redshifts significantly increase the three-dimensional information available for the distance class 5 and 6 Abell clusters and allow the spatial correlation function around rich superclusters to be estimated.
NASA Astrophysics Data System (ADS)
Martins, Cyril; Lenz, Benjamin; Perfetti, Luca; Brouet, Veronique; Bertran, François; Biermann, Silke
2018-03-01
We address the role of nonlocal Coulomb correlations and short-range magnetic fluctuations in the high-temperature phase of Sr2IrO4 within state-of-the-art spectroscopic and first-principles theoretical methods. Introducing an "oriented-cluster dynamical mean-field scheme", we compute momentum-resolved spectral functions, which we find to be in excellent agreement with angle-resolved photoemission spectra. We show that while short-range antiferromagnetic fluctuations are crucial to accounting for the electronic properties of Sr2IrO4 even in the high-temperature paramagnetic phase, long-range magnetic order is not a necessary ingredient of the insulating state. Upon doping, an exotic metallic state is generated, exhibiting cuprate-like pseudo-gap spectral properties, for which we propose a surprisingly simple theoretical mechanism.
Large Scale Structure Studies: Final Results from a Rich Cluster Redshift Survey
NASA Astrophysics Data System (ADS)
Slinglend, K.; Batuski, D.; Haase, S.; Hill, J.
1995-12-01
The results from the COBE satellite show the existence of structure on scales on the order of 10% or more of the horizon scale of the universe. Rich clusters of galaxies from the Abell-ACO catalogs show evidence of structure on scales of 100 Mpc and hold the promise of confirming structure on the scale of the COBE result. Unfortunately, until now, redshift information has been unavailable for a large percentage of these clusters, so present knowledge of their three dimensional distribution has quite large uncertainties. Our approach in this effort has been to use the MX multifiber spectrometer on the Steward 2.3m to measure redshifts of at least ten galaxies in each of 88 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8 (estimated z<= 0.12) and zero or one measured redshifts. This work has resulted in a deeper, 95% complete and more reliable sample of 3-D positions of rich clusters. The primary intent of this survey has been to constrain theoretical models for the formation of the structure we see in the universe today through 2-pt. spatial correlation function and other analyses of the large scale structures traced by these clusters. In addition, we have obtained enough redshifts per cluster to greatly improve the quality and size of the sample of reliable cluster velocity dispersions available for use in other studies of cluster properties. This new data has also allowed the construction of an updated and more reliable supercluster candidate catalog. Our efforts have resulted in effectively doubling the volume traced by these clusters. Presented here is the resulting 2-pt. spatial correlation function, as well as density plots and several other figures quantifying the large scale structure from this much deeper and complete sample. Also, with 10 or more redshifts in most of our cluster fields, we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.
2017-01-01
Purpose Clinical test batteries for evaluation of knee function after injury to the Anterior Cruciate Ligament (ACL) should be valid and feasible, while reliably capturing the outcome of rehabilitation. There is currently a lack of consensus as to which of the many available assessment tools for knee function that should be included. The present aim was to use a statistical approach to investigate the contribution of frequently used tests to avoid redundancy, and filter them down to a proposed comprehensive and yet feasible test battery for long-term evaluation after ACL injury. Methods In total 48 outcome variables related to knee function, all potentially relevant for a long-term follow-up, were included from a cross-sectional study where 70 ACL-injured (17–28 years post injury) individuals were compared to 33 controls. Cluster analysis and logistic regression were used to group variables and identify an optimal test battery, from which a summarized estimator of knee function representing various functional aspects was derived. Results As expected, several variables were strongly correlated, and the variables also fell into logical clusters with higher within-correlation (max ρ = 0.61) than between clusters (max ρ = 0.19). An extracted test battery with just four variables assessing one-leg balance, isokinetic knee extension strength and hop performance (one-leg hop, side hop) were mathematically combined to an estimator of knee function, which acceptably classified ACL-injured individuals and controls. This estimator, derived from objective measures, correlated significantly with self-reported function, e.g. Lysholm score (ρ = 0.66; p<0.001). Conclusions The proposed test battery, based on a solid statistical approach, includes assessments which are all clinically feasible, while also covering complementary aspects of knee function. Similar test batteries could be determined for earlier phases of ACL rehabilitation or to enable longitudinal monitoring. Such developments, established on a well-grounded consensus of measurements, would facilitate comparisons of studies and enable evidence-based rehabilitation. PMID:28459885
Functional cortical network in alpha band correlates with social bargaining.
Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco
2014-01-01
Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals' alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts.
Functional Cortical Network in Alpha Band Correlates with Social Bargaining
Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco
2014-01-01
Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals’ alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts. PMID:25286240
Völlm, Birgit; Richardson, Paul; McKie, Shane; Elliott, Rebecca; Dolan, Mairead; Deakin, Bill
2007-11-15
Decision making is guided by the likely consequences of behavioural choices. Neuronal correlates of financial reward have been described in a number of functional imaging studies in humans. Areas implicated in reward include ventral striatum, dopaminergic midbrain, amygdala and orbitofrontal cortex. Response to loss has not been as extensively studied but may involve prefrontal and medial temporal cortices. It has been proposed that increased sensitivity to reward and reduced sensitivity to punishment underlie some of the psychopathology in impulsive personality disordered individuals. However, few imaging studies using reinforcement tasks have been conducted in this group. In this fMRI study, we investigate the effects of positive (monetary reward) and negative (monetary loss) outcomes on BOLD responses in two target selection tasks. The experimental group comprised eight people with Cluster B (antisocial and borderline) personality disorder, whilst the control group contained fourteen healthy participants. A key finding was the absence of prefrontal responses and reduced BOLD signal in the subcortical reward system in the PD group during positive reinforcement. Impulsivity scores correlated negatively with prefrontal responses in the PD but not the control group during both, reward and loss. Our results suggest dysfunctional responses to rewarding and aversive stimuli in Cluster B personality disordered individuals but do not support the notion of hypersensitivity to reward and hyposensitivity to loss.
Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Xu, Richard Yi Da; Luo, Xiangfeng
2018-05-01
Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two optimized nonnegative sparse factor matrices, which could benefit many tasks, such as document-word co-clustering. However, the traditional SNMF typically assumes the number of latent factors (i.e., dimensionality of the factor matrices) to be fixed. This assumption makes it inflexible in practice. In this paper, we propose a doubly sparse nonparametric NMF framework to mitigate this issue by using dependent Indian buffet processes (dIBP). We apply a correlation function for the generation of two stick weights associated with each column pair of factor matrices while still maintaining their respective marginal distribution specified by IBP. As a consequence, the generation of two factor matrices will be columnwise correlated. Under this framework, two classes of correlation function are proposed: 1) using bivariate Beta distribution and 2) using Copula function. Compared with the single IBP-based NMF, this paper jointly makes two factor matrices nonparametric and sparse, which could be applied to broader scenarios, such as co-clustering. This paper is seen to be much more flexible than Gaussian process-based and hierarchial Beta process-based dIBPs in terms of allowing the two corresponding binary matrix columns to have greater variations in their nonzero entries. Our experiments on synthetic data show the merits of this paper compared with the state-of-the-art models in respect of factorization efficiency, sparsity, and flexibility. Experiments on real-world data sets demonstrate the efficiency of this paper in document-word co-clustering tasks.
Schizophrenia classification using functional network features
NASA Astrophysics Data System (ADS)
Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle
2012-03-01
This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.
Analyzing survival curves at a fixed point in time for paired and clustered right-censored data
Su, Pei-Fang; Chi, Yunchan; Lee, Chun-Yi; Shyr, Yu; Liao, Yi-De
2018-01-01
In clinical trials, information about certain time points may be of interest in making decisions about treatment effectiveness. Rather than comparing entire survival curves, researchers can focus on the comparison at fixed time points that may have a clinical utility for patients. For two independent samples of right-censored data, Klein et al. (2007) compared survival probabilities at a fixed time point by studying a number of tests based on some transformations of the Kaplan-Meier estimators of the survival function. However, to compare the survival probabilities at a fixed time point for paired right-censored data or clustered right-censored data, their approach would need to be modified. In this paper, we extend the statistics to accommodate the possible within-paired correlation and within-clustered correlation, respectively. We use simulation studies to present comparative results. Finally, we illustrate the implementation of these methods using two real data sets. PMID:29456280
Family Functioning, Identity Formation, and the Ability of Conflict Resolution among Adolescents
ERIC Educational Resources Information Center
Kiani, Behnaz; Hojatkhah, Seyed Mohsen; Torabi-Nami, Mohammad
2016-01-01
Family is perhaps the most influential system in individuals' life in which various behaviors are learnt. Family functioning refers to the ability of family to meet its responsibilities. The present correlation study used a multi-stage cluster sampling method to recruit 686 subjects including 338 males and 348 females from all high school students…
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
Environment-based selection effects of Planck clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kosyra, R.; Gruen, D.; Seitz, S.
2015-07-24
We investigate whether the large-scale structure environment of galaxy clusters imprints a selection bias on Sunyaev–Zel'dovich (SZ) catalogues. Such a selection effect might be caused by line of sight (LoS) structures that add to the SZ signal or contain point sources that disturb the signal extraction in the SZ survey. We use the Planck PSZ1 union catalogue in the Sloan Digital Sky Survey (SDSS) region as our sample of SZ-selected clusters. We calculate the angular two-point correlation function (2pcf) for physically correlated, foreground and background structure in the RedMaPPer SDSS DR8 catalogue with respect to each cluster. We compare ourmore » results with an optically selected comparison cluster sample and with theoretical predictions. In contrast to the hypothesis of no environment-based selection, we find a mean 2pcf for background structures of -0.049 on scales of ≲40 arcmin, significantly non-zero at ~4σ, which means that Planck clusters are more likely to be detected in regions of low background density. We hypothesize this effect arises either from background estimation in the SZ survey or from radio sources in the background. We estimate the defect in SZ signal caused by this effect to be negligibly small, of the order of ~10 -4 of the signal of a typical Planck detection. Analogously, there are no implications on X-ray mass measurements. However, the environmental dependence has important consequences for weak lensing follow up of Planck galaxy clusters: we predict that projection effects account for half of the mass contained within a 15 arcmin radius of Planck galaxy clusters. We did not detect a background underdensity of CMASS LRGs, which also leaves a spatially varying redshift dependence of the Planck SZ selection function as a possible cause for our findings.« less
Chiang-Ni, Chuan; Zheng, Po-Xing; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong
2016-01-01
emm typing is the most widely used molecular typing method for the human pathogen Streptococcus pyogenes (group A streptococcus [GAS]). emm typing is based on a small variable region of the emm gene; however, the emm cluster typing system defines GAS types according to the nearly complete sequence of the emm gene. Therefore, emm cluster typing is considered to provide more information regarding the functional and structural properties of M proteins in different emm types of GAS. In the present study, 677 isolates collected between 1994 and 2008 in a hospital in southern Taiwan were analyzed by the emm cluster typing system. emm clusters A-C4, E1, E6, and A-C3 were the most prevalent emm cluster types and accounted for 67.4% of total isolates. emm clusters A-C4 and E1 were associated with noninvasive diseases, whereas E6 was significantly associated with both invasive and noninvasive manifestations. In addition, emm clusters D4, E2, and E3 were significantly associated with invasive manifestations. Furthermore, we found that the functional properties of M protein, including low fibrinogen-binding and high IgG-binding activities, were correlated significantly with invasive manifestations. In summary, the present study provides updated epidemiological information on GAS emm cluster types in southern Taiwan. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
NASA Astrophysics Data System (ADS)
Ziane, M.; Amitouche, F.; Bouarab, S.; Vega, A.
2017-12-01
Structural and electronic properties of pure molybdenum Mo n and molybdenum-sulfide Mo n S ( n = 1 - 10) clusters were investigated in the framework of the density functional theory within the generalized gradient approximation to exchange and correlation with the aim of addressing how doping with a single S atom affects the geometries, magnetic properties, and reactivity of pure molybdenum clusters. These clusters exhibit a less marked tendency to dimerization than their isoelectronic Cr counterparts despite sharing their half-filled valence shell configuration. Doping with a single S impurity is enough to change the structure of the host molybdenum cluster to a large extent, as well as to modify the bonding pattern, the magnetic state and the magnetic moment distribution in the Mo host. Vertical ionization potentials and electron affinities are calculated to determine global reactivity indicators like the electronegativity and the chemical hardness. The results are discussed in terms of the thermodynamical and relative stabilities, charge transfer effects, and spin-polarized densities of electronic states.
Traveling-cluster approximation for uncorrelated amorphous systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sen, A.K.; Mills, R.; Kaplan, T.
1984-11-15
We have developed a formalism for including cluster effects in the one-electron Green's function for a positionally disordered (liquid or amorphous) system without any correlation among the scattering sites. This method is an extension of the technique known as the traveling-cluster approximation (TCA) originally obtained and applied to a substitutional alloy by Mills and Ratanavararaksa. We have also proved the appropriate fixed-point theorem, which guarantees, for a bounded local potential, that the self-consistent equations always converge upon iteration to a unique, Herglotz solution. To our knowledge, this is the only analytic theory for considering cluster effects. Furthermore, we have performedmore » some computer calculations in the pair TCA, for the model case of delta-function potentials on a one-dimensional random chain. These results have been compared with ''exact calculations'' (which, in principle, take into account all cluster effects) and with the coherent-potential approximation (CPA), which is the single-site TCA. The density of states for the pair TCA clearly shows some improvement over the CPA and yet, apparently, the pair approximation distorts some of the features of the exact results.« less
Human frataxin is an allosteric switch that activates the Fe-S cluster biosynthetic complex.
Tsai, Chi-Lin; Barondeau, David P
2010-11-02
Cellular depletion of the human protein frataxin is correlated with the neurodegenerative disease Friedreich's ataxia and results in the inactivation of Fe-S cluster proteins. Most researchers agree that frataxin functions in the biogenesis of Fe-S clusters, but its precise role in this process is unclear. Here we provide in vitro evidence that human frataxin binds to a Nfs1, Isd11, and Isu2 complex to generate the four-component core machinery for Fe-S cluster biosynthesis. Frataxin binding dramatically changes the K(M) for cysteine from 0.59 to 0.011 mM and the catalytic efficiency (k(cat)/K(M)) of the cysteine desulfurase from 25 to 7900 M⁻¹s⁻¹. Oxidizing conditions diminish the levels of both complex formation and frataxin-based activation, whereas ferrous iron further stimulates cysteine desulfurase activity. Together, these results indicate human frataxin functions with Fe(2+) as an allosteric activator that triggers sulfur delivery and Fe-S cluster assembly. We propose a model in which cellular frataxin levels regulate human Fe-S cluster biosynthesis that has implications for mitochondrial dysfunction, oxidative stress response, and both neurodegenerative and cardiovascular disease.
Li, Yaqian; Du, Xilin; Lu, Zhi John; Wu, Daqiang; Zhao, Yilei; Ren, Bin; Huang, Jiaofang; Huang, Xianqing; Xu, Yuhong; Xu, Yuquan
2011-01-01
Background Phenazines are important compounds produced by pseudomonads and other bacteria. Two phz gene clusters called phzA1-G1 and phzA2-G2, respectively, were found in the genome of Pseudomonas sp. M18, an effective biocontrol agent, which is highly homologous to the opportunistic human pathogen P. aeruginosa PAO1, however little is known about the correlation between the expressions of two phz gene clusters. Methodology/Principal Findings Two chromosomal insertion inactivated mutants for the two gene clusters were constructed respectively and the correlation between the expressions of two phz gene clusters was investigated in strain M18. Phenazine-1-carboxylic acid (PCA) molecules produced from phzA2-G2 gene cluster are able to auto-regulate expression itself and activate the expression of phzA1-G1 gene cluster in a circulated amplification pattern. However, the post-transcriptional expression of phzA1-G1 transcript was blocked principally through 5′-untranslated region (UTR). In contrast, the phzA2-G2 gene cluster was transcribed to a lesser extent and translated efficiently and was negatively regulated by the GacA signal transduction pathway, mainly at a post-transcriptional level. Conclusions/Significance A single molecule, PCA, produced in different quantities by the two phz gene clusters acted as the functional mediator and the two phz gene clusters developed a specific regulatory mechanism which acts through 5′-UTR to transfer a single, but complex bacterial signaling event in Pseudomonas sp. strain M18. PMID:21559370
Krewald, Vera; Neese, Frank; Pantazis, Dimitrios A
2016-04-28
The redox potential of synthetic oligonuclear transition metal complexes has been shown to correlate with the Lewis acidity of a redox-inactive cation connected to the redox-active transition metals of the cluster via oxo or hydroxo bridges. Such heterometallic clusters are important cofactors in many metalloenzymes, where it is speculated that the redox-inactive constituent ion of the cluster serves to optimize its redox potential for electron transfer or catalysis. A principal example is the oxygen-evolving complex in photosystem II of natural photosynthesis, a Mn4CaO5 cofactor that oxidizes water into dioxygen, protons and electrons. Calcium is critical for catalytic function, but its precise role is not yet established. In analogy to synthetic complexes it has been suggested that Ca(2+) fine-tunes the redox potential of the manganese cluster. Here we evaluate this hypothesis by computing the relative redox potentials of substituted derivatives of the oxygen-evolving complex with the cations Sr(2+), Gd(3+), Cd(2+), Zn(2+), Mg(2+), Sc(3+), Na(+) and Y(3+) for two sequential transitions of its catalytic cycle. The theoretical approach is validated with a series of experimentally well-characterized Mn3AO4 cubane complexes that are structural mimics of the enzymatic cluster. Our results reproduce perfectly the experimentally observed correlation between the redox potential and the Lewis acidities of redox-inactive cations for the synthetic complexes. However, it is conclusively demonstrated that this correlation does not hold for the oxygen evolving complex. In the enzyme the redox potential of the cluster only responds to the charge of the redox-inactive cations and remains otherwise insensitive to their precise identity, precluding redox-tuning of the metal cluster as a primary role for Ca(2+) in biological water oxidation.
NASA Astrophysics Data System (ADS)
Teramae, Tatsuya; Kushida, Daisuke; Takemori, Fumiaki; Kitamura, Akira
Authors proposed the estimation method combining k-means algorithm and NN for evaluating massage. However, this estimation method has a problem that discrimination ratio is decreased to new user. There are two causes of this problem. One is that generalization of NN is bad. Another one is that clustering result by k-means algorithm has not high correlation coefficient in a class. Then, this research proposes k-means algorithm according to correlation coefficient and incremental learning for NN. The proposed k-means algorithm is method included evaluation function based on correlation coefficient. Incremental learning is method that NN is learned by new data and initialized weight based on the existing data. The effect of proposed methods are verified by estimation result using EEG data when testee is given massage.
Self-clarity and different clusters of insight and self-stigma in mental illness.
Hasson-Ohayon, Ilanit; Mashiach-Eizenberg, Michal; Lysaker, Paul H; Roe, David
2016-06-30
The current study explored the self-experience of persons with Serious Mental Illness (SMI) by investigating the associations between different insight and self-stigma clusters, self-clarity, hope, recovery, and functioning. One hundred seven persons diagnosed with a SMI were administered six scales: self-concept clarity, self-stigma, insight into the illness, hope, recovery, and functioning. Correlations and cluster analyses were performed. Insight, as measured by a self-report scale was not related to any other variable. Self-stigma was negatively associated with self-clarity, hope, recovery and functioning. Three clusters emerged: moderate stigma/high insight (n=31), high stigma/moderate insight (n=28), and low stigma/low insight (n=42). The group with low stigma and low insight had higher mean levels of self-clarity and hope than the other two groups. There were no significant differences between cluster 1 (moderate stigma/high insight) and cluster 2 (high stigma/moderate insight) in all the variables beside self-clarity. The group with moderate stigma and high insight had significantly higher mean levels of self-clarity than the group with high stigma and moderate insight. Results reveal that when people diagnosed with SMI do not have high levels of self-stigma they often report a positive and clear sense of self accompanied with hope, regardless of having low insight. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena
2017-10-01
Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.
Organization and hierarchy of the human functional brain network lead to a chain-like core.
Mastrandrea, Rossana; Gabrielli, Andrea; Piras, Fabrizio; Spalletta, Gianfranco; Caldarelli, Guido; Gili, Tommaso
2017-07-07
The brain is a paradigmatic example of a complex system: its functionality emerges as a global property of local mesoscopic and microscopic interactions. Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise. Here we present the analysis of functional magnetic resonance imaging data from forty healthy humans at rest for the investigation of the basal scaffold of the functional brain network organization. We show how brain regions tend to coordinate by forming a highly hierarchical chain-like structure of homogeneously clustered anatomical areas. A maximum spanning tree approach revealed the centrality of the occipital cortex and the peculiar aggregation of cerebellar regions to form a closed core. We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.
Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe; Zurzolo, Chiara
2017-12-01
Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. © 2017 The Author(s).
Phenetic Comparison of Prokaryotic Genomes Using k-mers
Déraspe, Maxime; Raymond, Frédéric; Boisvert, Sébastien; Culley, Alexander; Roy, Paul H.; Laviolette, François; Corbeil, Jacques
2017-01-01
Abstract Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets. PMID:28957508
Utility and Limitations of Using Gene Expression Data to Identify Functional Associations
Peng, Cheng; Shiu, Shin-Han
2016-01-01
Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950
The correlation function of galaxy ellipticities produced by gravitational lensing
NASA Technical Reports Server (NTRS)
Miralda-Escude, Jordi
1991-01-01
The correlation of galaxy ellipticities produced by gravitational lensing is calculated as a function of the power spectrum of density fluctuations in the universe by generalizing an analytical method developed by Gunn (1967). The method is applied to a model where identical objects with spherically symmetric density profiles are randomly laid down in space, and to the cold dark matter model. The possibility of detecting this correlation is discussed. Although an ellipticity correlation can also be caused by an intrinsic alignment of the axes of galaxies belonging to a cluster or a supercluster, a method is suggested by which one type of correlation can be distinguished from another. The advantage of this ellipticity correlation is that it is one of the few astronomical observations that can directly probe large-scale mass fluctuations in the universe.
Assessing Many-Body Effects of Water Self-Ions. I: OH-(H2O) n Clusters.
Egan, Colin K; Paesani, Francesco
2018-04-10
The importance of many-body effects in the hydration of the hydroxide ion (OH - ) is investigated through a systematic analysis of the many-body expansion of the interaction energy carried out at the CCSD(T) level of theory, extrapolated to the complete basis set limit, for the low-lying isomers of OH - (H 2 O) n clusters, with n = 1-5. This is accomplished by partitioning individual fragments extracted from the whole clusters into "groups" that are classified by both the number of OH - and water molecules and the hydrogen bonding connectivity within each fragment. With the aid of the absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) method, this structure-based partitioning is found to largely correlate with the character of different many-body interactions, such as cooperative and anticooperative hydrogen bonding, within each fragment. This analysis emphasizes the importance of a many-body representation of inductive electrostatics and charge transfer in modeling OH - hydration. Furthermore, the rapid convergence of the many-body expansion of the interaction energy also suggests a rigorous path for the development of analytical potential energy functions capable of describing individual OH - -water many-body terms, with chemical accuracy. Finally, a comparison between the reference CCSD(T) many-body interaction terms with the corresponding values obtained with various exchange-correlation functionals demonstrates that range-separated, dispersion-corrected, hybrid functionals exhibit the highest accuracy, while GGA functionals, with or without dispersion corrections, are inadequate to describe OH - -water interactions.
Hydrodynamic fractionation of finite size gold nanoparticle clusters.
Tsai, De-Hao; Cho, Tae Joon; DelRio, Frank W; Taurozzi, Julian; Zachariah, Michael R; Hackley, Vincent A
2011-06-15
We demonstrate a high-resolution in situ experimental method for performing simultaneous size classification and characterization of functional gold nanoparticle clusters (GNCs) based on asymmetric-flow field flow fractionation (AFFF). Field emission scanning electron microscopy, atomic force microscopy, multi-angle light scattering (MALS), and in situ ultraviolet-visible optical spectroscopy provide complementary data and imagery confirming the cluster state (e.g., dimer, trimer, tetramer), packing structure, and purity of fractionated populations. An orthogonal analysis of GNC size distributions is obtained using electrospray-differential mobility analysis (ES-DMA). We find a linear correlation between the normalized MALS intensity (measured during AFFF elution) and the corresponding number concentration (measured by ES-DMA), establishing the capacity for AFFF to quantify the absolute number concentration of GNCs. The results and corresponding methodology summarized here provide the proof of concept for general applications involving the formation, isolation, and in situ analysis of both functional and adventitious nanoparticle clusters of finite size. © 2011 American Chemical Society
Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex
Wilson, Daniel E.; Whitney, David E.; Scholl, Benjamin; Fitzpatrick, David
2016-01-01
The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo 2-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input-output nonlinearity that could not be explained by spike threshold alone, and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity. PMID:27294510
Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping.
Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui
2017-01-01
Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.
Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping
Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui
2017-01-01
Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD. PMID:29209199
Functional brain segmentation using inter-subject correlation in fMRI.
Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi
2017-05-01
The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
The structure of a gene co-expression network reveals biological functions underlying eQTLs.
Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali
2013-01-01
What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.
Cluster fusion-fission dynamics in the Singapore stock exchange
NASA Astrophysics Data System (ADS)
Teh, Boon Kin; Cheong, Siew Ann
2015-10-01
In this paper, we investigate how the cross-correlations between stocks in the Singapore stock exchange (SGX) evolve over 2008 and 2009 within overlapping one-month time windows. In particular, we examine how these cross-correlations change before, during, and after the Sep-Oct 2008 Lehman Brothers Crisis. To do this, we extend the complete-linkage hierarchical clustering algorithm, to obtain robust clusters of stocks with stronger intracluster correlations, and weaker intercluster correlations. After we identify the robust clusters in all time windows, we visualize how these change in the form of a fusion-fission diagram. Such a diagram depicts graphically how the cluster sizes evolve, the exchange of stocks between clusters, as well as how strongly the clusters mix. From the fusion-fission diagram, we see a giant cluster growing and disintegrating in the SGX, up till the Lehman Brothers Crisis in September 2008 and the market crashes of October 2008. After the Lehman Brothers Crisis, clusters in the SGX remain small for few months before giant clusters emerge once again. In the aftermath of the crisis, we also find strong mixing of component stocks between clusters. As a result, the correlation between initially strongly-correlated pairs of stocks decay exponentially with average life time of about a month. These observations impact strongly how portfolios and trading strategies should be formulated.
Lysaker, Paul H; Wickett, Amanda M; Lancaster, Rebecca S; Davis, Louanne W
2004-05-01
Cluster B personality traits have been detected in persons with schizophrenia, at a rate exceeding that of the general population. Unclear, however, is how to account for such high rates of Cluster B traits. Accordingly, this study explored the hypothesis that the presence of these traits may be linked to impairments in neurocognition, and childhood abuse history. To test this, we simultaneously obtained an assessment of Cluster B traits using the Millon Clinical Multiaxial Inventory III, along with measures of attention, verbal memory, affect recognition, executive function and childhood abuse history among 37 persons with schizophrenia spectrum disorders in a post acute phases of illness. Pearson correlation coefficients revealed that higher levels of histrionic and narcissistic traits were related to poorer neurocognition while higher levels of narcissistic traits were negatively correlated with childhood physical abuse. Higher levels of borderline traits were uniquely related to the report of childhood sexual abuse while higher levels of antisocial traits were related to higher levels of childhood physical abuse. Theoretical and clinical implications are discussed.
Star Cluster Formation in Cosmological Simulations. I. Properties of Young Clusters
NASA Astrophysics Data System (ADS)
Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.; Meng, Xi; Semenov, Vadim A.; Kravtsov, Andrey V.
2017-01-01
We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope is α ≈ 1.8{--}2, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. Comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.
Fraiman, Daniel; Chialvo, Dante R.
2012-01-01
The study of spontaneous fluctuations of brain activity, often referred as brain noise, is getting increasing attention in functional magnetic resonance imaging (fMRI) studies. Despite important efforts, much of the statistical properties of such fluctuations remain largely unknown. This work scrutinizes these fluctuations looking at specific statistical properties which are relevant to clarify its dynamical origins. Here, three statistical features which clearly differentiate brain data from naive expectations for random processes are uncovered: First, the variance of the fMRI mean signal as a function of the number of averaged voxels remains constant across a wide range of observed clusters sizes. Second, the anomalous behavior of the variance is originated by bursts of synchronized activity across regions, regardless of their widely different sizes. Finally, the correlation length (i.e., the length at which the correlation strength between two regions vanishes) as well as mutual information diverges with the cluster's size considered, such that arbitrarily large clusters exhibit the same collective dynamics than smaller ones. These three properties are known to be exclusive of complex systems exhibiting critical dynamics, where the spatio-temporal dynamics show these peculiar type of fluctuations. Thus, these findings are fully consistent with previous reports of brain critical dynamics, and are relevant for the interpretation of the role of fluctuations and variability in brain function in health and disease. PMID:22934058
Cosmological Constraints from Galaxy Clustering and the Mass-to-number Ratio of Galaxy Clusters
NASA Astrophysics Data System (ADS)
Tinker, Jeremy L.; Sheldon, Erin S.; Wechsler, Risa H.; Becker, Matthew R.; Rozo, Eduardo; Zu, Ying; Weinberg, David H.; Zehavi, Idit; Blanton, Michael R.; Busha, Michael T.; Koester, Benjamin P.
2012-01-01
We place constraints on the average density (Ω m ) and clustering amplitude (σ8) of matter using a combination of two measurements from the Sloan Digital Sky Survey: the galaxy two-point correlation function, wp (rp ), and the mass-to-galaxy-number ratio within galaxy clusters, M/N, analogous to cluster M/L ratios. Our wp (rp ) measurements are obtained from DR7 while the sample of clusters is the maxBCG sample, with cluster masses derived from weak gravitational lensing. We construct nonlinear galaxy bias models using the Halo Occupation Distribution (HOD) to fit both wp (rp ) and M/N for different cosmological parameters. HOD models that match the same two-point clustering predict different numbers of galaxies in massive halos when Ω m or σ8 is varied, thereby breaking the degeneracy between cosmology and bias. We demonstrate that this technique yields constraints that are consistent and competitive with current results from cluster abundance studies, without the use of abundance information. Using wp (rp ) and M/N alone, we find Ω0.5 m σ8 = 0.465 ± 0.026, with individual constraints of Ω m = 0.29 ± 0.03 and σ8 = 0.85 ± 0.06. Combined with current cosmic microwave background data, these constraints are Ω m = 0.290 ± 0.016 and σ8 = 0.826 ± 0.020. All errors are 1σ. The systematic uncertainties that the M/N technique are most sensitive to are the amplitude of the bias function of dark matter halos and the possibility of redshift evolution between the SDSS Main sample and the maxBCG cluster sample. Our derived constraints are insensitive to the current level of uncertainties in the halo mass function and in the mass-richness relation of clusters and its scatter, making the M/N technique complementary to cluster abundances as a method for constraining cosmology with future galaxy surveys.
Band structures in coupled-cluster singles-and-doubles Green's function (GFCCSD)
NASA Astrophysics Data System (ADS)
Furukawa, Yoritaka; Kosugi, Taichi; Nishi, Hirofumi; Matsushita, Yu-ichiro
2018-05-01
We demonstrate that the coupled-cluster singles-and-doubles Green's function (GFCCSD) method is a powerful and prominent tool drawing the electronic band structures and the total energies, which many theoretical techniques struggle to reproduce. We have calculated single-electron energy spectra via the GFCCSD method for various kinds of systems, ranging from ionic to covalent and van der Waals, for the first time: the one-dimensional LiH chain, one-dimensional C chain, and one-dimensional Be chain. We have found that the bandgap becomes narrower than in HF due to the correlation effect. We also show that the band structures obtained from the GFCCSD method include both quasiparticle and satellite peaks successfully. Besides, taking one-dimensional LiH as an example, we discuss the validity of restricting the active space to suppress the computational cost of the GFCCSD method. We show that the calculated results without bands that do not contribute to the chemical bonds are in good agreement with full-band calculations. With the GFCCSD method, we can calculate the total energies and spectral functions for periodic systems in an explicitly correlated manner.
Exact diagonalization library for quantum electron models
NASA Astrophysics Data System (ADS)
Iskakov, Sergei; Danilov, Michael
2018-04-01
We present an exact diagonalization C++ template library (EDLib) for solving quantum electron models, including the single-band finite Hubbard cluster and the multi-orbital impurity Anderson model. The observables that can be computed using EDLib are single particle Green's functions and spin-spin correlation functions. This code provides three different types of Hamiltonian matrix storage that can be chosen based on the model.
A Solution Space for a System of Null-State Partial Differential Equations: Part 1
NASA Astrophysics Data System (ADS)
Flores, Steven M.; Kleban, Peter
2015-01-01
This article is the first of four that completely and rigorously characterize a solution space for a homogeneous system of 2 N + 3 linear partial differential equations (PDEs) in 2 N variables that arises in conformal field theory (CFT) and multiple Schramm-Löwner evolution (SLE). In CFT, these are null-state equations and conformal Ward identities. They govern partition functions for the continuum limit of a statistical cluster or loop-gas model, such as percolation, or more generally the Potts models and O( n) models, at the statistical mechanical critical point. (SLE partition functions also satisfy these equations.) For such a lattice model in a polygon with its 2 N sides exhibiting a free/fixed side-alternating boundary condition , this partition function is proportional to the CFT correlation function where the w i are the vertices of and where is a one-leg corner operator. (Partition functions for "crossing events" in which clusters join the fixed sides of in some specified connectivity are linear combinations of such correlation functions.) When conformally mapped onto the upper half-plane, methods of CFT show that this correlation function satisfies the system of PDEs that we consider. In this first article, we use methods of analysis to prove that the dimension of this solution space is no more than C N , the Nth Catalan number. While our motivations are based in CFT, our proofs are completely rigorous. This proof is contained entirely within this article, except for the proof of Lemma 14, which constitutes the second article (Flores and Kleban, in Commun Math Phys, arXiv:1404.0035, 2014). In the third article (Flores and Kleban, in Commun Math Phys, arXiv:1303.7182, 2013), we use the results of this article to prove that the solution space of this system of PDEs has dimension C N and is spanned by solutions constructed with the CFT Coulomb gas (contour integral) formalism. In the fourth article (Flores and Kleban, in Commun Math Phys, arXiv:1405.2747, 2014), we prove further CFT-related properties about these solutions, some useful for calculating cluster-crossing probabilities of critical lattice models in polygons.
Nucleon localization and fragment formation in nuclear fission
Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.
2016-12-27
An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.
An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less
Weak lensing magnification of SpARCS galaxy clusters
NASA Astrophysics Data System (ADS)
Tudorica, A.; Hildebrandt, H.; Tewes, M.; Hoekstra, H.; Morrison, C. B.; Muzzin, A.; Wilson, G.; Yee, H. K. C.; Lidman, C.; Hicks, A.; Nantais, J.; Erben, T.; van der Burg, R. F. J.; Demarco, R.
2017-12-01
Context. Measuring and calibrating relations between cluster observables is critical for resource-limited studies. The mass-richness relation of clusters offers an observationally inexpensive way of estimating masses. Its calibration is essential for cluster and cosmological studies, especially for high-redshift clusters. Weak gravitational lensing magnification is a promising and complementary method to shear studies, that can be applied at higher redshifts. Aims: We aim to employ the weak lensing magnification method to calibrate the mass-richness relation up to a redshift of 1.4. We used the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS) galaxy cluster candidates (0.2 < z < 1.4) and optical data from the Canada France Hawaii Telescope (CFHT) to test whether magnification can be effectively used to constrain the mass of high-redshift clusters. Methods: Lyman-break galaxies (LBGs) selected using the u-band dropout technique and their colours were used as a background sample of sources. LBG positions were cross-correlated with the centres of the sample of SpARCS clusters to estimate the magnification signal, which was optimally-weighted using an externally-calibrated LBG luminosity function. The signal was measured for cluster sub-samples, binned in both redshift and richness. Results: We measured the cross-correlation between the positions of galaxy cluster candidates and LBGs and detected a weak lensing magnification signal for all bins at a detection significance of 2.6-5.5σ. In particular, the significance of the measurement for clusters with z> 1.0 is 4.1σ; for the entire cluster sample we obtained an average M200 of 1.28 -0.21+0.23 × 1014 M⊙. Conclusions: Our measurements demonstrated the feasibility of using weak lensing magnification as a viable tool for determining the average halo masses for samples of high redshift galaxy clusters. The results also established the success of using galaxy over-densities to select massive clusters at z > 1. Additional studies are necessary for further modelling of the various systematic effects we discussed.
Fast Electron Correlation Methods for Molecular Clusters without Basis Set Superposition Errors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kamiya, Muneaki; Hirata, So; Valiev, Marat
2008-02-19
Two critical extensions to our fast, accurate, and easy-to-implement binary or ternary interaction method for weakly-interacting molecular clusters [Hirata et al. Mol. Phys. 103, 2255 (2005)] have been proposed, implemented, and applied to water hexamers, hydrogen fluoride chains and rings, and neutral and zwitterionic glycine–water clusters with an excellent result for an initial performance assessment. Our original method included up to two- or three-body Coulomb, exchange, and correlation energies exactly and higher-order Coulomb energies in the dipole–dipole approximation. In this work, the dipole moments are replaced by atom-centered point charges determined so that they reproduce the electrostatic potentials of themore » cluster subunits as closely as possible and also self-consistently with one another in the cluster environment. They have been shown to lead to dramatic improvement in the description of short-range electrostatic potentials not only of large, charge-separated subunits like zwitterionic glycine but also of small subunits. Furthermore, basis set superposition errors (BSSE) known to plague direct evaluation of weak interactions have been eliminated by com-bining the Valiron–Mayer function counterpoise (VMFC) correction with our binary or ternary interaction method in an economical fashion (quadratic scaling n2 with respect to the number of subunits n when n is small and linear scaling when n is large). A new variant of VMFC has also been proposed in which three-body and all higher-order Coulomb effects on BSSE are estimated approximately. The BSSE-corrected ternary interaction method with atom-centered point charges reproduces the VMFC-corrected results of conventional electron correlation calculations within 0.1 kcal/mol. The proposed method is significantly more accurate and also efficient than conventional correlation methods uncorrected of BSSE.« less
NASA Astrophysics Data System (ADS)
Lehtola, Susi; Tubman, Norm M.; Whaley, K. Birgitta; Head-Gordon, Martin
2017-10-01
Approximate full configuration interaction (FCI) calculations have recently become tractable for systems of unforeseen size, thanks to stochastic and adaptive approximations to the exponentially scaling FCI problem. The result of an FCI calculation is a weighted set of electronic configurations, which can also be expressed in terms of excitations from a reference configuration. The excitation amplitudes contain information on the complexity of the electronic wave function, but this information is contaminated by contributions from disconnected excitations, i.e., those excitations that are just products of independent lower-level excitations. The unwanted contributions can be removed via a cluster decomposition procedure, making it possible to examine the importance of connected excitations in complicated multireference molecules which are outside the reach of conventional algorithms. We present an implementation of the cluster decomposition analysis and apply it to both true FCI wave functions, as well as wave functions generated from the adaptive sampling CI algorithm. The cluster decomposition is useful for interpreting calculations in chemical studies, as a diagnostic for the convergence of various excitation manifolds, as well as as a guidepost for polynomially scaling electronic structure models. Applications are presented for (i) the double dissociation of water, (ii) the carbon dimer, (iii) the π space of polyacenes, and (iv) the chromium dimer. While the cluster amplitudes exhibit rapid decay with an increasing rank for the first three systems, even connected octuple excitations still appear important in Cr2, suggesting that spin-restricted single-reference coupled-cluster approaches may not be tractable for some problems in transition metal chemistry.
Marginal regression approach for additive hazards models with clustered current status data.
Su, Pei-Fang; Chi, Yunchan
2014-01-15
Current status data arise naturally from tumorigenicity experiments, epidemiology studies, biomedicine, econometrics and demographic and sociology studies. Moreover, clustered current status data may occur with animals from the same litter in tumorigenicity experiments or with subjects from the same family in epidemiology studies. Because the only information extracted from current status data is whether the survival times are before or after the monitoring or censoring times, the nonparametric maximum likelihood estimator of survival function converges at a rate of n(1/3) to a complicated limiting distribution. Hence, semiparametric regression models such as the additive hazards model have been extended for independent current status data to derive the test statistics, whose distributions converge at a rate of n(1/2) , for testing the regression parameters. However, a straightforward application of these statistical methods to clustered current status data is not appropriate because intracluster correlation needs to be taken into account. Therefore, this paper proposes two estimating functions for estimating the parameters in the additive hazards model for clustered current status data. The comparative results from simulation studies are presented, and the application of the proposed estimating functions to one real data set is illustrated. Copyright © 2013 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kobas, Miroslav; Weber, Thomas; Steurer, Walter
The three-dimensional (3D) difference Patterson (autocorrelation) function of a disordered quasicrystal (Edagawa phase) has been analyzed. 3D diffuse x-ray diffraction data were collected in situ at 300, 1070, and 1120 K. A method, the punch-and-fill technique, has been developed for separating diffuse scattering and Bragg reflections. Its potential and limits are discussed in detail. The different Patterson maps are interpreted in terms of intercluster correlations as a function of temperature. Both at high and low temperatures, the clusters decorate the vertices of the same quasiperiodic covering. At low temperatures, for the disordered part of the structure, short-range intercluster correlations aremore » present, whereas at higher temperatures, medium-range intercluster correlations are formed. This indicates disorder mainly inside clusters at low temperatures, whereas at higher temperatures disorder takes place inside larger superclusters. Qualitatively, the Patterson maps may be interpreted by intercluster correlations mainly inside pentagonal superclusters below 1120 K, and inside the larger decagonal superclusters at 1120 K. The results of our diffraction study are published in two parts. Part I focuses on the 3D Patterson analysis based on experimental data, Part II reports modeling of structural disorder in decagonal Al-Co-Ni.« less
Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters.
Pathak, A K; Mukherjee, T; Maity, D K
2007-07-28
We report vertical detachment energy (VDE) and IR spectra of Br2.-.(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2.-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150 K. A linear relationship is obtained for VDE versus (n+3)(-1/3) and bulk VDE of Br2.- aqueous solution is calculated as 10.01 eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by approximately 0.5 eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by approximately 6.4 eV. Calculated IR spectra show that the formation of Br2.--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2.-.(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.
Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters
NASA Astrophysics Data System (ADS)
Pathak, A. K.; Mukherjee, T.; Maity, D. K.
2007-07-01
We report vertical detachment energy (VDE) and IR spectra of Br2•-•(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2•-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150K. A linear relationship is obtained for VDE versus (n+3)-1/3 and bulk VDE of Br2•- aqueous solution is calculated as 10.01eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by ˜0.5eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by ˜6.4eV. Calculated IR spectra show that the formation of Br2•--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2•-•(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.
Hubbard pair cluster in the external fields. Studies of the magnetic properties
NASA Astrophysics Data System (ADS)
Balcerzak, T.; Szałowski, K.
2018-06-01
The magnetic properties of the two-site Hubbard cluster (dimer or pair), embedded in the external electric and magnetic fields and treated as the open system, are studied by means of the exact diagonalization of the Hamiltonian. The formalism of the grand canonical ensemble is adopted. The phase diagrams, on-site magnetizations, spin-spin correlations, mean occupation numbers and hopping energy are investigated and illustrated in figures. An influence of temperature, mean electron concentration, Coulomb U parameter and external fields on the quantities of interest is presented and discussed. In particular, the anomalous behaviour of the magnetization and correlation function vs. temperature near the critical magnetic field is found. Also, the effect of magnetization switching by the external fields is demonstrated.
NASA Astrophysics Data System (ADS)
Whitmore, Bradley C.; Chandar, Rupali; Bowers, Ariel S.; Larsen, Soeren; Lindsay, Kevin; Ansari, Asna; Evans, Jessica
2014-04-01
Luminosity functions (LFs) have been determined for star cluster populations in 20 nearby (4-30 Mpc), star-forming galaxies based on Advanced Camera for Surveys source lists generated by the Hubble Legacy Archive (HLA). These cluster catalogs provide one of the largest sets of uniform, automatically generated cluster candidates available in the literature at present. Comparisons are made with other recently generated cluster catalogs demonstrating that the HLA-generated catalogs are of similar quality, but in general do not go as deep. A typical cluster LF can be approximated by a power law, dN/dLvpropL α, with an average value for α of -2.37 and rms scatter = 0.18 when using the F814W ("I") band. A comparison of fitting results based on methods that use binned and unbinned data shows good agreement, although there may be a systematic tendency for the unbinned (maximum likelihood) method to give slightly more negative values of α for galaxies with steeper LFs. We find that galaxies with high rates of star formation (or equivalently, with the brightest or largest numbers of clusters) have a slight tendency to have shallower values of α. In particular, the Antennae galaxy (NGC 4038/39), a merging system with a relatively high star formation rate (SFR), has the second flattest LF in the sample. A tentative correlation may also be present between Hubble type and values of α, in the sense that later type galaxies (i.e., Sd and Sm) appear to have flatter LFs. Hence, while there do appear to be some weak correlations, the relative similarity in the values of α for a large number of star-forming galaxies suggests that, to first order, the LFs are fairly universal. We examine the bright end of the LFs and find evidence for a downturn, although it only pertains to about 1% of the clusters. Our uniform database results in a small scatter (≈0.4 to 0.5 mag) in the correlation between the magnitude of the brightest cluster (M brightest) and log of the number of clusters brighter than MI = -9 (log N). We also examine the magnitude of the brightest cluster versus log SFR for a sample including both dwarf galaxies and ULIRGs. This shows that the correlation extends over roughly six orders of magnitude but with scatter that is larger than for our spiral sample, probably because of the high levels of extinction in many of the LIRGs. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Also based on data obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESA), and the Canadian Astronomy Data Centre (CADC/NRC/CSA). Support for Program number 11781 was provided by NASA through a grant from the Space Telescope Science Institute.
Statistical framework and noise sensitivity of the amplitude radial correlation contrast method.
Kipervaser, Zeev Gideon; Pelled, Galit; Goelman, Gadi
2007-09-01
A statistical framework for the amplitude radial correlation contrast (RCC) method, which integrates a conventional pixel threshold approach with cluster-size statistics, is presented. The RCC method uses functional MRI (fMRI) data to group neighboring voxels in terms of their degree of temporal cross correlation and compares coherences in different brain states (e.g., stimulation OFF vs. ON). By defining the RCC correlation map as the difference between two RCC images, the map distribution of two OFF states is shown to be normal, enabling the definition of the pixel cutoff. The empirical cluster-size null distribution obtained after the application of the pixel cutoff is used to define a cluster-size cutoff that allows 5% false positives. Assuming that the fMRI signal equals the task-induced response plus noise, an analytical expression of amplitude-RCC dependency on noise is obtained and used to define the pixel threshold. In vivo and ex vivo data obtained during rat forepaw electric stimulation are used to fine-tune this threshold. Calculating the spatial coherences within in vivo and ex vivo images shows enhanced coherence in the in vivo data, but no dependency on the anesthesia method, magnetic field strength, or depth of anesthesia, strengthening the generality of the proposed cutoffs. Copyright (c) 2007 Wiley-Liss, Inc.
A Perfusion MRI Study of Emotional Valence and Arousal in Parkinson's Disease
Limsoontarakul, Sunsern; Campbell, Meghan C.; Black, Kevin J.
2011-01-01
Background. Brain regions subserving emotion have mostly been studied using functional magnetic resonance imaging (fMRI) during emotion provocation procedures in healthy participants. Objective. To identify neuroanatomical regions associated with spontaneous changes in emotional state over time. Methods. Self-rated emotional valence and arousal scores, and regional cerebral blood flow (rCBF) measured by perfusion MRI, were measured 4 or 8 times spanning at least 2 weeks in each of 21 subjects with Parkinson's disease (PD). A random-effects SPM analysis, corrected for multiple comparisons, identified significant clusters of contiguous voxels in which rCBF varied with valence or arousal. Results. Emotional valence correlated positively with rCBF in several brain regions, including medial globus pallidus, orbital prefrontal cortex (PFC), and white matter near putamen, thalamus, insula, and medial PFC. Valence correlated negatively with rCBF in striatum, subgenual cingulate cortex, ventrolateral PFC, and precuneus—posterior cingulate cortex (PCC). Arousal correlated positively with rCBF in clusters including claustrum-thalamus-ventral striatum and inferior parietal lobule and correlated negatively in clusters including posterior insula—mediodorsal thalamus and midbrain. Conclusion. This study demonstrates that the temporal stability of perfusion MRI allows within-subject investigations of spontaneous fluctuations in mental state, such as mood, over relatively long-time intervals. PMID:21969917
Matter and charge distributions of 6He and 5,6,7,9Li within the dynamic-correlation model
NASA Astrophysics Data System (ADS)
Tomaselli, M.; Hjorth-Jensen, M.; Fritzsche, S.; Egelhof, P.; Neumaier, S. R.; Mutterer, M.; Kühl, T.; Dax, A.; Wang, H.
2000-12-01
The matter and the charge distributions of the 6He and 5,6,7,9Li isotopes are investigated within the dynamic-correlation model (DCM) which describes the ground states of light nuclei in terms of microscopic correlated clusters: the valence particles and the intrinsic vacuum states. The amplitudes of these mixed-mode wave functions are calculated in the framework of nonperturbative solutions of the equation of motion method (EOMM). The matter and charge mean square radii are in good agreement with experimental results. The calculated matter distribution of the 6He nucleus is characterized by a halo structure less pronounced than that calculated by the three cluster models. The charge distribution of 6Li reproduces well the electron scattering data. Good agreement with experimental data has been also achieved for the proton scattering cross sections of p-6He at an energy of 0.7 GeV/nucleon.
Singlet-paired coupled cluster theory for open shells
NASA Astrophysics Data System (ADS)
Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.
2016-06-01
Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior for strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.
Gehring, Karin; Taphoorn, Martin J.B.; Sitskoorn, Margriet M.; Aaronson, Neil K.
2015-01-01
Background Studies in cancer and noncancer populations demonstrate lower than expected correlations between subjective cognitive symptoms and cognitive functioning as determined by standardized neuropsychological tests. This paper systematically examines the association between subjective and objective cognitive functioning in patients with low-grade glioma and the associations of these indicators of cognitive function with clusters of sociodemographic, clinical, and self-reported physical and mental health factors. Methods Multiple regression analyses with the subjective and 2 objective indicators of cognitive functioning as dependent variables and 4 clusters of predictor variables were conducted in 169 patients with predominantly low-grade glioma. Results Correlations between the subjective and the 2 objective cognitive indicators were negligible (0.04) to low (0.24). Objective cognitive deficits were predominantly associated with sociodemographic (older age, lower education, male sex) and clinical (left hemisphere tumor) variables, while lower ratings of subjective cognitive function were more closely related to self-reported mental health symptoms (fatigue, lower mental well-being), physical (motor) dysfunction and female sex. Self-reported communication deficits were associated significantly with both subjective and objective dysfunction. Conclusions We recommend that both subjective and objective measures of cognitive functioning, together with a measure of psychological distress, be used for comprehensive neuropsychological assessments of patients with glioma to determine which areas are most affected and which specific intervention strategies are most appropriate. PMID:26034638
Constrained variation in Jastrow method at high density
DOE Office of Scientific and Technical Information (OSTI.GOV)
Owen, J.C.; Bishop, R.F.; Irvine, J.M.
1976-11-01
A method is derived for constraining the correlation function in a Jastrow variational calculation which permits the truncation of the cluster expansion after two-body terms, and which permits exact minimization of the two-body cluster by functional variation. This method is compared with one previously proposed by Pandharipande and is found to be superior both theoretically and practically. The method is tested both on liquid /sup 3/He, by using the Lennard--Jones potential, and on the model system of neutrons treated as Boltzmann particles (''homework'' problem). Good agreement is found both with experiment and with other calculations involving the explicit evaluation ofmore » higher-order terms in the cluster expansion. The method is then applied to a more realistic model of a neutron gas up to a density of 4 neutrons per F/sup 3/, and is found to give ground-state energies considerably lower than those of Pandharipande. (AIP)« less
Clustering stocks using partial correlation coefficients
NASA Astrophysics Data System (ADS)
Jung, Sean S.; Chang, Woojin
2016-11-01
A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.
Demir, Özlem; Baronio, Roberta; Salehi, Faezeh; Wassman, Christopher D.; Hall, Linda; Hatfield, G. Wesley; Chamberlin, Richard; Kaiser, Peter; Lathrop, Richard H.; Amaro, Rommie E.
2011-01-01
The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain (“cancer mutants”). Activity can be restored by second-site suppressor mutations (“rescue mutants”). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 µs of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r2 = 0.77) with reported values of experimentally measured ΔΔG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants. PMID:22028641
Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong
2011-01-01
We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.
A Study of the Dependence of the Properties of Galaxy Clusters on Cluster Morphology.
NASA Astrophysics Data System (ADS)
Lugger, Phyllis Minnie
1982-03-01
A quantitative study of the properties of clusters of galaxies as a function of cluster morphology has been carried out using photographic plates obtained with the Palomar 48 inch Schmidt telescope. Surface brightness profiles of 35 first ranked cluster galaxies and luminosity functions of nine clusters are presented and analyzed. The dispersion in the metric magnitudes of first ranked galaxies is quite small ((TURN) 0.4 mag) which is consistent with the results of Kristian, Sandage and Westphal as well as Hoessel, Gunn and Thuan. For the cD (supergiant elliptical) galaxy sample, the mean metric magnitude is (TURN) 0.5 mag brighter than for the non-cD galaxies. The dispersion in the metric magnitudes for the 10 cD galaxies studied is found to be much smaller ((sigma) (TURN) 0.1 mag) than the dispersion in the metric magnitudes of the non-cD first ranked galaxies ((sigma) (TURN) 0.4 mag). The de Vaucouleurs effective radius - magnitude relation determined in the present study for first ranked galaxies (log r(,e) = -0.2 M + const.) is consistent with the extrapolations to brighter magnitudes of the range of relations found by Strom and Strom. The average residuals from the mean radius-magnitude relation for the cD and non-cD galaxy samples were not found to differ at a significant level. Luminosity functions for the region within 0.5 Mpc of the cluster center for three of the clusters studied (A1656, A2147, and A2199) show a deficit of bright galaxies when compared to a concentric annular region with bounds of 0.5 and 1.0 Mpc. Characteristic magnitudes for the nine clusters (determined from square regions 4.6 Mpc on a side) show no significant correlation with cluster morphology, central density, or total magnitude of the first ranked galaxy. The mean values of the Schechter function parameters M('*) and (alpha) are in very good agreement with the previous determinations by Schechter and by Dressler. The differential luminosity functions for A569 and A1656 do not rise monotonically to fainter magnitudes but instead show dips. These data are used to test predictions of several recent theories of the dynamical evolution of clusters of galaxies.
Findings in resting-state fMRI by differences from K-means clustering.
Chyzhyk, Darya; Graña, Manuel
2014-01-01
Resting state fMRI has growing number of studies with diverse aims, always centered on some kind of functional connectivity biomarker obtained from correlation regarding seed regions, or by analytical decomposition of the signal towards the localization of the spatial distribution of functional connectivity patterns. In general, studies are computationally costly and very sensitive to noise and preprocessing of data. In this paper we consider clustering by K-means as a exploratory procedure which can provide some results with little computational effort, due to efficient implementations that are readily available. We demonstrate the approach on a dataset of schizophrenia patients, finding differences between patients with and without auditory hallucinations.
2010-01-01
Background Molecular chaperones have been shown to be important in the growth of the malaria parasite Plasmodium falciparum and inhibition of chaperone function by pharmacological agents has been shown to abrogate parasite growth. A recent study has demonstrated that clinical isolates of the parasite have distinct physiological states, one of which resembles environmental stress response showing up-regulation of specific molecular chaperones. Methods Chaperone networks operational in the distinct physiological clusters in clinical malaria parasites were constructed using cytoscape by utilizing their clinical expression profiles. Results Molecular chaperones show distinct profiles in the previously defined physiologically distinct states. Further, expression profiles of the chaperones from different cellular compartments correlate with specific patient clusters. While cluster 1 parasites, representing a starvation response, show up-regulation of organellar chaperones, cluster 2 parasites, which resemble active growth based on glycolysis, show up-regulation of cytoplasmic chaperones. Interestingly, cytoplasmic Hsp90 and its co-chaperones, previously implicated as drug targets in malaria, cluster in the same group. Detailed analysis of chaperone expression in the patient cluster 2 reveals up-regulation of the entire Hsp90-dependent pro-survival circuitries. In addition, cluster 2 also shows up-regulation of Plasmodium export element (PEXEL)-containing Hsp40s thought to have regulatory and host remodeling roles in the infected erythrocyte. Conclusion In all, this study demonstrates an intimate involvement of parasite-encoded chaperones, PfHsp90 in particular, in defining pathogenesis of malaria. PMID:20719001
FAST TRACK COMMUNICATION Critical exponents of domain walls in the two-dimensional Potts model
NASA Astrophysics Data System (ADS)
Dubail, Jérôme; Lykke Jacobsen, Jesper; Saleur, Hubert
2010-12-01
We address the geometrical critical behavior of the two-dimensional Q-state Potts model in terms of the spin clusters (i.e. connected domains where the spin takes a constant value). These clusters are different from the usual Fortuin-Kasteleyn clusters, and are separated by domain walls that can cross and branch. We develop a transfer matrix technique enabling the formulation and numerical study of spin clusters even when Q is not an integer. We further identify geometrically the crossing events which give rise to conformal correlation functions. This leads to an infinite series of fundamental critical exponents h_{\\ell _1-\\ell _2,2\\ell _1}, valid for 0 <= Q <= 4, that describe the insertion of ell1 thin and ell2 thick domain walls.
Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform
NASA Astrophysics Data System (ADS)
Pando, Jesus
1997-10-01
The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)
Sample size determination for GEE analyses of stepped wedge cluster randomized trials.
Li, Fan; Turner, Elizabeth L; Preisser, John S
2018-06-19
In stepped wedge cluster randomized trials, intact clusters of individuals switch from control to intervention from a randomly assigned period onwards. Such trials are becoming increasingly popular in health services research. When a closed cohort is recruited from each cluster for longitudinal follow-up, proper sample size calculation should account for three distinct types of intraclass correlations: the within-period, the inter-period, and the within-individual correlations. Setting the latter two correlation parameters to be equal accommodates cross-sectional designs. We propose sample size procedures for continuous and binary responses within the framework of generalized estimating equations that employ a block exchangeable within-cluster correlation structure defined from the distinct correlation types. For continuous responses, we show that the intraclass correlations affect power only through two eigenvalues of the correlation matrix. We demonstrate that analytical power agrees well with simulated power for as few as eight clusters, when data are analyzed using bias-corrected estimating equations for the correlation parameters concurrently with a bias-corrected sandwich variance estimator. © 2018, The International Biometric Society.
Tsui, Emily Y.; Agapie, Theodor
2013-01-01
Understanding the effect of redox-inactive metals on the properties of biological and heterogeneous water oxidation catalysts is important both fundamentally and for improvement of future catalyst designs. In this work, heterometallic manganese–oxido cubane clusters [MMn3O4] (M = Sr2+, Zn2+, Sc3+, Y3+) structurally relevant to the oxygen-evolving complex (OEC) of photosystem II were prepared and characterized. The reduction potentials of these clusters and other related mixed metal manganese–tetraoxido complexes are correlated with the Lewis acidity of the apical redox-inactive metal in a manner similar to a related series of heterometallic manganese–dioxido clusters. The redox potentials of the [SrMn3O4] and [CaMn3O4] clusters are close, which is consistent with the observation that the OEC is functional only with one of these two metals. Considering our previous studies of [MMn3O2] moieties, the present results with more structurally accurate models of the OEC ([MMn3O4]) suggest a general relationship between the reduction potentials of heterometallic oxido clusters and the Lewis acidities of incorporated cations that applies to diverse structural motifs. These findings support proposals that one function of calcium in the OEC is to modulate the reduction potential of the cluster to allow electron transfer. PMID:23744039
SOMBI: Bayesian identification of parameter relations in unstructured cosmological data
NASA Astrophysics Data System (ADS)
Frank, Philipp; Jasche, Jens; Enßlin, Torsten A.
2016-11-01
This work describes the implementation and application of a correlation determination method based on self organizing maps and Bayesian inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the self organizing map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian information criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide applications of our method to cosmological data. In particular, we present results of a correlation analysis between galaxy and active galactic nucleus (AGN) properties provided by the SDSS catalog with the cosmic large-scale-structure (LSS). The results indicate that the combined galaxy and LSS dataset indeed is clustered into several sub-samples of data with different average properties (for example different stellar masses or web-type classifications). The majority of data clusters appear to have a similar correlation structure between galaxy properties and the LSS. In particular we revealed a positive and linear dependency between the stellar mass, the absolute magnitude and the color of a galaxy with the corresponding cosmic density field. A remaining subset of data shows inverted correlations, which might be an artifact of non-linear redshift distortions.
Star cluster formation in cosmological simulations. I. Properties of young clusters
Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.; ...
2017-01-03
We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope ismore » $$\\alpha \\approx 1.8\\mbox{–}2$$, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. As a result, comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.« less
Star cluster formation in cosmological simulations. I. Properties of young clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Hui; Gnedin, Oleg Y.; Gnedin, Nickolay Y.
We present a new implementation of star formation in cosmological simulations by considering star clusters as a unit of star formation. Cluster particles grow in mass over several million years at the rate determined by local gas properties, with high time resolution. The particle growth is terminated by its own energy and momentum feedback on the interstellar medium. We test this implementation for Milky Way-sized galaxies at high redshift by comparing the properties of model clusters with observations of young star clusters. We find that the cluster initial mass function is best described by a Schechter function rather than a single power law. In agreement with observations, at low masses the logarithmic slope ismore » $$\\alpha \\approx 1.8\\mbox{–}2$$, while the cutoff at high mass scales with the star formation rate (SFR). A related trend is a positive correlation between the surface density of the SFR and fraction of stars contained in massive clusters. Both trends indicate that the formation of massive star clusters is preferred during bursts of star formation. These bursts are often associated with major-merger events. We also find that the median timescale for cluster formation ranges from 0.5 to 4 Myr and decreases systematically with increasing star formation efficiency. Local variations in the gas density and cluster accretion rate naturally lead to the scatter of the overall formation efficiency by an order of magnitude, even when the instantaneous efficiency is kept constant. As a result, comparison of the formation timescale with the observed age spread of young star clusters provides an additional important constraint on the modeling of star formation and feedback schemes.« less
Rate laws of the self-induced aggregation kinetics of Brownian particles
NASA Astrophysics Data System (ADS)
Mondal, Shrabani; Sen, Monoj Kumar; Baura, Alendu; Bag, Bidhan Chandra
2016-03-01
In this paper we have studied the self induced aggregation kinetics of Brownian particles in the presence of both multiplicative and additive noises. In addition to the drift due to the self aggregation process, the environment may induce a drift term in the presence of a multiplicative noise. Then there would be an interplay between the two drift terms. It may account qualitatively the appearance of the different laws of aggregation process. At low strength of white multiplicative noise, the cluster number decreases as a Gaussian function of time. If the noise strength becomes appreciably large then the variation of cluster number with time is fitted well by the mono exponentially decaying function of time. For additive noise driven case, the decrease of cluster number can be described by the power law. But in case of multiplicative colored driven process, cluster number decays multi exponentially. However, we have explored how the rate constant (in the mono exponentially cluster number decaying case) depends on strength of interference of the noises and their intensity. We have also explored how the structure factor at long time depends on the strength of the cross correlation (CC) between the additive and the multiplicative noises.
Automating the expert consensus paradigm for robust lung tissue classification
NASA Astrophysics Data System (ADS)
Rajagopalan, Srinivasan; Karwoski, Ronald A.; Raghunath, Sushravya; Bartholmai, Brian J.; Robb, Richard A.
2012-03-01
Clinicians confirm the efficacy of dynamic multidisciplinary interactions in diagnosing Lung disease/wellness from CT scans. However, routine clinical practice cannot readily accomodate such interactions. Current schemes for automating lung tissue classification are based on a single elusive disease differentiating metric; this undermines their reliability in routine diagnosis. We propose a computational workflow that uses a collection (#: 15) of probability density functions (pdf)-based similarity metrics to automatically cluster pattern-specific (#patterns: 5) volumes of interest (#VOI: 976) extracted from the lung CT scans of 14 patients. The resultant clusters are refined for intra-partition compactness and subsequently aggregated into a super cluster using a cluster ensemble technique. The super clusters were validated against the consensus agreement of four clinical experts. The aggregations correlated strongly with expert consensus. By effectively mimicking the expertise of physicians, the proposed workflow could make automation of lung tissue classification a clinical reality.
Symptom correlates of cerebral blood flow following acute concussion.
Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A
2017-01-01
Concussion is associated with significant symptoms within hours to days post-injury, including disturbances in physical function, cognition, sleep and emotion. However, little is known about how subjective impairments correlate with objective measures of cerebrovascular function following brain injury. This study examined the relationship between symptoms and cerebral blood flow (CBF) in individuals following sport-related concussion. Seventy university level athletes had CBF measured using Arterial Spin Labelling (ASL), including 35 with acute concussion and 35 matched controls and their symptoms were assessed using the Sport Concussion Assessment Tool 3 (SCAT3). For concussed athletes, greater total symptom severity was associated with elevated posterior cortical CBF, although mean CBF was not significantly different from matched controls ( p = 0.46). Examining symptom clusters, athletes reporting greater cognitive symptoms also had lower frontal and subcortical CBF, relative to athletes with greater somatic symptoms. The "cognitive" and "somatic" subgroups also exhibited significant differences in CBF relative to controls ( p ≤ 0.026). This study demonstrates objective CBF correlates of symptoms in recently concussed athletes and shows that specific symptom clusters may have distinct patterns of altered CBF, significantly extending our understanding of the neurobiology of concussion and traumatic brain injury.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krolewski, Alex G.; Eisenstein, Daniel J., E-mail: akrolewski@college.harvard.edu
2015-04-10
We study the dependence of quasar clustering on quasar luminosity and black hole mass by measuring the angular overdensity of photometrically selected galaxies imaged by the Wide-field Infrared Survey Explorer (WISE) about z ∼ 0.8 quasars from SDSS. By measuring the quasar–galaxy cross-correlation function and using photometrically selected galaxies, we achieve a higher density of tracer objects and a more sensitive detection of clustering than measurements of the quasar autocorrelation function. We test models of quasar formation and evolution by measuring the luminosity dependence of clustering amplitude. We find a significant overdensity of WISE galaxies about z ∼ 0.8 quasarsmore » at 0.2–6.4 h{sup −1} Mpc in projected comoving separation. We find no appreciable increase in clustering amplitude with quasar luminosity across a decade in luminosity, and a power-law fit between luminosity and clustering amplitude gives an exponent of −0.01 ± 0.06 (1 σ error). We also fail to find a significant relationship between clustering amplitude and black hole mass, although our dynamic range in true mass is suppressed due to the large uncertainties in virial black hole mass estimates. Our results indicate that a small range in host dark matter halo mass maps to a large range in quasar luminosity.« less
Large-Angular-Scale Clustering as a Clue to the Source of UHECRs
NASA Astrophysics Data System (ADS)
Berlind, Andreas A.; Farrar, Glennys R.
We explore what can be learned about the sources of UHECRs from their large-angular-scale clustering (referred to as their "bias" by the cosmology community). Exploiting the clustering on large scales has the advantage over small-scale correlations of being insensitive to uncertainties in source direction from magnetic smearing or measurement error. In a Cold Dark Matter cosmology, the amplitude of large-scale clustering depends on the mass of the system, with more massive systems such as galaxy clusters clustering more strongly than less massive systems such as ordinary galaxies or AGN. Therefore, studying the large-scale clustering of UHECRs can help determine a mass scale for their sources, given the assumption that their redshift depth is as expected from the GZK cutoff. We investigate the constraining power of a given UHECR sample as a function of its cutoff energy and number of events. We show that current and future samples should be able to distinguish between the cases of their sources being galaxy clusters, ordinary galaxies, or sources that are uncorrelated with the large-scale structure of the universe.
Rand, Kristin A.; Song, Chi; Dean, Eric; Serie, Daniel J.; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H.; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S.; Bock, Cathryn H.; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K.; V.Conti, David; Zimmerman, Todd; Hwang, Amie E.; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L.; Berndt, Sonja I.; Blot, William J.; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W. Ryan; Stevens, Victoria L.; Lieber, Michael R.; Goodman, Phyllis J.; Hennis, Anselm J.M.; Hsing, Ann W.; Mehta, Jayesh; Kittles, Rick A.; Kolb, Suzanne; Klein, Eric A.; Leske, Cristina; Murphy, Adam B.; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S.; Vij, Ravi; Rybicki, Benjamin A.; Stanford, Janet L.; Signorello, Lisa B.; Witte, John S.; Ambrosone, Christine B.; Bhatti, Parveen; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F.; Hu, Jennifer J.; Ziegler, Regina G.; Nyante, Sarah J.; Bandera, Elisa V.; Birmann, Brenda M.; Ingles, Sue A.; Press, Michael F.; Atanackovic, Djordje; Glenn, Martha J.; Cannon-Albright, Lisa A.; Jones, Brandt; Tricot, Guido; Martin, Thomas G.; Kumar, Shaji K.; Wolf, Jeffrey L.; Deming, Sandra L.; Rothman, Nathaniel; Brooks-Wilson, Angela R.; Rajkumar, S. Vincent; Kolonel, Laurence N.; Chanock, Stephen J.; Slager, Susan L.; Severson, Richard K.; Janakiraman, Nalini; Terebelo, Howard R.; Brown, Elizabeth E.; De Roos, Anneclaire J.; Mohrbacher, Ann F.; Colditz, Graham A.; Giles, Graham G.; Spinelli, John J.; Chiu, Brian C.; Munshi, Nikhil C.; Anderson, Kenneth C.; Levy, Joan; Zonder, Jeffrey A.; Orlowski, Robert Z.; Lonial, Sagar; Camp, Nicola J.; Vachon, Celine M.; Ziv, Elad; Stram, Daniel O.; Hazelett, Dennis J.; Haiman, Christopher A.; Cozen, Wendy
2017-01-01
Background Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM). Methods We performed association testing of common variation in eight regions in 1,264 MM patients and 1,479 controls of European ancestry (EA) and 1,305 MM patients and 7,078 controls of African ancestry (AA) and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. Results We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (p<0.05) associated with MM risk in AAs and EAs and the variant in 3p22.1 was associated in EAs only. In a combined AA-EA meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically signficantly associated with MM risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4. Correlated variants in 7p15.3 clustered around an enhancer at the 3′ end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR=1.32, p=2.93×10−7) in TNFRSF13B, encodes a lymphocyte-specific protein in the tumor necrosis factor receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7. Conclusions We found that reported MM susceptibility regions contain risk variants important across populations supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. Impact A subset of reported risk loci for multiple myeloma have consistent affects across populations and are likely to be functional. PMID:27587788
The Angular Correlation Function of Galaxies from Early Sloan Digital Sky Survey Data
NASA Astrophysics Data System (ADS)
Connolly, Andrew J.; Scranton, Ryan; Johnston, David; Dodelson, Scott; Eisenstein, Daniel J.; Frieman, Joshua A.; Gunn, James E.; Hui, Lam; Jain, Bhuvnesh; Kent, Stephen; Loveday, Jon; Nichol, Robert C.; O'Connell, Liam; Postman, Marc; Scoccimarro, Roman; Sheth, Ravi K.; Stebbins, Albert; Strauss, Michael A.; Szalay, Alexander S.; Szapudi, István; Tegmark, Max; Vogeley, Michael S.; Zehavi, Idit; Annis, James; Bahcall, Neta; Brinkmann, J.; Csabai, István; Doi, Mamoru; Fukugita, Masataka; Hennessy, G. S.; Hindsley, Robert; Ichikawa, Takashi; Ivezić, Željko; Kim, Rita S. J.; Knapp, Gillian R.; Kunszt, Peter; Lamb, D. Q.; Lee, Brian C.; Lupton, Robert H.; McKay, Timothy A.; Munn, Jeff; Peoples, John; Pier, Jeff; Rockosi, Constance; Schlegel, David; Stoughton, Christopher; Tucker, Douglas L.; Yanny, Brian; York, Donald G.
2002-11-01
The Sloan Digital Sky Survey is one of the first multicolor photometric and spectroscopic surveys designed to measure the statistical properties of galaxies within the local universe. In this paper we present some of the initial results on the angular two-point correlation function measured from the early SDSS galaxy data. The form of the correlation function, over the magnitude interval 18
Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder
Zhang, Tijiang; Wang, Jinhui; Yang, Yanchun; Wu, Qizhu; Li, Bin; Chen, Long; Yue, Qiang; Tang, Hehan; Yan, Chaogan; Lui, Su; Huang, Xiaoqi; Chan, Raymond C.K.; Zang, Yufeng; He, Yong; Gong, Qiyong
2011-01-01
Background Obsessive–compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD–related alterations in functional connectivity patterns in the brain’s top–down control network. Methods We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level–dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top–down control and then analyzed using graph theory-based approaches. Results Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain’s control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Conclusion Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder. PMID:20964957
NASA Astrophysics Data System (ADS)
Mathias, Gerald; Egwolf, Bernhard; Nonella, Marco; Tavan, Paul
2003-06-01
We present a combination of the structure adapted multipole method with a reaction field (RF) correction for the efficient evaluation of electrostatic interactions in molecular dynamics simulations under periodic boundary conditions. The algorithm switches from an explicit electrostatics evaluation to a continuum description at the maximal distance that is consistent with the minimum image convention, and, thus, avoids the use of a periodic electrostatic potential. A physically motivated switching function enables charge clusters interacting with a given charge to smoothly move into the solvent continuum by passing through the spherical dielectric boundary surrounding this charge. This transition is complete as soon as the cluster has reached the so-called truncation radius Rc. The algorithm is used to examine the dependence of thermodynamic properties and correlation functions on Rc in the three point transferable intermolecular potential water model. Our test simulations on pure liquid water used either the RF correction or a straight cutoff and values of Rc ranging from 14 Å to 40 Å. In the RF setting, the thermodynamic properties and the correlation functions show convergence for Rc increasing towards 40 Å. In the straight cutoff case no such convergence is found. Here, in particular, the dipole-dipole correlation functions become completely artificial. The RF description of the long-range electrostatics is verified by comparison with the results of a particle-mesh Ewald simulation at identical conditions.
Grauvogl, Andrea; Pelzer, Britt; Radder, Veerle; van Lankveld, Jacques
2018-02-01
Recently, the etiology of sexual dysfunctions in women has been approached from different angles. In clinical practice and in previous studies, it has been observed that women with sexual problems experience anxiety problems and express more rigid and perfectionistic personality traits than women without these problems. To investigate whether personality disorder characteristics according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) and psychological symptoms are associated with sexual problems in women. 188 women 18 to 25 years old participated in this cross-sectional study. Questionnaires measuring sexual functioning (Female Sexual Function Index), personality disorder characteristics (Assessment of DSM-IV-TR Personality Disorders Questionnaire), and psychological symptoms (Brief Symptom Inventory and Center for Epidemiological Studies Depression Scale) were used. The main outcome measure used was sexual functioning assessed by self-report. Results, using analysis of variance, indicated that women with sexual problems report significantly more cluster A (specifically schizoid) and C (specifically avoidant and obsessive-compulsive) personality disorder characteristics than women without sexual problems. Furthermore, using multiple regression analyses, higher cluster A (specifically schizoid) and lower cluster B (specifically borderline and antisocial) personality disorder characteristics indicated lower levels of sexual functioning. Psychological symptoms partly mediated the effect of cluster A personality disorder characteristics on sexual functioning. The results of this study indicate that clinical practice should extend its scope by focusing more on improving adaptive personality characteristics, such as extraversion and individualism seen in cluster B personality characteristics, and decreasing the perfectionistic, introvert, and self-doubting characteristics seen in cluster C personality characteristics. Because of the correlational design and use of self-report measures, causal relations cannot be established between personality disorder characteristics and sexual functioning. Overall, the results indicate that personality disorder characteristics can play an important associative role in the development and maintenance of sexual functioning problems in women. Grauvogl A, Pelzer B, Radder V, van Lankveld J. Associations Between Personality Disorder Characteristics, Psychological Symptoms, and Sexual Functioning in Young Women. J Sex Med 2018;15:192-200. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
Cluster analysis of obesity and asthma phenotypes.
Sutherland, E Rand; Goleva, Elena; King, Tonya S; Lehman, Erik; Stevens, Allen D; Jackson, Leisa P; Stream, Amanda R; Fahy, John V; Leung, Donald Y M
2012-01-01
Asthma is a heterogeneous disease with variability among patients in characteristics such as lung function, symptoms and control, body weight, markers of inflammation, and responsiveness to glucocorticoids (GC). Cluster analysis of well-characterized cohorts can advance understanding of disease subgroups in asthma and point to unsuspected disease mechanisms. We utilized an hypothesis-free cluster analytical approach to define the contribution of obesity and related variables to asthma phenotype. In a cohort of clinical trial participants (n = 250), minimum-variance hierarchical clustering was used to identify clinical and inflammatory biomarkers important in determining disease cluster membership in mild and moderate persistent asthmatics. In a subset of participants, GC sensitivity was assessed via expression of GC receptor alpha (GCRα) and induction of MAP kinase phosphatase-1 (MKP-1) expression by dexamethasone. Four asthma clusters were identified, with body mass index (BMI, kg/m(2)) and severity of asthma symptoms (AEQ score) the most significant determinants of cluster membership (F = 57.1, p<0.0001 and F = 44.8, p<0.0001, respectively). Two clusters were composed of predominantly obese individuals; these two obese asthma clusters differed from one another with regard to age of asthma onset, measures of asthma symptoms (AEQ) and control (ACQ), exhaled nitric oxide concentration (F(E)NO) and airway hyperresponsiveness (methacholine PC(20)) but were similar with regard to measures of lung function (FEV(1) (%) and FEV(1)/FVC), airway eosinophilia, IgE, leptin, adiponectin and C-reactive protein (hsCRP). Members of obese clusters demonstrated evidence of reduced expression of GCRα, a finding which was correlated with a reduced induction of MKP-1 expression by dexamethasone Obesity is an important determinant of asthma phenotype in adults. There is heterogeneity in expression of clinical and inflammatory biomarkers of asthma across obese individuals. Reduced expression of the dominant functional isoform of the GCR may mediate GC insensitivity in obese asthmatics.
Linear and quadratic static response functions and structure functions in Yukawa liquids.
Magyar, Péter; Donkó, Zoltán; Kalman, Gabor J; Golden, Kenneth I
2014-08-01
We compute linear and quadratic static density response functions of three-dimensional Yukawa liquids by applying an external perturbation potential in molecular dynamics simulations. The response functions are also obtained from the equilibrium fluctuations (static structure factors) in the system via the fluctuation-dissipation theorems. The good agreement of the quadratic response functions, obtained in the two different ways, confirms the quadratic fluctuation-dissipation theorem. We also find that the three-point structure function may be factorizable into two-point structure functions, leading to a cluster representation of the equilibrium triplet correlation function.
Mitigating the impact of the DESI fiber assignment on galaxy clustering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burden, Angela; Padmanabhan, Nikhil; Cahn, Robert N.
2017-03-01
We present a simple strategy to mitigate the impact of an incomplete spectroscopic redshift galaxy sample as a result of fiber assignment and survey tiling. The method has been designed for the Dark Energy Spectroscopic Instrument (DESI) galaxy survey but may have applications beyond this. We propose a modification to the usual correlation function that nulls the almost purely angular modes affected by survey incompleteness due to fiber assignment. Predictions of this modified statistic can be calculated given a model of the two point correlation function. The new statistic can be computed with a slight modification to the data cataloguesmore » input to the standard correlation function code and does not incur any additional computational time. Finally we show that the spherically averaged baryon acoustic oscillation signal is not biased by the new statistic.« less
The VLT LBG Redshift Survey - III. The clustering and dynamics of Lyman-break galaxies at z ˜ 3
NASA Astrophysics Data System (ADS)
Bielby, R.; Hill, M. D.; Shanks, T.; Crighton, N. H. M.; Infante, L.; Bornancini, C. G.; Francke, H.; Héraudeau, P.; Lambas, D. G.; Metcalfe, N.; Minniti, D.; Padilla, N.; Theuns, T.; Tummuangpak, P.; Weilbacher, P.
2013-03-01
We present a catalogue of 2135 galaxy redshifts from the VLT LBG Redshift Survey (VLRS), a spectroscopic survey of z ≈ 3 galaxies in wide fields centred on background quasi-stellar objects. We have used deep optical imaging to select galaxies via the Lyman-break technique. Spectroscopy of the Lyman-break galaxies (LBGs) was then made using the Very Large Telescope (VLT) Visible Multi-Object Spectrograph (VIMOS) instrument, giving a mean redshift of z = 2.79. We analyse the clustering properties of the VLRS sample and also of the VLRS sample combined with the smaller area Keck-based survey of Steidel et al. From the semiprojected correlation function, wp(σ), for the VLRS and combined surveys, we find that the results are well fit with a single power-law model, with clustering scale lengths of r0 = 3.46 ± 0.41 and 3.83 ± 0.24 h-1 Mpc, respectively. We note that the corresponding combined ξ(r) slope is flatter than for local galaxies at γ = 1.5-1.6 rather than γ = 1.8. This flat slope is confirmed by the z-space correlation function, ξ(s), and in the range 10 < s < 100 h-1 Mpc the VLRS shows an ≈2.5σ excess over the Λ cold dark matter (ΛCDM) linear prediction. This excess may be consistent with recent evidence for non-Gaussianity in clustering results at z ≈ 1. We then analyse the LBG z-space distortions using the 2D correlation function, ξ(σ, π), finding for the combined sample a large-scale infall parameter of β = 0.38 ± 0.19 and a velocity dispersion of sqrt{< w_z^2rangle }=420^{+140}_{-160} km s^{-1}. Based on our measured β, we are able to determine the gravitational growth rate, finding a value of f(z = 3) = 0.99 ± 0.50 (or fσ8 = 0.26 ± 0.13), which is the highest redshift measurement of the growth rate via galaxy clustering and is consistent with ΛCDM. Finally, we constrain the mean halo mass for the LBG population, finding that the VLRS and combined sample suggest mean halo masses of log(MDM/M⊙) = 11.57 ± 0.15 and 11.73 ± 0.07, respectively.
NASA Astrophysics Data System (ADS)
Minami, Kazuhiko
2017-12-01
An infinite number of spin chains are solved and it is derived that the ground-state phase transitions belong to the universality classes with central charge c = m / 2, where m is an integer. The models are diagonalized by automatically obtained transformations, many of which are different from the Jordan-Wigner transformation. The free energies, correlation functions, string order parameters, exponents, central charges, and the phase diagram are obtained. Most of the examples consist of the stabilizers of the cluster state. A unified structure of the one-dimensional XY and cluster-type spin chains is revealed, and other series of solvable models can be obtained through this formula.
Yin, Shi; Bernstein, Elliot R
2016-10-21
A new magnetic-bottle time-of-flight photoelectron spectroscopy (PES) apparatus is constructed in our laboratory. The PES spectra of iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide [FeS m (SH) n - ; m, n = 0-3, 0 < (m + n) ≤ 3] cluster anions, obtained at 2.331 eV (532 nm) and 3.492 eV (355 nm) photon energies, are reported. The electronic structure and bonding properties of these clusters are additionally investigated at different levels of density functional theory. The most probable structures and ground state spin multiplicity for these cluster anions are tentatively assigned by comparing their theoretical first vertical detachment energies (VDEs) with their respective experiment values. The behavior of S and (SH) as ligands in these iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide cluster anions is investigated and compared. The experimental first VDEs for Fe(SH) 1-3 - cluster anions are lower than those found for their respective FeS 1-3 - cluster anions. The experimental first VDEs for FeS 1-3 - clusters are observed to increase for the first two S atoms bound to Fe - ; however, due to the formation of an S-S bond for the FeS 3 - cluster, its first VDE is found to be ∼0.41 eV lower than the first VDE for the FeS 2 - cluster. The first VDEs of Fe(SH) 1-3 - cluster anions are observed to increase with the increasing numbers of SH groups. The calculated partial charges of the Fe atom for ground state FeS 1-3 - and Fe(SH) 1-3 - clusters are apparently related to and correlated with their determined first VDEs. The higher first VDE is correlated with a higher, more positive partial charge for the Fe atom of these cluster anions. Iron sulfide/hydrosulfide mixed cluster anions are also explored in this work: the first VDE for FeS(SH) - is lower than that for FeS 2 - , but higher than that for Fe(SH) 2 - ; the first VDEs for FeS 2 (SH) - and FeS(SH) 2 - are close to that for FeS 3 - , but higher than that for Fe(SH) 3 - . The first VDEs of general iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide clusters [FeS m (SH) n - ; m, n = 0-3, 0 < (m + n) ≤ 3] are dependent on three properties of these anions: 1. the partial charge on the Fe atom, 2. disulfide bond formation (S-S) in the cluster, and 3. the number of hydrosulfide ligands in the cluster. The higher the partial charge on the Fe atom of these clusters, the larger the first VDE; however, cluster S-S bonding and more (SH) ligands in the cluster lower the cluster anion first VDE.
NASA Astrophysics Data System (ADS)
Yin, Shi; Bernstein, Elliot R.
2016-10-01
A new magnetic-bottle time-of-flight photoelectron spectroscopy (PES) apparatus is constructed in our laboratory. The PES spectra of iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide [FeSm(SH)n-; m, n = 0-3, 0 < (m + n) ≤ 3] cluster anions, obtained at 2.331 eV (532 nm) and 3.492 eV (355 nm) photon energies, are reported. The electronic structure and bonding properties of these clusters are additionally investigated at different levels of density functional theory. The most probable structures and ground state spin multiplicity for these cluster anions are tentatively assigned by comparing their theoretical first vertical detachment energies (VDEs) with their respective experiment values. The behavior of S and (SH) as ligands in these iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide cluster anions is investigated and compared. The experimental first VDEs for Fe(SH)1-3- cluster anions are lower than those found for their respective FeS1-3- cluster anions. The experimental first VDEs for FeS1-3- clusters are observed to increase for the first two S atoms bound to Fe-; however, due to the formation of an S-S bond for the FeS3- cluster, its first VDE is found to be ˜0.41 eV lower than the first VDE for the FeS2- cluster. The first VDEs of Fe(SH)1-3- cluster anions are observed to increase with the increasing numbers of SH groups. The calculated partial charges of the Fe atom for ground state FeS1-3- and Fe(SH)1-3- clusters are apparently related to and correlated with their determined first VDEs. The higher first VDE is correlated with a higher, more positive partial charge for the Fe atom of these cluster anions. Iron sulfide/hydrosulfide mixed cluster anions are also explored in this work: the first VDE for FeS(SH)- is lower than that for FeS2-, but higher than that for Fe(SH)2-; the first VDEs for FeS2(SH)- and FeS(SH)2- are close to that for FeS3-, but higher than that for Fe(SH)3-. The first VDEs of general iron sulfide, hydrosulfide, and mixed sulfide/hydrosulfide clusters [FeSm(SH)n-; m, n = 0-3, 0 < (m + n) ≤ 3] are dependent on three properties of these anions: 1. the partial charge on the Fe atom, 2. disulfide bond formation (S-S) in the cluster, and 3. the number of hydrosulfide ligands in the cluster. The higher the partial charge on the Fe atom of these clusters, the larger the first VDE; however, cluster S-S bonding and more (SH) ligands in the cluster lower the cluster anion first VDE.
Percolation analysis for cosmic web with discrete points
NASA Astrophysics Data System (ADS)
Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung
2016-03-01
Percolation analysis has long been used to quantify the connectivity of the cosmic web. Unlike most of the previous works using density field on grids, we have studied percolation analysis based on discrete points. Using a Friends-of-Friends (FoF) algorithm, we generate the S-bb relation, between the fractional mass of the largest connected group (S) and the FoF linking length (bb). We propose a new model, the Probability Cloud Cluster Expansion Theory (PCCET) to relate the S-bb relation with correlation functions. We show that the S-bb relation reflects a combination of all orders of correlation functions. We have studied the S-bb relation with simulation and find that the S-bb relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with Halo Abundance Matching (HAM), we have generated a mock galaxy catalogue. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalogue with the latest galaxy catalogue from SDSS DR12, we have found significant differences in their S-bb relations. This indicates that the mock catalogue cannot accurately recover higher order correlation functions than the two-point correlation function, which reveals the limit of HAM method.
Extraversion and neuroticism relate to topological properties of resting-state brain networks.
Gao, Qing; Xu, Qiang; Duan, Xujun; Liao, Wei; Ding, Jurong; Zhang, Zhiqiang; Li, Yuan; Lu, Guangming; Chen, Huafu
2013-01-01
With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here, we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI) data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e., betweenness centrality (BC), was positively associated with neuroticism scores in the right precentral gyrus (PreCG), right caudate nucleus, right olfactory cortex, and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus (MTG), indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.
Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C
2017-01-30
In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gomez, John A.; Henderson, Thomas M.; Scuseria, Gustavo E.
Restricted single-reference coupled cluster theory truncated to single and double excitations accurately describes weakly correlated systems, but often breaks down in the presence of static or strong correlation. Good coupled cluster energies in the presence of degeneracies can be obtained by using a symmetry-broken reference, such as unrestricted Hartree-Fock, but at the cost of good quantum numbers. A large body of work has shown that modifying the coupled cluster ansatz allows for the treatment of strong correlation within a single-reference, symmetry-adapted framework. The recently introduced singlet-paired coupled cluster doubles (CCD0) method is one such model, which recovers correct behavior formore » strong correlation without requiring symmetry breaking in the reference. Here, we extend singlet-paired coupled cluster for application to open shells via restricted open-shell singlet-paired coupled cluster singles and doubles (ROCCSD0). The ROCCSD0 approach retains the benefits of standard coupled cluster theory and recovers correct behavior for strongly correlated, open-shell systems using a spin-preserving ROHF reference.« less
Nicoludis, John M; Lau, Sze-Yi; Schärfe, Charlotta P I; Marks, Debora S; Weihofen, Wilhelm A; Gaudet, Rachelle
2015-11-03
Clustered protocadherin (Pcdh) proteins mediate dendritic self-avoidance in neurons via specific homophilic interactions in their extracellular cadherin (EC) domains. We determined crystal structures of EC1-EC3, containing the homophilic specificity-determining region, of two mouse clustered Pcdh isoforms (PcdhγA1 and PcdhγC3) to investigate the nature of the homophilic interaction. Within the crystal lattices, we observe antiparallel interfaces consistent with a role in trans cell-cell contact. Antiparallel dimerization is supported by evolutionary correlations. Two interfaces, located primarily on EC2-EC3, involve distinctive clustered Pcdh structure and sequence motifs, lack predicted glycosylation sites, and contain residues highly conserved in orthologs but not paralogs, pointing toward their biological significance as homophilic interaction interfaces. These two interfaces are similar yet distinct, reflecting a possible difference in interaction architecture between clustered Pcdh subfamilies. These structures initiate a molecular understanding of clustered Pcdh assemblies that are required to produce functional neuronal networks. Copyright © 2015 Elsevier Ltd. All rights reserved.
Accurate Modeling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model
NASA Astrophysics Data System (ADS)
Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron; Scoccimarro, Roman
2015-01-01
The large-scale distribution of galaxies can be explained fairly simply by assuming (i) a cosmological model, which determines the dark matter halo distribution, and (ii) a simple connection between galaxies and the halos they inhabit. This conceptually simple framework, called the halo model, has been remarkably successful at reproducing the clustering of galaxies on all scales, as observed in various galaxy redshift surveys. However, none of these previous studies have carefully modeled the systematics and thus truly tested the halo model in a statistically rigorous sense. We present a new accurate and fully numerical halo model framework and test it against clustering measurements from two luminosity samples of galaxies drawn from the SDSS DR7. We show that the simple ΛCDM cosmology + halo model is not able to simultaneously reproduce the galaxy projected correlation function and the group multiplicity function. In particular, the more luminous sample shows significant tension with theory. We discuss the implications of our findings and how this work paves the way for constraining galaxy formation by accurate simultaneous modeling of multiple galaxy clustering statistics.
Sidlauskaite, Justina; Caeyenberghs, Karen; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R
2015-01-01
Prior studies demonstrate altered organization of functional brain networks in attention-deficit/hyperactivity disorder (ADHD). However, the structural underpinnings of these functional disturbances are poorly understood. In the current study, we applied a graph-theoretic approach to whole-brain diffusion magnetic resonance imaging data to investigate the organization of structural brain networks in adults with ADHD and unaffected controls using deterministic fiber tractography. Groups did not differ in terms of global network metrics - small-worldness, global efficiency and clustering coefficient. However, there were widespread ADHD-related effects at the nodal level in relation to local efficiency and clustering. The affected nodes included superior occipital, supramarginal, superior temporal, inferior parietal, angular and inferior frontal gyri, as well as putamen, thalamus and posterior cerebellum. Lower local efficiency of left superior temporal and supramarginal gyri was associated with higher ADHD symptom scores. Also greater local clustering of right putamen and lower local clustering of left supramarginal gyrus correlated with ADHD symptom severity. Overall, the findings indicate preserved global but altered local network organization in adult ADHD implicating regions underpinning putative ADHD-related neuropsychological deficits.
Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues
NASA Astrophysics Data System (ADS)
Nie, Chun-Xiao
2018-02-01
In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.
Cluster correlation and fragment emission in 12C+12C at 95 MeV/nucleon
NASA Astrophysics Data System (ADS)
Tian, G.; Chen, Z.; Han, R.; Shi, F.; Luo, F.; Sun, Q.; Song, L.; Zhang, X.; Xiao, G. Q.; Wada, R.; Ono, A.
2018-03-01
The impact of cluster correlations has been studied in the intermediate mass fragment (IMF) emission in 12C+12C at 95 MeV/nucleon, using antisymmetrized molecular dynamics (AMD) model simulations. In AMD, the cluster correlation is introduced as a process to form light clusters with A ≤4 in the final states of a collision induced by the nucleon-nucleon residual interaction. Correlations between light clusters are also considered to form light nuclei with A ≤9 . This version of AMD, combined with GEMINI to calculate the decay of primary fragments, reproduces the experimental energy spectra of IMFs well overall with reasonable reproduction of light charged particles when we carefully analyze the excitation energies of primary fragments produced by AMD and their secondary decays. The results indicate that the cluster correlation plays a crucial role for producing fragments at relatively low excitation energies in the intermediate-energy heavy-ion collisions.
Theory of inhomogeneous quantum systems. III. Variational wave functions for Fermi fluids
NASA Astrophysics Data System (ADS)
Krotscheck, E.
1985-04-01
We develop a general variational theory for inhomogeneous Fermi systems such as the electron gas in a metal surface, the surface of liquid 3He, or simple models of heavy nuclei. The ground-state wave function is expressed in terms of two-body correlations, a one-body attenuation factor, and a model-system Slater determinant. Massive partial summations of cluster expansions are performed by means of Born-Green-Yvon and hypernetted-chain techniques. An optimal single-particle basis is generated by a generalized Hartree-Fock equation in which the two-body correlations screen the bare interparticle interaction. The optimization of the pair correlations leads to a state-averaged random-phase-approximation equation and a strictly microscopic determination of the particle-hole interaction.
Lukey, Michael J; Roessler, Maxie M; Parkin, Alison; Evans, Rhiannon M; Davies, Rosalind A; Lenz, Oliver; Friedrich, Baerbel; Sargent, Frank; Armstrong, Fraser A
2011-10-26
An important clue to the mechanism for O(2) tolerance of certain [NiFe]-hydrogenases is the conserved presence of a modified environment around the iron-sulfur cluster that is proximal to the active site. The O(2)-tolerant enzymes contain two cysteines, located at opposite ends of this cluster, which are glycines in their O(2)-sensitive counterparts. The strong correlation highlights special importance for electron-transfer activity in the protection mechanism used to combat O(2). Site-directed mutagenesis has been carried out on Escherichia coli hydrogenase-1 to substitute these cysteines (C19 and C120) individually and collectively for glycines, and the effects of each replacement have been determined using protein film electrochemistry and electron paramagnetic resonance (EPR) spectroscopy. The "split" iron-sulfur cluster EPR signal thus far observed when oxygen-tolerant [NiFe]-hydrogenases are subjected to oxidizing potentials is found not to provide any simple, reliable correlation with oxygen tolerance. Oxygen tolerance is largely conferred by a single cysteine (C19), replacement of which by glycine removes the ability to function even in 1% O(2).
Nguyen, Hien D; Ullmann, Jeremy F P; McLachlan, Geoffrey J; Voleti, Venkatakaushik; Li, Wenze; Hillman, Elizabeth M C; Reutens, David C; Janke, Andrew L
2018-02-01
Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.
Magnetized liquid 3He at finite temperature: A variational calculation approach
NASA Astrophysics Data System (ADS)
Bordbar, Gholam Hossein; Mohammadi Sabet, Mohammad Taghi
2016-08-01
Using the spin-dependent (SD) and spin-independent (SI) correlation functions, we have investigated the properties of liquid 3He in the presence of magnetic field at finite temperature. Our calculations have been done using the variational method based on cluster expansion of the energy functional. Our results show that the low field magnetic susceptibility obeys Curie law at high temperatures. This behavior is in a good agreement with the experimental data as well as the molecular field theory results in which the spin dependency has been introduced in correlation function. Reduced susceptibility as a function of temperature as well as reduced temperature has been also investigated, and again we have seen that the spin-dependent correlation function leads to a good agreement with the experimental data. The Landau parameter, F0a, has been calculated, and for this parameter, a value about - 0.75 has been found in the case of spin-spin correlation. In the case of spin-independent correlation function, this value is about - 0.7. Therefore, inclusion of spin dependency in the correlation function leads to a more compatible value of F0a with experimental data. The magnetization and susceptibility of liquid 3He have also been investigated as a function of magnetic field. Our results show a downward curvature in magnetization of system with spin-dependent correlation for all densities and relevant temperatures. A metamagnetic behavior has been observed as a maximum in susceptibility versus magnetic field, when the spin-spin correlation has been considered. This maximum occurs at 45T ≤ B ≤ 100T for all densities and temperatures. This behavior has not been observed in the case of spin-independent correlation function.
Cosmology from galaxy clusters as observed by Planck
NASA Astrophysics Data System (ADS)
Pierpaoli, Elena
We propose to use current all-sky data on galaxy clusters in the radio/infrared bands in order to constrain cosmology. This will be achieved performing parameter estimation with number counts and power spectra for galaxy clusters detected by Planck through their Sunyaev—Zeldovich signature. The ultimate goal of this proposal is to use clusters as tracers of matter density in order to provide information about fundamental properties of our Universe, such as the law of gravity on large scale, early Universe phenomena, structure formation and the nature of dark matter and dark energy. We will leverage on the availability of a larger and deeper cluster catalog from the latest Planck data release in order to include, for the first time, the cluster power spectrum in the cosmological parameter determination analysis. Furthermore, we will extend clusters' analysis to cosmological models not yet investigated by the Planck collaboration. These aims require a diverse set of activities, ranging from the characterization of the clusters' selection function, the choice of the cosmological cluster sample to be used for parameter estimation, the construction of mock samples in the various cosmological models with correct correlation properties in order to produce reliable selection functions and noise covariance matrices, and finally the construction of the appropriate likelihood for number counts and power spectra. We plan to make the final code available to the community and compatible with the most widely used cosmological parameter estimation code. This research makes use of data from the NASA satellites Planck and, less directly, Chandra, in order to constrain cosmology; and therefore perfectly fits the NASA objectives and the specifications of this solicitation.
Guidez, Emilie B; Gordon, Mark S
2015-03-12
The modeling of dispersion interactions in density functional theory (DFT) is commonly performed using an energy correction that involves empirically fitted parameters for all atom pairs of the system investigated. In this study, the first-principles-derived dispersion energy from the effective fragment potential (EFP) method is implemented for the density functional theory (DFT-D(EFP)) and Hartree-Fock (HF-D(EFP)) energies. Overall, DFT-D(EFP) performs similarly to the semiempirical DFT-D corrections for the test cases investigated in this work. HF-D(EFP) tends to underestimate binding energies and overestimate intermolecular equilibrium distances, relative to coupled cluster theory, most likely due to incomplete accounting for electron correlation. Overall, this first-principles dispersion correction yields results that are in good agreement with coupled-cluster calculations at a low computational cost.
Nielsen, J D; Dean, C B
2008-09-01
A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.
Quon, Harry; Hui, Xuan; Cheng, Zhi; Robertson, Scott; Peng, Luke; Bowers, Michael; Moore, Joseph; Choflet, Amanda; Thompson, Alex; Muse, Mariah; Kiess, Ana; Page, Brandi; Fakhry, Carole; Gourin, Christine; O'Hare, Jolyne; Graham, Peter; Szczesniak, Michal; Maclean, Julia; Cook, Ian; McNutt, Todd
2017-12-01
To test the hypothesis that quantifying swallow function with multiple patient-reported outcome (PRO) instruments is an important strategy to yield insights in the development of personalized deintensified therapies seeking to reduce the risk of head and neck cancer (HNC) treatment-related dysphagia (HNCTD). Irradiated HNC subjects seen in follow-up care (April 2015 to December 2015) who prospectively completed the Sydney Swallow Questionnaire (SSQ) and the MD Anderson Dysphagia Inventory (MDADI) concurrently on the web interface to our Oncospace database were evaluated. A correlation matrix quantified the relationship between the SSQ and MDADI. Machine-learning unsupervised cluster analysis using the elbow criterion and CLUSPLOT analysis to establish its validity was performed. We identified 89 subjects. The MDADI and SSQ scores were moderately but significantly correlated (correlation coefficient -0.69). K-means cluster analysis demonstrated that 3 unique statistical cohorts (elbow criterion) could be identified with CLUSPLOT analysis, confirming that 100% of variances were accounted for. Correlation coefficients between the individual items in the SSQ and the MDADI demonstrated weak to moderate negative correlation, except for SSQ17 (quality of life question). Pilot analysis demonstrates that the MDADI and SSQ are complementary. Three unique clusters of patients can be defined, suggesting that a unique dysphagia signature for HNCTD may be definable. Longitudinal studies relying on only a single PRO, such as MDADI, may be inadequate for classifying HNCTD. Copyright © 2017 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giannantonio, T.; et al.
Optical imaging surveys measure both the galaxy density and the gravitational lensing-induced shear fields across the sky. Recently, the Dark Energy Survey (DES) collaboration used a joint fit to two-point correlations between these observables to place tight constraints on cosmology (DES Collaboration et al. 2017). In this work, we develop the methodology to extend the DES Collaboration et al. (2017) analysis to include cross-correlations of the optical survey observables with gravitational lensing of the cosmic microwave background (CMB) as measured by the South Pole Telescope (SPT) and Planck. Using simulated analyses, we show how the resulting set of five two-pointmore » functions increases the robustness of the cosmological constraints to systematic errors in galaxy lensing shear calibration. Additionally, we show that contamination of the SPT+Planck CMB lensing map by the thermal Sunyaev-Zel'dovich effect is a potentially large source of systematic error for two-point function analyses, but show that it can be reduced to acceptable levels in our analysis by masking clusters of galaxies and imposing angular scale cuts on the two-point functions. The methodology developed here will be applied to the analysis of data from the DES, the SPT, and Planck in a companion work.« less
Taylor, Jeanette
2005-01-01
Substance use disorders (SUDs) and Cluster B personality disorders (PDs) are both marked by impulsivity and poor behavioral control and may result in part from shared neurobiological or executive cognitive functioning deficits. To examine the potential utility of such models in explaining variance in SUDs and PDs at the lower end of symptom expression and impairment, 123 (73 female) volunteer college students were administered 2 measures of executive cognitive functioning; a task assessing autonomic reactivity to aversive noise blasts; a life events and a peer substance use measure; and structured clinical interviews to assess symptoms of substance abuse/dependence and antisocial, borderline, histrionic, and narcissistic PDs. As expected, symptoms of SUDs and PDs were significantly positively correlated. Antisocial PD, alcohol and cannabis use disorder symptoms were significantly positively related to proportion of friends who use alcohol and drugs regularly and drug use among romantic partners. Number of negative life events was positively related to PD symptoms and to alcohol use disorder symptoms. Executive cognitive functioning was not related to SUD and PD symptoms in the expected direction. Findings suggest that, among higher functioning young adults, environmental factors may be particularly relevant to our understanding of SUDs and certain PDs.
NASA Astrophysics Data System (ADS)
Heßelmann, Andreas
2017-06-01
A many-body Green's-function method employing an infinite order summation of ring and exchange-ring contributions to the self-energy is presented. The individual correlation and relaxation contributions to the quasiparticle energies are calculated using an iterative scheme which utilizes density fitting of the particle-hole, particle-particle and hole-hole densities. It is shown that the ionization energies and electron affinities of this approach agree better with highly accurate coupled-cluster singles and doubles with perturbative triples energy difference results than those obtained with second-order Green's-function approaches. An analysis of the correlation and relaxation terms of the self-energy for the direct- and exchange-random-phase-approximation (RPA) Green's-function methods shows that the inclusion of exchange interactions leads to a reduction of the two contributions in magnitude. These differences, however, strongly cancel each other when summing the individual terms to the quasiparticle energies. Due to this, the direct- and exchange-RPA methods perform similarly for the description of ionization energies (IPs) and electron affinities (EAs). The coupled-cluster reference IPs and EAs, if corrected to the adiabatic energy differences between the neutral and charged molecules, were shown to be in very good agreement with experimental measurements.
What correlation effects are covered by density functional theory?
NASA Astrophysics Data System (ADS)
He, Yuan; Grafenstein, Jurgen; Kraka, Elfi; Cremer, Dieter
The electron density distribution rho(r) generated by a DFT calculation was systematically studied by comparison with a series of reference densities obtained by wavefunction theory (WFT) methods that cover typical electron correlation effects. As a sensitive indicator for correlation effects the dipole moment of the CO molecule was used. The analysis reveals that typical LDA and GGA exchange functionals already simulate effects that are actually reminiscent of pair and three-electron correlation effects covered by MP2, MP4, and CCSD(T) in WFT. Correlation functionals contract the density towards the bond and the valence region thus taking negative charge out of the van der Waals region. It is shown that these improvements are relevant for the description of van der Waals interactions. Similar to certain correlated single-determinant WFT methods, BLYP and other GGA functionals underestimate ionic terms needed for a correct description of polar bonds. This is compensated for in hybrid functionals by mixing in HF exchange. The balanced mixing of local and non-local exchange and correlation effects leads to the correct description of polar bonds as in the B3LYP description of the CO molecule. The density obtained with B3LYP is closer to CCSD and CCSD(T) than to MP2 or MP4, which indicates that the B3LYP hybrid functional mimics those pair and three-electron correlation effects, which in WFT are only covered by coupled cluster methods.
Clustering of quasars in SDSS-IV eBOSS: study of potential systematics and bias determination
DOE Office of Scientific and Technical Information (OSTI.GOV)
Laurent, Pierre; Goff, Jean-Marc Le; Burtin, Etienne
2017-07-01
We study the first year of the eBOSS quasar sample in the redshift range 0.9< z <2.2 which includes 68,772 homogeneously selected quasars. We show that the main source of systematics in the evaluation of the correlation function arises from inhomogeneities in the quasar target selection, particularly related to the extinction and depth of the imaging data used for targeting. We propose a weighting scheme that mitigates these systematics. We measure the quasar correlation function and provide the most accurate measurement to date of the quasar bias in this redshift range, b {sub Q} = 2.45 ± 0.05 at z-barmore » =1.55, together with its evolution with redshift. We use this information to determine the minimum mass of the halo hosting the quasars and the characteristic halo mass, which we find to be both independent of redshift within statistical error. Using a recently-measured quasar-luminosity-function we also determine the quasar duty cycle. The size of this first year sample is insufficient to detect any luminosity dependence to quasar clustering and this issue should be further studied with the final ∼500,000 eBOSS quasar sample.« less
NASA Technical Reports Server (NTRS)
Prescod-Weinstein, Chanda; Afshordi, Niayesh
2011-01-01
Structure formation provides a strong test of any cosmic acceleration model because a successful dark energy model must not inhibit or overpredict the development of observed large-scale structures. Traditional approaches to studies of structure formation in the presence of dark energy or a modified gravity implement a modified Press-Schechter formalism, which relates the linear overdensities to the abundance of dark matter haloes at the same time. We critically examine the universality of the Press-Schechter formalism for different cosmologies, and show that the halo abundance is best correlated with spherical linear overdensity at 94% of collapse (or observation) time. We then extend this argument to ellipsoidal collapse (which decreases the fractional time of best correlation for small haloes), and show that our results agree with deviations from modified Press-Schechter formalism seen in simulated mass functions. This provides a novel universal prescription to measure linear density evolution, based on current and future observations of cluster (or dark matter) halo mass function. In particular, even observations of cluster abundance in a single epoch will constrain the entire history of linear growth of cosmological of perturbations.
Clustering of quasars in SDSS-IV eBOSS: study of potential systematics and bias determination
NASA Astrophysics Data System (ADS)
Laurent, Pierre; Eftekharzadeh, Sarah; Le Goff, Jean-Marc; Myers, Adam; Burtin, Etienne; White, Martin; Ross, Ashley J.; Tinker, Jeremy; Tojeiro, Rita; Bautista, Julian; Brinkmann, Jonathan; Comparat, Johan; Dawson, Kyle; du Mas des Bourboux, Hélion; Kneib, Jean-Paul; McGreer, Ian D.; Palanque-Delabrouille, Nathalie; Percival, Will J.; Prada, Francisco; Rossi, Graziano; Schneider, Donald P.; Weinberg, David; Yèche, Christophe; Zarrouk, Pauline; Zhao, Gong-Bo
2017-07-01
We study the first year of the eBOSS quasar sample in the redshift range 0.9
NASA Astrophysics Data System (ADS)
Tian, Hua; Zhang, Chong; Wang, Lu; Zhao, JiJun; Dong, Chuang; Wen, Bin; Wang, Qing
2011-06-01
We have performed ab initio molecular dynamics simulation of Cu64Zr36 alloy at descending temperatures (from 2000 K to 400 K) and discussed the evolution of short-range order with temperature. The pair-correlation functions, coordination numbers, and chemical compositions of the most abundant local clusters have been analyzed. We found that icosahedral short-range order exists in the liquid, undercooled, and glass states, and it becomes dominant in the glass states. Moreover, we demonstrated the existence of Cu-centered Cu8Zr5 icosahedral clusters as the major local structural unit in the Cu64Zr36 amorphous alloy. This finding agrees well with our previous cluster model of Cu-Zr-based BMG as well as experimental evidences from synchrotron x ray and neutron diffraction measurements.
Clustering of galaxies near damped Lyman-alpha systems with (z) = 2.6
NASA Technical Reports Server (NTRS)
Wolfe, A. M
1993-01-01
The galaxy two-point correlation function, xi, at (z) = 2.6 is determined by comparing the number of Ly-alpha-emitting galaxies in narrowband CCD fields selected for the presence of damped L-alpha absorption to their number in randomly selected control fields. Comparisons between the presented determination of (xi), a density-weighted volume average of xi, and model predictions for (xi) at large redshifts show that models in which the clustering pattern is fixed in proper coordinates are highly unlikely, while better agreement is obtained if the clustering pattern is fixed in comoving coordinates. Therefore, clustering of Ly-alpha-emitting galaxies around damped Ly-alpha systems at large redshifts is strong. It is concluded that the faint blue galaxies are drawn from a parent population different from normal galaxies, the presumed offspring of damped Ly-alpha systems.
Direct construction of mesoscopic models from microscopic simulations
NASA Astrophysics Data System (ADS)
Lei, Huan; Caswell, Bruce; Karniadakis, George Em
2010-02-01
Starting from microscopic molecular-dynamics (MD) simulations of constrained Lennard-Jones (LJ) clusters (with constant radius of gyration Rg ), we construct two mesoscopic models [Langevin dynamics and dissipative particle dynamics (DPD)] by coarse graining the LJ clusters into single particles. Both static and dynamic properties of the coarse-grained models are investigated and compared with the MD results. The effective mean force field is computed as a function of the intercluster distance, and the corresponding potential scales linearly with the number of particles per cluster and the temperature. We verify that the mean force field can reproduce the equation of state of the atomistic systems within a wide density range but the radial distribution function only within the dilute and the semidilute regime. The friction force coefficients for both models are computed directly from the time-correlation function of the random force field of the microscopic system. For high density or a large cluster size the friction force is overestimated and the diffusivity underestimated due to the omission of many-body effects as a result of the assumed pairwise form of the coarse-grained force field. When the many-body effect is not as pronounced (e.g., smaller Rg or semidilute system), the DPD model can reproduce the dynamic properties of the MD system.
Damianos, Konstantina; Ferrando, Riccardo
2012-02-21
The structural modifications of small supported gold clusters caused by realistic surface defects (steps) in the MgO(001) support are investigated by computational methods. The most stable gold cluster structures on a stepped MgO(001) surface are searched for in the size range up to 24 Au atoms, and locally optimized by density-functional calculations. Several structural motifs are found within energy differences of 1 eV: inclined leaflets, arched leaflets, pyramidal hollow cages and compact structures. We show that the interaction with the step clearly modifies the structures with respect to adsorption on the flat defect-free surface. We find that leaflet structures clearly dominate for smaller sizes. These leaflets are either inclined and quasi-horizontal, or arched, at variance with the case of the flat surface in which vertical leaflets prevail. With increasing cluster size pyramidal hollow cages begin to compete against leaflet structures. Cage structures become more and more favourable as size increases. The only exception is size 20, at which the tetrahedron is found as the most stable isomer. This tetrahedron is however quite distorted. The comparison of two different exchange-correlation functionals (Perdew-Burke-Ernzerhof and local density approximation) show the same qualitative trends. This journal is © The Royal Society of Chemistry 2012
Observing the clustering properties of galaxy clusters in dynamical dark-energy cosmologies
NASA Astrophysics Data System (ADS)
Fedeli, C.; Moscardini, L.; Bartelmann, M.
2009-06-01
We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are assumed, including the concordance ΛCDM and various cosmologies with dynamical evolution of the dark energy. Particular attention is paid to models with a significant contribution of dark energy at early times which affects the process of structure formation. Past light cone and selection effects in cluster catalogs are carefully modeled by realistic scaling relations between cluster mass and observables and by properly taking into account the selection functions of the different instruments. The results show that early dark-energy models are expected to produce significantly lower values of effective bias and both spatial and angular correlation amplitudes with respect to the standard ΛCDM model. Among the cluster catalogs studied in this work, it turns out that those based on eRosita, Planck, and South Pole Telescope observations are the most promising for distinguishing between various dark-energy models.
Ozdemir, Filiz Ciledag; Pehlivan, Erkan; Melekoglu, Rauf
2017-01-01
To investigate the pelvic floor muscle strength of the women andevaluateits possible correlation with sexual dysfunction. In this cross-sectional type study, stratified clusters were used for the sampling method. Index of Female Sexual Function (IFSF) worksheetwere used for questions on sexual function. The pelvic floor muscle strength of subjects was assessed byperineometer. The chi-squared test, logistic regression and Pearson's correlation analysis were used for the statistical analysis. Four hundred thirty primiparous women, mean age 38.5 participated in this study. The average pelvic floor muscle strength value was found 31.4±9.6 cm H 2 O and the average Index of Female Sexual Function (IFSF) score was found 26.5±6.9. Parity (odds ratio OR=5.546) and age 40 or higher (OR=3.484) were found correlated with pelvic floor muscle weakness (p<0.05). The factors directly correlated with sexual dysfunction were found being overweight (OR=2.105) and age 40 or higher (OR=2.451) (p<0.05). Pearson's correlation analysis showed that there was a statistically significantlinear correlation between the muscular strength of the pelvic floor and sexual function (p=0.001). The results suggested subjects with decreased pelvic floor muscle strength value had higher frequency of sexual dysfunction.
Silver, Sunshine C; Gardenghi, David J; Naik, Sunil G; Shepard, Eric M; Huynh, Boi Hanh; Szilagyi, Robert K; Broderick, Joan B
2014-03-01
Spore photoproduct lyase (SPL), a member of the radical S-adenosyl-L-methionine (SAM) superfamily, catalyzes the direct reversal of the spore photoproduct, a thymine dimer specific to bacterial spores, to two thymines. SPL requires SAM and a redox-active [4Fe-4S] cluster for catalysis. Mössbauer analysis of anaerobically purified SPL indicates the presence of a mixture of cluster states with the majority (40 %) as [2Fe-2S](2+) clusters and a smaller amount (15 %) as [4Fe-4S](2+) clusters. On reduction, the cluster content changes to primarily (60 %) [4Fe-4S](+). The speciation information from Mössbauer data allowed us to deconvolute iron and sulfur K-edge X-ray absorption spectra to uncover electronic (X-ray absorption near-edge structure, XANES) and geometric (extended X-ray absorption fine structure, EXAFS) structural features of the Fe-S clusters, and their interactions with SAM. The iron K-edge EXAFS data provide evidence for elongation of a [2Fe-2S] rhomb of the [4Fe-4S] cluster on binding SAM on the basis of an Fe···Fe scatterer at 3.0 Å. The XANES spectra of reduced SPL in the absence and presence of SAM overlay one another, indicating that SAM is not undergoing reductive cleavage. The X-ray absorption spectroscopy data for SPL samples and data for model complexes from the literature allowed the deconvolution of contributions from [2Fe-2S] and [4Fe-4S] clusters to the sulfur K-edge XANES spectra. The analysis of pre-edge features revealed electronic changes in the Fe-S clusters as a function of the presence of SAM. The spectroscopic findings were further corroborated by density functional theory calculations that provided insights into structural and electronic perturbations that can be correlated by considering the role of SAM as a catalyst or substrate.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mészáros, Szabolcs; Martell, Sarah L.; Shetrone, Matthew
We investigate the light-element behavior of red giant stars in northern globular clusters (GCs) observed by the SDSS-III Apache Point Observatory Galactic Evolution Experiment. We derive abundances of 9 elements (Fe, C, N, O, Mg, Al, Si, Ca, and Ti) for 428 red giant stars in 10 GCs. The intrinsic abundance range relative to measurement errors is examined, and the well-known C–N and Mg–Al anticorrelations are explored using an extreme-deconvolution code for the first time in a consistent way. We find that Mg and Al drive the population membership in most clusters, except in M107 and M71, the two mostmore » metal-rich clusters in our study, where the grouping is most sensitive to N. We also find a diversity in the abundance distributions, with some clusters exhibiting clear abundance bimodalities (for example M3 and M53) while others show extended distributions. The spread of Al abundances increases significantly as cluster average metallicity decreases as previously found by other works, which we take as evidence that low metallicity, intermediate mass AGB polluters were more common in the more metal-poor clusters. The statistically significant correlation of [Al/Fe] with [Si/Fe] in M15 suggests that {sup 28}Si leakage has occurred in this cluster. We also present C, N, and O abundances for stars cooler than 4500 K and examine the behavior of A(C+N+O) in each cluster as a function of temperature and [Al/Fe]. The scatter of A(C+N+O) is close to its estimated uncertainty in all clusters and independent of stellar temperature. A(C+N+O) exhibits small correlations and anticorrelations with [Al/Fe] in M3 and M13, but we cannot be certain about these relations given the size of our abundance uncertainties. Star-to-star variations of α-element (Si, Ca, Ti) abundances are comparable to our estimated errors in all clusters.« less
NASA Astrophysics Data System (ADS)
Mészáros, Szabolcs; Martell, Sarah L.; Shetrone, Matthew; Lucatello, Sara; Troup, Nicholas W.; Bovy, Jo; Cunha, Katia; García-Hernández, Domingo A.; Overbeek, Jamie C.; Allende Prieto, Carlos; Beers, Timothy C.; Frinchaboy, Peter M.; García Pérez, Ana E.; Hearty, Fred R.; Holtzman, Jon; Majewski, Steven R.; Nidever, David L.; Schiavon, Ricardo P.; Schneider, Donald P.; Sobeck, Jennifer S.; Smith, Verne V.; Zamora, Olga; Zasowski, Gail
2015-05-01
We investigate the light-element behavior of red giant stars in northern globular clusters (GCs) observed by the SDSS-III Apache Point Observatory Galactic Evolution Experiment. We derive abundances of 9 elements (Fe, C, N, O, Mg, Al, Si, Ca, and Ti) for 428 red giant stars in 10 GCs. The intrinsic abundance range relative to measurement errors is examined, and the well-known C-N and Mg-Al anticorrelations are explored using an extreme-deconvolution code for the first time in a consistent way. We find that Mg and Al drive the population membership in most clusters, except in M107 and M71, the two most metal-rich clusters in our study, where the grouping is most sensitive to N. We also find a diversity in the abundance distributions, with some clusters exhibiting clear abundance bimodalities (for example M3 and M53) while others show extended distributions. The spread of Al abundances increases significantly as cluster average metallicity decreases as previously found by other works, which we take as evidence that low metallicity, intermediate mass AGB polluters were more common in the more metal-poor clusters. The statistically significant correlation of [Al/Fe] with [Si/Fe] in M15 suggests that 28Si leakage has occurred in this cluster. We also present C, N, and O abundances for stars cooler than 4500 K and examine the behavior of A(C+N+O) in each cluster as a function of temperature and [Al/Fe]. The scatter of A(C+N+O) is close to its estimated uncertainty in all clusters and independent of stellar temperature. A(C+N+O) exhibits small correlations and anticorrelations with [Al/Fe] in M3 and M13, but we cannot be certain about these relations given the size of our abundance uncertainties. Star-to-star variations of α-element (Si, Ca, Ti) abundances are comparable to our estimated errors in all clusters.
Diffuse Optical Light in Galaxy Clusters. II. Correlations with Cluster Properties
NASA Astrophysics Data System (ADS)
Krick, J. E.; Bernstein, R. A.
2007-08-01
We have measured the flux, profile, color, and substructure in the diffuse intracluster light (ICL) in a sample of 10 galaxy clusters with a range of mass, morphology, redshift, and density. Deep, wide-field observations for this project were made in two bands at the 1 m Swope and 2.5 m du Pont telescopes at Las Campanas Observatory. Careful attention in reduction and analysis was paid to the illumination correction, background subtraction, point-spread function determination, and galaxy subtraction. ICL flux is detected in both bands in all 10 clusters ranging from 7.6×1010 to 7.0×1011 h-170 Lsolar in r and 1.4×1010 to 1.2×1011 h-170 Lsolar in the B band. These fluxes account for 6%-22% of the total cluster light within one-quarter of the virial radius in r and 4%-21% in the B band. Average ICL B-r colors range from 1.5 to 2.8 mag when k- and evolution corrected to the present epoch. In several clusters we also detect ICL in group environments near the cluster center and up to 1 h-170 Mpc distant from the cluster center. Our sample, having been selected from the Abell sample, is incomplete in that it does not include high-redshift clusters with low density, low flux, or low mass, and it does not include low-redshift clusters with high flux, high mass, or high density. This bias makes it difficult to interpret correlations between ICL flux and cluster properties. Despite this selection bias, we do find that the presence of a cD galaxy corresponds to both centrally concentrated galaxy profiles and centrally concentrated ICL profiles. This is consistent with ICL either forming from galaxy interactions at the center or forming at earlier times in groups and later combining in the center.
Lu, Hong; Patil, Prabhu; Van Sluys, Marie-Anne; White, Frank F; Ryan, Robert P; Dow, J Maxwell; Rabinowicz, Pablo; Salzberg, Steven L; Leach, Jan E; Sonti, Ramesh; Brendel, Volker; Bogdanove, Adam J
2008-01-01
Xanthomonas is a large genus of plant-associated and plant-pathogenic bacteria. Collectively, members cause diseases on over 392 plant species. Individually, they exhibit marked host- and tissue-specificity. The determinants of this specificity are unknown. To assess potential contributions to host- and tissue-specificity, pathogenesis-associated gene clusters were compared across genomes of eight Xanthomonas strains representing vascular or non-vascular pathogens of rice, brassicas, pepper and tomato, and citrus. The gum cluster for extracellular polysaccharide is conserved except for gumN and sequences downstream. The xcs and xps clusters for type II secretion are conserved, except in the rice pathogens, in which xcs is missing. In the otherwise conserved hrp cluster, sequences flanking the core genes for type III secretion vary with respect to insertion sequence element and putative effector gene content. Variation at the rpf (regulation of pathogenicity factors) cluster is more pronounced, though genes with established functional relevance are conserved. A cluster for synthesis of lipopolysaccharide varies highly, suggesting multiple horizontal gene transfers and reassortments, but this variation does not correlate with host- or tissue-specificity. Phylogenetic trees based on amino acid alignments of gum, xps, xcs, hrp, and rpf cluster products generally reflect strain phylogeny. However, amino acid residues at four positions correlate with tissue specificity, revealing hpaA and xpsD as candidate determinants. Examination of genome sequences of xanthomonads Xylella fastidiosa and Stenotrophomonas maltophilia revealed that the hrp, gum, and xcs clusters are recent acquisitions in the Xanthomonas lineage. Our results provide insight into the ancestral Xanthomonas genome and indicate that differentiation with respect to host- and tissue-specificity involved not major modifications or wholesale exchange of clusters, but subtle changes in a small number of genes or in non-coding sequences, and/or differences outside the clusters, potentially among regulatory targets or secretory substrates.
Clustering of galaxies in a hierarchical universe - I. Methods and results at z=0
NASA Astrophysics Data System (ADS)
Kauffmann, Guinevere; Colberg, Jorg M.; Diaferio, Antonaldo; White, Simon D. M.
1999-02-01
We introduce a new technique for following the formation and evolution of galaxies in cosmological N-body simulations. Dissipationless simulations are used to track the formation and merging of dark matter haloes as a function of redshift. Simple prescriptions, taken directly from semi-analytic models of galaxy formation, are adopted for gas cooling, star formation, supernova feedback and the merging of galaxies within the haloes. This scheme enables us to explore the clustering properties of galaxies, and to investigate how selection by luminosity, colour or type influences the results. In this paper we study the properties of the galaxy distribution at z=0. These include B- and K-band luminosity functions, two-point correlation functions, pairwise peculiar velocities, cluster mass-to-light ratios, B-V colours, and star formation rates. We focus on two variants of a cold dark matter (CDM) cosmology: a high-density (Omega =1) model with shape-parameter Gamma =0.21 (tau CDM), and a low-density model with Omega =0.3 and Lambda =0.7 (Lambda CDM). Both models are normalized to reproduce the I-band Tully-Fisher relation of Giovanelli et al. near a circular velocity of 220 km s^-1. Our results depend strongly both on this normalization and on the adopted prescriptions for star formation and feedback. Very different assumptions are required to obtain an acceptable model in the two cases. For tau CDM, efficient feedback is required to suppress the growth of galaxies, particularly in low-mass field haloes. Without it, there are too many galaxies and the correlation function exhibits a strong turnover on scales below 1 Mpc. For Lambda CDM, feedback must be weaker, otherwise too few L_* galaxies are produced and the correlation function is too steep. Although neither model is perfect, both come close to reproducing most of the data. Given the uncertainties in modelling some of the critical physical processes, we conclude that it is not yet possible to draw firm conclusions about the values of cosmological parameters from studies of this kind. Further observational work on global star formation and feedback effects is required to narrow the range of possibilities.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghadar, Yasaman; Clark, Aurora E.
2012-02-02
The interaction potentials between immiscible polar and non-polar solvents are a major driving force behind the formation of liquid:liquid interfaces. In this work, the interaction energy of water–pentane dimer has been determined using coupled-cluster theory with single double (triple) excitations [CCSD(T)], 2nd order Möller Plesset perturbation theory (MP2), density fitted local MP2 (DF-LMP2), as well as density functional theory using a wide variety of density functionals and several different basis sets. The M05-2X exchange correlation functionals exhibit excellent agreement with CCSD(T) and DF-LMP2 after taking into account basis set superposition error. The gas phase water–pentane interaction energy is found tomore » be quite sensitive to the specific pentane isomer (2,2- dimethylpropane vs. n-pentane) and relative orientation of the monomeric constituents. Subsequent solution phase cluster calculations of 2,2-dimethylpropane and n-pentane solvated by water indicate a positive free energy of solvation that is in good agreement with available experimental data. Structural parameters are quite sensitive to the density functional employed and reflect differences in the two-body interaction energy calculated by each method. In contrast, cluster calculations of pentane solvation of H2O solute are found to be inadequate for describing the organic solvent, likely due to limitations associated with the functionals employed (B3LYP, BHandH, and M05-2X).« less
Yoo, Jae Hyun; Oh, Yunhye; Jang, Byongsu; Song, Jihye; Kim, Jiwon; Kim, Seonwoo; Lee, Jiyoung; Shin, Hye-Yeon; Kwon, Jeong-Yi; Kim, Yun-Hee; Jeong, Bumseok; Joung, Yoo-Sook
2016-11-30
Equine-assisted activities and therapy (EAA/T) have been used as adjunct treatment options for physical and psychosocial rehabilitation. However, the therapeutic effects on resting-state brain function have not yet been studied. The aim of this study is to investigate the effects of EAA/T on participants with attention-deficit/hyperactivity disorder (ADHD) by comparing resting-state functional magnetic resonance imaging (rs-fMRI) signals and their clinical correlates. Ten participants with ADHD participated in a 12-week EAA/T program without any medication. Two rs-fMRIs were acquired for all participants before and after EAA/T. For estimating therapeutic effect, the regional homogeneity (ReHo) method was applied to capture the changes in the regional synchronization of functional signals. After the EAA/T program, clear symptom improvement was found even without medication. Surface-based pairwise comparisons revealed that ReHo in the right precuneus and right pars orbitalis clusters had significantly diminished after the program. Reduced ReHo in the right precuneus cluster was positively correlated with changes in the scores on DuPaul's ADHD Rating Scale-Korean version. Our results indicate that EAA/T is associated with short-range functional connectivity in the regions related to the default mode network and the behavioral inhibition system, which are associated with symptom improvement.
Yoo, Jae Hyun; Oh, Yunhye; Jang, Byongsu; Song, Jihye; Kim, Jiwon; Kim, Seonwoo; Lee, Jiyoung; Shin, Hye-Yeon; Kwon, Jeong-Yi; Kim, Yun-Hee; Jeong, Bumseok; Joung, Yoo-Sook
2016-01-01
Objective Equine-assisted activities and therapy (EAA/T) have been used as adjunct treatment options for physical and psychosocial rehabilitation. However, the therapeutic effects on resting-state brain function have not yet been studied. The aim of this study is to investigate the effects of EAA/T on participants with attention-deficit/hyperactivity disorder (ADHD) by comparing resting-state functional magnetic resonance imaging (rs-fMRI) signals and their clinical correlates. Methods Ten participants with ADHD participated in a 12-week EAA/T program without any medication. Two rs-fMRIs were acquired for all participants before and after EAA/T. For estimating therapeutic effect, the regional homogeneity (ReHo) method was applied to capture the changes in the regional synchronization of functional signals. Results After the EAA/T program, clear symptom improvement was found even without medication. Surface-based pairwise comparisons revealed that ReHo in the right precuneus and right pars orbitalis clusters had significantly diminished after the program. Reduced ReHo in the right precuneus cluster was positively correlated with changes in the scores on DuPaul’s ADHD Rating Scale-Korean version. Conclusion Our results indicate that EAA/T is associated with short-range functional connectivity in the regions related to the default mode network and the behavioral inhibition system, which are associated with symptom improvement. PMID:27776388
Baudin, Pablo; Kristensen, Kasper
2017-06-07
We present a new framework for calculating coupled cluster (CC) excitation energies at a reduced computational cost. It relies on correlated natural transition orbitals (NTOs), denoted CIS(D')-NTOs, which are obtained by diagonalizing generalized hole and particle density matrices determined from configuration interaction singles (CIS) information and additional terms that represent correlation effects. A transition-specific reduced orbital space is determined based on the eigenvalues of the CIS(D')-NTOs, and a standard CC excitation energy calculation is then performed in that reduced orbital space. The new method is denoted CorNFLEx (Correlated Natural transition orbital Framework for Low-scaling Excitation energy calculations). We calculate second-order approximate CC singles and doubles (CC2) excitation energies for a test set of organic molecules and demonstrate that CorNFLEx yields excitation energies of CC2 quality at a significantly reduced computational cost, even for relatively small systems and delocalized electronic transitions. In order to illustrate the potential of the method for large molecules, we also apply CorNFLEx to calculate CC2 excitation energies for a series of solvated formamide clusters (up to 4836 basis functions).
Redshift space clustering of galaxies and cold dark matter model
NASA Technical Reports Server (NTRS)
Bahcall, Neta A.; Cen, Renyue; Gramann, Mirt
1993-01-01
The distorting effect of peculiar velocities on the power speturm and correlation function of IRAS and optical galaxies is studied. The observed redshift space power spectra and correlation functions of IRAS and optical the galaxies over the entire range of scales are directly compared with the corresponding redshift space distributions using large-scale computer simulations of cold dark matter (CDM) models in order to study the distortion effect of peculiar velocities on the power spectrum and correlation function of the galaxies. It is found that the observed power spectrum of IRAS and optical galaxies is consistent with the spectrum of an Omega = 1 CDM model. The problems that such a model currently faces may be related more to the high value of Omega in the model than to the shape of the spectrum. A low-density CDM model is also investigated and found to be consistent with the data.
Evolution of the Mass and Luminosity Functions of Globular Star Clusters
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul; Fall, S. Michael
2016-12-01
We reexamine the dynamical evolution of the mass and luminosity functions of globular star clusters (GCMF and GCLF). Fall & Zhang (2001, FZ01) showed that a power-law MF, as commonly seen among young cluster systems, would evolve by dynamical processes over a Hubble time into a peaked MF with a shape very similar to the observed GCMF in the Milky Way and other galaxies. To simplify the calculations, the semi-analytical FZ01 model adopted the “classical” theory of stellar escape from clusters, and neglected variations in the M/L ratios of clusters. Kruijssen & Portegies Zwart (2009, KPZ09) modified the FZ01 model to include “retarded” and mass-dependent stellar escape, the latter causing significant M/L variations. KPZ09 asserted that their model was compatible with observations, whereas the FZ01 model was not. We show here that this claim is not correct; the FZ01 and KPZ09 models fit the observed Galactic GCLF equally well. We also show that there is no detectable correlation between M/L and L for GCs in the Milky Way and Andromeda galaxies, in contradiction with the KPZ09 model. Our comparisons of the FZ01 and KPZ09 models with observations can be explained most simply if stars escape at rates approaching the classical limit for high-mass clusters, as expected on theoretical grounds.
Evolution of the early-type galaxy fraction in clusters since z = 0.8
NASA Astrophysics Data System (ADS)
Simard, L.; Clowe, D.; Desai, V.; Dalcanton, J. J.; von der Linden, A.; Poggianti, B. M.; White, S. D. M.; Aragón-Salamanca, A.; De Lucia, G.; Halliday, C.; Jablonka, P.; Milvang-Jensen, B.; Saglia, R. P.; Pelló, R.; Rudnick, G. H.; Zaritsky, D.
2009-12-01
We study the morphological content of a large sample of high-redshift clusters to determine its dependence on cluster mass and redshift. Quantitative morphologies are based on PSF-convolved, 2D bulge+disk decompositions of cluster and field galaxies on deep Very Large Telescope FORS2 images of eighteen, optically-selected galaxy clusters at 0.45 < z < 0.80 observed as part of the ESO Distant Cluster Survey (“EDisCS”). Morphological content is characterized by the early-type galaxy fraction f_et, and early-type galaxies are objectively selected based on their bulge fraction and image smoothness. This quantitative selection is equivalent to selecting galaxies visually classified as E or S0. Changes in early-type fractions as a function of cluster velocity dispersion, redshift and star-formation activity are studied. A set of 158 clusters extracted from the Sloan Digital Sky Survey is analyzed exactly as the distant EDisCS sample to provide a robust local comparison. We also compare our results to a set of clusters from the Millennium Simulation. Our main results are: (1) the early-type fractions of the SDSS and EDisCS clusters exhibit no clear trend as a function of cluster velocity dispersion. (2) Mid-z EDisCS clusters around σ = 500 km s-1 have f_et ≃ 0.5 whereas high-z EDisCS clusters have f_et ≃ 0.4. This represents a ~25% increase over a time interval of 2 Gyr. (3) There is a marked difference in the morphological content of EDisCS and SDSS clusters. None of the EDisCS clusters have early-type galaxy fractions greater than 0.6 whereas half of the SDSS clusters lie above this value. This difference is seen in clusters of all velocity dispersions. (4) There is a strong and clear correlation between morphology and star formation activity in SDSS and EDisCS clusters in the sense that decreasing fractions of [OII] emitters are tracked by increasing early-type fractions. This correlation holds independent of cluster velocity dispersion and redshift even though the fraction of [OII] emitters decreases from z ˜0.8 to z ˜ 0.06 in all environments. Our results pose an interesting challenge to structural transformation and star formation quenching processes that strongly depend on the global cluster environment (e.g., a dense ICM) and suggest that cluster membership may be of lesser importance than other variables in determining galaxy properties. Based on observations obtained in visitor and service modes at the ESO Very Large Telescope (VLT) as part of the Large Programme 166.A-0162 (the ESO Distant Cluster Survey). Also based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These observations are associated with proposal 9476. Support for this proposal was provided by NASA through a grant from the Space Telescope Science Institute. Table [see full textsee full textsee full textsee full textsee full text] is only available in electronic form at http://www.aanda.org
NASA Astrophysics Data System (ADS)
Chen, Siyue; Leung, Henry; Dondo, Maxwell
2014-05-01
As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.
The Clustering of High-redshift (2.9 ≤ z ≤ 5.1) Quasars in SDSS Stripe 82
NASA Astrophysics Data System (ADS)
Timlin, John D.; Ross, Nicholas P.; Richards, Gordon T.; Myers, Adam D.; Pellegrino, Andrew; Bauer, Franz E.; Lacy, Mark; Schneider, Donald P.; Wollack, Edward J.; Zakamska, Nadia L.
2018-05-01
We present a measurement of the two-point autocorrelation function of photometrically selected high-z quasars over ∼100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the Spitzer IRAC Equatorial Survey and the Spitzer-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-z quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ z ≤ 5.1 and are generally fainter than i = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of δ = 1.39 ± 0.618 and amplitude of θ 0 = 0.‧71 ± 0.‧546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey (< z> =3.38), the bias is b = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83× {10}12{h}-1 {M}ȯ . Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-z.
Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan
2016-04-01
Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.
NASA Astrophysics Data System (ADS)
Li, Ming-Hua; Zhu, Weishan; Zhao, Dong
2018-05-01
The gas is the dominant component of baryonic matter in most galaxy groups and clusters. The spatial offsets of gas centre from the halo centre could be an indicator of the dynamical state of cluster. Knowledge of such offsets is important for estimate the uncertainties when using clusters as cosmological probes. In this paper, we study the centre offsets roff between the gas and that of all the matter within halo systems in ΛCDM cosmological hydrodynamic simulations. We focus on two kinds of centre offsets: one is the three-dimensional PB offsets between the gravitational potential minimum of the entire halo and the barycentre of the ICM, and the other is the two-dimensional PX offsets between the potential minimum of the halo and the iterative centroid of the projected synthetic X-ray emission of the halo. Haloes at higher redshifts tend to have larger values of rescaled offsets roff/r200 and larger gas velocity dispersion σ v^gas/σ _{200}. For both types of offsets, we find that the correlation between the rescaled centre offsets roff/r200 and the rescaled 3D gas velocity dispersion, σ _v^gas/σ _{200} can be approximately described by a quadratic function as r_{off}/r_{200} ∝ (σ v^gas/σ _{200} - k_2)2. A Bayesian analysis with MCMC method is employed to estimate the model parameters. Dependence of the correlation relation on redshifts and the gas mass fraction are also investigated.
NASA Astrophysics Data System (ADS)
Mahanta, Upakul; Goswami, Aruna; Duorah, Hiralal; Duorah, Kalpana
2017-08-01
Elemental abundance patterns of globular cluster stars can provide important clues for understanding cluster formation and early chemical evolution. The origin of the abundance patterns, however, still remains poorly understood. We have studied the impact of p-capture reaction cycles on the abundances of oxygen, sodium and aluminium considering nuclear reaction cycles of carbon-nitrogen-oxygen-fluorine, neon-sodium and magnesium-aluminium in massive stars in stellar conditions of temperature range 2×107 to 10×107 K and typical density of 102 gm cc-1. We have estimated abundances of oxygen, sodium and aluminium with respect to Fe, which are then assumed to be ejected from those stars because of rotation reaching a critical limit. These ejected abundances of elements are then compared with their counterparts that have been observed in some metal-poor evolved stars, mainly giants and red giants, of globular clusters M3, M4, M13 and NGC 6752. We observe an excellent agreement with [O/Fe] between the estimated and observed abundance values for globular clusters M3 and M4 with a correlation coefficient above 0.9 and a strong linear correlation for the remaining two clusters with a correlation coefficient above 0.7. The estimated [Na/Fe] is found to have a correlation coefficient above 0.7, thus implying a strong correlation for all four globular clusters. As far as [Al/Fe] is concerned, it also shows a strong correlation between the estimated abundance and the observed abundance for globular clusters M13 and NGC 6752, since here also the correlation coefficient is above 0.7 whereas for globular cluster M4 there is a moderate correlation found with a correlation coefficient above 0.6. Possible sources of these discrepancies are discussed.
Tunability of the circadian action of tetrachromatic solid-state light sources
NASA Astrophysics Data System (ADS)
Žukauskas, A.; Vaicekauskas, R.
2015-01-01
An approach to the optimization of the spectral power distribution of solid-state light sources with the tunable non-image forming photobiological effect on the human circadian rhythm is proposed. For tetrachromatic clusters of model narrow-band (direct-emission) light-emitting diodes (LEDs), the limiting tunability of the circadian action factor (CAF), which is the ratio of the circadian efficacy to luminous efficacy of radiation, was established as a function of constraining color fidelity and luminous efficacy of radiation. For constant correlated color temperatures (CCTs), the CAF of the LED clusters can be tuned above and below that of the corresponding blackbody radiators, whereas for variable CCT, the clusters can have circadian tunability covering that of a temperature-tunable blackbody radiator.
NASA Astrophysics Data System (ADS)
Okabe, Nobuhiro; Futamase, Toshifumi; Kajisawa, Masaru; Kuroshima, Risa
2014-04-01
We present a 4 deg2 weak gravitational lensing survey of subhalos in the very nearby Coma cluster using the Subaru/Suprime-Cam. The large apparent size of cluster subhalos allows us to measure the mass of 32 subhalos detected in a model-independent manner, down to the order of 10-3 of the virial mass of the cluster. Weak-lensing mass measurements of these shear-selected subhalos enable us to investigate subhalo properties and the correlation between subhalo masses and galaxy luminosities for the first time. The mean distortion profiles stacked over subhalos show a sharply truncated feature which is well-fitted by a Navarro-Frenk-White (NFW) mass model with the truncation radius, as expected due to tidal destruction by the main cluster. We also found that subhalo masses, truncation radii, and mass-to-light ratios decrease toward the cluster center. The subhalo mass function, dn/dln M sub, in the range of 2 orders of magnitude in mass, is well described by a single power law or a Schechter function. Best-fit power indices of 1.09^{+0.42}_{-0.32} for the former model and 0.99_{-0.23}^{+0.34} for the latter, are in remarkable agreement with slopes of ~0.9-1.0 predicted by the cold dark matter paradigm. The tangential distortion signals in the radial range of 0.02-2 h -1 Mpc from the cluster center show a complex structure which is well described by a composition of three mass components of subhalos, the NFW mass distribution as a smooth component of the main cluster, and a lensing model from a large scale structure behind the cluster. Although the lensing signals are 1 order of magnitude lower than those for clusters at z ~ 0.2, the total signal-to-noise ratio, S/N = 13.3, is comparable, or higher, because the enormous number of background source galaxies compensates for the low lensing efficiency of the nearby cluster. Based on data collected from the Subaru Telescope and obtained from SMOKA, operated by the Astronomy Data Center, National Astronomical Observatory of Japan.
Eymard, B; de la Porte, S; Pannier, C; Berrih-Aknin, S; Morel, E; Fardeau, M; Bach, J F; Koenig, J
1988-08-01
We studied the functional activities (FA) of sera obtained from 83 myasthenic patients on rat muscle cultures. Using the same sets of cultures, two parameters were evaluated after exposure to sera: residual fraction (RF) of acetylcholine receptors (AChR) coupled to 125I-labelled alpha-bungarotoxin (alpha Bgt) (81 sera) and the number of rhodamine labelled clusters (56 sera). Two types of culture were assayed: muscle alone and nerve-muscle cocultures (12 cases). In all combinations (fluorescence, radiolabelling, muscle alone and nerve-muscle cocultures), we found a significant correlation between FA and antibody (Ab) titre, and no correlation between FA and clinical severity: only sera with a high or intermediate Ab titre were effective, whatever the clinical severity of disease. With active sera, AChR loss was about 50% whereas the disappearance of AChR clusters was quite complete, which suggests AChR redistribution induced by MG sera.
Wüst, Stas; Dröse, Stefan; Heidler, Juliana; Wittig, Ilka; Klockner, Ina; Franko, Andras; Bonke, Erik; Günther, Stefan; Gärtner, Ulrich; Boettger, Thomas; Braun, Thomas
2018-05-01
Muscle stem cells undergo a dramatic metabolic switch to oxidative phosphorylation during differentiation, which is achieved by massively increased mitochondrial activity. Since expression of the muscle-specific miR-1/133a gene cluster correlates with increased mitochondrial activity during muscle stem cell (MuSC) differentiation, we examined the potential role of miR-1/133a in metabolic maturation of skeletal muscles in mice. We found that miR-1/133a downregulate Mef2A in differentiated myocytes, thereby suppressing the Dlk1-Dio3 gene cluster, which encodes multiple microRNAs inhibiting expression of mitochondrial genes. Loss of miR-1/133a in skeletal muscles or increased Mef2A expression causes continuous high-level expression of the Dlk1-Dio3 gene cluster, compromising mitochondrial function. Failure to terminate the stem cell-like metabolic program characterized by high-level Dlk1-Dio3 gene cluster expression initiates profound changes in muscle physiology, essentially abrogating endurance running. Our results suggest a major role of miR-1/133a in metabolic maturation of skeletal muscles but exclude major functions in muscle development and MuSC maintenance. Copyright © 2018 Elsevier Inc. All rights reserved.
Jiang, Wenyu; Li, Jianping; Chen, Xuemei; Ye, Wei; Zheng, Jinou
2017-01-01
Previous studies have shown that temporal lobe epilepsy (TLE) involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE) patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peng, Bo; Govind, Niranjan; Aprà, Edoardo
In this paper we apply equation-of-motion coupled cluster (EOMCC) methods in studies of vertical ionization potentials (IP) and electron affinities (EA) for sin- gled walled carbon nanotubes. EOMCC formulations for ionization potentials and electron affinities employing excitation manifolds spanned by single and double ex- citations (IP/EA-EOMCCSD) are used to study IPs and EAs of nanotubes as a function of nanotube length. Several armchair nanotubes corresponding to C20nH20 models with n = 2 - 6 have been used in benchmark calculations. In agreement with previous studies, we demonstrate that the electronegativity of C20nH20 systems remains, to a large extent, independent ofmore » nanotube length. We also compare IP/EA- EOMCCSD results with those obtained with the coupled cluster models with single and double excitations corrected by perturbative triples, CCSD(T), and density func- tional theory (DFT) using global and range-separated hybrid exchange-correlation functionals.« less
GEsture: an online hand-drawing tool for gene expression pattern search.
Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning
2018-01-01
Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.
Uberuaga, Blas Pedro; Vernon, Louis J.; Martinez, Enrique; Voter, Arthur F.
2015-01-01
Nanocrystalline materials have received great attention due to their potential for improved functionality and have been proposed for extreme environments where the interfaces are expected to promote radiation tolerance. However, the precise role of the interfaces in modifying defect behavior is unclear. Using long-time simulations methods, we determine the mobility of defects and defect clusters at grain boundaries in Cu. We find that mobilities vary significantly with boundary structure and cluster size, with larger clusters exhibiting reduced mobility, and that interface sink efficiency depends on the kinetics of defects within the interface via the in-boundary annihilation rate of defects. Thus, sink efficiency is a strong function of defect mobility, which depends on boundary structure, a property that evolves with time. Further, defect mobility at boundaries can be slower than in the bulk, which has general implications for the properties of polycrystalline materials. Finally, we correlate defect energetics with the volumes of atomic sites at the boundary. PMID:25766999
Uberuaga, Blas Pedro; Vernon, Louis J.; Martinez, Enrique; ...
2015-03-13
Nanocrystalline materials have received great attention due to their potential for improved functionality and have been proposed for extreme environments where the interfaces are expected to promote radiation tolerance. However, the precise role of the interfaces in modifying defect behavior is unclear. Using long-time simulations methods, we determine the mobility of defects and defect clusters at grain boundaries in Cu. We find that mobilities vary significantly with boundary structure and cluster size, with larger clusters exhibiting reduced mobility, and that interface sink efficiency depends on the kinetics of defects within the interface via the in-boundary annihilation rate of defects. Thus,more » sink efficiency is a strong function of defect mobility, which depends on boundary structure, a property that evolves with time. Further, defect mobility at boundaries can be slower than in the bulk, which has general implications for the properties of polycrystalline materials. Finally, we correlate defect energetics with the volumes of atomic sites at the boundary.« less
Shakil, Sadia; Lee, Chin-Hui; Keilholz, Shella Dawn
2016-01-01
A promising recent development in the study of brain function is the dynamic analysis of resting-state functional MRI scans, which can enhance understanding of normal cognition and alterations that result from brain disorders. One widely used method of capturing the dynamics of functional connectivity is sliding window correlation (SWC). However, in the absence of a “gold standard” for comparison, evaluating the performance of the SWC in typical resting-state data is challenging. This study uses simulated networks (SNs) with known transitions to examine the effects of parameters such as window length, window offset, window type, noise, filtering, and sampling rate on the SWC performance. The SWC time course was calculated for all node pairs of each SN and then clustered using the k-means algorithm to determine how resulting brain states match known configurations and transitions in the SNs. The outcomes show that the detection of state transitions and durations in the SWC is most strongly influenced by the window length and offset, followed by noise and filtering parameters. The effect of the image sampling rate was relatively insignificant. Tapered windows provide less sensitivity to state transitions than rectangular windows, which could be the result of the sharp transitions in the SNs. Overall, the SWC gave poor estimates of correlation for each brain state. Clustering based on the SWC time course did not reliably reflect the underlying state transitions unless the window length was comparable to the state duration, highlighting the need for new adaptive window analysis techniques. PMID:26952197
Notelaers, Kristof; Smisdom, Nick; Rocha, Susana; Janssen, Daniel; Meier, Jochen C; Rigo, Jean-Michel; Hofkens, Johan; Ameloot, Marcel
2012-12-01
The spatio-temporal membrane behavior of glycine receptors (GlyRs) is known to be of influence on receptor homeostasis and functionality. In this work, an elaborate fluorimetric strategy was applied to study the GlyR α3K and L isoforms. Previously established differential clustering, desensitization and synaptic localization of these isoforms imply that membrane behavior is crucial in determining GlyR α3 physiology. Therefore diffusion and aggregation of homomeric α3 isoform-containing GlyRs were studied in HEK 293 cells. A unique combination of multiple diffraction-limited ensemble average methods and subdiffraction single particle techniques was used in order to achieve an integrated view of receptor properties. Static measurements of aggregation were performed with image correlation spectroscopy (ICS) and, single particle based, direct stochastic optical reconstruction microscopy (dSTORM). Receptor diffusion was measured by means of raster image correlation spectroscopy (RICS), temporal image correlation spectroscopy (TICS), fluorescence recovery after photobleaching (FRAP) and single particle tracking (SPT). The results show a significant difference in diffusion coefficient and cluster size between the isoforms. This reveals a positive correlation between desensitization and diffusion and disproves the notion that receptor aggregation is a universal mechanism for accelerated desensitization. The difference in diffusion coefficient between the clustering GlyR α3L and the non-clustering GlyR α3K cannot be explained by normal diffusion. SPT measurements indicate that the α3L receptors undergo transient trapping and directed motion, while the GlyR α3K displays mild hindered diffusion. These findings are suggestive of differential molecular interaction of the isoforms after incorporation in the membrane. Copyright © 2012 Elsevier B.V. All rights reserved.
Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten
2015-03-01
Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing, especially in brain regions involved in working memory performance. Copyright © 2014 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
Murphy, Glen; Salomone, Sonia
2013-01-01
While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that…
NASA Astrophysics Data System (ADS)
Kaupp, Martin; Arbuznikov, Alexei V.; Heßelmann, Andreas; Görling, Andreas
2010-05-01
The isotropic hyperfine coupling constants of the free N(S4) and P(S4) atoms have been evaluated with high-level post-Hartree-Fock and density-functional methods. The phosphorus hyperfine coupling presents a significant challenge to both types of methods. With large basis sets, MP2 and coupled-cluster singles and doubles calculations give much too small values for the phosphorus atom. Triple excitations are needed in coupled-cluster calculations to achieve reasonable agreement with experiment. None of the standard density functionals reproduce even the correct sign of this hyperfine coupling. Similarly, the computed hyperfine couplings depend crucially on the self-consistent treatment in exact-exchange density-functional theory within the optimized effective potential (OEP) method. Well-balanced auxiliary and orbital basis sets are needed for basis-expansion exact-exchange-only OEP approaches to come close to Hartree-Fock or numerical OEP data. Results from the localized Hartree-Fock and Krieger-Li-Iafrate approximations deviate notably from exact OEP data in spite of very similar total energies. Of the functionals tested, only full exact-exchange methods augmented by a correlation functional gave at least the correct sign of the P(S4) hyperfine coupling but with too low absolute values. The subtle interplay between the spin-polarization contributions of the different core shells has been analyzed, and the influence of even very small changes in the exchange-correlation potential could be identified.
Probing dark energy with lensing magnification in photometric surveys.
Schneider, Michael D
2014-02-14
I present an estimator for the angular cross correlation of two tracers of the cosmological large-scale structure that utilizes redshift information to isolate separate physical contributions. The estimator is derived by solving the Limber equation for a reweighting of the foreground tracer that nulls either clustering or lensing contributions to the cross correlation function. Applied to future photometric surveys, the estimator can enhance the measurement of gravitational lensing magnification effects to provide a competitive independent constraint on the dark energy equation of state.
A CONSTRAINT ON QUASAR CLUSTERING AT z = 5 FROM A BINARY QUASAR
DOE Office of Scientific and Technical Information (OSTI.GOV)
McGreer, Ian D.; Fan, Xiaohui; Eftekharzadeh, Sarah
2016-03-15
We report the discovery of a quasar pair at z = 5 separated by 21″. Both objects were identified as quasar candidates using simple color selection techniques applied to photometric catalogs from the Canada–France–Hawaii Telescope (CFHT) Legacy Survey (CFHTLS). Spectra obtained with the MMT present no discernible offset in redshift between the two objects; on the other hand, there are clear differences in the emission line profiles and in the multiwavelength spectral energy distributions that strongly disfavor the hypothesis that they are gravitationally lensed images of a single quasar. Both quasars are surprisingly bright given their proximity (a projected separation of ∼135more » kpc), with i = 19.4 and i = 21.4. Previous measurements of the luminosity function demonstrate that luminous quasars are extremely rare at z = 5; the existence of this pair suggests that quasars have strong small-scale clustering at high redshift. Assuming a real-space correlation function of the form ξ(r) ∝ (r/r{sub 0}){sup −2}, this discovery implies a correlation length of r{sub 0} ≳ 20h{sup −1} Mpc, consistent with a rapid strengthening of quasar clustering at high redshift as seen in previous observations and predicted by theoretical models where feedback effects are inefficient at shutting down black hole growth at high redshift.« less
Explicitly-correlated Gaussian geminals in electronic structure calculations
NASA Astrophysics Data System (ADS)
Szalewicz, Krzysztof; Jeziorski, Bogumił
2010-11-01
Explicitly correlated functions have been used since 1929, but initially only for two-electron systems. In 1960, Boys and Singer showed that if the correlating factor is of Gaussian form, many-electron integrals can be computed for general molecules. The capability of explicitly correlated Gaussian (ECG) functions to accurately describe many-electron atoms and molecules was demonstrated only in the early 1980s when Monkhorst, Zabolitzky and the present authors cast the many-body perturbation theory (MBPT) and coupled cluster (CC) equations as a system of integro-differential equations and developed techniques of solving these equations with two-electron ECG functions (Gaussian-type geminals, GTG). This work brought a new accuracy standard to MBPT/CC calculations. In 1985, Kutzelnigg suggested that the linear r 12 correlating factor can also be employed if n-electron integrals, n > 2, are factorised with the resolution of identity. Later, this factor was replaced by more general functions f (r 12), most often by ? , usually represented as linear combinations of Gaussian functions which makes the resulting approach (called F12) a special case of the original GTG expansion. The current state-of-art is that, for few-electron molecules, ECGs provide more accurate results than any other basis available, but for larger systems the F12 approach is the method of choice, giving significant improvements over orbital calculations.
Puzzle of magnetic moments of Ni clusters revisited using quantum Monte Carlo method.
Lee, Hung-Wen; Chang, Chun-Ming; Hsing, Cheng-Rong
2017-02-28
The puzzle of the magnetic moments of small nickel clusters arises from the discrepancy between values predicted using density functional theory (DFT) and experimental measurements. Traditional DFT approaches underestimate the magnetic moments of nickel clusters. Two fundamental problems are associated with this puzzle, namely, calculating the exchange-correlation interaction accurately and determining the global minimum structures of the clusters. Theoretically, the two problems can be solved using quantum Monte Carlo (QMC) calculations and the ab initio random structure searching (AIRSS) method correspondingly. Therefore, we combined the fixed-moment AIRSS and QMC methods to investigate the magnetic properties of Ni n (n = 5-9) clusters. The spin moments of the diffusion Monte Carlo (DMC) ground states are higher than those of the Perdew-Burke-Ernzerhof ground states and, in the case of Ni 8-9 , two new ground-state structures have been discovered using the DMC calculations. The predicted results are closer to the experimental findings, unlike the results predicted in previous standard DFT studies.
Alternative splicing modulates Kv channel clustering through a molecular ball and chain mechanism
NASA Astrophysics Data System (ADS)
Zandany, Nitzan; Marciano, Shir; Magidovich, Elhanan; Frimerman, Teddy; Yehezkel, Rinat; Shem-Ad, Tzilhav; Lewin, Limor; Abdu, Uri; Orr, Irit; Yifrach, Ofer
2015-03-01
Ion channel clustering at the post-synaptic density serves a fundamental role in action potential generation and transmission. Here, we show that interaction between the Shaker Kv channel and the PSD-95 scaffold protein underlying channel clustering is modulated by the length of the intrinsically disordered C terminal channel tail. We further show that this tail functions as an entropic clock that times PSD-95 binding. We thus propose a ‘ball and chain’ mechanism to explain Kv channel binding to scaffold proteins, analogous to the mechanism describing channel fast inactivation. The physiological relevance of this mechanism is demonstrated in that alternative splicing of the Shaker channel gene to produce variants of distinct tail lengths resulted in differential channel cell surface expression levels and clustering metrics that correlate with differences in affinity of the variants for PSD-95. We suggest that modulating channel clustering by specific spatial-temporal spliced variant targeting serves a fundamental role in nervous system development and tuning.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Lin -Lin; Johnson, Duane D.; Tringides, Michael C.
Density functional theory is used to study structural energetics of Pb vacancy cluster formation on C 60/Pb/Si(111) to explain the unusually fast and error-free transformations between the “Devil's Staircase” (DS) phases on the Pb/Si(111) wetting layer at low temperature (~110K). The formation energies of vacancy clusters are calculated in C 60/Pb/Si(111) as Pb atoms are progressively ejected from the initial dense Pb wetting layer. Vacancy clusters larger than five Pb atoms are found to be stable with seven being the most stable, while vacancy clusters smaller than five are highly unstable, which agrees well with the observed ejection rate ofmore » ~5 Pb atoms per C 60. Furthermore, the high energy cost (~0.8 eV) for the small vacancy clusters to form indicates convincingly that the unusually fast transformation observed experimentally between the DS phases, upon C 60 adsorption at low temperature, cannot be the result of single-atom random walk diffusion but of correlated multi-atom processes.« less
Effects of Charge Transfer on the Adsorption of CO on Small Molybdenum-Doped Platinum Clusters.
Ferrari, Piero; Vanbuel, Jan; Tam, Nguyen Minh; Nguyen, Minh Tho; Gewinner, Sandy; Schöllkopf, Wieland; Fielicke, André; Janssens, Ewald
2017-03-23
The interaction of carbon monoxide with platinum alloy nanoparticles is an important problem in the context of fuel cell catalysis. In this work, molybdenum-doped platinum clusters have been studied in the gas phase to obtain a better understanding of the fundamental nature of the Pt-CO interaction in the presence of a dopant atom. For this purpose, Pt n + and MoPt n-1 + (n=3-7) clusters were studied by combined mass spectrometry and density functional theory calculations, making it possible to investigate the effects of molybdenum doping on the reactivity of platinum clusters with CO. In addition, IR photodissociation spectroscopy was used to measure the stretching frequency of CO molecules adsorbed on Pt n + and MoPt n-1 + (n=3-14), allowing an investigation of dopant-induced charge redistribution within the clusters. This electronic charge transfer is correlated with the observed changes in reactivity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Boser, Quinn A; Valevicius, Aïda M; Lavoie, Ewen B; Chapman, Craig S; Pilarski, Patrick M; Hebert, Jacqueline S; Vette, Albert H
2018-04-27
Quantifying angular joint kinematics of the upper body is a useful method for assessing upper limb function. Joint angles are commonly obtained via motion capture, tracking markers placed on anatomical landmarks. This method is associated with limitations including administrative burden, soft tissue artifacts, and intra- and inter-tester variability. An alternative method involves the tracking of rigid marker clusters affixed to body segments, calibrated relative to anatomical landmarks or known joint angles. The accuracy and reliability of applying this cluster method to the upper body has, however, not been comprehensively explored. Our objective was to compare three different upper body cluster models with an anatomical model, with respect to joint angles and reliability. Non-disabled participants performed two standardized functional upper limb tasks with anatomical and cluster markers applied concurrently. Joint angle curves obtained via the marker clusters with three different calibration methods were compared to those from an anatomical model, and between-session reliability was assessed for all models. The cluster models produced joint angle curves which were comparable to and highly correlated with those from the anatomical model, but exhibited notable offsets and differences in sensitivity for some degrees of freedom. Between-session reliability was comparable between all models, and good for most degrees of freedom. Overall, the cluster models produced reliable joint angles that, however, cannot be used interchangeably with anatomical model outputs to calculate kinematic metrics. Cluster models appear to be an adequate, and possibly advantageous alternative to anatomical models when the objective is to assess trends in movement behavior. Copyright © 2018 Elsevier Ltd. All rights reserved.
The Spatial Distribution of the Young Stellar Clusters in the Star-forming Galaxy NGC 628
NASA Astrophysics Data System (ADS)
Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Aloisi, A.; Bright, S. N.; Christian, C.; Cignoni, M.; Dale, D. A.; Dobbs, C.; Elmegreen, D. M.; Fumagalli, M.; Gallagher, J. S., III; Grebel, E. K.; Johnson, K. E.; Lee, J. C.; Messa, M.; Smith, L. J.; Ryon, J. E.; Thilker, D.; Ubeda, L.; Wofford, A.
2015-12-01
We present a study of the spatial distribution of the stellar cluster populations in the star-forming galaxy NGC 628. Using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey), we have identified 1392 potential young (≲ 100 Myr) stellar clusters within the galaxy using a combination of visual inspection and automatic selection. We investigate the clustering of these young stellar clusters and quantify the strength and change of clustering strength with scale using the two-point correlation function. We also investigate how image boundary conditions and dust lanes affect the observed clustering. The distribution of the clusters is well fit by a broken power law with negative exponent α. We recover a weighted mean index of α ∼ -0.8 for all spatial scales below the break at 3.″3 (158 pc at a distance of 9.9 Mpc) and an index of α ∼ -0.18 above 158 pc for the accumulation of all cluster types. The strength of the clustering increases with decreasing age and clusters older than 40 Myr lose their clustered structure very rapidly and tend to be randomly distributed in this galaxy, whereas the mass of the star cluster has little effect on the clustering strength. This is consistent with results from other studies that the morphological hierarchy in stellar clustering resembles the same hierarchy as the turbulent interstellar medium.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishimura, Yoshifumi; Department of Applied Chemistry and Institute of Molecular Science, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu 30010, Taiwan; Lee, Yuan-Pern
Vibrational infrared (IR) spectra of gas-phase O–H⋅⋅⋅O methanol clusters up to pentamer are simulated using self-consistent-charge density functional tight-binding method using two distinct methodologies: standard normal mode analysis and Fourier transform of the dipole time-correlation function. The twofold simulations aim at the direct critical assignment of the C–H stretching region of the recently recorded experimental spectra [H.-L. Han, C. Camacho, H. A. Witek, and Y.-P. Lee, J. Chem. Phys. 134, 144309 (2011)]. Both approaches confirm the previous assignment (ibid.) of the C–H stretching bands based on the B3LYP/ANO1 harmonic frequencies, showing that ν{sub 3}, ν{sub 9}, and ν{sub 2} C–Hmore » stretching modes of the proton-accepting (PA) and proton-donating (PD) methanol monomers experience only small splittings upon the cluster formation. This finding is in sharp discord with the assignment based on anharmonic B3LYP/VPT2/ANO1 vibrational frequencies (ibid.), suggesting that some procedural faults, likely related to the breakdown of the perturbational vibrational treatment, led the anharmonic calculations astray. The IR spectra based on the Fourier transform of the dipole time-correlation function include new, previously unaccounted for physical factors such as non-zero temperature of the system and large amplitude motions of the clusters. The elevation of temperature results in a considerable non-homogeneous broadening of the observed IR signals, while the presence of large-amplitude motions (methyl group rotations and PA-PD flipping), somewhat surprisingly, does not introduce any new features in the spectrum.« less
Yadav, Rajeev; Lu, H Peter
2018-03-28
The N-methyl-d-aspartate (NMDA) receptor ion-channel is activated by the binding of ligands, along with the application of action potential, important for synaptic transmission and memory functions. Despite substantial knowledge of the structure and function, the gating mechanism of the NMDA receptor ion channel for electric on-off signals is still a topic of debate. We investigate the NMDA receptor partition distribution and the associated channel's open-close electric signal trajectories using a combined approach of correlating single-molecule fluorescence photo-bleaching, single-molecule super-resolution imaging, and single-channel electric patch-clamp recording. Identifying the compositions of NMDA receptors, their spatial organization and distributions over live cell membranes, we observe that NMDA receptors are organized inhomogeneously: nearly half of the receptor proteins are individually dispersed; whereas others exist in heterogeneous clusters of around 50 nm in size as well as co-localized within the diffraction limited imaging area. We demonstrate that inhomogeneous interactions and partitions of the NMDA receptors can be a cause of the heterogeneous gating mechanism of NMDA receptors in living cells. Furthermore, comparing the imaging results with the ion-channel electric current recording, we propose that the clustered NMDA receptors may be responsible for the variation in the current amplitude observed in the on-off two-state ion-channel electric signal trajectories. Our findings shed new light on the fundamental structure-function mechanism of NMDA receptors and present a conceptual advancement of the ion-channel mechanism in living cells.
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
2018-04-01
I discuss a scenario in which the ultraviolet (UV) upturn of giant early-type galaxies (ETGs) is primarily due to helium-rich stellar populations that formed in massive metal-rich globular clusters (GCs), which subsequently dissolved in the strong tidal field in the central regions of the massive host galaxy. These massive GCs are assumed to show UV upturns similar to those observed recently in M87, the central giant elliptical galaxy in the Virgo cluster of galaxies. Data taken from the literature reveal a strong correlation between the strength of the UV upturn and the specific frequency of metal-rich GCs in ETGs. Adopting a Schechter function parameterization of GC mass functions, simulations of long-term dynamical evolution of GC systems show that the observed correlation between UV upturn strength and GC specific frequency can be explained by variations in the characteristic truncation mass {{ \\mathcal M }}{{c}} such that {{ \\mathcal M }}{{c}} increases with ETG luminosity in a way that is consistent with observed GC luminosity functions in ETGs. These findings suggest that the nature of the UV upturn in ETGs and the variation of its strength among ETGs are causally related to that of helium-rich populations in massive GCs, rather than intrinsic properties of field stars in massive galactic spheroids. With this in mind, I predict that future studies will find that [N/Fe] decreases with increasing galactocentric radius in massive ETGs, and that such gradients have the largest amplitudes in ETGs with the strongest UV upturns.
Atmospheric effects on cluster analyses. [for remote sensing application
NASA Technical Reports Server (NTRS)
Kiang, R. K.
1979-01-01
Ground reflected radiance, from which information is extracted through techniques of cluster analyses for remote sensing application, is altered by the atmosphere when it reaches the satellite. Therefore it is essential to understand the effects of the atmosphere on Landsat measurements, cluster characteristics and analysis accuracy. A doubling model is employed to compute the effective reflectivity, observed from the satellite, as a function of ground reflectivity, solar zenith angle and aerosol optical thickness for standard atmosphere. The relation between the effective reflectivity and ground reflectivity is approximately linear. It is shown that for a horizontally homogeneous atmosphere, the classification statistics from a maximum likelihood classifier remains unchanged under these transforms. If inhomogeneity is present, the divergence between clusters is reduced, and correlation between spectral bands increases. Radiance reflected by the background area surrounding the target may also reach the satellite. The influence of background reflectivity on effective reflectivity is discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ding, Jun; Ma, Evan; Asta, Mark
Using molecular dynamics simulations, we have studied the atomic correlations characterizing the second peak in the radial distribution function (RDF) of metallic glasses and liquids. The analysis was conducted from the perspective of different connection schemes of atomic packing motifs, based on the number of shared atoms between two linked coordination polyhedra. The results demonstrate that the cluster connections by face-sharing, specifically with three common atoms, are most favored when transitioning from the liquid to glassy state, and exhibit the stiffest elastic response during shear deformation. These properties of the connections and the resultant atomic correlations are generally the samemore » for different types of packing motifs in different alloys. Splitting of the second RDF peak was observed for the inherent structure of the equilibrium liquid, originating solely from cluster connections; this trait can then be inherited in the metallic glass formed via subsequent quenching of the parent liquid through the glass transition, in the absence of any additional type of local structural order. In conclusion, increasing ordering and cluster connection during cooling, however, may tune the position and intensity of the split peaks.« less
Bond Order Correlations in the 2D Hubbard Model
NASA Astrophysics Data System (ADS)
Moore, Conrad; Abu Asal, Sameer; Yang, Shuxiang; Moreno, Juana; Jarrell, Mark
We use the dynamical cluster approximation to study the bond correlations in the Hubbard model with next nearest neighbor (nnn) hopping to explore the region of the phase diagram where the Fermi liquid phase is separated from the pseudogap phase by the Lifshitz line at zero temperature. We implement the Hirsch-Fye cluster solver that has the advantage of providing direct access to the computation of the bond operators via the decoupling field. In the pseudogap phase, the parallel bond order susceptibility is shown to persist at zero temperature while it vanishes for the Fermi liquid phase which allows the shape of the Lifshitz line to be mapped as a function of filling and nnn hopping. Our cluster solver implements NVIDIA's CUDA language to accelerate the linear algebra of the Quantum Monte Carlo to help alleviate the sign problem by allowing for more Monte Carlo updates to be performed in a reasonable amount of computation time. Work supported by the NSF EPSCoR Cooperative Agreement No. EPS-1003897 with additional support from the Louisiana Board of Regents.
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method.
Sinha, Debalina; Pavanello, Michele
2015-08-28
The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term the Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.
Exact kinetic energy enables accurate evaluation of weak interactions by the FDE-vdW method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sinha, Debalina; Pavanello, Michele, E-mail: m.pavanello@rutgers.edu
2015-08-28
The correlation energy of interaction is an elusive and sought-after interaction between molecular systems. By partitioning the response function of the system into subsystem contributions, the Frozen Density Embedding (FDE)-vdW method provides a computationally amenable nonlocal correlation functional based on the adiabatic connection fluctuation dissipation theorem applied to subsystem density functional theory. In reproducing potential energy surfaces of weakly interacting dimers, we show that FDE-vdW, either employing semilocal or exact nonadditive kinetic energy functionals, is in quantitative agreement with high-accuracy coupled cluster calculations (overall mean unsigned error of 0.5 kcal/mol). When employing the exact kinetic energy (which we term themore » Kohn-Sham (KS)-vdW method), the binding energies are generally closer to the benchmark, and the energy surfaces are also smoother.« less
Calderón, Lucas A; Garza, Jorge; Espinal, Juan F
2015-12-24
The effect of sodium on the thermodynamics and kinetics of carbon gasification with carbon dioxide was studied by using quantum chemistry methods. Specifically, in the density functional context, two exchange-correlation functionals were used: B3LYP and M06. Some results obtained by these exchange-correlation functionals were contrasted with those obtained by the CCSD(T) method. It was found that density functional theory gives similar conclusions with respect to the coupled-cluster method. As one important conclusion we can mention that the thermodynamics of carbon monoxide desorption is not favored by the sodium presence. However, the presence of this metal induces: (a) an easier formation of one semiquinone group, (b) the dissociation of carbon dioxide, and (c) an increment on the CO desorption rate for one of the proposed pathways.
Coupled-cluster treatment of molecular strong-field ionization
NASA Astrophysics Data System (ADS)
Jagau, Thomas-C.
2018-05-01
Ionization rates and Stark shifts of H2, CO, O2, H2O, and CH4 in static electric fields have been computed with coupled-cluster methods in a basis set of atom-centered Gaussian functions with a complex-scaled exponent. Consideration of electron correlation is found to be of great importance even for a qualitatively correct description of the dependence of ionization rates and Stark shifts on the strength and orientation of the external field. The analysis of the second moments of the molecular charge distribution suggests a simple criterion for distinguishing tunnel and barrier suppression ionization in polyatomic molecules.
Griffiths' inequalities for Ashkin-Teller model
NASA Technical Reports Server (NTRS)
Lee, C. T.
1973-01-01
The two Griffiths' (1967) inequalities for the correlation functions of Ising ferromagnets with two-body interactions, and two other inequalities obtained by Kelly and Sherman (1968) and by Sherman (1969) are shown to hold not only for the Ashkin-Teller (1943) model but also for a generalized Ashkin-Teller model (Kihara et al., 1954) with many-body interactions involving arbitrary clusters of particles. A cluster of particles is understood to mean a collection of pairs of particles rather than a group of particles. The four generalized inequalities under consideration are presented in the form of theorems, and a new inequality is obtained.
Hydrogen bonding in water clusters and their ionized counterparts.
Neela, Y Indra; Mahadevi, A Subha; Sastry, G Narahari
2010-12-30
Ab initio and DFT computations were carried out on four distinct hydrogen-bonded arrangements of water clusters (H(2)O)(n), n = 2-20, represented as W1D, W2D, W2DH, and W3D. The variation in the strength of hydrogen bond as a function of the chain length is studied. In all the four cases, there is a substantial cooperative interaction, albeit in different degrees. The effect of basis set superposition error (BSSE) on the complexation energy of water clusters has been analyzed. Atoms in molecules (AIM) analysis performed to evaluate the nature of the hydrogen bonding shows a high correlation between hydrogen bond strength and the trends in complexation energy. Solvated water clusters exhibit lower complexation energies compared to corresponding gas-phase geometries on PCM (polarized continuum model) optimization. The feasibility of stripping an electron or addition of an electron increases dramatically as the cluster size increases. Although W3D caged structures are stable for neutral clusters, the helical W2DH arrangement appeared to be an optimal choice for its ionized counterparts.
NASA Technical Reports Server (NTRS)
Bauschlicher, Charles W., Jr.; Partridge, Harry; Scuseria, Gustavo E.
1992-01-01
The correlation contribution to the M-C binding energy for the MCH2(+) systems can exceed 100 kcal/mol. At the self-consistent field (SCF) level, these systems can be more than 50 kcal/mol above the fragment energies. In spite of the poor zeroth-order reference, the coupled cluster single and double excitation method with a perturbational estimate of triple excitations, CCSD(T), method is shown to provide an accurate description of these systems. The maximum difference between the CCSD(T) and internally contracted averaged coupled-pair functional binding energies is 1.5 kcal/mol for CrCH2(+), with the remaining systems agreeing to within 1.0 kcal/mol.
NASA Astrophysics Data System (ADS)
Guzzo, L.; Bartlett, J. G.; Cappi, A.; Maurogordato, S.; Zucca, E.; Zamorani, G.; Balkowski, C.; Blanchard, A.; Cayatte, V.; Chincarini, G.; Collins, C. A.; Maccagni, D.; MacGillivray, H.; Merighi, R.; Mignoli, M.; Proust, D.; Ramella, M.; Scaramella, R.; Stirpe, G. M.; Vettolani, G.
2000-03-01
We present analyses of the two-point correlation properties of the ESO Slice Project (ESP) galaxy redshift survey, both in redshift and real space. From the redshift-space correlation function $xi (r) i(s) we are able to trace positive clustering out to separations as large as 50 h^{-1} Mpc, after which xi (r) i(s) smoothly breaks down, crossing the zero value between 60 and 80 h^{-1} Mpc. This is best seen from the whole magnitude-limited redshift catalogue, using the J_3 miniμm-variance weighting estimator. xi (r) i(s) is reasonably well described by a shallow power law with \\gamma\\sim 1.5 between 3 and 50 h^{-1} Mpc, while on smaller scales (0.2-2 h^{-1} Mpc) it has a shallower slope (\\gamma\\sim 1). This flattening is shown to be mostly due to the redshift-space damping produced by virialized structures, and is less evident when volume-limited samples of the survey are analysed. We examine the full effect of redshift-space distortions by computing the two-dimensional correlation function xi (r) i(r_p,\\pi) , from which we project out the real-space xi (r) i(r) below 10 h^{-1} Mpc. This function is well described by a power-law model (r/r_o)^{-\\gamma}, with r_o=4.15^{+0.20}_{-0.21} h^{-1} Mpc and \\gamma=1.67^{+0.07}_{-0.09} for the whole magnitude-limited catalogue. Comparison to other redshift surveys shows a consistent picture in which galaxy clustering remains positive out to separations of 50 h^{-1} Mpc or larger, in substantial agreement with the results obtained from angular surveys like the APM and EDSGC. Also the shape of the two-point correlation function is remarkably unanimous among these data sets, in all cases requiring more power on scales larger than 5 h^{-1} Mpc (a `shoulder'), with respect to a simple extrapolation of the canonical xi (r) i(r) =(r/5)^{-1.8}. The analysis of xi (r) i(s) for volume-limited subsamples with different luminosity shows evidence of luminosity segregation only for the most luminous sample with Mb_J <= -20.5. For these galaxies, the amplitude of clustering is on all scales >4 h^{-1} Mpc about a factor of 2 above that of all other subsamples containing less luminous galaxies. When redshift-space distortions are removed through projection of xi (r) i(r_p,\\pi) , however, a weak dependence on luminosity is seen at small separations also at fainter magnitudes, resulting in a growth of r_o from 3.45_{-0.30}^{+0.21} h^{-1} Mpc to 5.15_{-0.44}^{+0.39} h^{-1} Mpc, when the limiting absolute magnitude of the sample changes from M=-18.5 to M=-20. This effect is masked in redshift space, as the mean pairwise velocity dispersion experiences a parallel increase, basically erasing the effect of the clustering growth on xi (r) i(s) . Based on observations collected at the European Southern Observatory, La Silla, Chile.}
NASA Astrophysics Data System (ADS)
Huang, Chen; Chi, Yu-Chieh
2017-12-01
The key element in Kohn-Sham (KS) density functional theory is the exchange-correlation (XC) potential. We recently proposed the exchange-correlation potential patching (XCPP) method with the aim of directly constructing high-level XC potential in a large system by patching the locally computed, high-level XC potentials throughout the system. In this work, we investigate the patching of the exact exchange (EXX) and the random phase approximation (RPA) correlation potentials. A major challenge of XCPP is that a cluster's XC potential, obtained by solving the optimized effective potential equation, is only determined up to an unknown constant. Without fully determining the clusters' XC potentials, the patched system's XC potential is "uneven" in the real space and may cause non-physical results. Here, we developed a simple method to determine this unknown constant. The performance of XCPP-RPA is investigated on three one-dimensional systems: H20, H10Li8, and the stretching of the H19-H bond. We investigated two definitions of EXX: (i) the definition based on the adiabatic connection and fluctuation dissipation theorem (ACFDT) and (ii) the Hartree-Fock (HF) definition. With ACFDT-type EXX, effective error cancellations were observed between the patched EXX and the patched RPA correlation potentials. Such error cancellations were absent for the HF-type EXX, which was attributed to the fact that for systems with fractional occupation numbers, the integral of the HF-type EXX hole is not -1. The KS spectra and band gaps from XCPP agree reasonably well with the benchmarks as we make the clusters large.
NASA Astrophysics Data System (ADS)
Zhu, L.; Li, Z.; Li, C.; Wang, B.; Chen, Z.; McClellan, J. H.; Peng, Z.
2017-12-01
Spatial-temporal evolution of aftershocks is important for illumination of earthquake physics and for rapid response of devastative earthquakes. To improve aftershock catalogs of the 2008 MW7.9 Wenchuan earthquake in Sichuan, China, Alibaba cloud and China Earthquake Administration jointly launched a seismological contest in May 2017 [Fang et al., 2017]. This abstract describes how we handle this problem in this competition. We first used Short-Term Average/Long-Term Average (STA/LTA) and Kurtosis function to obtain over 55000 candidate phase picks (P or S). Based on Signal to Noise Ratio (SNR), about 40000 phases (P or S) are selected. So far, these 40000 phases have a hit rate of 40% among the manually picks. The causes include that 1) there exist false picks (neither P nor S); 2) some P and S arrivals are mis-labeled. To improve our results, we correlate the 40000 phases over continuous waveforms to obtain the phases missed by during the first pass. This results in 120,000 events. After constructing an affinity matrix based on the cross-correlation for newly detected phases, subspace clustering methods [Vidal 2011] are applied to group those phases into separated subspaces. Initial results show good agreement between empirical and clustered labels of P phases. Half of the empirical S phases are clustered into the P phase cluster. This may be a combined effect of 1) mislabeling isolated P phases to S phases and 2) clustering errors due to a small incomplete sample pool. Phases that were falsely detected in the initial results can be also teased out. To better characterize P and S phases, our next step is to apply subspace clustering methods directly to the waveforms, instead of using the cross-correlation coefficients of detected phases. After that, supervised learning, e.g., a convolutional neural network, can be employed to improve the pick accuracy. Updated results will be presented at the meeting.
Halo Intrinsic Alignment: Dependence on Mass, Formation Time, and Environment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xia, Qianli; Kang, Xi; Wang, Peng
In this paper we use high-resolution cosmological simulations to study halo intrinsic alignment and its dependence on mass, formation time, and large-scale environment. In agreement with previous studies using N -body simulations, it is found that massive halos have stronger alignment. For the first time, we find that for a given halo mass older halos have stronger alignment and halos in cluster regions also have stronger alignment than those in filaments. To model these dependencies, we extend the linear alignment model with inclusion of halo bias and find that the halo alignment with its mass and formation time dependence canmore » be explained by halo bias. However, the model cannot account for the environment dependence, as it is found that halo bias is lower in clusters and higher in filaments. Our results suggest that halo bias and environment are independent factors in determining halo alignment. We also study the halo alignment correlation function and find that halos are strongly clustered along their major axes and less clustered along the minor axes. The correlated halo alignment can extend to scales as large as 100 h {sup −1} Mpc, where its feature is mainly driven by the baryon acoustic oscillation effect.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tsai, Chi-Lin; Bridwell-Rabb, Jennifer; Barondeau, David P
2011-11-07
Friedreich's ataxia (FRDA) is a progressive neurodegenerative disease that has been linked to defects in the protein frataxin (Fxn). Most FRDA patients have a GAA expansion in the first intron of their Fxn gene that decreases protein expression. Some FRDA patients have a GAA expansion on one allele and a missense mutation on the other allele. Few functional details are known for the ~15 different missense mutations identified in FRDA patients. Here in vitro evidence is presented that indicates the FRDA I154F and W155R variants bind more weakly to the complex of Nfs1, Isd11, and Isu2 and thereby are defectivemore » in forming the four-component SDUF complex that constitutes the core of the Fe-S cluster assembly machine. The binding affinities follow the trend Fxn ~ I154F > W155F > W155A ~ W155R. The Fxn variants also have diminished ability to function as part of the SDUF complex to stimulate the cysteine desulfurase reaction and facilitate Fe-S cluster assembly. Four crystal structures, including the first for a FRDA variant, reveal specific rearrangements associated with the loss of function and lead to a model for Fxn-based activation of the Fe-S cluster assembly complex. Importantly, the weaker binding and lower activity for FRDA variants correlate with the severity of disease progression. Together, these results suggest that Fxn facilitates sulfur transfer from Nfs1 to Isu2 and that these in vitro assays are sensitive and appropriate for deciphering functional defects and mechanistic details for human Fe-S cluster biosynthesis.« less
Shokouhi, Sepideh; Rogers, Baxter P; Kang, Hakmook; Ding, Zhaohua; Claassen, Daniel O; Mckay, John W; Riddle, William R
2015-01-01
Amyloid-beta (Aβ) imaging with positron emission tomography (PET) holds promise for detecting the presence of Aβ plaques in the cortical gray matter. Many image analyses focus on regional average measurements of tracer activity distribution; however, considerable additional information is available in the images. Metrics that describe the statistical properties of images, such as the two-point correlation function (S2), have found wide applications in astronomy and materials science. S2 provides a detailed characterization of spatial patterns in images typically referred to as clustering or flocculence. The objective of this study was to translate the two-point correlation method into Aβ-PET of the human brain using 11C-Pittsburgh compound B (11C-PiB) to characterize longitudinal changes in the tracer distribution that may reflect changes in Aβ plaque accumulation. We modified the conventional S2 metric, which is primarily used for binary images and formulated a weighted two-point correlation function (wS2) to describe nonbinary, real-valued PET images with a single statistical function. Using serial 11C-PiB scans, we calculated wS2 functions from two-dimensional PET images of different cortical regions as well as three-dimensional data from the whole brain. The area under the wS2 functions was calculated and compared with the mean/median of the standardized uptake value ratio (SUVR). For three-dimensional data, we compared the area under the wS2 curves with the subjects' cerebrospinal fluid measures. Overall, the longitudinal changes in wS2 correlated with the increase in mean SUVR but showed lower variance. The whole brain results showed a higher inverse correlation between the cerebrospinal Aβ and wS2 than between the cerebrospinal Aβ and SUVR mean/median. We did not observe any confounding of wS2 by region size or injected dose. The wS2 detects subtle changes and provides additional information about the binding characteristics of radiotracers and Aβ accumulation that are difficult to verify with mean SUVR alone.
Non-linear clustering in the cold plus hot dark matter model
NASA Astrophysics Data System (ADS)
Bonometto, Silvio A.; Borgani, Stefano; Ghigna, Sebastiano; Klypin, Anatoly; Primack, Joel R.
1995-03-01
The main aim of this work is to find out if hierarchical scaling, observed in galaxy clustering, can be dynamically explained by studying N-body simulations. Previous analyses of dark matter (DM) particle distributions indicated heavy distortions with respect to the hierarchical pattern. Here, we shall describe how such distortions are to be interpreted and why they can be fully reconciled with the observed galaxy clustering. This aim is achieved by using high-resolution (512^3 grid-points) particle-mesh (PM) N-body simulations to follow the development of non-linear clustering in a Omega=1 universe, dominated either by cold dark matter (CDM) or by a mixture of cold+hot dark matter (CHDM) with Omega_cold=0.6, and Omega_hot=0.3 and Omega_baryon=0.1 a simulation box of side 100 Mpc (h=0.5) is used. We analyse two CHDM realizations with biasing factor b=1.5 (COBE normalization), starting from different initial random numbers, and compare them with CDM simulations with b=1 (COBE-compatible) and b=1.5. We evaluate high-order correlation functions and the void probability function (VPF). Correlation functions are obtained from both counts in cells and counts of neighbours. The analysis is carried out for DM particles and for galaxies identified as massive haloes of the evolved density field. We confirm that clustering of DM particles systematically exhibits deviations from hierarchical scaling, although the deviation increases somewhat in redshift space. Deviations from the hierarchical scaling of DM particles are found to be related to the spectrum shape, in a way that indicates that such distortions arise from finite sampling effects. We identify galaxy positions in the simulations and show that, quite differently from the DM particle background, galaxies follow hierarchical scaling (S_q=xi_q/& xgr^q-1_2=consta nt) far more closely, with reduced skewness and kurtosis coefficients S_3~2.5 and S_4~7.5, in general agreement with observational results. Unlike DM, the scaling of galaxy clustering is must marginally affected by redshift distortions and is obtained for both CDM and CHDM models. Hierarchical scaling in simulations is confirmed by VPF analysis. Also in this case, we find substantial agreement with observational findings.
NASA Astrophysics Data System (ADS)
Hollett, Joshua W.; Pegoretti, Nicholas
2018-04-01
Separate, one-parameter, on-top density functionals are derived for the short-range dynamic correlation between opposite and parallel-spin electrons, in which the electron-electron cusp is represented by an exponential function. The combination of both functionals is referred to as the Opposite-spin exponential-cusp and Fermi-hole correction (OF) functional. The two parameters of the OF functional are set by fitting the ionization energies and electron affinities, of the atoms He to Ar, predicted by ROHF in combination with the OF functional to the experimental values. For ionization energies, the overall performance of ROHF-OF is better than completely renormalized coupled-cluster [CR-CC(2,3)] and better than, or as good as, conventional density functional methods. For electron affinities, the overall performance of ROHF-OF is less impressive. However, for both ionization energies and electron affinities of third row atoms, the mean absolute error of ROHF-OF is only 3 kJ mol-1.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Davidge, T. J.
2012-12-20
The stellar contents of the open clusters King 12, NGC 7788, and NGC 7790 are investigated using MegaCam images. Comparisons with isochrones yield an age <20 Myr for King 12, 20-40 Myr for NGC 7788, and 60-80 Myr for NGC 7790 based on the properties of stars near the main-sequence turnoff (MSTO) in each cluster. The reddening of NGC 7788 is much larger than previously estimated. The luminosity functions (LFs) of King 12 and NGC 7788 show breaks that are attributed to the onset of pre-main-sequence (PMS) objects, and comparisons with models of PMS evolution yield ages that are consistentmore » with those measured from stars near the MSTO. In contrast, the r' LF of main-sequence stars in NGC 7790 is matched to r' = 20 by a model that is based on the solar neighborhood mass function. The structural properties of all three clusters are investigated by examining the two-point angular correlation function of blue main-sequence stars. King 12 and NGC 7788 are each surrounded by a stellar halo that extends out to a radius of 5 arcmin ({approx}3.4 pc). It is suggested that these halos form in response to large-scale mass ejection early in the evolution of the clusters, as predicted by models. In contrast, blue main-sequence stars in NGC 7790 are traced out to a radius of {approx}7.5 arcmin ({approx}5.5 pc), with no evidence of a halo. It is suggested that all three clusters may have originated in the same star-forming complex, but not in the same giant molecular cloud.« less
Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S
2017-08-01
Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.
Structure-function clustering in multiplex brain networks
NASA Astrophysics Data System (ADS)
Crofts, J. J.; Forrester, M.; O'Dea, R. D.
2016-10-01
A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.
NASA Astrophysics Data System (ADS)
Kazin, Eyal A.; Sánchez, Ariel G.; Cuesta, Antonio J.; Beutler, Florian; Chuang, Chia-Hsun; Eisenstein, Daniel J.; Manera, Marc; Padmanabhan, Nikhil; Percival, Will J.; Prada, Francisco; Ross, Ashley J.; Seo, Hee-Jong; Tinker, Jeremy; Tojeiro, Rita; Xu, Xiaoying; Brinkmann, J.; Joel, Brownstein; Nichol, Robert C.; Schlegel, David J.; Schneider, Donald P.; Thomas, Daniel
2013-10-01
We analyse the 2D correlation function of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS sample of massive galaxies of the ninth data release to measure cosmic expansion H and the angular diameter distance DA at a mean redshift of
Which Density Functional Should Be Used to Describe Protonated Water Clusters?
Shi, Ruili; Huang, Xiaoming; Su, Yan; Lu, Hai-Gang; Li, Si-Dian; Tang, Lingli; Zhao, Jijun
2017-04-27
Protonated water cluster is one of the most important hydrogen-bond network systems. Finding an appropriate DFT method to study the properties of protonated water clusters can substantially improve the economy in computational resources without sacrificing the accuracy compared to high-level methods. Using high-level MP2 and CCSD(T) methods as well as experimental results as benchmark, we systematically examined the effect of seven exchange-correlation GGA functionals (with BLYP, B3LYP, X3LYP, PBE0, PBE1W, M05-2X, and B97-D parametrizations) in describing the geometric parameters, interaction energies, dipole moments, and vibrational properties of protonated water clusters H + (H 2 O) 2-9,12 . The overall performance of all these functionals is acceptable, and each of them has its advantage in certain aspects. X3LYP is the best to describe the interaction energies, and PBE0 and M05-2X are also recommended to investigate interaction energies. PBE0 gives the best anharmonic frequencies, followed by PBE1W, B97-D and BLYP methods. PBE1W, B3LYP, B97-D, and X3LYP can yield better geometries. The capability of B97-D to distinguish the relative energies between isomers is the best among all the seven methods, followed by M05-2X and PBE0.
Parallel algorithm of VLBI software correlator under multiprocessor environment
NASA Astrophysics Data System (ADS)
Zheng, Weimin; Zhang, Dong
2007-11-01
The correlator is the key signal processing equipment of a Very Lone Baseline Interferometry (VLBI) synthetic aperture telescope. It receives the mass data collected by the VLBI observatories and produces the visibility function of the target, which can be used to spacecraft position, baseline length measurement, synthesis imaging, and other scientific applications. VLBI data correlation is a task of data intensive and computation intensive. This paper presents the algorithms of two parallel software correlators under multiprocessor environments. A near real-time correlator for spacecraft tracking adopts the pipelining and thread-parallel technology, and runs on the SMP (Symmetric Multiple Processor) servers. Another high speed prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm is realized on a small Beowulf cluster platform. Both correlators have the characteristic of flexible structure, scalability, and with 10-station data correlating abilities.
Global Patterns of Guild Composition and Functional Diversity of Spiders
Cardoso, Pedro; Pekár, Stano; Jocqué, Rudy; Coddington, Jonathan A.
2011-01-01
The objectives of this work are: (1) to define spider guilds for all extant families worldwide; (2) test if guilds defined at family level are good surrogates of species guilds; (3) compare the taxonomic and guild composition of spider assemblages from different parts of the world; (4) compare the taxonomic and functional diversity of spider assemblages and; (5) relate functional diversity with habitat structure. Data on foraging strategy, prey range, vertical stratification and circadian activity was collected for 108 families. Spider guilds were defined by hierarchical clustering. We searched for inconsistencies between family guild placement and the known guild of each species. Richness and abundance per guild before and after correcting guild placement were compared, as were the proportions of each guild and family between all possible pairs of sites. Functional diversity per site was calculated based on hierarchical clustering. Eight guilds were discriminated: (1) sensing, (2) sheet, (3) space, and (4) orb web weavers; (5) specialists; (6) ambush, (7) ground, and (8) other hunters. Sixteen percent of the species richness corresponding to 11% of all captured individuals was incorrectly attributed to a guild by family surrogacy; however, the correlation of uncorrected vs. corrected guilds was invariably high. The correlation of guild richness or abundances was generally higher than the correlation of family richness or abundances. Functional diversity was not always higher in the tropics than in temperate regions. Families may potentially serve as ecological surrogates for species. Different families may present similar roles in the ecosystems, with replacement of some taxa by other within the same guild. Spiders in tropical regions seem to have higher redundancy of functional roles and/or finer resource partitioning than in temperate regions. Although species and family diversity were higher in the tropics, functional diversity seems to be also influenced by altitude and habitat structure. PMID:21738772
Chen, Hua-Jun; Chen, Qiu-Feng; Yang, Zhe-Ting; Shi, Hai-Bin
2018-05-30
A higher risk of cognitive impairments has been found after an overt hepatic encephalopathy (OHE) episode in cirrhotic patients. We investigated the effect of prior OHE episodes on the topological organization of the functional brain network and its association with the relevant cognitive impairments. Resting-state functional MRI data were acquired from 41 cirrhotic patients (19 with prior OHE (Prior-OHE) and 22 without (Non-Prior-OHE)) and 21 healthy controls (HC). A Psychometric Hepatic Encephalopathy Score (PHES) assessed cognition. The whole-brain functional network was constructed by thresholding functional correlation matrices of 90 brain regions (derived from the Automated Anatomic Labeling atlas). The topological properties of the brain network, including small-worldness, network efficiency, and nodal efficiency, were examined using graph theory-based analysis. Globally, the Prior-OHE group had a significantly decreased clustering coefficient and local efficiency, compared with the controls. Locally, the nodal efficiency in the bilateral medial superior frontal gyrus and the right postcentral gyrus decreased in the Prior-OHE group, while the nodal efficiency in the bilateral anterior cingulate/paracingulate gyri and right superior parietal gyrus increased in the Prior-OHE group. The alterations of global and regional network parameters progressed from Non-Prior-OHE to Prior-OHE and the clustering coefficient and local efficiency values were significantly correlated with PHES results. In conclusion, cirrhosis leads to the reduction of brain functional network efficiency, which could be aggravated by a prior OHE episode. Aberrant topological organization of the functional brain network may contribute to a higher risk of cognitive impairments in Prior-OHE patients.
A cross-correlation-based estimate of the galaxy luminosity function
NASA Astrophysics Data System (ADS)
van Daalen, Marcel P.; White, Martin
2018-06-01
We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased redshift distributions and, for the first time, redshift-dependent luminosity functions, using only clustering information and the apparent magnitudes of the galaxies as input. In contrast to many existing techniques for recovering unbiased redshift distributions, the output of our method is not degenerate with the galaxy bias b(z), which is achieved by modelling the shape of the luminosity bias. We successfully apply our method to a mock galaxy survey and discuss improvements to be made before applying our model to real data.
Statistics of voids in hierarchical universes
NASA Technical Reports Server (NTRS)
Fry, J. N.
1986-01-01
As one alternative to the N-point galaxy correlation function statistics, the distribution of holes or the probability that a volume of given size and shape be empty of galaxies can be considered. The probability of voids resulting from a variety of hierarchical patterns of clustering is considered, and these are compared with the results of numerical simulations and with observations. A scaling relation required by the hierarchical pattern of higher order correlation functions is seen to be obeyed in the simulations, and the numerical results show a clear difference between neutrino models and cold-particle models; voids are more likely in neutrino universes. Observational data do not yet distinguish but are close to being able to distinguish between models.
Rand, Kristin A; Song, Chi; Dean, Eric; Serie, Daniel J; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S; Bock, Cathryn H; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K; Conti, David V; Zimmerman, Todd; Hwang, Amie E; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L; Berndt, Sonja I; Blot, William J; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W Ryan; Stevens, Victoria L; Lieber, Michael R; Goodman, Phyllis J; Hennis, Anselm J M; Hsing, Ann W; Mehta, Jayesh; Kittles, Rick A; Kolb, Suzanne; Klein, Eric A; Leske, Cristina; Murphy, Adam B; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S; Vij, Ravi; Rybicki, Benjamin A; Stanford, Janet L; Signorello, Lisa B; Witte, John S; Ambrosone, Christine B; Bhatti, Parveen; John, Esther M; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Birmann, Brenda M; Ingles, Sue A; Press, Michael F; Atanackovic, Djordje; Glenn, Martha J; Cannon-Albright, Lisa A; Jones, Brandt; Tricot, Guido; Martin, Thomas G; Kumar, Shaji K; Wolf, Jeffrey L; Deming Halverson, Sandra L; Rothman, Nathaniel; Brooks-Wilson, Angela R; Rajkumar, S Vincent; Kolonel, Laurence N; Chanock, Stephen J; Slager, Susan L; Severson, Richard K; Janakiraman, Nalini; Terebelo, Howard R; Brown, Elizabeth E; De Roos, Anneclaire J; Mohrbacher, Ann F; Colditz, Graham A; Giles, Graham G; Spinelli, John J; Chiu, Brian C; Munshi, Nikhil C; Anderson, Kenneth C; Levy, Joan; Zonder, Jeffrey A; Orlowski, Robert Z; Lonial, Sagar; Camp, Nicola J; Vachon, Celine M; Ziv, Elad; Stram, Daniel O; Hazelett, Dennis J; Haiman, Christopher A; Cozen, Wendy
2016-12-01
Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10 -7 ) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR. ©2016 American Association for Cancer Research.
Didic, Mira; Felician, Olivier; Gour, Natalina; Bernard, Rafaelle; Pécheux, Christophe; Mundler, Olivier; Ceccaldi, Mathieu; Guedj, Eric
2015-09-01
The ε4 allele of the apolipoprotein E (APO-E4) gene, a genetic risk factor for Alzheimer's disease (AD), also modulates brain metabolism and function in healthy subjects. The aim of the present study was to explore cerebral metabolism using FDG PET in healthy APO-E4 carriers by comparing cognitively normal APO-E4 carriers to noncarriers and to assess if patterns of metabolism are correlated with performance on cognitive tasks. Moreover, metabolic connectivity patterns were established in order to assess if the organization of neural networks is influenced by genetic factors. Whole-brain PET statistical analysis was performed at voxel-level using SPM8 with a threshold of p < 0.005, corrected for volume, with age, gender and level of education as nuisance variables. Significant hypometabolism between APO-E4 carriers (n = 11) and noncarriers (n = 30) was first determined. Mean metabolic values with clinical/neuropsychological data were extracted at the individual level, and correlations were searched using Spearman's rank test in the whole group. To evaluate metabolic connectivity from metabolic cluster(s) previously identified in the intergroup comparison, voxel-wise interregional correlation analysis (IRCA) was performed between groups of subjects. APO-E4 carriers had reduced metabolism within the left anterior medial temporal lobe (MTL), where neuropathological changes first appear in AD, including the entorhinal and perirhinal cortices. A correlation between metabolism in this area and performance on the DMS48 (delayed matching to sample-48 items) was found, in line with converging evidence involving the perirhinal cortex in object-based memory. Finally, a voxel-wise IRCA revealed stronger metabolic connectivity of the MTL cluster with neocortical frontoparietal regions in carriers than in noncarriers, suggesting compensatory metabolic networks. Exploring cerebral metabolism using FDG PET can contribute to a better understanding of the influence of genetic factors on cerebral metabolism at both the local and network levels leading to phenotypical variations of the healthy brain and selective vulnerability.
Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P
2017-11-29
Transcription factors (TFs) form a complex regulatory network within the cell that is crucial to cell functioning and human health. While methods to establish where a TF binds to DNA are well established, these methods provide no information describing how TFs interact with one another when they do bind. TFs tend to bind the genome in clusters, and current methods to identify these clusters are either limited in scope, unable to detect relationships beyond motif similarity, or not applied to TF-TF interactions. Here, we present a proximity-based graph clustering approach to identify TF clusters using either ChIP-seq or motif search data. We use TF co-occurrence to construct a filtered, normalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while maintaining TF-cluster and cluster-cluster interactions. We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-based TFBS searching for an example TF. We show that our method produces small, manageable clusters that encapsulate many known, experimentally validated transcription factor interactions and that our method is capable of capturing interactions that motif similarity methods might miss. Our graph structure is able to significantly increase the accuracy of motif TFBS searching, demonstrating that the TF-TF connections within the graph correlate with biological TF-TF interactions. The interactions identified by our method correspond to biological reality and allow for fast exploration of TF clustering and regulatory dynamics.
Bhattacharya, Anindya; De, Rajat K
2010-08-01
Distance based clustering algorithms can group genes that show similar expression values under multiple experimental conditions. They are unable to identify a group of genes that have similar pattern of variation in their expression values. Previously we developed an algorithm called divisive correlation clustering algorithm (DCCA) to tackle this situation, which is based on the concept of correlation clustering. But this algorithm may also fail for certain cases. In order to overcome these situations, we propose a new clustering algorithm, called average correlation clustering algorithm (ACCA), which is able to produce better clustering solution than that produced by some others. ACCA is able to find groups of genes having more common transcription factors and similar pattern of variation in their expression values. Moreover, ACCA is more efficient than DCCA with respect to the time of execution. Like DCCA, we use the concept of correlation clustering concept introduced by Bansal et al. ACCA uses the correlation matrix in such a way that all genes in a cluster have the highest average correlation values with the genes in that cluster. We have applied ACCA and some well-known conventional methods including DCCA to two artificial and nine gene expression datasets, and compared the performance of the algorithms. The clustering results of ACCA are found to be more significantly relevant to the biological annotations than those of the other methods. Analysis of the results show the superiority of ACCA over some others in determining a group of genes having more common transcription factors and with similar pattern of variation in their expression profiles. Availability of the software: The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to be consulted before installation and execution of the software. Copyright 2010 Elsevier Inc. All rights reserved.
Datta, Somnath; Nevalainen, Jaakko; Oja, Hannu
2012-01-01
SUMMARY Rank based tests are alternatives to likelihood based tests popularized by their relative robustness and underlying elegant mathematical theory. There has been a serge in research activities in this area in recent years since a number of researchers are working to develop and extend rank based procedures to clustered dependent data which include situations with known correlation structures (e.g., as in mixed effects models) as well as more general form of dependence. The purpose of this paper is to test the symmetry of a marginal distribution under clustered data. However, unlike most other papers in the area, we consider the possibility that the cluster size is a random variable whose distribution is dependent on the distribution of the variable of interest within a cluster. This situation typically arises when the clusters are defined in a natural way (e.g., not controlled by the experimenter or statistician) and in which the size of the cluster may carry information about the distribution of data values within a cluster. Under the scenario of an informative cluster size, attempts to use some form of variance adjusted sign or signed rank tests would fail since they would not maintain the correct size under the distribution of marginal symmetry. To overcome this difficulty Datta and Satten (2008; Biometrics, 64, 501–507) proposed a Wilcoxon type signed rank test based on the principle of within cluster resampling. In this paper we study this problem in more generality by introducing a class of valid tests employing a general score function. Asymptotic null distribution of these tests is obtained. A simulation study shows that a more general choice of the score function can sometimes result in greater power than the Datta and Satten test; furthermore, this development offers the user a wider choice. We illustrate our tests using a real data example on spinal cord injury patients. PMID:23074359
Datta, Somnath; Nevalainen, Jaakko; Oja, Hannu
2012-09-01
Rank based tests are alternatives to likelihood based tests popularized by their relative robustness and underlying elegant mathematical theory. There has been a serge in research activities in this area in recent years since a number of researchers are working to develop and extend rank based procedures to clustered dependent data which include situations with known correlation structures (e.g., as in mixed effects models) as well as more general form of dependence.The purpose of this paper is to test the symmetry of a marginal distribution under clustered data. However, unlike most other papers in the area, we consider the possibility that the cluster size is a random variable whose distribution is dependent on the distribution of the variable of interest within a cluster. This situation typically arises when the clusters are defined in a natural way (e.g., not controlled by the experimenter or statistician) and in which the size of the cluster may carry information about the distribution of data values within a cluster.Under the scenario of an informative cluster size, attempts to use some form of variance adjusted sign or signed rank tests would fail since they would not maintain the correct size under the distribution of marginal symmetry. To overcome this difficulty Datta and Satten (2008; Biometrics, 64, 501-507) proposed a Wilcoxon type signed rank test based on the principle of within cluster resampling. In this paper we study this problem in more generality by introducing a class of valid tests employing a general score function. Asymptotic null distribution of these tests is obtained. A simulation study shows that a more general choice of the score function can sometimes result in greater power than the Datta and Satten test; furthermore, this development offers the user a wider choice. We illustrate our tests using a real data example on spinal cord injury patients.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca
Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps ofmore » X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.« less
Hierarchical clustering using correlation metric and spatial continuity constraint
Stork, Christopher L.; Brewer, Luke N.
2012-10-02
Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.
Meltzer, H Y; Matsubara, S; Lee, J C
1989-10-01
The pKi values of 13 reference typical and 7 reference atypical antipsychotic drugs (APDs) for rat striatal dopamine D-1 and D-2 receptor binding sites and cortical serotonin (5-HT2) receptor binding sites were determined. The atypical antipsychotics had significantly lower pKi values for the D-2 but not 5-HT2 binding sites. There was a trend for a lower pKi value for the D-1 binding site for the atypical APD. The 5-HT2 and D-1 pKi values were correlated for the typical APD whereas the 5-HT2 and D-2 pKi values were correlated for the atypical APD. A stepwise discriminant function analysis to determine the independent contribution of each pKi value for a given binding site to the classification as a typical or atypical APD entered the D-2 pKi value first, followed by the 5-HT2 pKi value. The D-1 pKi value was not entered. A discriminant function analysis correctly classified 19 of 20 of these compounds plus 14 of 17 additional test compounds as typical or atypical APD for an overall correct classification rate of 89.2%. The major contributors to the discriminant function were the D-2 and 5-HT2 pKi values. A cluster analysis based only on the 5-HT2/D2 ratio grouped 15 of 17 atypical + one typical APD in one cluster and 19 of 20 typical + two atypical APDs in a second cluster, for an overall correct classification rate of 91.9%. When the stepwise discriminant function was repeated for all 37 compounds, only the D-2 and 5-HT2 pKi values were entered into the discriminant function.(ABSTRACT TRUNCATED AT 250 WORDS)
Optimized Clustering Estimators for BAO Measurements Accounting for Significant Redshift Uncertainty
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ross, Ashley J.; Banik, Nilanjan; Avila, Santiago
2017-05-15
We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the BAO information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertaintymore » $$\\sigma_z \\geq 0.02(1+z)$$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $$\\sigma_z \\geq 0.02(1+z)$$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.« less
Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty
NASA Astrophysics Data System (ADS)
Ross, Ashley J.; Banik, Nilanjan; Avila, Santiago; Percival, Will J.; Dodelson, Scott; Garcia-Bellido, Juan; Crocce, Martin; Elvin-Poole, Jack; Giannantonio, Tommaso; Manera, Marc; Sevilla-Noarbe, Ignacio
2017-12-01
We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line of sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty σz ≥ 0.02(1 + z), we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for σz ≥ 0.02(1 + z). For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 (DES Y1) sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.
NASA Astrophysics Data System (ADS)
Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.
2018-04-01
Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.
Deris, Nadja; Montag, Christian; Reuter, Martin; Weber, Bernd; Markett, Sebastian
2017-02-15
According to Jaak Panksepp's Affective Neuroscience Theory and the derived self-report measure, the Affective Neuroscience Personality Scales (ANPS), differences in the responsiveness of primary emotional systems form the basis of human personality. In order to investigate neuronal correlates of personality, the underlying neuronal circuits of the primary emotional systems were analyzed in the present fMRI-study by associating the ANPS to functional connectivity in the resting brain. N=120 healthy participants were invited for the present study. The results were reinvestigated in an independent, smaller sample of N=52 participants. A seed-based whole brain approach was conducted with seed-regions bilaterally in the basolateral and superficial amygdalae. The selection of seed-regions was based on meta-analytic data on affective processing and the Juelich histological atlas. Multiple regression analyses on the functional connectivity maps revealed associations with the SADNESS-scale in both samples. Functional resting-state connectivity between the left basolateral amygdala and a cluster in the postcentral gyrus, and between the right basolateral amygdala and clusters in the superior parietal lobe and subgyral in the parietal lobe was associated with SADNESS. No other ANPS-scale revealed replicable results. The present findings give first insights into the neuronal basis of the SADNESS-scale of the ANPS and support the idea of underlying neuronal circuits. In combination with previous research on genetic associations of the ANPS functional resting-state connectivity is discussed as a possible endophenotype of personality. Copyright © 2016 Elsevier Inc. All rights reserved.
Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys
NASA Astrophysics Data System (ADS)
Yang, Xiaohu; Mo, H. J.; Jing, Y. P.; van den Bosch, Frank C.; Chu, YaoQuan
2004-06-01
In two recent papers, we developed a powerful technique to link the distribution of galaxies to that of dark matter haloes by considering halo occupation numbers as a function of galaxy luminosity and type. In this paper we use these distribution functions to populate dark matter haloes in high-resolution N-body simulations of the standard ΛCDM cosmology with Ωm= 0.3, ΩΛ= 0.7 and σ8= 0.9. Stacking simulation boxes of 100 h-1 Mpc and 300 h-1 Mpc with 5123 particles each we construct mock galaxy redshift surveys out to a redshift of z= 0.2 with a numerical resolution that guarantees completeness down to 0.01L*. We use these mock surveys to investigate various clustering statistics. The predicted two-dimensional correlation function ξ(rp, π) reveals clear signatures of redshift space distortions. The projected correlation functions for galaxies with different luminosities and types, derived from ξ(rp, π), match the observations well on scales larger than ~3 h-1 Mpc. On smaller scales, however, the model overpredicts the clustering power by about a factor two. Modelling the `finger-of-God' effect on small scales reveals that the standard ΛCDM model predicts pairwise velocity dispersions (PVD) that are ~400 km s-1 too high at projected pair separations of ~1 h-1 Mpc. A strong velocity bias in massive haloes, with bvel≡σgal/σdm~ 0.6 (where σgal and σdm are the velocity dispersions of galaxies and dark matter particles, respectively) can reduce the predicted PVD to the observed level, but does not help to resolve the overprediction of clustering power on small scales. Consistent results can be obtained within the standard ΛCDM model only when the average mass-to-light ratio of clusters is of the order of 1000 (M/L)solar in the B-band. Alternatively, as we show by a simple approximation, a ΛCDM model with σ8~= 0.75 may also reproduce the observational results. We discuss our results in light of the recent WMAP results and the constraints on σ8 obtained independently from other observations.
Patterns of Individual Variation in Visual Pathway Structure and Function in the Sighted and Blind
Datta, Ritobrato; Benson, Noah C.; Prasad, Sashank; Jacobson, Samuel G.; Cideciyan, Artur V.; Bridge, Holly; Watkins, Kate E.; Butt, Omar H.; Dain, Aleksandra S.; Brandes, Lauren; Gennatas, Efstathios D.
2016-01-01
Many structural and functional brain alterations accompany blindness, with substantial individual variation in these effects. In normally sighted people, there is correlated individual variation in some visual pathway structures. Here we examined if the changes in brain anatomy produced by blindness alter the patterns of anatomical variation found in the sighted. We derived eight measures of central visual pathway anatomy from a structural image of the brain from 59 sighted and 53 blind people. These measures showed highly significant differences in mean size between the sighted and blind cohorts. When we examined the measurements across individuals within each group we found three clusters of correlated variation, with V1 surface area and pericalcarine volume linked, and independent of the thickness of V1 cortex. These two clusters were in turn relatively independent of the volumes of the optic chiasm and lateral geniculate nucleus. This same pattern of variation in visual pathway anatomy was found in the sighted and the blind. Anatomical changes within these clusters were graded by the timing of onset of blindness, with those subjects with a post-natal onset of blindness having alterations in brain anatomy that were intermediate to those seen in the sighted and congenitally blind. Many of the blind and sighted subjects also contributed functional MRI measures of cross-modal responses within visual cortex, and a diffusion tensor imaging measure of fractional anisotropy within the optic radiations and the splenium of the corpus callosum. We again found group differences between the blind and sighted in these measures. The previously identified clusters of anatomical variation were also found to be differentially related to these additional measures: across subjects, V1 cortical thickness was related to cross-modal activation, and the volume of the optic chiasm and lateral geniculate was related to fractional anisotropy in the visual pathway. Our findings show that several of the structural and functional effects of blindness may be reduced to a smaller set of dimensions. It also seems that the changes in the brain that accompany blindness are on a continuum with normal variation found in the sighted. PMID:27812129
Yang, Albert C.; Tsai, Shih-Jen; Hong, Chen-Jee; Wang, Cynthia; Chen, Tai-Jui; Liou, Ying-Jay; Peng, Chung-Kang
2011-01-01
Background Genetic polymorphisms in the gene encoding the β-adrenergic receptors (β-AR) have a pivotal role in the functions of the autonomic nervous system. Using heart rate variability (HRV) as an indicator of autonomic function, we present a bottom-up genotype–phenotype analysis to investigate the association between β-AR gene polymorphisms and heart rate dynamics. Methods A total of 221 healthy Han Chinese adults (59 males and 162 females, aged 33.6±10.8 years, range 19 to 63 years) were recruited and genotyped for three common β-AR polymorphisms: β1-AR Ser49Gly, β2-AR Arg16Gly and β2-AR Gln27Glu. Each subject underwent two hours of electrocardiogram monitoring at rest. We applied an information-based similarity (IBS) index to measure the pairwise dissimilarity of heart rate dynamics among study subjects. Results With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype. Furthermore, the non-randomness index, a nonlinear HRV measure derived from the IBS method, was significantly lower in Arg16 homozygotes than in Gly16 carriers. The non-randomness index was negatively correlated with parasympathetic-related HRV variables and positively correlated with those HRV indices reflecting a sympathovagal shift toward sympathetic activity. Conclusions We demonstrate a bottom-up categorization approach combining the IBS method and hierarchical cluster analysis to detect subgroups of subjects with HRV phenotypes associated with β-AR polymorphisms. Our results provide evidence that β2-AR polymorphisms are significantly associated with the acceleration/deceleration pattern of heart rate oscillation, reflecting the underlying mode of autonomic nervous system control. PMID:21573230
Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.
Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra
2016-11-20
The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Estimating life expectancies for US small areas: a regression framework
NASA Astrophysics Data System (ADS)
Congdon, Peter
2014-01-01
Analysis of area mortality variations and estimation of area life tables raise methodological questions relevant to assessing spatial clustering, and socioeconomic inequalities in mortality. Existing small area analyses of US life expectancy variation generally adopt ad hoc amalgamations of counties to alleviate potential instability of mortality rates involved in deriving life tables, and use conventional life table analysis which takes no account of correlated mortality for adjacent areas or ages. The alternative strategy here uses structured random effects methods that recognize correlations between adjacent ages and areas, and allows retention of the original county boundaries. This strategy generalizes to include effects of area category (e.g. poverty status, ethnic mix), allowing estimation of life tables according to area category, and providing additional stabilization of estimated life table functions. This approach is used here to estimate stabilized mortality rates, derive life expectancies in US counties, and assess trends in clustering and in inequality according to county poverty category.
Li, Zheng; Vendrell, Oriol
2016-01-01
The ultrafast nuclear and electronic dynamics of protonated water clusters H+(H2O)n after extreme ultraviolet photoionization is investigated. In particular, we focus on cluster cations with n = 3, 6, and 21. Upon ionization, two positive charges are present in the cluster related to the excess proton and the missing electron, respectively. A correlation is found between the cluster's geometrical conformation and initial electronic energy with the size of the final fragments produced. For situations in which the electron hole and proton are initially spatially close, the two entities become correlated and separate in a time-scale of 20 to 40 fs driven by strong non-adiabatic effects. PMID:26798842
Whistlers observed outside the plasmasphere: Correlation to plasmaspheric/plasmapause features
NASA Astrophysics Data System (ADS)
Adrian, M. L.; Fung, S. F.; Gallagher, D. L.; Green, J. L.
2015-09-01
Whistlers observed outside the plasmasphere by Cluster have been correlated with the global plasmasphere using Imager for Magnetopause-to-Aurora Global Exploration-Extreme Ultraviolet Imager (IMAGE-EUV) observations. Of the 12 Cluster-observed whistler events reported, EUV is able to provide global imaging of the plasmasphere for every event and demonstrates a direct correlation between the detection of lightning-generated whistlers beyond the plasmapause and the presence of a global perturbation of the local plasmapause. Of these 12 correlated events, seven of the Cluster-observed whistlers (or 58%) are associated with the Cluster spacecraft lying radially outward from a plasmaspheric notch. Two of the Cluster-observed whistlers (17%) are associated with the low-density region between the late afternoon plasmapause and the western wall of a plasmaspheric drainage plume. The final three Cluster-observed whistler events (25%) are associated with a nonradial, nonazimuthal depletion in plasmaspheric He+ emission that are termed "notch-like" crenulations. In one of these cases, the notch-like crenulations appear to be manifestations entrained within the plasmasphere boundary layer of a standing wave on the surface of the plasmasphere. The correlated Cluster/IMAGE-EUV observations suggest that the depleted flux tubes that connect the ionosphere to the low-density regions of plasmaspheric trough and inner magnetosphere facilitate the escape of whistler waves from the plasmasphere.
NASA Astrophysics Data System (ADS)
Taira, T.; Kato, A.
2013-12-01
A high-resolution Vp/Vs ratio estimate is one of the key parameters to understand spatial variations of composition and physical state within the Earth. Lin and Shearer (2007, BSSA) recently developed a methodology to obtain local Vp/Vs ratios in individual similar earthquake clusters, based on P- and S-wave differential times. A waveform cross-correlation approach is typically employed to measure those differential times for pairs of seismograms from similar earthquakes clusters, at narrow time windows around the direct P and S waves. This approach effectively collects P- and S-wave differential times and however requires the robust P- and S-wave time windows that are extracted based on either manually or automatically picked P- and S-phases. We present another technique to estimate P- and S-wave differential times by exploiting temporal properties of delayed time as a function of elapsed time on the seismograms with a moving-window cross-correlation analysis (e.g., Snieder, 2002, Phys. Rev. E; Niu et al. 2003, Nature). Our approach is based on the principle that the delayed time for the direct S wave differs from that for the direct P wave. Two seismograms aligned by the direct P waves from a pair of similar earthquakes yield that delayed times become zero around the direct P wave. In contrast, delayed times obtained from time windows including the direct S wave have non-zero value. Our approach, in principle, is capable of measuring both P- and S-wave differential times from single-component seismograms. In an ideal case, the temporal evolution of delayed time becomes a step function with its discontinuity at the onset of the direct S wave. The offset in the resulting step function would be the S-wave differential time, relative to the P-wave differential time as the two waveforms are aligned by the direct P wave. We apply our moving-window cross-correlation technique to the two different data sets collected at: 1) the Wakayama district, Japan and 2) the Geysers geothermal field, California. The both target areas are characterized by earthquake swarms that provide a number of similar events clusters. We use the following automated procedure to systematically analyze the two data sets: 1) the identification of the direct P arrivals by using an Akaike Information Criterion based phase picking algorithm introduced by Zhang and Thurber (2003, BSSA), 2) the waveform alignment by the P-wave with a waveform cross-correlation to obtain P-wave differential time, 3) the moving-time window analysis to estimate the S-differential time. Kato et al. (2010, GRL) have estimated the Vp/Vs ratios for a few similar earthquake clusters from the Wakayama data set, by a conventional approach to obtain differential times. We find that the resulting Vp/Vs ratios from our approach for the same earthquake clusters are comparable with those obtained from Kato et al. (2010, GRL). We show that the moving-window cross-correlation technique effectively measures both P- and S-wave differential times for the seismograms in which the clear P and S phases are not observed. We will show spatial distributions in Vp/Vs ratios in our two target areas.
Personalized Medicine in Veterans with Traumatic Brain Injuries
2013-05-01
Pair-Group Method using Arithmetic averages ( UPGMA ) based on cosine correlation of row mean centered log2 signal values; this was the top 50%-tile...cluster- ing was performed by the UPGMA method using Cosine correlation as the similarity metric. For comparative purposes, clustered heat maps included...non-mTBI cases were subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as the similarity
Personalized Medicine in Veterans with Traumatic Brain Injuries
2014-07-01
9 control cases are subjected to unsupervised hierarchical clustering analysis using the UPGMA algorithm with cosine correlation as the similarity...in unsu- pervised hierarchical clustering by the Un- weighted Pair-Group Method using Arithmetic averages ( UPGMA ) based on cosine correlation of row...of log2 trans- formed MAS5.0 signal values; probe set cluster- ing was performed by the UPGMA method using Cosine correlation as the similarity
Besga, Ariadna; Chyzhyk, Darya; Gonzalez-Ortega, Itxaso; Echeveste, Jon; Graña-Lecuona, Marina; Graña, Manuel; Gonzalez-Pinto, Ana
2017-01-01
Background: Late Onset Bipolar Disorder (LOBD) is the development of Bipolar Disorder (BD) at an age above 50 years old. It is often difficult to differentiate from other aging dementias, such as Alzheimer's Disease (AD), because they share cognitive and behavioral impairment symptoms. Objectives: We look for WM tract voxel clusters showing significant differences when comparing of AD vs. LOBD, and its correlations with systemic blood plasma biomarkers (inflammatory, neurotrophic factors, and oxidative stress). Materials: A sample of healthy controls (HC) ( n = 19), AD patients ( n = 35), and LOBD patients ( n = 24) was recruited at the Alava University Hospital. Blood plasma samples were obtained at recruitment time and analyzed to extract the inflammatory, oxidative stress, and neurotrophic factors. Several modalities of MRI were acquired for each subject, Methods: Fractional anisotropy (FA) coefficients are obtained from diffusion weighted imaging (DWI). Tract based spatial statistics (TBSS) finds FA skeleton clusters of WM tract voxels showing significant differences for all possible contrasts between HC, AD, and LOBD. An ANOVA F -test over all contrasts is carried out. Results of F -test are used to mask TBSS detected clusters for the AD > LOBD and LOBD > AD contrast to select the image clusters used for correlation analysis. Finally, Pearson's correlation coefficients between FA values at cluster sites and systemic blood plasma biomarker values are computed. Results: The TBSS contrasts with by ANOVA F -test has identified strongly significant clusters in the forceps minor, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and cingulum gyrus. The correlation analysis of these tract clusters found strong negative correlation of AD with the nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) blood biomarkers. Negative correlation of AD and positive correlation of LOBD with inflammation biomarker IL6 was also found. Conclusion: TBSS voxel clusters tract atlas localizations are consistent with greater behavioral impairment and mood disorders in LOBD than in AD. Correlation analysis confirms that neurotrophic factors (i.e., NGF, BDNF) play a great role in AD while are absent in LOBD pathophysiology. Also, correlation results of IL1 and IL6 suggest stronger inflammatory effects in LOBD than in AD.
Assessing the role of spatial correlations during collective cell spreading
Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.
2014-01-01
Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987
Density-dependent clustering: I. Pulling back the curtains on motions of the BAO peak
NASA Astrophysics Data System (ADS)
Neyrinck, Mark C.; Szapudi, István; McCullagh, Nuala; Szalay, Alexander S.; Falck, Bridget; Wang, Jie
2018-05-01
The most common statistic used to analyze large-scale structure surveys is the correlation function, or power spectrum. Here, we show how `slicing' the correlation function on local density brings sensitivity to interesting non-Gaussian features in the large-scale structure, such as the expansion or contraction of baryon acoustic oscillations (BAO) according to the local density. The sliced correlation function measures the large-scale flows that smear out the BAO, instead of just correcting them as reconstruction algorithms do. Thus, we expect the sliced correlation function to be useful in constraining the growth factor, and modified gravity theories that involve the local density. Out of the studied cases, we find that the run of the BAO peak location with density is best revealed when slicing on a ˜40 h-1 Mpc filtered density. But slicing on a ˜100 h-1 Mpc filtered density may be most useful in distinguishing between underdense and overdense regions, whose BAO peaks are separated by a substantial ˜5 h-1 Mpc at z = 0. We also introduce `curtain plots' showing how local densities drive particle motions toward or away from each other over the course of an N-body simulation.
Urinary cortisol and psychopathology in obese binge eating subjects.
Lavagnino, Luca; Amianto, Federico; Parasiliti Caprino, Mirko; Maccario, Mauro; Arvat, Emanuela; Ghigo, Ezio; Abbate Daga, Giovanni; Fassino, Secondo
2014-12-01
Investigations on the relationship between obesity, binge eating and the function of hypothalamic-pituitary-adrenal (HPA) axis have led to inconsistent results. General psychopathology affects HPA axis function. The present study aims to examine correlations between binge eating, general psychopathology and HPA axis function in obese binge eaters. Twenty-four hour urinary free cortisol (UFC/24 h) was measured in 71 obese binge eating women. The patients were administered psychometric tests investigating binge eating, psychopathology and clinical variables. The relationship between binge eating, psychopathology and urinary cortisol was investigated, controlling for age and BMI. We found an inverse correlation between UFC/24 h and binge eating, depression, obsessive-compusive symptoms, somatization and sensitivity. In a regression model a significant inverse correlation between urinary cortisol and psychopathology was confirmed. Urinary cortisol levels in obese patients with binge eating disorder show an inverse correlation with several dimensions of psychopathology which are considered to be typical of a cluster of psychiatric disorders characterized by low HPA axis function, and are very common in obese binge eating patients. If these results are confirmed, UFC/24 h might be considered a biomarker of psychopathology in obese binge eaters. Copyright © 2014 Elsevier Ltd. All rights reserved.
Collective transport for active matter run-and-tumble disk systems on a traveling-wave substrate
Sándor, Csand; Libál, Andras; Reichhardt, Charles; ...
2017-01-17
Here, we examine numerically the transport of an assembly of active run-and-tumble disks interacting with a traveling-wave substrate. We show that as a function of substrate strength, wave speed, disk activity, and disk density, a variety of dynamical phases arise that are correlated with the structure and net flux of disks. We find that there is a sharp transition into a state in which the disks are only partially coupled to the substrate and form a phase-separated cluster state. This transition is associated with a drop in the net disk flux, and it can occur as a function of themore » substrate speed, maximum substrate force, disk run time, and disk density. Since variation of the disk activity parameters produces different disk drift rates for a fixed traveling-wave speed on the substrate, the system we consider could be used as an efficient method for active matter species separation. Within the cluster phase, we find that in some regimes the motion of the cluster center of mass is in the opposite direction to that of the traveling wave, while when the maximum substrate force is increased, the cluster drifts in the direction of the traveling wave. This suggests that swarming or clustering motion can serve as a method by which an active system can collectively move against an external drift.« less
Collective transport for active matter run-and-tumble disk systems on a traveling-wave substrate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sándor, Csand; Libál, Andras; Reichhardt, Charles
Here, we examine numerically the transport of an assembly of active run-and-tumble disks interacting with a traveling-wave substrate. We show that as a function of substrate strength, wave speed, disk activity, and disk density, a variety of dynamical phases arise that are correlated with the structure and net flux of disks. We find that there is a sharp transition into a state in which the disks are only partially coupled to the substrate and form a phase-separated cluster state. This transition is associated with a drop in the net disk flux, and it can occur as a function of themore » substrate speed, maximum substrate force, disk run time, and disk density. Since variation of the disk activity parameters produces different disk drift rates for a fixed traveling-wave speed on the substrate, the system we consider could be used as an efficient method for active matter species separation. Within the cluster phase, we find that in some regimes the motion of the cluster center of mass is in the opposite direction to that of the traveling wave, while when the maximum substrate force is increased, the cluster drifts in the direction of the traveling wave. This suggests that swarming or clustering motion can serve as a method by which an active system can collectively move against an external drift.« less
Manoharan, Sujatha C; Ramakrishnan, Swaminathan
2009-10-01
In this work, prediction of forced expiratory volume in pulmonary function test, carried out using spirometry and neural networks is presented. The pulmonary function data were recorded from volunteers using commercial available flow volume spirometer in standard acquisition protocol. The Radial Basis Function neural networks were used to predict forced expiratory volume in 1 s (FEV1) from the recorded flow volume curves. The optimal centres of the hidden layer of radial basis function were determined by k-means clustering algorithm. The performance of the neural network model was evaluated by computing their prediction error statistics of average value, standard deviation, root mean square and their correlation with the true data for normal, restrictive and obstructive cases. Results show that the adopted neural networks are capable of predicting FEV1 in both normal and abnormal cases. Prediction accuracy was more in obstructive abnormality when compared to restrictive cases. It appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.
NASA Technical Reports Server (NTRS)
Lightman, A. P.; Grindlay, J. E.
1982-01-01
Globular clusters are thought to be among the oldest objects in the Galaxy, and provide, in this connection, important clues for determining the age and process of formation of the Galaxy. The present investigation is concerned with puzzles relating to the X-ray emission of globular clusters, taking into account questions regarding the location of X-ray emitting clusters (XEGC) unusually near the galactic plane and/or galactic center. An adopted model is discussed for the nature, formation, and lifetime of X-ray sources in globular clusters. An analysis of the available data is conducted in connection with a search for correlations between binary formation time scales, central relaxation times, galactic locations, and X-ray emission. The positive correlation found between distance from galactic center and two-body binary formation time for globular clusters, explanations for this correlation, and the hypothesis that X-ray sources in globular clusters require binary star systems provide a possible explanation of the considered puzzles.
Heterogeneous dynamics of ionic liquids: A four-point time correlation function approach
NASA Astrophysics Data System (ADS)
Liu, Jiannan; Willcox, Jon A. L.; Kim, Hyung J.
2018-05-01
Many ionic liquids show behavior similar to that of glassy systems, e.g., large and long-lasted deviations from Gaussian dynamics and clustering of "mobile" and "immobile" groups of ions. Herein a time-dependent four-point density correlation function—typically used to characterize glassy systems—is implemented for the ionic liquids, choline acetate, and 1-butyl-3-methylimidazolium acetate. Dynamic correlation beyond the first ionic solvation shell on the time scale of nanoseconds is found in the ionic liquids, revealing the cooperative nature of ion motions. The traditional solvent, acetonitrile, on the other hand, shows a much shorter length-scale that decays after a few picoseconds.
Aspects of Scale Invariance in Physics and Biology
NASA Astrophysics Data System (ADS)
Alba, Vasyl
We study three systems that have scale invariance. The first system is a conformal field theory in d > 3 dimensions. We prove that if there is a unique stress-energy tensor and at least one higher-spin conserved current in the theory, then the correlation functions of the stress-energy tensors and the conserved currents of higher-spin must coincide with one of the following possibilities: a) a theory of n free bosons, b) a theory of n free fermions or c) a theory of n (d-2)/2-forms. The second system is the primordial gravitational wave background in a theory with inflation. We show that the scale invariant spectrum of primordial gravitational waves is isotropic only in the zero-order approximation, and it gets a small correction due to the primordial scalar fluctuations. When anisotropy is measured experimentally, our result will allow us to distinguish between different inflationary models. The third system is a biological system. The question we are asking is whether there is some simplicity or universality underlying the complexities of natural animal behavior. We use the walking fruit fly (Drosophila melanogaster) as a model system. Based on the result that unsupervised flies' behaviors can be categorized into one hundred twenty-two discrete states (stereotyped movements), which all individuals from a single species visit repeatedly, we demonstrated that the sequences of states are strongly non-Markovian. In particular, correlations persist for an order of magnitude longer than expected from a model of random state-to-state transitions. The correlation function has a power-law decay, which is a hint of some kind of criticality in the system. We develop a generalization of the information bottleneck method that allows us to cluster these states into a small number of clusters. This more compact description preserves a lot of temporal correlation. We found that it is enough to use a two-cluster representation of the data to capture long-range correlations, which opens a way for a more quantitative description of the system. Usage of the maximal entropy method allowed us to find a description that closely resembles a famous inverse-square Ising model in 1d in a small magnetic field.
Concerted hydrogen atom exchange between three HF molecules
NASA Technical Reports Server (NTRS)
Komornicki, Andrew; Dixon, David A.; Taylor, Peter R.
1992-01-01
We have investigated the termolecular reaction involving concerted hydrogen exchange between three HF molecules, with particular emphasis on the effects of correlation at the various stationary points along the reaction. Using an extended basis, we have located the geometries of the stable hydrogen-bonded trimer, which is of C(sub 3h) symmetry, and the transition state for hydrogen exchange, which is of D(sub 3h) symmetry. The energies of the exchange reation were then evaluated at the correlated level, using a large atomic natural orbital basis and correlating all valence electrons. Several correlation treatments were used, namely, configration interaction with single and double excitations, coupled-pair functional, and coupled-cluster methods. We are thus able to measure the effect of accounting for size-extensivity. Zero-point corrections to the correlated level energetics were determined using analytic second derivative techniques at the SCF level. Our best calculations, which include the effects of connected triple excitations in the coupled-cluster procedure, indicate that the trimer is bound by 9 +/- 1 kcal/mol relative to three separate monomers, in excellent agreement with previous estimates. The barrier to concerted hydrogen exchange is 15 kcal/mol above the trimer, or only 4.7 kcal/mol above three separated monomers. Thus the barrier to hydrogen exchange between HF molecules via this termolecular process is very low.
Hou, Liyuan; Yang, Jucai; Liu, Yuming
2017-04-01
The structures and properties of Ho-doped Si clusters, including their adiabatic electron affinities (AEAs), simulated photoelectron spectra (PESs), stabilities, magnetic moments, and charge-transfer characteristics, were systematically investigated using four density-functional methods. The results show that the double-hybrid functional (which includes an MP2 correlation component) can accurately predict the ground-state structure and properties of Ho-doped Si clusters. The ground-state structures of HoSi n (n = 3-9) are sextuplet electronic states. The structures of these Ho-doped Si clusters (aside from HoSi 7 ) are substitutional. The ground-state structures of HoSi n - are quintuplet electronic states. Their predicted AEAs are in excellent agreement with the experimental ones. The mean absolute error in the theoretical AEAs of HoSi n (n = 4-9) is only 0.04 eV. The simulated PESs for HoSi n - (n = 5-9) are in good agreement with the experimental PESs. Based on its simulated PES and theoretical AEA, we reassigned the experimental PES of HoSi 4 - and obtained an experimental AEA of 2.2 ± 0.1 eV. The dissociation energies of Ho from HoSi n and HoSi n - (n = 3-9) were evaluated to test the relative stabilities of the clusters. HOMO-LUMO gap analysis indicated that doping the Si clusters with the rare-earth metal atom significantly increases their photochemical reactivity. Natural population analysis showed that the magnetic moments of HoSi n (n = 3-9) and their anions derive mainly from the Ho atom. It was also found that the magnetic moments of Ho in the HoSi n clusters are larger than the magnetic moment of an isolated Ho atom.
Bryantsev, Vyacheslav S; Diallo, Mamadou S; van Duin, Adri C T; Goddard, William A
2009-04-14
In this paper we assess the accuracy of the B3LYP, X3LYP, and newly developed M06-L, M06-2X, and M06 functionals to predict the binding energies of neutral and charged water clusters including (H2O)n, n = 2-8, 20), H3O(+)(H2O)n, n = 1-6, and OH(-)(H2O)n, n = 1-6. We also compare the predicted energies of two ion hydration and neutralization reactions on the basis of the calculated binding energies. In all cases, we use as benchmarks calculated binding energies of water clusters extrapolated to the complete basis set limit of the second-order Møller-Plesset perturbation theory with the effects of higher order correlation estimated at the coupled-cluster theory with single, double, and perturbative triple excitations in the aug-cc-pVDZ basis set. We rank the accuracy of the functionals on the basis of the mean unsigned error (MUE) between calculated benchmark and density functional theory energies. The corresponding MUE (kcal/mol) for each functional is listed in parentheses. We find that M06-L (0.73) and M06 (0.84) give the most accurate binding energies using very extended basis sets such as aug-cc-pV5Z. For more affordable basis sets, the best methods for predicting the binding energies of water clusters are M06-L/aug-cc-pVTZ (1.24), B3LYP/6-311++G(2d,2p) (1.29), and M06/aug-cc-PVTZ (1.33). M06-L/aug-cc-pVTZ also gives more accurate energies for the neutralization reactions (1.38), whereas B3LYP/6-311++G(2d,2p) gives more accurate energies for the ion hydration reactions (1.69).
Two-cluster structure of some alpha-scattering resonances in the sd shell
DOE Office of Scientific and Technical Information (OSTI.GOV)
Budzanowski, A.; Grotowski, K.; Strzalkowski, A.
1975-01-01
The excitation functions of the elastic scattering of alpha particles at backward angles on $sup 24$Mg and $sup 28$Si nuclei in the energy range from 23 to 28 MeV measured by Bobrowska et al. exhibit distinct maxima. It was shown that these maxima are not correlated with the structures seen in the excitation functions of the ($alpha$,$alpha$') and ($alpha$,p) reactions leading to low- lying excited states of the final nucleus possibly indicating the presence of Ericson fluctuations. (auth)
Wang, Chao; Wu, Huawang; Chen, Fangfang; Xu, Jinping; Li, Hongming; Li, Hong; Wang, Jiaojian
2018-07-01
Major depressive disorder (MDD) is characterized by impairments in emotional and cognitive functions. Emerging studies have shown that cognition and emotion interact by reaching identical brain regions, and the insula is one such region with functional and structural heterogeneity. Although previous literatures have shown the role of insula in MDD,it remains unclear whether the insular subregions show differential change patterns in MDD. Using the resting-state fMRI data in a group of 23 drug-free MDD patients and 34 healthy controls (HCs), we investigated whether the abnormal connectivity patterns of insular sub-regions or any behavioural correlates can be detected in MDD. Further hierarchical cluster analysis was used to identify the functional connectivity-clustering patterns of insular sub-regions. Compared with HCs, the MDD exhibited higher connectivities between dorsal agranular insula and inferior parietal lobule and between ventral dysgranular and granular insula and thalamus/habehula, and lower connectivity of hypergranular insula to subgenual anterior cingulate cortex. Moreover, the three subregions with significant group differences were in three separate functional systems along anterior-to-posteior gradient. The anterior and middle insula showed positive correlation with depressive severity, while the posterior insular was to the contrary. The small and unbalanced sample size, only included moderate and severe depression and the possible inter-individual differences may limit the interpretability. These findings provided evidences for the MDD-related effects in functional connectivity patterns of insular subregions, and revealed that the subregions might be involved in different neural circuits associated with the contrary impacts on the depressive symptoms. Copyright © 2017 Elsevier B.V. All rights reserved.
The mass-ratio and eccentricity distributions of barium and S stars, and red giants in open clusters
NASA Astrophysics Data System (ADS)
Van der Swaelmen, M.; Boffin, H. M. J.; Jorissen, A.; Van Eck, S.
2017-01-01
Context. A complete set of orbital parameters for barium stars, including the longest orbits, has recently been obtained thanks to a radial-velocity monitoring with the HERMES spectrograph installed on the Flemish Mercator telescope. Barium stars are supposed to belong to post-mass-transfer systems. Aims: In order to identify diagnostics distinguishing between pre- and post-mass-transfer systems, the properties of barium stars (more precisely their mass-function distribution and their period-eccentricity (P-e) diagram) are compared to those of binary red giants in open clusters. As a side product, we aim to identify possible post-mass-transfer systems among the cluster giants from the presence of s-process overabundances. We investigate the relation between the s-process enrichment, the location in the (P-e) diagram, and the cluster metallicity and turn-off mass. Methods: To invert the mass-function distribution and derive the mass-ratio distribution, we used the method pioneered by Boffin et al. (1992) that relies on a Richardson-Lucy deconvolution algorithm. The derivation of s-process abundances in the open-cluster giants was performed through spectral synthesis with MARCS model atmospheres. Results: A fraction of 22% of post-mass-transfer systems is found among the cluster binary giants (with companion masses between 0.58 and 0.87 M⊙, typical for white dwarfs), and these systems occupy a wider area than barium stars in the (P-e) diagram. Barium stars have on average lower eccentricities at a given orbital period. When the sample of binary giant stars in clusters is restricted to the subsample of systems occupying the same locus as the barium stars in the (P-e) diagram, and with a mass function compatible with a WD companion, 33% (=4/12) show a chemical signature of mass transfer in the form of s-process overabundances (from rather moderate - about 0.3 dex - to more extreme - about 1 dex). The only strong barium star in our sample is found in the cluster with the lowest metallicity in the sample (I.e. star 173 in NGC 2420, with [Fe/H] = -0.26), whereas the barium stars with mild s-process abundance anomalies (from 0.25 to 0.6 dex) are found in the clusters with slightly subsolar metallicities. Our finding confirms the classical prediction that the s-process nucleosynthesis is more efficient at low metallicities, since the s-process overabundance is not clearly correlated with the cluster turn-off (TO) mass; such a correlation would instead hint at the importance of the dilution factor. We also find a mild barium star in NGC 2335, a cluster with a large TO mass of 4.3 M⊙, which implies that asymptotic giant branch stars that massive still operate the s-process and the third dredge-up. Based on observations made with the Mercator Telescope, operated on the island of La Palma by the Flemish Community, at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias, and on observations made with the HARPS spectrograph installed on the 3.6 m telescope at the European Southern Observatory.
Connecting optical and X-ray tracers of galaxy cluster relaxation
NASA Astrophysics Data System (ADS)
Roberts, Ian D.; Parker, Laura C.; Hlavacek-Larrondo, Julie
2018-04-01
Substantial effort has been devoted in determining the ideal proxy for quantifying the morphology of the hot intracluster medium in clusters of galaxies. These proxies, based on X-ray emission, typically require expensive, high-quality X-ray observations making them difficult to apply to large surveys of groups and clusters. Here, we compare optical relaxation proxies with X-ray asymmetries and centroid shifts for a sample of Sloan Digital Sky Survey clusters with high-quality, archival X-ray data from Chandra and XMM-Newton. The three optical relaxation measures considered are the shape of the member-galaxy projected velocity distribution - measured by the Anderson-Darling (AD) statistic, the stellar mass gap between the most-massive and second-most-massive cluster galaxy, and the offset between the most-massive galaxy (MMG) position and the luminosity-weighted cluster centre. The AD statistic and stellar mass gap correlate significantly with X-ray relaxation proxies, with the AD statistic being the stronger correlator. Conversely, we find no evidence for a correlation between X-ray asymmetry or centroid shift and the MMG offset. High-mass clusters (Mhalo > 1014.5 M⊙) in this sample have X-ray asymmetries, centroid shifts, and Anderson-Darling statistics which are systematically larger than for low-mass systems. Finally, considering the dichotomy of Gaussian and non-Gaussian clusters (measured by the AD test), we show that the probability of being a non-Gaussian cluster correlates significantly with X-ray asymmetry but only shows a marginal correlation with centroid shift. These results confirm the shape of the radial velocity distribution as a useful proxy for cluster relaxation, which can then be applied to large redshift surveys lacking extensive X-ray coverage.
Cluster size selectivity in the product distribution of ethene dehydrogenation on niobium clusters.
Parnis, J Mark; Escobar-Cabrera, Eric; Thompson, Matthew G K; Jacula, J Paul; Lafleur, Rick D; Guevara-García, Alfredo; Martínez, Ana; Rayner, David M
2005-08-18
Ethene reactions with niobium atoms and clusters containing up to 25 constituent atoms have been studied in a fast-flow metal cluster reactor. The clusters react with ethene at about the gas-kinetic collision rate, indicating a barrierless association process as the cluster removal step. Exceptions are Nb8 and Nb10, for which a significantly diminished rate is observed, reflecting some cluster size selectivity. Analysis of the experimental primary product masses indicates dehydrogenation of ethene for all clusters save Nb10, yielding either Nb(n)C2H2 or Nb(n)C2. Over the range Nb-Nb6, the extent of dehydrogenation increases with cluster size, then decreases for larger clusters. For many clusters, secondary and tertiary product masses are also observed, showing varying degrees of dehydrogenation corresponding to net addition of C2H4, C2H2, or C2. With Nb atoms and several small clusters, formal addition of at least six ethene molecules is observed, suggesting a polymerization process may be active. Kinetic analysis of the Nb atom and several Nb(n) cluster reactions with ethene shows that the process is consistent with sequential addition of ethene units at rates corresponding approximately to the gas-kinetic collision frequency for several consecutive reacting ethene molecules. Some variation in the rate of ethene pick up is found, which likely reflects small energy barriers or steric constraints associated with individual mechanistic steps. Density functional calculations of structures of Nb clusters up to Nb(6), and the reaction products Nb(n)C2H2 and Nb(n)C2 (n = 1...6) are presented. Investigation of the thermochemistry for the dehydrogenation of ethene to form molecular hydrogen, for the Nb atom and clusters up to Nb6, demonstrates that the exergonicity of the formation of Nb(n)C2 species increases with cluster size over this range, which supports the proposal that the extent of dehydrogenation is determined primarily by thermodynamic constraints. Analysis of the structural variations present in the cluster species studied shows an increase in C-H bond lengths with cluster size that closely correlates with the increased thermodynamic drive to full dehydrogenation. This correlation strongly suggests that all steps in the reaction are barrierless, and that weakening of the C-H bonds is directly reflected in the thermodynamics of the overall dehydrogenation process. It is also demonstrated that reaction exergonicity in the initial partial dehydrogenation step must be carried through as excess internal energy into the second dehydrogenation step.
NASA Astrophysics Data System (ADS)
Fricke, Daniel
2012-12-01
We analyze the correlations in patterns of trading for members of the Italian interbank trading platform e-MID. The trading strategy of a particular member institution is defined as the sequence of (intra-) daily net trading volumes within a certain semester. Based on this definition, we show that there are significant and persistent bilateral correlations between institutions’ trading strategies. In most semesters we find two clusters, with positively (negatively) correlated trading strategies within (between) clusters. We show that the two clusters mostly contain continuous net buyers and net sellers of money, respectively, and that cluster memberships of individual banks are highly persistent. Additionally, we highlight some problems related to our definition of trading strategies. Our findings add further evidence on the fact that preferential lending relationships on the micro-level lead to community structure on the macro-level.
NASA Astrophysics Data System (ADS)
Majumder, Chiranjib; Kulshreshtha, S. K.
2004-12-01
Structural and electronic properties of metal-doped silicon clusters ( MSi10 , M=Li , Be, B, C, Na, Mg, Al, and Si) have been investigated via ab initio molecular dynamics simulation under the formalism of the density functional theory. The exchange-correlation energy has been calculated using the generalized gradient approximation method. Several stable isomers of MSi10 clusters have been identified based on different initial configurations and their relative stabilities have been analyzed. From the results it is revealed that the location of the impurity atom depends on the nature of interaction between the impurity atom and the host cluster and the size of the impurty atom. Whereas Be and B atoms form stable isomers, the impurity atom being placed at the center of the bicapped tetragonal antiprism structure of the Si10 cluster, all other elements diffuse outside the cage of Si10 cluster. Further, to understand the stability and the chemical bonding, the LCAO-MO based all electron calculations have been carried out for the lowest energy isomers using the hybrid B3LYP energy functional. Based on the interaction energy of the M atoms with Si10 clusters it is found that p-p interaction dominates over the s-p interaction and smaller size atoms interact more strongly. Based on the binding energy, the relative stability of MSi10 clusters is found to follow the order of CSi10>BSi10>BeSi10>Si11>AlSi10>LiSi10>NaSi10>MgSi10 , leading one to infer that while the substitution of C, B and Be enhances the stability of the Si11 cluster, others have an opposite effect. The extra stability of the BeSi10 clusters is due to its encapsulated close packed structure and large energy gap between the HOMO and LUMO energy levels.
NASA Technical Reports Server (NTRS)
Cen, R. Y.; Ostriker, J. P.; Spergel, D. N.; Turok, N.
1991-01-01
Hydrodynamical simulations of galaxy formation in a texture-seeded cosmology are presented, with attention given to Omega = 1 galaxies dominated by both hot dark matter (HDM) and cold dark matter (CDM). The simulations include both gravitational and hydrodynamical physics with a detailed treatment of collisional and radiative thermal processes, and use a cooling criterion to estimate galaxy formation. Background radiation fields and Zel'dovich-Sunyaev fluctuations are explicitly computed. The derived galaxy mass function is well fitted by the observed Schechter luminosity function for a baryonic M/L of 3 and total M/L of 60 in galaxies. In both HDM and CDM texture scenarios, the 'galaxies' and 'clusters' are significantly more strongly correlated than the dark matter due to physical bias processes. The slope of the correlation function in both cases is consistent with observations. In contrast to Gaussian models, peaks in the dark matter density distributrion are less correlated than average.
Spectra of random networks in the weak clustering regime
NASA Astrophysics Data System (ADS)
Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen; Rodrigues, Francisco A.
2018-03-01
The asymptotic behavior of dynamical processes in networks can be expressed as a function of spectral properties of the corresponding adjacency and Laplacian matrices. Although many theoretical results are known for the spectra of traditional configuration models, networks generated through these models fail to describe many topological features of real-world networks, in particular non-null values of the clustering coefficient. Here we study effects of cycles of order three (triangles) in network spectra. By using recent advances in random matrix theory, we determine the spectral distribution of the network adjacency matrix as a function of the average number of triangles attached to each node for networks without modular structure and degree-degree correlations. Implications to network dynamics are discussed. Our findings can shed light in the study of how particular kinds of subgraphs influence network dynamics.
Excitonic Order and Superconductivity in the Two-Orbital Hubbard Model: Variational Cluster Approach
NASA Astrophysics Data System (ADS)
Fujiuchi, Ryo; Sugimoto, Koudai; Ohta, Yukinori
2018-06-01
Using the variational cluster approach based on the self-energy functional theory, we study the possible occurrence of excitonic order and superconductivity in the two-orbital Hubbard model with intra- and inter-orbital Coulomb interactions. It is known that an antiferromagnetic Mott insulator state appears in the regime of strong intra-orbital interaction, a band insulator state appears in the regime of strong inter-orbital interaction, and an excitonic insulator state appears between them. In addition to these states, we find that the s±-wave superconducting state appears in the small-correlation regime, and the dx2 - y2-wave superconducting state appears on the boundary of the antiferromagnetic Mott insulator state. We calculate the single-particle spectral function of the model and compare the band gap formation due to the superconducting and excitonic orders.
A taxonomy of epithelial human cancer and their metastases
2009-01-01
Background Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination. Methods We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures. Results Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination. Conclusion Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile. PMID:20017941
Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation
Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.
2016-01-01
Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038
Accretion-induced luminosity spreads in young clusters: evidence from stellar rotation
NASA Astrophysics Data System (ADS)
Littlefair, S. P.; Naylor, Tim; Mayne, N. J.; Saunders, Eric; Jeffries, R. D.
2011-05-01
We present an analysis of the rotation of young stars in the associations Cepheus OB3b, NGC 2264, 2362 and the Orion Nebula Cluster (ONC). We discover a correlation between rotation rate and position in a colour-magnitude diagram (CMD) such that stars which lie above an empirically determined median pre-main sequence rotate more rapidly than stars which lie below this sequence. The same correlation is seen, with a high degree of statistical significance, in each association studied here. If position within the CMD is interpreted as being due to genuine age spreads within a cluster, then the stars above the median pre-main sequence would be the youngest stars. This would in turn imply that the most rapidly rotating stars in an association are the youngest, and hence those with the largest moments of inertia and highest likelihood of ongoing accretion. Such a result does not fit naturally into the existing picture of angular momentum evolution in young stars, where the stars are braked effectively by their accretion discs until the disc disperses. Instead, we argue that, for a given association of young stars, position within the CMD is not primarily a function of age, but of accretion history. We show that this hypothesis could explain the correlation we observe between rotation rate and position within the CMD.
NASA Astrophysics Data System (ADS)
He, Wanqiu; Akiyama, Masayuki; Bosch, James; Enoki, Motohiro; Harikane, Yuichi; Ikeda, Hiroyuki; Kashikawa, Nobunari; Kawaguchi, Toshihiro; Komiyama, Yutaka; Lee, Chien-Hsiu; Matsuoka, Yoshiki; Miyazaki, Satoshi; Nagao, Tohru; Nagashima, Masahiro; Niida, Mana; Nishizawa, Atsushi J.; Oguri, Masamune; Onoue, Masafusa; Oogi, Taira; Ouchi, Masami; Schulze, Andreas; Shirasaki, Yuji; Silverman, John D.; Tanaka, Manobu M.; Tanaka, Masayuki; Toba, Yoshiki; Uchiyama, Hisakazu; Yamashita, Takuji
2018-01-01
We examine the clustering of quasars over a wide luminosity range, by utilizing 901 quasars at \\overline{z}_phot˜ 3.8 with -24.73 < M1450 < -22.23 photometrically selected from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) S16A Wide2 date release and 342 more luminous quasars at 3.4 < zspec < 4.6 with -28.0 < M1450 < -23.95 from the Sloan Digital Sky Survey that fall in the HSC survey fields. We measure the bias factors of two quasar samples by evaluating the cross-correlation functions (CCFs) between the quasar samples and 25790 bright z ˜ 4 Lyman break galaxies in M1450 < -21.25 photometrically selected from the HSC dataset. Over an angular scale of 10.0" to 1000.0", the bias factors are 5.93+1.34-1.43 and 2.73+2.44-2.55 for the low- and high-luminosity quasars, respectively, indicating no significant luminosity dependence of quasar clustering at z ˜ 4. It is noted that the bias factor of the luminous quasars estimated by the CCF is smaller than that estimated by the auto-correlation function over a similar redshift range, especially on scales below 40.0". Moreover, the bias factor of the less-luminous quasars implies the minimal mass of their host dark matter halos is 0.3-2 × 1012 h-1 M⊙, corresponding to a quasar duty cycle of 0.001-0.06.
Oh, Sang Young; Lee, Minho; Seo, Joon Beom; Kim, Namkug; Lee, Sang Min; Lee, Jae Seung; Oh, Yeon Mok
2017-01-01
A novel approach of size-based emphysema clustering has been developed, and the size variation and collapse of holes in emphysema clusters are evaluated at inspiratory and expiratory computed tomography (CT). Thirty patients were visually evaluated for the size-based emphysema clustering technique and a total of 72 patients were evaluated for analyzing collapse of the emphysema hole in this study. A new approach for the size differentiation of emphysema holes was developed using the length scale, Gaussian low-pass filtering, and iteration approach. Then, the volumetric CT results of the emphysema patients were analyzed using the new method, and deformable registration was carried out between inspiratory and expiratory CT. Blind visual evaluations of EI by two readers had significant correlations with the classification using the size-based emphysema clustering method ( r -values of reader 1: 0.186, 0.890, 0.915, and 0.941; reader 2: 0.540, 0.667, 0.919, and 0.942). The results of collapse of emphysema holes using deformable registration were compared with the pulmonary function test (PFT) parameters using the Pearson's correlation test. The mean extents of low-attenuation area (LAA), E1 (<1.5 mm), E2 (<7 mm), E3 (<15 mm), and E4 (≥15 mm) were 25.9%, 3.0%, 11.4%, 7.6%, and 3.9%, respectively, at the inspiratory CT, and 15.3%, 1.4%, 6.9%, 4.3%, and 2.6%, respectively at the expiratory CT. The extents of LAA, E2, E3, and E4 were found to be significantly correlated with the PFT parameters ( r =-0.53, -0.43, -0.48, and -0.25), with forced expiratory volume in 1 second (FEV 1 ; -0.81, -0.62, -0.75, and -0.40), and with diffusing capacity of the lungs for carbon monoxide (cDLco), respectively. The fraction of emphysema that shifted to the smaller subgroup showed a significant correlation with FEV 1 , cDLco, forced expiratory flow at 25%-75% of forced vital capacity, and residual volume (RV)/total lung capacity ( r =0.56, 0.73, 0.40, and -0.58). A detailed assessment of the size variation and collapse of emphysema holes may be useful for understanding the dynamic collapse of emphysema and its functional relation.
Vibrational properties of gold nanoparticles obtained by green synthesis
NASA Astrophysics Data System (ADS)
Alvarez, Ramón A. B.; Cortez-Valadez, M.; Bueno, L. Oscar Neira; Britto Hurtado, R.; Rocha-Rocha, O.; Delgado-Beleño, Y.; Martinez-Nuñez, C. E.; Serrano-Corrales, Luis Ivan; Arizpe-Chávez, H.; Flores-Acosta, M.
2016-10-01
This study reports the synthesis and characterization of gold nanoparticles through an ecological method to obtain nanostructures from the extract of the plant Opuntia ficus-indica. Colloidal nanoparticles show sizes that vary between 10-20 nm, and present various geometric morphologies. The samples were characterized through optical absorption, Raman Spectroscopy and Transmission Electron Microscopy (TEM). Additionally, low energy metallic clusters of Aun (n=2-20 atoms) were modeled by computational quantum chemistry. The theoretical results were obtained with Density Functional Theory (DFT). The predicted results of Au clusters show a tendency and are correlated with the experimental results concerning the optical absorption bands and Raman spectroscopy in gold nanoparticles.
A method for analyzing clustered interval-censored data based on Cox's model.
Kor, Chew-Teng; Cheng, Kuang-Fu; Chen, Yi-Hau
2013-02-28
Methods for analyzing interval-censored data are well established. Unfortunately, these methods are inappropriate for the studies with correlated data. In this paper, we focus on developing a method for analyzing clustered interval-censored data. Our method is based on Cox's proportional hazard model with piecewise-constant baseline hazard function. The correlation structure of the data can be modeled by using Clayton's copula or independence model with proper adjustment in the covariance estimation. We establish estimating equations for the regression parameters and baseline hazards (and a parameter in copula) simultaneously. Simulation results confirm that the point estimators follow a multivariate normal distribution, and our proposed variance estimations are reliable. In particular, we found that the approach with independence model worked well even when the true correlation model was derived from Clayton's copula. We applied our method to a family-based cohort study of pandemic H1N1 influenza in Taiwan during 2009-2010. Using the proposed method, we investigate the impact of vaccination and family contacts on the incidence of pH1N1 influenza. Copyright © 2012 John Wiley & Sons, Ltd.
Multilevel covariance regression with correlated random effects in the mean and variance structure.
Quintero, Adrian; Lesaffre, Emmanuel
2017-09-01
Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik
2013-01-01
Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zheng; Vendrell, Oriol
2016-01-13
The ultrafast nuclear and electronic dynamics of protonated water clusters H+(H2O)n after extreme ultraviolet photoionization is investigated. In particular, we focus on cluster cations with n = 3, 6, and 21. Upon ionization, two positive charges are present in the cluster related to the excess proton and the missing electron, respectively. A correlation is found between the cluster's geometrical conformation and initial electronic energy with the size of the final fragments produced. As a result, for situations in which the electron hole and proton are initially spatially close, the two entities become correlated and separate in a time-scale of 20more » to 40 fs driven by strong non-adiabatic effects.« less
Global hybrids from the semiclassical atom theory satisfying the local density linear response.
Fabiano, Eduardo; Constantin, Lucian A; Cortona, Pietro; Della Sala, Fabio
2015-01-13
We propose global hybrid approximations of the exchange-correlation (XC) energy functional which reproduce well the modified fourth-order gradient expansion of the exchange energy in the semiclassical limit of many-electron neutral atoms and recover the full local density approximation (LDA) linear response. These XC functionals represent the hybrid versions of the APBE functional [Phys. Rev. Lett. 2011, 106, 186406] yet employing an additional correlation functional which uses the localization concept of the correlation energy density to improve the compatibility with the Hartree-Fock exchange as well as the coupling-constant-resolved XC potential energy. Broad energetic and structural testing, including thermochemistry and geometry, transition metal complexes, noncovalent interactions, gold clusters and small gold-molecule interfaces, as well as an analysis of the hybrid parameters, show that our construction is quite robust. In particular, our testing shows that the resulting hybrid, including 20% of Hartree-Fock exchange and named hAPBE, performs remarkably well for a broad palette of systems and properties, being generally better than popular hybrids (PBE0 and B3LYP). Semiempirical dispersion corrections are also provided.
Broca’s area network in language function: a pooling-data connectivity study
Bernal, Byron; Ardila, Alfredo; Rosselli, Monica
2015-01-01
Background and Objective: Modern neuroimaging developments have demonstrated that cognitive functions correlate with brain networks rather than specific areas. The purpose of this paper was to analyze the connectivity of Broca’s area based on language tasks. Methods: A connectivity modeling study was performed by pooling data of Broca’s activation in language tasks. Fifty-seven papers that included 883 subjects in 84 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the map; thresholds at p < 0.01 were corrected for multiple comparisons and false discovery rate. Resulting images were co-registered into MNI standard space. Results: A network consisting of 16 clusters of activation was obtained. Main clusters were located in the frontal operculum, left posterior temporal region, supplementary motor area, and the parietal lobe. Less common clusters were seen in the sub-cortical structures including the left thalamus, left putamen, secondary visual areas, and the right cerebellum. Conclusion: Broca’s area-44-related networks involved in language processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation, and limitations of the results are discussed. PMID:26074842
Fermi liquid, clustering, and structure factor in dilute warm nuclear matter
NASA Astrophysics Data System (ADS)
Röpke, G.; Voskresensky, D. N.; Kryukov, I. A.; Blaschke, D.
2018-02-01
Properties of nuclear systems at subsaturation densities can be obtained from different approaches. We demonstrate the use of the density autocorrelation function which is related to the isothermal compressibility and, after integration, to the equation of state. This way we connect the Landau Fermi liquid theory well elaborated in nuclear physics with the approaches to dilute nuclear matter describing cluster formation. A quantum statistical approach is presented, based on the cluster decomposition of the polarization function. The fundamental quantity to be calculated is the dynamic structure factor. Comparing with the Landau Fermi liquid theory which is reproduced in lowest approximation, the account of bound state formation and continuum correlations gives the correct low-density result as described by the second virial coefficient and by the mass action law (nuclear statistical equilibrium). Going to higher densities, the inclusion of medium effects is more involved compared with other quantum statistical approaches, but the relation to the Landau Fermi liquid theory gives a promising approach to describe not only thermodynamic but also collective excitations and non-equilibrium properties of nuclear systems in a wide region of the phase diagram.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eliav, E.; Kaldor, U.; Ishikawa, Y.
1994-12-31
Relativistic pair correlation energies of Xe were computed by employing a recently developed relativistic coupled cluster theory based on the no-pair Dirac-Coulomb-Breit Hamiltonian. The matrix Dirac-Fock-Breit SCF and relativistic coupled cluster calculations were performed by means of expansion in basis sets of well-tempered Gaussian spinors. A detailed study of the pair correlation energies in Xe is performed, in order to investigate the effects of the low-frequency Breit interaction on the correlation energies of Xe. Nonadditivity of correlation and relativistic (particularly Breit) effects is discussed.
The adsorption of Run (n = 1-4) on γ-Al2O3 Surface: A DFT study
NASA Astrophysics Data System (ADS)
Liu, Zhe; Guo, Yafei; Chen, Yu; Shen, Rong
2018-05-01
The density functional theory (DFT) was adopted to study the adsorption and growth of Run (n = 1-4) clusters on γ-Al2O3 surface, which is of great significances for the design of many important catalysts, especially for carbon dioxide methanation. It is found that both the Rusbnd Ru bond length and adsorption energy Eads of Ru clusters with the surface increase with the Run clusters increasing. The growth ability of the supported Run cluster is weaker than the gas phase Run clusters through comparing their respective growth process, which ascribes to the stabilization of γ-Al2O3 support. An interesting discovery is that the basin structure was supposed to be the most favorable adsorption geometry for Run clusters. Additionally, the distances between Ru atoms in the adsorbed clusters are longer than that in their isolated counterparts. Bader charge analysis was conducted for the most stable configurations of Run (n = 1-4) clusters on γ-Al2O3 surface as well. And the results suggest that Run (n = 1-4) clusters serve as the electron donators. The result of projected density of states (PDOS) shows that strong adsorption of Ru atom on the γ-Al2O3 surface correlates with strong interaction between d orbital of Ru atom and p orbital of Al or O atom of the Al2O3 support.
NASA Astrophysics Data System (ADS)
Lehmann, I.; Scholz, R.-D.
1997-04-01
We present new tidal radii for seven Galactic globular clusters using the method of automated star counts on Schmidt plates of the Tautenburg, Palomar and UK telescopes. The plates were fully scanned with the APM system in Cambridge (UK). Special account was given to a reliable background subtraction and the correction of crowding effects in the central cluster region. For the latter we used a new kind of crowding correction based on a statistical approach to the distribution of stellar images and the luminosity function of the cluster stars in the uncrowded area. The star counts were correlated with surface brightness profiles of different authors to obtain complete projected density profiles of the globular clusters. Fitting an empirical density law (King 1962) we derived the following structural parameters: tidal radius r_t_, core radius r_c_ and concentration parameter c. In the cases of NGC 5466, M 5, M 12, M 13 and M 15 we found an indication for a tidal tail around these objects (cf. Grillmair et al. 1995).
VizieR Online Data Catalog: Tidal radii of 7 globular clusters (Lehmann+ 1997)
NASA Astrophysics Data System (ADS)
Lehmann, I.; Scholz, R.-D.
1998-02-01
We present new tidal radii for seven Galactic globular clusters using the method of automated star counts on Schmidt plates of the Tautenburg, Palomar and UK telescopes. The plates were fully scanned with the APM system in Cambridge (UK). Special account was given to a reliable background subtraction and the correction of crowding effects in the central cluster region. For the latter we used a new kind of crowding correction based on a statistical approach to the distribution of stellar images and the luminosity function of the cluster stars in the uncrowded area. The star counts were correlated with surface brightness profiles of different authors to obtain complete projected density profiles of the globular clusters. Fitting an empirical density law (King 1962AJ.....67..471K) we derived the following structural parameters: tidal radius rt, core radius rc and concentration parameter c. In the cases of NGC 5466, M 5, M 12, M 13 and M 15 we found an indication for a tidal tail around these objects (cf. Grillmair et al., 1995AJ....109.2553G). (1 data file).
An adaptive clustering algorithm for image matching based on corner feature
NASA Astrophysics Data System (ADS)
Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song
2018-04-01
The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.
C 60 -induced Devil's Staircase transformation on a Pb/Si(111) wetting layer
Wang, Lin -Lin; Johnson, Duane D.; Tringides, Michael C.
2015-12-03
Density functional theory is used to study structural energetics of Pb vacancy cluster formation on C 60/Pb/Si(111) to explain the unusually fast and error-free transformations between the “Devil's Staircase” (DS) phases on the Pb/Si(111) wetting layer at low temperature (~110K). The formation energies of vacancy clusters are calculated in C 60/Pb/Si(111) as Pb atoms are progressively ejected from the initial dense Pb wetting layer. Vacancy clusters larger than five Pb atoms are found to be stable with seven being the most stable, while vacancy clusters smaller than five are highly unstable, which agrees well with the observed ejection rate ofmore » ~5 Pb atoms per C 60. Furthermore, the high energy cost (~0.8 eV) for the small vacancy clusters to form indicates convincingly that the unusually fast transformation observed experimentally between the DS phases, upon C 60 adsorption at low temperature, cannot be the result of single-atom random walk diffusion but of correlated multi-atom processes.« less
Spatial organization and dynamics of RNase E and ribosomes in Caulobacter crescentus.
Bayas, Camille A; Wang, Jiarui; Lee, Marissa K; Schrader, Jared M; Shapiro, Lucy; Moerner, W E
2018-04-17
We report the dynamic spatial organization of Caulobacter crescentus RNase E (RNA degradosome) and ribosomal protein L1 (ribosome) using 3D single-particle tracking and superresolution microscopy. RNase E formed clusters along the central axis of the cell, while weak clusters of ribosomal protein L1 were deployed throughout the cytoplasm. These results contrast with RNase E and ribosome distribution in Escherichia coli , where RNase E colocalizes with the cytoplasmic membrane and ribosomes accumulate in polar nucleoid-free zones. For both RNase E and ribosomes in Caulobacter , we observed a decrease in confinement and clustering upon transcription inhibition and subsequent depletion of nascent RNA, suggesting that RNA substrate availability for processing, degradation, and translation facilitates confinement and clustering. Importantly, RNase E cluster positions correlated with the subcellular location of chromosomal loci of two highly transcribed rRNA genes, suggesting that RNase E's function in rRNA processing occurs at the site of rRNA synthesis. Thus, components of the RNA degradosome and ribosome assembly are spatiotemporally organized in Caulobacter , with chromosomal readout serving as the template for this organization.
Calculation of boron-isotope fractionation between B(OH) 3(aq) and B(OH)4-(aq)
NASA Astrophysics Data System (ADS)
Rustad, James R.; Bylaska, Eric J.; Jackson, Virgil E.; Dixon, David A.
2010-05-01
Density functional and correlated molecular orbital calculations (MP2) are carried out on B(OH) 3· nH 2O clusters ( n = 0, 6, 32), and B(OH)4-· nH 2O ( n = 0, 8, 11, 32) to estimate the equilibrium distribution of 10B and 11B isotopes between boric acid and borate in aqueous solution. For the large 32-water clusters, multiple conformations are generated from ab initio molecular dynamics simulations to account for the effect of solvent fluctuations on the isotopic fractionation. We provide an extrapolated value of the equilibrium constant α34 for the isotope exchange reaction 10B(OH) 3(aq) + 11B(OH)4- (aq) = 11B(OH) 3(aq) + 11B(OH)4- (aq) of 1.026-1.028 near the MP2 complete basis set limit with 32 explicit waters of solvation. With some exchange-correlation functionals we find potentially important contributions from a tetrahedral neutral B(OH) 3·H 2O Lewis acid-base complex. The extrapolations presented here suggest that DFT calculations give a value for 10 3ln α34 about 15% higher than the MP2 calculations.
Clustering on very small scales from a large, complete sample of confirmed quasar pairs
NASA Astrophysics Data System (ADS)
Eftekharzadeh, Sarah; Myers, Adam D.; Djorgovski, Stanislav G.; Graham, Matthew J.; Hennawi, Joseph F.; Mahabal, Ashish A.; Richards, Gordon T.
2016-06-01
We present by far the largest sample of spectroscopically confirmed binaryquasars with proper transverse separations of 17.0 ≤ Rprop ≤ 36.6 h-1 kpc. Our sample, whichis an order-of-magnitude larger than previous samples, is selected from Sloan Digital Sky Survey (SDSS) imaging over an area corresponding to the SDSS 6th data release (DR6). Our quasars are targeted using a Kernel Density Estimation technique (KDE), and confirmed using long-slit spectroscopy on a range of facilities.Our most complete sub-sample of 44 binary quasars with g<20.85, extends across angular scales of 2.9" < Δθ < 6.3", and is targeted from a parent sample that would be equivalent to a full spectroscopic survey of nearly 300,000 quasars.We determine the projected correlation function of quasars (\\bar Wp) over proper transverse scales of 17.0 ≤ Rprop ≤ 36.6 h-1 kpc, and also in 4 bins of scale within this complete range.To investigate the redshift evolution of quasar clustering on small scales, we make the first self-consistent measurement of the projected quasar correlation function in 4 bins of redshift over 0.4 ≤ z ≤ 2.3.
NASA Astrophysics Data System (ADS)
Zhao, Tongtiegang; Liu, Pan; Zhang, Yongyong; Ruan, Chengqing
2017-09-01
Global climate model (GCM) forecasts are an integral part of long-range hydroclimatic forecasting. We propose to use clustering to explore anomaly correlation, which indicates the performance of raw GCM forecasts, in the three-dimensional space of latitude, longitude, and initialization time. Focusing on a certain period of the year, correlations for forecasts initialized at different preceding periods form a vector. The vectors of anomaly correlation across different GCM grid cells are clustered to reveal how GCM forecasts perform as time progresses. Through the case study of Climate Forecast System Version 2 (CFSv2) forecasts of summer precipitation in China, we observe that the correlation at a certain cell oscillates with lead time and can become negative. The use of clustering reveals two meaningful patterns that characterize the relationship between anomaly correlation and lead time. For some grid cells in Central and Southwest China, CFSv2 forecasts exhibit positive correlations with observations and they tend to improve as time progresses. This result suggests that CFSv2 forecasts tend to capture the summer precipitation induced by the East Asian monsoon and the South Asian monsoon. It also indicates that CFSv2 forecasts can potentially be applied to improving hydrological forecasts in these regions. For some other cells, the correlations are generally close to zero at different lead times. This outcome implies that CFSv2 forecasts still have plenty of room for further improvement. The robustness of the patterns has been tested using both hierarchical clustering and k-means clustering and examined with the Silhouette score.
Manna, Debashree; Kesharwani, Manoj K; Sylvetsky, Nitai; Martin, Jan M L
2017-07-11
Benchmark ab initio energies for BEGDB and WATER27 data sets have been re-examined at the MP2 and CCSD(T) levels with both conventional and explicitly correlated (F12) approaches. The basis set convergence of both conventional and explicitly correlated methods has been investigated in detail, both with and without counterpoise corrections. For the MP2 and CCSD-MP2 contributions, rapid basis set convergence observed with explicitly correlated methods is compared to conventional methods. However, conventional, orbital-based calculations are preferred for the calculation of the (T) term, since it does not benefit from F12. CCSD(F12*) converges somewhat faster with the basis set than CCSD-F12b for the CCSD-MP2 term. The performance of various DFT methods is also evaluated for the BEGDB data set, and results show that Head-Gordon's ωB97X-V and ωB97M-V functionals outperform all other DFT functionals. Counterpoise-corrected DSD-PBEP86 and raw DSD-PBEPBE-NL also perform well and are close to MP2 results. In the WATER27 data set, the anionic (deprotonated) water clusters exhibit unacceptably slow basis set convergence with the regular cc-pVnZ-F12 basis sets, which have only diffuse s and p functions. To overcome this, we have constructed modified basis sets, denoted aug-cc-pVnZ-F12 or aVnZ-F12, which have been augmented with diffuse functions on the higher angular momenta. The calculated final dissociation energies of BEGDB and WATER27 data sets are available in the Supporting Information. Our best calculated dissociation energies can be reproduced through n-body expansion, provided one pushes to the basis set and electron correlation limit for the two-body term; for the three-body term, post-MP2 contributions (particularly CCSD-MP2) are important for capturing the three-body dispersion effects. Terms beyond four-body can be adequately captured at the MP2-F12 level.
Structures and stabilities of Al(n) (+), Al(n), and Al(n) (-) (n=13-34) clusters.
Aguado, Andrés; López, José M
2009-02-14
Putative global minima of neutral (Al(n)) and singly charged (Al(n) (+) and Al(n) (-)) aluminum clusters with n=13-34 have been located from first-principles density functional theory structural optimizations. The calculations include spin polarization and employ the generalized gradient approximation of Perdew, Burke, and Ernzerhof to describe exchange-correlation electronic effects. Our results show that icosahedral growth dominates the structures of aluminum clusters for n=13-22. For n=23-34, there is a strong competition between decahedral structures, relaxed fragments of a fcc crystalline lattice (some of them including stacking faults), and hexagonal prismatic structures. For such small cluster sizes, there is no evidence yet for a clear establishment of the fcc atomic packing prevalent in bulk aluminum. The global minimum structure for a given number of atoms depends significantly on the cluster charge for most cluster sizes. An explicit comparison is made with previous theoretical results in the range n=13-30: for n=19, 22, 24, 25, 26, 29, 30 we locate a lower energy structure than previously reported. Sizes n=32, 33 are studied here for the first time by an ab initio technique.
Enhanced Abundances in Spiral Galaxies of the Pegasus I Cluster
NASA Astrophysics Data System (ADS)
Robertson, Paul; Shields, Gregory A.; Blanc, Guillermo A.
2012-03-01
We study the influence of cluster environment on the chemical evolution of spiral galaxies in the Pegasus I cluster. We determine the gas-phase heavy element abundances of six galaxies in Pegasus derived from H II region spectra obtained from integral-field spectroscopy. These abundances are analyzed in the context of Virgo, whose spirals are known to show increasing interstellar metallicity as a function of H I deficiency. The galaxies in the Pegasus cluster, despite its lower density and velocity dispersion, also display gas loss due to interstellar-medium-intracluster-medium interaction, albeit to a lesser degree. Based on the abundances of three H I deficient spirals and two H I normal spirals, we observe a heavy element abundance offset of +0.13 ± 0.07 dex for the H I deficient galaxies. This abundance differential is consistent with the differential observed in Virgo for galaxies with a similar H I deficiency, and we observe a correlation between log (O/H) and the H I deficiency parameter DEF for the two clusters analyzed together. Our results suggest that similar environmental mechanisms are driving the heavy element enhancement in both clusters.
NASA Astrophysics Data System (ADS)
Secker, Jeffrey Alan
1995-01-01
We have developed a statistically rigorous and automated method to implement the detection, photometry and classification of faint objects on digital images. We use these methods to analyze deep R- and B-band CCD images of the central ~ 700 arcmin ^2 of the Coma cluster core, and an associated control field. We have detected and measured total R magnitudes and (B-R) colors for a sample of 3741 objects on the galaxy cluster fields, and 1164 objects on a remote control field, complete to a limiting magnitude of R = 22.5 mag. The typical uncertainties are +/- 0.06 and +/-0.12 mag in total magnitude and color respectively. The dwarf elliptical (dE) galaxies are confined to a well-defined sequence in the color range given by 0.7<= (B-R)<= 1.9 mag: within this interval there are 2535 dE candidates on our fields in the cluster core, and 694 objects on the control field. With an image scale of 0.53 arcsec/pixel and seeing near 1.2 arcsec, a large fraction of the dE galaxy candidates are resolved. We find a significant metallicity gradient in the radial distribution of the dwarf elliptical galaxies, which goes as Z~ R^{-0.32 } outwards from the cluster center at NGC 4874. As well, there is a strong color-luminosity correlation, in the sense that more luminous dE galaxies are redder in the mean. These effects give rise to a radial variation in the cluster luminosity function. The spatial distribution of the faint dE galaxies is well fit by a standard King model with a central surface density of Sigma _0 = 1.44 dEs arcmin^{ -2}, a core radius R_{ rm c} = 18.7 arcmin (~eq 0.44 Mpc), and a tidal radius of 1.44 deg ( ~eq 2.05 Mpc). This core is significantly larger than R_{rm c} = 12.3 arcmin (~eq 0.29 Mpc) found for the bright cluster galaxies. The composite luminosity function for Coma galaxies is modeled as the sum of a log -normal distribution for the giant galaxies and a Schechter function for the dwarf elliptical galaxies, with a faint -end slope of alpha = -1.41, consistent with known faint-end slopes for the Virgo and Fornax clusters. The early-type dwarf-to-giant ratio for the Coma cluster core is consistent with that of the Virgo cluster, and thus with the rich Coma cluster being formed as the merger of multiple less-rich galaxy clusters.
A tripartite clustering analysis on microRNA, gene and disease model.
Shen, Chengcheng; Liu, Ying
2012-02-01
Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.
Kim, Sang-Hee; Byun, Youngsoon
Symptom clusters must be identified in patients with high-grade brain cancers for effective symptom management during cancer-related therapy. The aims of this study were to identify symptom clusters in patients with high-grade brain cancers and to determine the relationship of each cluster with the performance status and quality of life (QOL) during concurrent chemoradiotherapy (CCRT). Symptoms were assessed using the Memorial Symptom Assessment Scale, and the performance status was evaluated using the Karnofsky Performance Scale. Quality of life was assessed using the Functional Assessment of Cancer Therapy-General. This prospective longitudinal survey was conducted before CCRT and at 2 to 3 weeks and 4 to 6 weeks after the initiation of CCRT. A total of 51 patients with newly diagnosed primary malignant brain cancer were included. Six symptom clusters were identified, and 2 symptom clusters were present at each time point (ie, "negative emotion" and "neurocognitive" clusters before CCRT, "negative emotion and decreased vitality" and "gastrointestinal and decreased sensory" clusters at 2-3 weeks, and "body image and decreased vitality" and "gastrointestinal" clusters at 4-6 weeks). The symptom clusters at each time point demonstrated a significant relationship with the performance status or QOL. Differences were observed in symptom clusters in patients with high-grade brain cancers during CCRT. In addition, the symptom clusters were correlated with the performance status and QOL of patients, and these effects could change during CCRT. The results of this study will provide suggestions for interventions to treat or prevent symptom clusters in patients with high-grade brain cancer during CCRT.
Bai, Mei; Dixon, Jane; Williams, Anna-Leila; Jeon, Sangchoon; Lazenby, Mark; McCorkle, Ruth
2016-11-01
Research shows that spiritual well-being correlates positively with quality of life (QOL) for people with cancer, whereas contradictory findings are frequently reported with respect to the differentiated associations between dimensions of spiritual well-being, namely peace, meaning and faith, and QOL. This study aimed to examine individual patterns of spiritual well-being among patients newly diagnosed with advanced cancer. Cluster analysis was based on the twelve items of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale at Time 1. A combination of hierarchical and k-means (non-hierarchical) clustering methods was employed to jointly determine the number of clusters. Self-rated health, depressive symptoms, peace, meaning and faith, and overall QOL were compared at Time 1 and Time 2. Hierarchical and k-means clustering methods both suggested four clusters. Comparison of the four clusters supported statistically significant and clinically meaningful differences in QOL outcomes among clusters while revealing contrasting relations of faith with QOL. Cluster 1, Cluster 3, and Cluster 4 represented high, medium, and low levels of overall QOL, respectively, with correspondingly high, medium, and low levels of peace, meaning, and faith. Cluster 2 was distinguished from other clusters by its medium levels of overall QOL, peace, and meaning and low level of faith. This study provides empirical support for individual difference in response to a newly diagnosed cancer and brings into focus conceptual and methodological challenges associated with the measure of spiritual well-being, which may partly contribute to the attenuated relation between faith and QOL.