Metal-superconductor transition in low-dimensional superconducting clusters embedded in two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Bucheli, D.; Caprara, S.; Castellani, C.; Grilli, M.

2013-02-01

Motivated by recent experimental data on thin film superconductors and oxide interfaces, we propose a random-resistor network apt to describe the occurrence of a metal-superconductor transition in a two-dimensional electron system with disorder on the mesoscopic scale. We consider low-dimensional (e.g. filamentary) structures of a superconducting cluster embedded in the two-dimensional network and we explore the separate effects and the interplay of the superconducting structure and of the statistical distribution of local critical temperatures. The thermal evolution of the resistivity is determined by a numerical calculation of the random-resistor network and, for comparison, a mean-field approach called effective medium theory (EMT). Our calculations reveal the relevance of the distribution of critical temperatures for clusters with low connectivity. In addition, we show that the presence of spatial correlations requires a modification of standard EMT to give qualitative agreement with the numerical results. Applying the present approach to an LaTiO3/SrTiO3 oxide interface, we find that the measured resistivity curves are compatible with a network of spatially dense but loosely connected superconducting islands.

The writer independent online handwriting recognition system frog on hand and cluster generative statistical dynamic time warping.

PubMed

Bahlmann, Claus; Burkhardt, Hans

2004-03-01

In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

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

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

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

Embedded Clusters

NASA Astrophysics Data System (ADS)

Ascenso, Joana

The past decade has seen an increase of star formation studies made at the molecular cloud scale, motivated mostly by the deployment of a wealth of sensitive infrared telescopes and instruments. Embedded clusters, long recognised as the basic units of coherent star formation in molecular clouds, are now seen to inhabit preferentially cluster complexes tens of parsecs across. This chapter gives an overview of some important properties of the embedded clusters in these complexes and of the complexes themselves, along with the implications of viewing star formation as a molecular-cloud scale process rather than an isolated process at the scale of clusters.

Enhanced Ionization of Embedded Clusters by Electron-Transfer-Mediated Decay in Helium Nanodroplets.

PubMed

LaForge, A C; Stumpf, V; Gokhberg, K; von Vangerow, J; Stienkemeier, F; Kryzhevoi, N V; O'Keeffe, P; Ciavardini, A; Krishnan, S R; Coreno, M; Prince, K C; Richter, R; Moshammer, R; Pfeifer, T; Cederbaum, L S; Mudrich, M

2016-05-20

We report the observation of electron-transfer-mediated decay (ETMD) involving magnesium (Mg) clusters embedded in helium (He) nanodroplets. ETMD is initiated by the ionization of He followed by removal of two electrons from the Mg clusters of which one is transferred to the He ion while the other electron is emitted into the continuum. The process is shown to be the dominant ionization mechanism for embedded clusters for photon energies above the ionization potential of He. For Mg clusters larger than five atoms we observe stable doubly ionized clusters. Thus, ETMD provides an efficient pathway to the formation of doubly ionized cold species in doped nanodroplets.

Calculating hyperfine couplings in large ionic crystals containing hundreds of QM atoms: subsystem DFT is the key.

PubMed

Kevorkyants, Ruslan; Wang, Xiqiao; Close, David M; Pavanello, Michele

2013-11-14

We present an application of the linear scaling frozen density embedding (FDE) formulation of subsystem DFT to the calculation of isotropic hyperfine coupling constants (hfcc's) of atoms belonging to a guanine radical cation embedded in a guanine hydrochloride monohydrate crystal. The model systems range from an isolated guanine to a 15,000 atom QM/MM cluster where the QM region is comprised of 36 protonated guanine cations, 36 chlorine anions, and 42 water molecules. Our calculations show that the embedding effects of the surrounding crystal cannot be reproduced by small model systems nor by a pure QM/MM procedure. Instead, a large QM region is needed to fully capture the complicated nature of the embedding effects in this system. The unprecedented system size for a relativistic all-electron isotropic hfcc calculation can be approached in this work because the local nature of the electronic structure of the organic crystals considered is fully captured by the FDE approach.

Identifying synonymy between relational phrases using word embeddings.

PubMed

Nguyen, Nhung T H; Miwa, Makoto; Tsuruoka, Yoshimasa; Tojo, Satoshi

2015-08-01

Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Most of the previous work that has addressed this task of synonymy resolution uses similarity metrics between relational phrases based on textual strings or dependency paths, which, for the most part, ignore the context around the relations. To overcome this shortcoming, we employ a word embedding technique to encode relational phrases. We then apply the k-means algorithm on top of the distributional representations to cluster the phrases. Our experimental results show that this approach outperforms state-of-the-art statistical models including latent Dirichlet allocation and Markov logic networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Diverse power iteration embeddings: Theory and practice

DOE PAGES

Huang, Hao; Yoo, Shinjae; Yu, Dantong; ...

2015-11-09

Manifold learning, especially spectral embedding, is known as one of the most effective learning approaches on high dimensional data, but for real-world applications it raises a serious computational burden in constructing spectral embeddings for large datasets. To overcome this computational complexity, we propose a novel efficient embedding construction, Diverse Power Iteration Embedding (DPIE). DPIE shows almost the same effectiveness of spectral embeddings and yet is three order of magnitude faster than spectral embeddings computed from eigen-decomposition. Our DPIE is unique in that (1) it finds linearly independent embeddings and thus shows diverse aspects of dataset; (2) the proposed regularized DPIEmore » is effective if we need many embeddings; (3) we show how to efficiently orthogonalize DPIE if one needs; and (4) Diverse Power Iteration Value (DPIV) provides the importance of each DPIE like an eigen value. As a result, such various aspects of DPIE and DPIV ensure that our algorithm is easy to apply to various applications, and we also show the effectiveness and efficiency of DPIE on clustering, anomaly detection, and feature selection as our case studies.« less

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

First-principles calculations of Ti and O NMR chemical shift tensors in ferroelectric perovskites

NASA Astrophysics Data System (ADS)

Pechkis, Daniel; Walter, Eric; Krakauer, Henry

2011-03-01

Complementary chemical shift calculations were carried out with embedded clusters, using quantum chemistry methods, and with periodic boundary conditions, using the GIPAW approach within the Quantum Espresso package. Compared to oxygen chemical shifts, δ̂ (O), cluster calculations for δ̂ (Ti) were found to be more sensitive to size effects, termination, and choice of gaussian-type atomic basis set, while GIPAW results were found to be more sensitive to the pseudopotential construction. The two approaches complemented each other in optimizing these factors. We show that the two approaches yield comparable chemical shifts for suitably converged simulations, and results are compared with available experimental measurements. Supported by ONR.

Prediction of tautomer ratios by embedded-cluster integral equation theory

NASA Astrophysics Data System (ADS)

Kast, Stefan M.; Heil, Jochen; Güssregen, Stefan; Schmidt, K. Friedemann

2010-04-01

The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol-1) as well as for the full set of quantitative reaction data (2.0 kcal mol-1) among the SAMPL2 participants.

Cluster Computing for Embedded/Real-Time Systems

NASA Technical Reports Server (NTRS)

Katz, D.; Kepner, J.

1999-01-01

Embedded and real-time systems, like other computing systems, seek to maximize computing power for a given price, and thus can significantly benefit from the advancing capabilities of cluster computing.

Ab initio simulations of scanning-tunneling-microscope images with embedding techniques and application to C58-dimers on Au(111).

PubMed

Wilhelm, Jan; Walz, Michael; Stendel, Melanie; Bagrets, Alexei; Evers, Ferdinand

2013-05-14

We present a modification of the standard electron transport methodology based on the (non-equilibrium) Green's function formalism to efficiently simulate STM-images. The novel feature of this method is that it employs an effective embedding technique that allows us to extrapolate properties of metal substrates with adsorbed molecules from quantum-chemical cluster calculations. To illustrate the potential of this approach, we present an application to STM-images of C58-dimers immobilized on Au(111)-surfaces that is motivated by recent experiments.

Acidity in DMSO from the embedded cluster integral equation quantum solvation model.

PubMed

Heil, Jochen; Tomazic, Daniel; Egbers, Simon; Kast, Stefan M

2014-04-01

The embedded cluster reference interaction site model (EC-RISM) is applied to the prediction of acidity constants of organic molecules in dimethyl sulfoxide (DMSO) solution. EC-RISM is based on a self-consistent treatment of the solute's electronic structure and the solvent's structure by coupling quantum-chemical calculations with three-dimensional (3D) RISM integral equation theory. We compare available DMSO force fields with reference calculations obtained using the polarizable continuum model (PCM). The results are evaluated statistically using two different approaches to eliminating the proton contribution: a linear regression model and an analysis of pK(a) shifts for compound pairs. Suitable levels of theory for the integral equation methodology are benchmarked. The results are further analyzed and illustrated by visualizing solvent site distribution functions and comparing them with an aqueous environment.

Identification of temporal variations in mental workload using locally-linear-embedding-based EEG feature reduction and support-vector-machine-based clustering and classification techniques.

PubMed

Yin, Zhong; Zhang, Jianhua

2014-07-01

Identifying the abnormal changes of mental workload (MWL) over time is quite crucial for preventing the accidents due to cognitive overload and inattention of human operators in safety-critical human-machine systems. It is known that various neuroimaging technologies can be used to identify the MWL variations. In order to classify MWL into a few discrete levels using representative MWL indicators and small-sized training samples, a novel EEG-based approach by combining locally linear embedding (LLE), support vector clustering (SVC) and support vector data description (SVDD) techniques is proposed and evaluated by using the experimentally measured data. The MWL indicators from different cortical regions are first elicited by using the LLE technique. Then, the SVC approach is used to find the clusters of these MWL indicators and thereby to detect MWL variations. It is shown that the clusters can be interpreted as the binary class MWL. Furthermore, a trained binary SVDD classifier is shown to be capable of detecting slight variations of those indicators. By combining the two schemes, a SVC-SVDD framework is proposed, where the clear-cut (smaller) cluster is detected by SVC first and then a subsequent SVDD model is utilized to divide the overlapped (larger) cluster into two classes. Finally, three-class MWL levels (low, normal and high) can be identified automatically. The experimental data analysis results are compared with those of several existing methods. It has been demonstrated that the proposed framework can lead to acceptable computational accuracy and has the advantages of both unsupervised and supervised training strategies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model.

PubMed

Bruneau, Marine; Mottet, Thierry; Moulin, Serge; Kerbiriou, Maël; Chouly, Franz; Chretien, Stéphane; Guyeux, Christophe

2018-02-01

In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clusters is not required here. For the sake of illustration, this method is applied on a set of 100 DNA sequences taken from the mitochondrially encoded NADH dehydrogenase 3 (ND3) gene, extracted from a collection of Platyhelminthes and Nematoda species. The resulting clusters are tightly consistent with the phylogenetic tree computed using a maximum likelihood approach on gene alignment. They are coherent too with the NCBI taxonomy. Further test results based on synthesized data are then provided, showing that the proposed approach is better able to recover the clusters than the most widely used software, namely Cd-hit-est and BLASTClust. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Mid-course multi-target tracking using continuous representation

NASA Technical Reports Server (NTRS)

Zak, Michail; Toomarian, Nikzad

1991-01-01

The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.

Electrostatically Embedded Many-Body Approximation for Systems of Water, Ammonia, and Sulfuric Acid and the Dependence of Its Performance on Embedding Charges.

PubMed

Leverentz, Hannah R; Truhlar, Donald G

2009-06-09

This work tests the capability of the electrostatically embedded many-body (EE-MB) method to calculate accurate (relative to conventional calculations carried out at the same level of electronic structure theory and with the same basis set) binding energies of mixed clusters (as large as 9-mers) consisting of water, ammonia, sulfuric acid, and ammonium and bisulfate ions. This work also investigates the dependence of the accuracy of the EE-MB approximation on the type and origin of the charges used for electrostatically embedding these clusters. The conclusions reached are that for all of the clusters and sets of embedding charges studied in this work, the electrostatically embedded three-body (EE-3B) approximation is capable of consistently yielding relative errors of less than 1% and an average relative absolute error of only 0.3%, and that the performance of the EE-MB approximation does not depend strongly on the specific set of embedding charges used. The electrostatically embedded pairwise approximation has errors about an order of magnitude larger than EE-3B. This study also explores the question of why the accuracy of the EE-MB approximation shows such little dependence on the types of embedding charges employed.

Gas expulsion in highly substructured embedded star clusters

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Near-infrared study of new embedded clusters in the Carina complex

NASA Astrophysics Data System (ADS)

Oliveira, R. A. P.; Bica, E.; Bonatto, C.

2018-05-01

We analyse the nature of a sample of stellar overdensities that we found projected on the Carina complex. This study is based on the Two Micron All Sky Survey photometry and involves the photometry decontamination of field stars, elaboration of intrinsic colour-magnitude diagrams [CMDs; J × (J - Ks)], colour-colour diagrams (J - H) × (H - Ks), and radial density profiles, in order to determine the structure and the main astrophysical parameters of the best candidates. The verification of an overdensity as an embedded cluster requires a CMD consistent with a PMS content and MS stars, if any. From these results, we are able to verify if they are, in fact, embedded clusters. The results were, in general, rewarding: in a sample of 101 overdensities, the analysis provided 15 candidates, of which three were previously catalogued as clusters (CCCP-Cl 16, Treasure Chest, and FSR 1555), and the 12 remaining are discoveries that provided significant results, with ages not above 4.5 Myr and distances compatible with the studied complex. The resulting values for the differential reddening of most candidates were relatively high, confirming that these clusters are still (partially or fully) embedded in the surrounding gas and dust, as a rule within a shell. Histograms with the distribution of the masses, ages, and distances were also produced, to give an overview of the results. We conclude that all the 12 newly found embedded clusters are related to the Carina complex.

Treatment of delocalized electron transfer in periodic and embedded cluster DFT calculations: The case of Cu on ZnO (10(1)0).

PubMed

Hellström, Matti; Spångberg, Daniel; Hermansson, Kersti

2015-12-15

We assess the consequences of the interface model-embedded-cluster or periodic-slab model-on the ability of DFT calculations to describe charge transfer (CT) in a particularly challenging case where periodic-slab calculations indicate a delocalized charge-transfer state. Our example is Cu atom adsorption on ZnO(10(1)0), and in fact the periodic slab calculations indicate three types of CT depending on the adsorption site: full CT, partial CT, and no CT. Interestingly, when full CT occurs in the periodic calculations, the calculated Cu atom adsorption energy depends on the underlying ZnO substrate supercell size, since when the electron enters the ZnO it delocalizes over as many atoms as possible. In the embedded-cluster calculations, the electron transferred to the ZnO delocalizes over the entire cluster region, and as a result the calculated Cu atom adsorption energy does not agree with the value obtained using a large periodic supercell, but instead to the adsorption energy obtained for a periodic supercell of roughly the same size as the embedded cluster. Different density functionals (of GGA and hybrid types) and basis sets (local atom-centered and plane-waves) were assessed, and we show that embedded clusters can be used to model Cu adsorption on ZnO(10(1)0), as long as care is taken to account for the effects of CT. © 2015 Wiley Periodicals, Inc.

Diverse Power Iteration Embeddings and Its Applications

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

Huang H.; Yoo S.; Yu, D.

2014-12-14

Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detectionmore » and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.« less

Observations on Si-based micro-clusters embedded in TaN thin film deposited by co-sputtering with oxygen contamination

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

Lee, Young Mi; Jung, Min-Sang; Choi, Duck-Kyun, E-mail: duck@hanyang.ac.kr, E-mail: mcjung@oist.jp

2015-08-15

Using scanning electron microscopy (SEM) and high-resolution x-ray photoelectron spectroscopy with the synchrotron radiation we investigated Si-based micro-clusters embedded in TaSiN thin films having oxygen contamination. TaSiN thin films were deposited by co-sputtering on fixed or rotated substrates and with various power conditions of TaN and Si targets. Three types of embedded micro-clusters with the chemical states of pure Si, SiO{sub x}-capped Si, and SiO{sub 2}-capped Si were observed and analyzed using SEM and Si 2p and Ta 4f core-level spectra were derived. Their different resistivities are presumably due to the different chemical states and densities of Si-based micro-clusters.

An extended transfer operator approach to identify separatrices in open flows

NASA Astrophysics Data System (ADS)

Lünsmann, Benedict; Kantz, Holger

2018-05-01

Vortices of coherent fluid volume are considered to have a substantial impact on transport processes in turbulent media. Yet, due to their Lagrangian nature, detecting these structures is highly nontrivial. In this respect, transfer operator approaches have been proven to provide useful tools: Approximating a possibly time-dependent flow as a discrete Markov process in space and time, information about coherent structures is contained in the operator's eigenvectors, which is usually extracted by employing clustering methods. Here, we propose an extended approach that couples surrounding filaments using "mixing boundary conditions" and focuses on the separation of the inner coherent set and embedding outer flow. The approach refrains from using unsupervised machine learning techniques such as clustering and uses physical arguments by maximizing a coherence ratio instead. We show that this technique improves the reconstruction of separatrices in stationary open flows and succeeds in finding almost-invariant sets in periodically perturbed flows.

Fundamental Theory of Crystal Decomposition

DTIC Science & Technology

1991-05-01

rather than combine them as is often the case in a computation based on the density functional method.4 In the Case of a cluster embedded in a...classical lattice, special care needs to be taken to ensure that mathematical consistency is achieved between the cluster and the embedding lattice. This has...localizing potential or KKLP. Simulation of a large crystallite or an infinite lattice containing a point defect represented by a cluster and a

IRAS observations of the Rho Ophiuchi infrared cluster - Spectral energy distributions and luminosity function

NASA Technical Reports Server (NTRS)

Wilking, Bruce A.; Lada, Charles J.; Young, Eric T.

1989-01-01

High-sensitivity IRAS coadded survey data, coupled with new high-sensitivity near-IR observations, are used to investigate the nature of embedded objects over an 4.3-sq-pc area comprising the central star-forming cloud of the Ophiuchi molecular complex; the area encompasses the central cloud of the Rho Ophiuchi complex and includes the core region. Seventy-eight members of the embedded cluster were identified; spectral energy distributions were constructed for 53 objects and were compared with theoretical models to gain insight into their evolutionary status. Bolometric luminosities could be estimated for nearly all of the association members, leading to a revised luminosity function for this dust-embedded cluster.

Large Magnetovolume Effect Induced by Embedding Ferromagnetic Clusters into Antiferromagnetic Matrix of Cobaltite Perovskite.

PubMed

Miao, Ping; Lin, Xiaohuan; Koda, Akihiro; Lee, Sanghyun; Ishikawa, Yoshihisa; Torii, Shuki; Yonemura, Masao; Mochiku, Takashi; Sagayama, Hajime; Itoh, Shinichi; Ikeda, Kazutaka; Otomo, Toshiya; Wang, Yinxia; Kadono, Ryosuke; Kamiyama, Takashi

2017-07-01

Materials that show negative thermal expansion (NTE) have significant industrial merit because they can be used to fabricate composites whose dimensions remain invariant upon heating. In some materials, NTE is concomitant with the spontaneous magnetization due to the magnetovolume effect (MVE). Here the authors report a new class of MVE material; namely, a layered perovskite PrBaCo 2 O 5.5+ x (0 ≤ x ≤ 0.41), in which strong NTE [β ≈ -3.6 × 10 -5 K -1 (90-110 K) at x = 0.24] is triggered by embedding ferromagnetic (F) clusters into the antiferromagnetic (AF) matrix. The strongest MVE is found near the boundary between F and AF phases in the phase diagram, indicating the essential role of competition between the F-clusters and the AF-matrix. Furthermore, the MVE is not limited to the PrBaCo 2 O 5.5+ x but is also observed in the NdBaCo 2 O 5.5+ x . The present study provides a new approach to obtaining MVE and offers a path to the design of NTE materials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

TRACING EMBEDDED STELLAR POPULATIONS IN CLUSTERS AND GALAXIES USING MOLECULAR EMISSION: METHANOL AS A SIGNATURE OF THE LOW-MASS END OF THE IMF

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

Kristensen, Lars E.; Bergin, Edwin A., E-mail: lkristensen@cfa.harvard.edu

2015-07-10

Most low-mass protostars form in clusters, in particular high-mass clusters; however, how low-mass stars form in high-mass clusters and what the mass distribution is are still open questions both in our own Galaxy and elsewhere. To access the population of forming embedded low-mass protostars observationally, we propose using molecular outflows as tracers. Because the outflow emission scales with mass, the effective contrast between low-mass protostars and their high-mass cousins is greatly lowered. In particular, maps of methanol emission at 338.4 GHz (J = 7{sub 0}–6{sub 0} A{sup +}) in low-mass clusters illustrate that this transition is an excellent probe ofmore » the low-mass population. We present here a model of a forming cluster where methanol emission is assigned to every embedded low-mass protostar. The resulting model image of methanol emission is compared to recent ALMA observations toward a high-mass cluster and the similarity is striking: the toy model reproduces observations to better than a factor of two and suggests that approximately 50% of the total flux originates in low-mass outflows. Future fine-tuning of the model will eventually make it a tool for interpreting the embedded low-mass population of distant regions within our own Galaxy and ultimately higher-redshift starburst galaxies, not just for methanol emission but also water and high-J CO.« less

Extending density functional embedding theory for covalently bonded systems.

PubMed

Yu, Kuang; Carter, Emily A

2017-12-19

Quantum embedding theory aims to provide an efficient solution to obtain accurate electronic energies for systems too large for full-scale, high-level quantum calculations. It adopts a hierarchical approach that divides the total system into a small embedded region and a larger environment, using different levels of theory to describe each part. Previously, we developed a density-based quantum embedding theory called density functional embedding theory (DFET), which achieved considerable success in metals and semiconductors. In this work, we extend DFET into a density-matrix-based nonlocal form, enabling DFET to study the stronger quantum couplings between covalently bonded subsystems. We name this theory density-matrix functional embedding theory (DMFET), and we demonstrate its performance in several test examples that resemble various real applications in both chemistry and biochemistry. DMFET gives excellent results in all cases tested thus far, including predicting isomerization energies, proton transfer energies, and highest occupied molecular orbital-lowest unoccupied molecular orbital gaps for local chromophores. Here, we show that DMFET systematically improves the quality of the results compared with the widely used state-of-the-art methods, such as the simple capped cluster model or the widely used ONIOM method.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Development of a Mandarin-English Bilingual Speech Recognition System for Real World Music Retrieval

NASA Astrophysics Data System (ADS)

Zhang, Qingqing; Pan, Jielin; Lin, Yang; Shao, Jian; Yan, Yonghong

In recent decades, there has been a great deal of research into the problem of bilingual speech recognition-to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language**. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was comparable to that of the baseline monolingual Mandarin system. The performance for bilingual utterances achieved 22.37% relative PER reduction.

Entomological impact and social participation in dengue control: a cluster randomized trial in Fortaleza, Brazil

PubMed Central

Caprara, Andrea; De Oliveira Lima, José Wellington; Rocha Peixoto, Ana Carolina; Vasconcelos Motta, Cyntia Monteiro; Soares Nobre, Joana Mary; Sommerfeld, Johannes; Kroeger, Axel

2015-01-01

Background This study intended to implement a novel intervention strategy, in Brazil, using an ecohealth approach and analyse its effectiveness and costs in reducing Aedes aegypti vector density as well as its acceptance, feasibility and sustainability. The intervention was conducted from 2012 to 2013 in the municipality of Fortaleza, northeast Brazil. Methodology A cluster randomized controlled trial was designed by comparing ten intervention clusters with ten control clusters where routine vector control activities were conducted. The intervention included: community workshops; community involvement in clean-up campaigns; covering the elevated containers and in-house rubbish disposal without larviciding; mobilization of schoolchildren and senior inhabitants; and distribution of information, education and communication (IEC) materials in the community. Results Differences in terms of social participation, commitment and leadership were present in the clusters. The results showed the effectiveness of the intervention package in comparison with the routine control programme. Differences regarding the costs of the intervention were reasonable and could be adopted by public health services. Conclusions Embedding social participation and environmental management for improved dengue vector control was feasible and significantly reduced vector densities. Such a participatory ecohealth approach offers a promising alternative to routine vector control measures. PMID:25604760

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.

Economic 3D-printing approach for transplantation of human stem cell-derived β-like cells

PubMed Central

Song, Jiwon; Millman, Jeffrey R.

2016-01-01

Transplantation of human pluripotent stem cells (hPSC) differentiated into insulin-producing β cells is a regenerative medicine approach being investigated for diabetes cell replacement therapy. This report presents a multifaceted transplantation strategy that combines differentiation into stem cell-derived β (SC-β) cells with 3D printing. By modulating the parameters of a low-cost 3D printer, we created a macroporous device composed of polylactic acid (PLA) that houses SC-β cell clusters within a degradable fibrin gel. Using finite element modeling of cellular oxygen diffusion-consumption and an in vitro culture system that allows for culture of devices at physiological oxygen levels, we identified cluster sizes that avoid severe hypoxia within 3D-printed devices and developed a microwell-based technique for resizing clusters within this range. Upon transplantation into mice, SC-β cell-embedded 3D-printed devices function for 12 weeks, are retrievable, and maintain structural integrity. Here, we demonstrate a novel 3D-printing approach that advances the use of differentiated hPSC for regenerative medicine applications and serves as a platform for future transplantation strategies. PMID:27906687

Economic 3D-printing approach for transplantation of human stem cell-derived β-like cells.

PubMed

Song, Jiwon; Millman, Jeffrey R

2016-12-01

Transplantation of human pluripotent stem cells (hPSC) differentiated into insulin-producing β cells is a regenerative medicine approach being investigated for diabetes cell replacement therapy. This report presents a multifaceted transplantation strategy that combines differentiation into stem cell-derived β (SC-β) cells with 3D printing. By modulating the parameters of a low-cost 3D printer, we created a macroporous device composed of polylactic acid (PLA) that houses SC-β cell clusters within a degradable fibrin gel. Using finite element modeling of cellular oxygen diffusion-consumption and an in vitro culture system that allows for culture of devices at physiological oxygen levels, we identified cluster sizes that avoid severe hypoxia within 3D-printed devices and developed a microwell-based technique for resizing clusters within this range. Upon transplantation into mice, SC-β cell-embedded 3D-printed devices function for 12 weeks, are retrievable, and maintain structural integrity. Here, we demonstrate a novel 3D-printing approach that advances the use of differentiated hPSC for regenerative medicine applications and serves as a platform for future transplantation strategies.

Embedding Fragment ab Initio Model Potentials in CASSCF/CASPT2 Calculations of Doped Solids: Implementation and Applications.

PubMed

Swerts, Ben; Chibotaru, Liviu F; Lindh, Roland; Seijo, Luis; Barandiaran, Zoila; Clima, Sergiu; Pierloot, Kristin; Hendrickx, Marc F A

2008-04-01

In this article, we present a fragment model potential approach for the description of the crystalline environment as an extension of the use of embedding ab initio model potentials (AIMPs). The biggest limitation of the embedding AIMP method is the spherical nature of its model potentials. This poses problems as soon as the method is applied to crystals containing strongly covalently bonded structures with highly nonspherical electron densities. The newly proposed method addresses this problem by keeping the full electron density as its model potential, thus allowing one to group sets of covalently bonded atoms into fragments. The implementation in the MOLCAS 7.0 quantum chemistry package of the new method, which we call the embedding fragment ab inito model potential method (embedding FAIMP), is reported here, together with results of CASSCF/CASPT2 calculations. The developed methodology is applied for two test problems: (i) the investigation of the lowest ligand field states (2)A1 and (2)B1 of the Cr(V) defect in the YVO4 crystal and (ii) the investigation of the lowest ligand field and ligand-metal charge transfer (LMCT) states at the Mn(II) substitutional impurity doped into CaCO3. Comparison with similar calculations involving AIMPs for all environmental atoms, including those from covalently bounded units, shows that the FAIMP treatment of the YVO4 units surrounding the CrO4(3-) cluster increases the excitation energy (2)B1 → (2)A1 by ca. 1000 cm(-1) at the CASSCF level of calculation. In the case of the Mn(CO3)6(10-) cluster, the FAIMP treatment of the CO3(2-) units of the environment give smaller corrections, of ca. 100 cm(-1), for the ligand-field excitation energies, which is explained by the larger ligands of this cluster. However, the correction for the energy of the lowest LMCT transition is found to be ca. 600 cm(-1) for the CASSCF and ca. 1300 cm(-1) for the CASPT2 calculation.

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

Wykes, M., E-mail: mikewykes@gmail.com; Parambil, R.; Gierschner, J.

Here, we present a general approach to treating vibronic coupling in molecular crystals based on atomistic simulations of large clusters. Such clusters comprise model aggregates treated at the quantum chemical level embedded within a realistic environment treated at the molecular mechanics level. As we calculate ground and excited state equilibrium geometries and vibrational modes of model aggregates, our approach is able to capture effects arising from coupling to intermolecular degrees of freedom, absent from existing models relying on geometries and normal modes of single molecules. Using the geometries and vibrational modes of clusters, we are able to simulate the fluorescencemore » spectra of aggregates for which the lowest excited state bears negligible oscillator strength (as is the case, e.g., ideal H-aggregates) by including both Franck-Condon (FC) and Herzberg-Teller (HT) vibronic transitions. The latter terms allow the adiabatic excited state of the cluster to couple with vibrations in a perturbative fashion via derivatives of the transition dipole moment along nuclear coordinates. While vibronic coupling simulations employing FC and HT terms are well established for single-molecules, to our knowledge this is the first time they are applied to molecular aggregates. Here, we apply this approach to the simulation of the low-temperature fluorescence spectrum of para-distyrylbenzene single-crystal H-aggregates and draw comparisons with coarse-grained Frenkel-Holstein approaches previously extensively applied to such systems.« less

Cohesive Energies of Some Transition Metal Compounds Using Embedded Clusters

NASA Astrophysics Data System (ADS)

Press, Mehernosh Rustom

The molecular-clusters approach to electronic structure calculation is especially well-suited to the study of properties that depend primarily on the local environment of a system, especially those with no translational symmetry, e.g. systems with defects and structural deformations. The presence of the rest of the crystal environment can be accounted for approximately by embedding the cluster in a self-consistent crystal potential. This thesis makes a contribution in the area of investigating the capability of embedded molecular-clusters to yield reliable bulk structural properties. To this end, an algorithm for calculating the cohesive energies of clusters within the discrete-variational X(,(alpha)) LCAO-MO formulation is set up and verified on simple solids: Li, Na, Cu and LiF. We then use this formulation to study transition metal compounds, for which the interesting physics lies in local lattice defects, foreign impurities and structural deformations. In a self -consistent calculation of the lattice energies and stability of defect clusters in wustite, Fe(,1-x)O, corner-sharing aggregates of the 4:1 defect are identified as the most stable defect configurations due to efficient compensation of the cluster charge. The intercalation properties of layered-transition-metal-dichalcogenides continues to be a fertile experimental working area, backed by comparatively little theoretical study. We find that intercalation of ZrS(,2) with Na perturbs the valence energy level structure sufficiently to induce a more ionic Zr-S bond, a narrowing of the optical gap and filling of the lowest unoccupied host lattice orbitals with the electron donated by Na. Fe - intercalation in ZrS(,2) is accommodated via a strong Fe-S bond, impurity-like band levels in the optical gap of the host and hybridization-driven compression and lowering of the conduction band energy levels. The piezoelectric cuprous halides, CuCl and CuBr, exhibit a host of intriguing properties due to a filled and very active d('10) shell at the Fermi energy. A self-consistent calculation via energy minimization of the internal strain in these compounds shows both Cu-halide bonds to be very rigid with little charge delocalization under strain. Piezoelectric response is calculated in terms of effective charges and quadrupolar moments, e(,T) and (DELTA)Q.

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

PubMed

Nikfarjam, Azadeh; Sarker, Abeed; O'Connor, Karen; Ginn, Rachel; Gonzalez, Graciela

2015-05-01

Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques. However, the language in social media is highly informal, and user-expressed medical concepts are often nontechnical, descriptive, and challenging to extract. There has been limited progress in addressing these challenges, and thus far, advanced machine learning-based NLP techniques have been underutilized. Our objective is to design a machine learning-based approach to extract mentions of adverse drug reactions (ADRs) from highly informal text in social media. We introduce ADRMine, a machine learning-based concept extraction system that uses conditional random fields (CRFs). ADRMine utilizes a variety of features, including a novel feature for modeling words' semantic similarities. The similarities are modeled by clustering words based on unsupervised, pretrained word representation vectors (embeddings) generated from unlabeled user posts in social media using a deep learning technique. ADRMine outperforms several strong baseline systems in the ADR extraction task by achieving an F-measure of 0.82. Feature analysis demonstrates that the proposed word cluster features significantly improve extraction performance. It is possible to extract complex medical concepts, with relatively high performance, from informal, user-generated content. Our approach is particularly scalable, suitable for social media mining, as it relies on large volumes of unlabeled data, thus diminishing the need for large, annotated training data sets. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—

NASA Astrophysics Data System (ADS)

Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya

2018-05-01

We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.

A WISE Survey of New Star Clusters in the Central Plane Region of the Milky Way

NASA Astrophysics Data System (ADS)

Ryu, Jinhyuk; Lee, Myung Gyoon

2018-04-01

We present the discovery of new star clusters in the central plane region (| l| < 30^\\circ and | b| < 6^\\circ ) of the Milky Way. In order to overcome the extinction problem and the spatial limit of previous surveys, we use the Wide-field Infrared Survey Explorer (WISE) data to find clusters. We also use other infrared survey data in the archive for additional analysis. We find 923 new clusters, of which 202 clusters are embedded clusters. These clusters are concentrated toward the Galactic plane and show a symmetric distribution with respect to the Galactic latitude. The embedded clusters show a stronger concentration to the Galactic plane than the nonembedded clusters. The new clusters are found more in the first Galactic quadrant, while previously known clusters are found more in the fourth Galactic quadrant. The spatial distribution of the combined sample of known clusters and new clusters is approximately symmetric with respect to the Galactic longitude. We estimate reddenings, distances, and relative ages of the 15 class A clusters using theoretical isochrones. Ten of them are relatively old (age >800 Myr) and five are young (age ≈4 Myr).

The STREGA survey - II. Globular cluster Palomar 12

NASA Astrophysics Data System (ADS)

Musella, I.; Di Criscienzo, M.; Marconi, M.; Raimondo, G.; Ripepi, V.; Cignoni, M.; Bono, G.; Brocato, E.; Dall'Ora, M.; Ferraro, I.; Grado, A.; Iannicola, G.; Limatola, L.; Molinaro, R.; Moretti, M. I.; Stetson, P. B.; Capaccioli, M.; Cioni, M.-R. L.; Getman, F.; Schipani, P.

2018-01-01

In the framework of the STREGA (STRucture and Evolution of the GAlaxy) survey, two fields around the globular cluster Pal 12 were observed with the aim of detecting the possible presence of streams and/or an extended halo. The adopted stellar tracers are the main sequence, turn-off and red giant branch stars. We discuss the luminosity function and the star counts in the observed region covering about 2 tidal radii, confirming that Pal 12 appears to be embedded in the Sagittarius Stream. Adopting an original approach to separate cluster and field stars, we do not find any evidence of significant extra-tidal Pal 12 stellar populations. The presence of the Sagittarius stream seems to have mimicked a larger tidal radius in previous studies. Indeed, adopting a King model, a redetermination of this value gives rT = 0.22 ± 0.1 deg.

Near infrared photometric and optical spectroscopic study of 22 low mass star clusters embedded in nebulae

NASA Astrophysics Data System (ADS)

Soares, J. B.; Bica, E.; Ahumada, A. V.; Clariá, J. J.

2008-02-01

Aims:Among the star clusters in the Galaxy, those embedded in nebulae represent the youngest group, which has only recently been explored. The analysis of a sample of 22 candidate embedded stellar systems in reflection nebulae and/or HII environments is presented. Methods: We employed optical spectroscopic observations of stars in the directions of the clusters carried out at CASLEO (Argentina) together with near infrared photometry from the 2MASS catalogue. Our analysis is based on source surface density, colour-colour diagrams and on theoretical pre-main sequence isochrones. We take into account the field star contamination by carrying out a statistical subtraction. Results: The studied objects have the characteristics of low mass systems. We derive their fundamental parameters. Most of the cluster ages are younger than 2 Myr. The studied embedded stellar systems in reflection nebulae and/or HII region complexes do not have stars of spectral types earlier than B. The total stellar masses locked in the clusters are in the range 20-220 M⊙. They are found to be gravitationally unstable and are expected to dissolve in a timescale of a few Myr. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina and the National Universities of La Plata, Córdoba and San Juan, Argentina.

Nonlinear dimensionality reduction of data lying on the multicluster manifold.

PubMed

Meng, Deyu; Leung, Yee; Fung, Tung; Xu, Zongben

2008-08-01

A new method, which is called decomposition-composition (D-C) method, is proposed for the nonlinear dimensionality reduction (NLDR) of data lying on the multicluster manifold. The main idea is first to decompose a given data set into clusters and independently calculate the low-dimensional embeddings of each cluster by the decomposition procedure. Based on the intercluster connections, the embeddings of all clusters are then composed into their proper positions and orientations by the composition procedure. Different from other NLDR methods for multicluster data, which consider associatively the intracluster and intercluster information, the D-C method capitalizes on the separate employment of the intracluster neighborhood structures and the intercluster topologies for effective dimensionality reduction. This, on one hand, isometrically preserves the rigid-body shapes of the clusters in the embedding process and, on the other hand, guarantees the proper locations and orientations of all clusters. The theoretical arguments are supported by a series of experiments performed on the synthetic and real-life data sets. In addition, the computational complexity of the proposed method is analyzed, and its efficiency is theoretically analyzed and experimentally demonstrated. Related strategies for automatic parameter selection are also examined.

Nanocomposite TiN films with embedded MoS2 inorganic fullerenes produced by combining supersonic cluster beam deposition with cathodic arc reactive evaporation

NASA Astrophysics Data System (ADS)

Piazzoni, C.; Blomqvist, M.; Podestà, A.; Bardizza, G.; Bonati, M.; Piseri, P.; Milani, P.; Davies, C.; Hatto, P.; Ducati, C.; Sedláčková, K.; Radnóczi, G.

2008-01-01

We report the production and characterization of nanocomposite thin films consisting of a titanium nitride matrix with embedded molybdenum disulphide fullerene-like nanoparticles. This was achieved by combining a cluster source generating a pulsed supersonic beam of MoS2 clusters with an industrial cathodic arc reactive evaporation apparatus used for TiN deposition. Cluster-assembled films show the presence of MoS2 nanocages and nanostructures and the survival of such structures dispersed in the TiN matrix in the co-deposited samples. Nanotribological characterization by atomic force microscopy shows that the presence of MoS2 nanoparticles even in very low concentration modifies the behaviour of the TiN matrix.

Rotation in young massive star clusters

NASA Astrophysics Data System (ADS)

Mapelli, Michela

2017-05-01

Hydrodynamical simulations of turbulent molecular clouds show that star clusters form from the hierarchical merger of several sub-clumps. We run smoothed-particle hydrodynamics simulations of turbulence-supported molecular clouds with mass ranging from 1700 to 43 000 M⊙. We study the kinematic evolution of the main cluster that forms in each cloud. We find that the parent gas acquires significant rotation, because of large-scale torques during the process of hierarchical assembly. The stellar component of the embedded star cluster inherits the rotation signature from the parent gas. Only star clusters with final mass < few × 100 M⊙ do not show any clear indication of rotation. Our simulated star clusters have high ellipticity (˜0.4-0.5 at t = 4 Myr) and are subvirial (Qvir ≲ 0.4). The signature of rotation is stronger than radial motions due to subvirial collapse. Our results suggest that rotation is common in embedded massive (≳1000 M⊙) star clusters. This might provide a key observational test for the hierarchical assembly scenario.

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

Yu, Kuang; Libisch, Florian; Carter, Emily A., E-mail: eac@princeton.edu

We report a new implementation of the density functional embedding theory (DFET) in the VASP code, using the projector-augmented-wave (PAW) formalism. Newly developed algorithms allow us to efficiently perform optimized effective potential optimizations within PAW. The new algorithm generates robust and physically correct embedding potentials, as we verified using several test systems including a covalently bound molecule, a metal surface, and bulk semiconductors. We show that with the resulting embedding potential, embedded cluster models can reproduce the electronic structure of point defects in bulk semiconductors, thereby demonstrating the validity of DFET in semiconductors for the first time. Compared to ourmore » previous version, the new implementation of DFET within VASP affords use of all features of VASP (e.g., a systematic PAW library, a wide selection of functionals, a more flexible choice of U correction formalisms, and faster computational speed) with DFET. Furthermore, our results are fairly robust with respect to both plane-wave and Gaussian type orbital basis sets in the embedded cluster calculations. This suggests that the density functional embedding method is potentially an accurate and efficient way to study properties of isolated defects in semiconductors.« less

Designing flexible engineering systems utilizing embedded architecture options

NASA Astrophysics Data System (ADS)

Pierce, Jeff G.

This dissertation develops and applies an integrated framework for embedding flexibility in an engineered system architecture. Systems are constantly faced with unpredictability in the operational environment, threats from competing systems, obsolescence of technology, and general uncertainty in future system demands. Current systems engineering and risk management practices have focused almost exclusively on mitigating or preventing the negative consequences of uncertainty. This research recognizes that high uncertainty also presents an opportunity to design systems that can flexibly respond to changing requirements and capture additional value throughout the design life. There does not exist however a formalized approach to designing appropriately flexible systems. This research develops a three stage integrated flexibility framework based on the concept of architecture options embedded in the system design. Stage One defines an eight step systems engineering process to identify candidate architecture options. This process encapsulates the operational uncertainty though scenario development, traces new functional requirements to the affected design variables, and clusters the variables most sensitive to change. The resulting clusters can generate insight into the most promising regions in the architecture to embed flexibility in the form of architecture options. Stage Two develops a quantitative option valuation technique, grounded in real options theory, which is able to value embedded architecture options that exhibit variable expiration behavior. Stage Three proposes a portfolio optimization algorithm, for both discrete and continuous options, to select the optimal subset of architecture options, subject to budget and risk constraints. Finally, the feasibility, extensibility and limitations of the framework are assessed by its application to a reconnaissance satellite system development problem. Detailed technical data, performance models, and cost estimates were compiled for the Tactical Imaging Constellation Architecture Study and leveraged to complete a realistic proof-of-concept.

Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism

PubMed Central

Sood, Anup; Miller, Alexandra M.; Brogi, Edi; Sui, Yunxia; Armenia, Joshua; McDonough, Elizabeth; Santamaria-Pang, Alberto; Stamper, Aleksandra; Campos, Carl; Pang, Zhengyu; Li, Qing; Port, Elisa; Graeber, Thomas G.; Schultz, Nikolaus; Ginty, Fiona; Larson, Steven M.

2016-01-01

The phenotypic diversity of cancer results from genetic and nongenetic factors. Most studies of cancer heterogeneity have focused on DNA alterations, as technologies for proteomic measurements in clinical specimen are currently less advanced. Here, we used a multiplexed immunofluorescence staining platform to measure the expression of 27 proteins at the single-cell level in formalin-fixed and paraffin-embedded samples from treatment-naive stage II/III human breast cancer. Unsupervised clustering of protein expression data from 638,577 tumor cells in 26 breast cancers identified 8 clusters of protein coexpression. In about one-third of breast cancers, over 95% of all neoplastic cells expressed a single protein coexpression cluster. The remaining tumors harbored tumor cells representing multiple protein coexpression clusters, either in a regional distribution or intermingled throughout the tumor. Tumor uptake of the radiotracer 18F-fluorodeoxyglucose was associated with protein expression clusters characterized by hormone receptor loss, PTEN alteration, and HER2 gene amplification. Our study demonstrates an approach to generate cellular heterogeneity metrics in routinely collected solid tumor specimens and integrate them with in vivo cancer phenotypes. PMID:27182557

Stable dissipative optical vortex clusters by inhomogeneous effective diffusion.

PubMed

Li, Huishan; Lai, Shiquan; Qui, Yunli; Zhu, Xing; Xie, Jianing; Mihalache, Dumitru; He, Yingji

2017-10-30

We numerically show the generation of robust vortex clusters embedded in a two-dimensional beam propagating in a dissipative medium described by the generic cubic-quintic complex Ginzburg-Landau equation with an inhomogeneous effective diffusion term, which is asymmetrical in the two transverse directions and periodically modulated in the longitudinal direction. We show the generation of stable optical vortex clusters for different values of the winding number (topological charge) of the input optical beam. We have found that the number of individual vortex solitons that form the robust vortex cluster is equal to the winding number of the input beam. We have obtained the relationships between the amplitudes and oscillation periods of the inhomogeneous effective diffusion and the cubic gain and diffusion (viscosity) parameters, which depict the regions of existence and stability of vortex clusters. The obtained results offer a method to form robust vortex clusters embedded in two-dimensional optical beams, and we envisage potential applications in the area of structured light.

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

PubMed

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Syndrome Surveillance Using Parametric Space-Time Clustering

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

KOCH, MARK W.; MCKENNA, SEAN A.; BILISOLY, ROGER L.

2002-11-01

As demonstrated by the anthrax attack through the United States mail, people infected by the biological agent itself will give the first indication of a bioterror attack. Thus, a distributed information system that can rapidly and efficiently gather and analyze public health data would aid epidemiologists in detecting and characterizing emerging diseases, including bioterror attacks. We propose using clusters of adverse health events in space and time to detect possible bioterror attacks. Space-time clusters can indicate exposure to infectious diseases or localized exposure to toxins. Most space-time clustering approaches require individual patient data. To protect the patient's privacy, we havemore » extended these approaches to aggregated data and have embedded this extension in a sequential probability ratio test (SPRT) framework. The real-time and sequential nature of health data makes the SPRT an ideal candidate. The result of space-time clustering gives the statistical significance of a cluster at every location in the surveillance area and can be thought of as a ''health-index'' of the people living in this area. As a surrogate to bioterrorism data, we have experimented with two flu data sets. For both databases, we show that space-time clustering can detect a flu epidemic up to 21 to 28 days earlier than a conventional periodic regression technique. We have also tested using simulated anthrax attack data on top of a respiratory illness diagnostic category. Results show we do very well at detecting an attack as early as the second or third day after infected people start becoming severely symptomatic.« less

Density-Difference-Driven Optimized Embedding Potential Method To Study the Spectroscopy of Br₂ in Water Clusters.

PubMed

Roncero, Octavio; Aguado, Alfredo; Batista-Romero, Fidel A; Bernal-Uruchurtu, Margarita I; Hernández-Lamoneda, Ramón

2015-03-10

A variant of the density difference driven optimized embedding potential (DDD-OEP) method, proposed by Roncero et al. (J. Chem. Phys. 2009, 131, 234110), has been applied to the calculation of excited states of Br2 within small water clusters. It is found that the strong interaction of Br2 with the lone electronic pair of the water molecules makes necessary to optimize specific embedding potentials for ground and excited electronic states, separately and using the corresponding densities. Diagnosis and convergence studies are presented with the aim of providing methods to be applied for the study of chromophores in solution. Also, some preliminary results obtained for the study of electronic states of Br2 in clathrate cages are presented.

a Probabilistic Embedding Clustering Method for Urban Structure Detection

NASA Astrophysics Data System (ADS)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, Stephen P.

1987-01-01

The results of ab-initio calculations are reported for (1) small transition metal clusters and (2) potential energy surfaces for chemical reactions important in hydrogen combustion and high temperature air chemistry.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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

PubMed

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

2015-09-14

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

SAFT-assisted sound beam focusing using phased arrays (PA-SAFT) for non-destructive evaluation

NASA Astrophysics Data System (ADS)

Nanekar, Paritosh; Kumar, Anish; Jayakumar, T.

2015-04-01

Focusing of sound has always been a subject of interest in ultrasonic non-destructive evaluation. An integrated approach to sound beam focusing using phased array and synthetic aperture focusing technique (PA-SAFT) has been developed in the authors' laboratory. The approach involves SAFT processing on ultrasonic B-scan image collected by a linear array transducer using a divergent sound beam. The objective is to achieve sound beam focusing using fewer elements than the ones required using conventional phased array. The effectiveness of the approach is demonstrated on aluminium blocks with artificial flaws and steel plate samples with embedded volumetric weld flaws, such as slag and clustered porosities. The results obtained by the PA-SAFT approach are found to be comparable to those obtained by conventional phased array and full matrix capture - total focusing method approaches.

Positronic probe of vacancy defects on surfaces of Au nanoparticles embedded in MgO

NASA Astrophysics Data System (ADS)

Xu, Jun; Moxom, J.; Somieski, B.; White, C. W.; Mills, A. P., Jr.; Suzuki, R.; Ishibashi, S.

2001-09-01

Clusters of four atomic vacancies were found in Au nanoparticle-embedded MgO by positron lifetime spectroscopy [Phys. Rev. Lett. 83, 4586 (1999)]. These clusters were also suggested to locate at the surface of Au nanoparticles by one-detector measurements of Doppler broadening of annihilation radiation. In this work we provide evidence, using two-detector coincidence experiments of Doppler broadening (2D-DBAR), to clarify that these vacancy clusters reside on the surfaces of Au nanoparticles. This work also demonstrates a method for identifying defects at nanomaterials interfaces: a combination of both positron lifetime spectroscopy, which tells the type of the defects, and 2D-DBAR measurements, which reveals chemical environment of the defects.

The Formation and Early Evolution of Embedded Massive Star Clusters

NASA Astrophysics Data System (ADS)

Barnes, Peter

We propose to combine Spitzer, WISE, Herschel, and other archival spacecraft data with an existing ground- and space-based mm-wave to near-IR survey of molecular clouds over a large portion of the Milky Way, in order to systematically study the formation and early evolution of massive stars and star clusters, and provide new observational calibrations for a theoretical paradigm of this key astrophysical problem. Central Objectives: The Galactic Census of High- and Medium-mass Protostars (CHaMP) is a large, unbiased, uniform, and panchromatic survey of massive star and cluster formation and early evolution, covering 20°x6° of the Galactic Plane. Its uniqueness lies in the comprehensive molecular spectroscopy of 303 massive dense clumps, which have also been included in several archival spacecraft surveys. Our objective is a systematic demographic analysis of massive star and cluster formation, one which has not been possible without knowledge of our CHaMP cloud sample, including all clouds with embedded clusters as well as those that have not yet formed massive stars. For proto-clusters deeply embedded within dense molecular clouds, analysis of these space-based data will: 1. Yield a complete census of Young Stellar Objects in each cluster. 2. Allow systematic measurements of embedded cluster properties: spectral energy distributions, luminosity functions, protostellar and disk fractions, and how these vary with cluster mass, age, and density. Combined with other, similarly complete and unbiased infrared and mm data, CHaMP's goals include: 3. A detailed comparison of the embedded stellar populations with their natal dense gas to derive extinction maps, star formation efficiencies and feedback effects, and the kinematics, physics, and chemistry of the gas in and around the clusters. 4. Tying the demographics, age spreads, and timescales of the clusters, based on pre-Main Sequence evolution, to that of the dense gas clumps and Giant Molecular Clouds. 5. A measurement of the local star formation rate per gas mass surface density in the Milky Way, as well as examining arm versus interarm dependencies. Methods and Techniques: We will primarily use archival cryogenic-Spitzer, WISE, and Herschel data, and support this with existing data from ground- and space-based facilities, to conduct a comprehensive assay of critical metrics (as above) and provide observational calibration of theoretical models over the entire massive star formation process. The mm-wave molecular maps of 303 dense gas clumps in multiple species, comprising all the gas above a column density limit of 100 Msun/pc^2, are already inhand. We have also surveyed the embedded stellar content of these clumps, down to subsolar masses, in the near-infrared J, H, and K bands and with deep Warm Spitzer data. Relevance to NASA programs: Analysis to date of the space- and ground-based data has yielded several new insights into evolutionary timescales and the chemical & energy evolution of clumps during the cluster formation process. Investigations as described in this proposal will yield new demographic insights on how the properties and evolution of molecular clouds relate to the properties of massive stars and clusters that form within them, and significantly enhance the science return from these spacecraft missions. The large number of resulting data products are already being made publicly available to the astronomical community, providing crucial information for future NASA science targets. This research will be performed within the framework of a broad international collaboration spanning four continents. This ambitious but practical program will therefore maximise the science payoff from these archival data sets, provide enhanced legacy data for more advanced studies with the next generation of ground- and space-based instruments such as JWST, and open up several new windows into the discovery space of Galactic star formation & interstellar medium studies.

Electron-induced chemistry in imidazole clusters embedded in helium nanodroplets

NASA Astrophysics Data System (ADS)

Kuhn, Martin; Raggl, Stefan; Martini, Paul; Gitzl, Norbert; Darian, Masoomeh Mahmoodi; Goulart, Marcelo; Postler, Johannes; Feketeová, Linda; Scheier, Paul

2018-02-01

Electron-induced chemistry in imidazole (IMI) clusters embedded in helium nanodroplets (with an average size of 2 × 105 He atoms) has been investigated with high-resolution time-of-flight mass spectrometry. The formation of both, negative and positive, ions was monitored as a function of the cluster size n. In both ion spectra a clear series of peaks with IMI cluster sizes up to at least 25 are observed. While the anions are formed by collisions of IMI n with He*-, the cations are formed through ionization of IMI n by He+ as the measured onset for the cation formation is observed at 24.6 eV (ionization energy of He). The most abundant series of anions are dehydrogenated anions IMI n-1(IMI-H)-, while other anion series are IMI clusters involving CN and C2H4 moieties. The formation of cations is dominated by the protonated cluster ions IMI n H+, while the intensity of parent cluster cations IMI n + is also observed preferentially for the small cluster size n. The observation of series of cluster cations [IMI n CH3]+ suggests either CH3+ cation to be solvated by n neutral IMI molecules, or the electron-induced chemistry has led to the formation of protonated methyl-imidazole solvated by ( n - 1) neutral IMI molecules.

Cross-entropy clustering framework for catchment classification

NASA Astrophysics Data System (ADS)

Tongal, Hakan; Sivakumar, Bellie

2017-09-01

There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

Beam power-dependent laser-induced fluorescence radiation quenching of silver-ion-exchanged glasses

NASA Astrophysics Data System (ADS)

Nahal, Arashmid; Khalesifard, Hamid Reza M.

2007-04-01

In this article, results of an investigation about the modification of silver ions embedded in a glass matrix under the action of a CW high-power Ar + laser beam, by means of laser-induced fluorescence, is reported. It is known [A. Nahal, H.R.M. Khalesifard, J. Mostafavi-Amjad, Appl. Phys. B 79 (2004) 513-518] that, as a result of the interaction of the laser beam with the sample, the embedded silver ions reduce to neutral ones and silver clusters are formed. We observed that the fluorescence radiation of the central part of the interaction area, on the sample, diminishes simultaneously with the formation of the neutral clusters. Further increase in the exposure time or the power of the beam results in reappearance of the fluorescence radiation, in the central part of the interaction area. We found that, during and after the interaction the spectrum of the fluorescence radiation changes. This makes it possible to study the laser-induced changes in the embedded silver ions and clusters, in real-time.

Image method for electrostatic energy of polarizable dipolar spheres

NASA Astrophysics Data System (ADS)

Gustafson, Kyle S.; Xu, Guoxi; Freed, Karl F.; Qin, Jian

2017-08-01

The multiple-scattering theory for the electrostatics of many-body systems of monopolar spherical particles, embedded in a dielectric medium, is generalized to describe the electrostatics of these particles with embedded dipoles and multipoles. The Neumann image line construction for the electrostatic polarization produced by one particle is generalized to compute the energy, forces, and torques for the many-body system as functions of the positions of the particles. The approach is validated by comparison with direct numerical calculation, and the convergence rate is analyzed and expressed in terms of the discontinuity in dielectric contrast and particle density. As an illustration of this formalism, the stability of small particle clusters is analyzed. The theory is developed in a form that can readily be adapted to Monte Carlo and molecular dynamics simulations for polarizable particles and, more generally, to study the interactions among polarizable molecules.

A Kinematic Survey in the Perseus Molecular Cloud: Results from the APOGEE Infrared Survey of Young Nebulous Clusters (IN-SYNC)

NASA Astrophysics Data System (ADS)

Covey, Kevin R.; Cottaar, M.; Foster, J. B.; Nidever, D. L.; Meyer, M.; Tan, J.; Da Rio, N.; Flaherty, K. M.; Stassun, K.; Frinchaboy, P. M.; Majewski, S.; APOGEE IN-SYNC Team

2014-01-01

Demographic studies of stellar clusters indicate that relatively few persist as bound structures for 100 Myrs or longer. If cluster dispersal is a 'violent' process, it could strongly influence the formation and early evolution of stellar binaries and planetary systems. Unfortunately, measuring the dynamical state of 'typical' (i.e., ~300-1000 member) young star clusters has been difficult, particularly for clusters still embedded within their parental molecular cloud. The near-infrared spectrograph for the Apache Point Observatory Galactic Evolution Experiment (APOGEE), which can measure precise radial velocities for 230 cluster stars simultaneously, is uniquely suited to diagnosing the dynamics of Galactic star formation regions. We give an overview of the INfrared Survey of Young Nebulous Clusters (IN-SYNC), an APOGEE ancillary science program that is carrying out a comparative study of young clusters in the Perseus molecular cloud: NGC 1333, a heavily embedded cluster, and IC 348, which has begun to disperse its surrounding molecular gas. These observations appear to rule out a significantly super-virial velocity dispersion in IC 348, contrary to predictions of models where a cluster's dynamics is strongly influenced by the dispersal of its primordial gas. We also summarize the properties of two newly identified spectroscopic binaries; binary systems such as these play a key role in the dynamical evolution of young clusters, and introduce velocity offsets that must be accounted for in measuring cluster velocity dispersions.

Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

PubMed Central

2012-01-01

Background Dimensionality reduction (DR) enables the construction of a lower dimensional space (embedding) from a higher dimensional feature space while preserving object-class discriminability. However several popular DR approaches suffer from sensitivity to choice of parameters and/or presence of noise in the data. In this paper, we present a novel DR technique known as consensus embedding that aims to overcome these problems by generating and combining multiple low-dimensional embeddings, hence exploiting the variance among them in a manner similar to ensemble classifier schemes such as Bagging. We demonstrate theoretical properties of consensus embedding which show that it will result in a single stable embedding solution that preserves information more accurately as compared to any individual embedding (generated via DR schemes such as Principal Component Analysis, Graph Embedding, or Locally Linear Embedding). Intelligent sub-sampling (via mean-shift) and code parallelization are utilized to provide for an efficient implementation of the scheme. Results Applications of consensus embedding are shown in the context of classification and clustering as applied to: (1) image partitioning of white matter and gray matter on 10 different synthetic brain MRI images corrupted with 18 different combinations of noise and bias field inhomogeneity, (2) classification of 4 high-dimensional gene-expression datasets, (3) cancer detection (at a pixel-level) on 16 image slices obtained from 2 different high-resolution prostate MRI datasets. In over 200 different experiments concerning classification and segmentation of biomedical data, consensus embedding was found to consistently outperform both linear and non-linear DR methods within all applications considered. Conclusions We have presented a novel framework termed consensus embedding which leverages ensemble classification theory within dimensionality reduction, allowing for application to a wide range of high-dimensional biomedical data classification and segmentation problems. Our generalizable framework allows for improved representation and classification in the context of both imaging and non-imaging data. The algorithm offers a promising solution to problems that currently plague DR methods, and may allow for extension to other areas of biomedical data analysis. PMID:22316103

A populous intermediate-age open cluster and evidence of an embedded cluster among the FSR globular cluster candidates

NASA Astrophysics Data System (ADS)

Bica, E.; Bonatto, C.

2008-03-01

We study the nature of the globular cluster (GC) candidates FSR 1603 and FSR1755 selected from the catalogue of Froebrich, Scholz & Raftery. Their properties are investigated with Two-Micron All-Sky Survey field-star decontaminated photometry, which is used to build colour-magnitude diagrams (CMDs) and stellar radial density profiles. FSR1603 has the open cluster Ruprecht 101 as optical counterpart, and we show it to be a massive intermediate-age cluster. Relevant parameters of FSR1603 are the age ~1Gyr, distance from the Sun dsolar ~ 2.7kpc, Galactocentric distance RGC ~ 6.4kpc, core radius RC ~ 1.1pc, mass function slope χ ~ 1.8, observed stellar mass (for stars with mass in the range 1.27 <= m <= 2.03Msolar) Mobs ~ 500Msolar and a total (extrapolated to m = 0.08Msolar) stellar mass Mtot ~ 2300Msolar. FSR1755, on the other hand, is not a populous cluster. It may be a sparse young cluster embedded in the HII region Sh2-3, subject to an absorption AV ~ 4.1, located at dsolar ~ 1.3kpc. Important field-star contamination, spatially variable heavy dust obscuration, even in Ks, and gas emission characterize its field. A nearly vertical, sparse blue stellar sequence shows up in the CMDs.

Final Technical Report for Quantum Embedding for Correlated Electronic Structure in Large Systems and the Condensed Phase

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

Chan, Garnet Kin-Lic

2017-04-30

This is the final technical report. We briefly describe some selected results below. Developments in density matrix embedding. DMET is a quantum embedding theory that we introduced at the beginning of the last funding period, around 2012-2013. Since the first DMET papers, which demonstrated proof-of- principle calculations on the Hubbard model and hydrogen rings, we have carried out a number of different developments, including: Extending the DMET technology to compute broken symmetry phases, including magnetic phases and super- conductivity (Pub. 13); Calibrating the accuracy of DMET and its cluster size convergence against other methods, and formulation of a dynamical clustermore » analog (Pubs. 4, 10) (see Fig. 1); Implementing DMET for ab-initio molecular calculations, and exploring different self-consistency criteria (Pubs. 9, 14); Using embedding to defi ne quantum classical interfaces Pub. 2; Formulating DMET for spectral functions (Pub. 7) (see Fig. 1); Extending DMET to coupled fermion-boson problems (Pub. 12). Together with these embedding developments, we have also implemented a wide variety of impurity solvers within our DMET framework, including DMRG (Pub. 3), AFQMC (Pub. 10), and coupled cluster theory (CC) (Pub. 9).« less

Solvation effects on chemical shifts by embedded cluster integral equation theory.

PubMed

Frach, Roland; Kast, Stefan M

2014-12-11

The accurate computational prediction of nuclear magnetic resonance (NMR) parameters like chemical shifts represents a challenge if the species studied is immersed in strongly polarizing environments such as water. Common approaches to treating a solvent in the form of, e.g., the polarizable continuum model (PCM) ignore strong directional interactions such as H-bonds to the solvent which can have substantial impact on magnetic shieldings. We here present a computational methodology that accounts for atomic-level solvent effects on NMR parameters by extending the embedded cluster reference interaction site model (EC-RISM) integral equation theory to the prediction of chemical shifts of N-methylacetamide (NMA) in aqueous solution. We examine the influence of various so-called closure approximations of the underlying three-dimensional RISM theory as well as the impact of basis set size and different treatment of electrostatic solute-solvent interactions. We find considerable and systematic improvement over reference PCM and gas phase calculations. A smaller basis set in combination with a simple point charge model already yields good performance which can be further improved by employing exact electrostatic quantum-mechanical solute-solvent interaction energies. A larger basis set benefits more significantly from exact over point charge electrostatics, which can be related to differences of the solvent's charge distribution.

Binaries at Birth: Stellar multiplicity in embedded clusters from radial velocity variations in the IN-SYNC survey

NASA Astrophysics Data System (ADS)

Oskar Jaehnig, Karl; Stassun, Keivan; Tan, Jonathan C.; Covey, Kevin R.; Da Rio, Nicola

2016-01-01

We study the nature of stellar multiplicity in young stellar systems using the INfrared Spectroscopy of Young Nebulous Clusters (IN-SYNC) survey, carried out in SDSS III with the APOGEE spectrograph. Multi-epoch observations of thousands of low-mass stars in Orion A, NGC2264, NGC1333 and IC348 have been carried out, yielding H-band spectra with R=22,500 for sources with H<12 mag. Radial velocity sensitivities ~0.3 km/s can be achieved, depending on the spectral type of the star. We search the IN-SYNC radial velocity catalog to identify sources with radial velocity variations indicative of spectroscopically undetected companions, analyze their spectral properties and discuss the implications for the overall multiplicity of stellar populations in young, embedded star clusters.

Electron and hole stability in GaN and ZnO.

PubMed

Walsh, Aron; Catlow, C Richard A; Miskufova, Martina; Sokol, Alexey A

2011-08-24

We assess the thermodynamic doping limits of GaN and ZnO on the basis of point defect calculations performed using the embedded cluster approach and employing a hybrid non-local density functional for the quantum mechanical region. Within this approach we have calculated a staggered (type-II) valence band alignment between the two materials, with the N 2p states contributing to the lower ionization potential of GaN. With respect to the stability of free electron and hole carriers, redox reactions resulting in charge compensation by ionic defects are found to be largely endothermic (unfavourable) for electrons and exothermic (favourable) for holes, which is consistent with the efficacy of electron conduction in these materials. Approaches for overcoming these fundamental thermodynamic limits are discussed. © 2011 IOP Publishing Ltd

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data.

PubMed

Mwangi, Benson; Soares, Jair C; Hasan, Khader M

2014-10-30

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamical evolution of stars and gas of young embedded stellar sub-clusters

NASA Astrophysics Data System (ADS)

Sills, Alison; Rieder, Steven; Scora, Jennifer; McCloskey, Jessica; Jaffa, Sarah

2018-06-01

We present simulations of the dynamical evolution of young embedded star clusters. Our initial conditions are directly derived from X-ray, infrared, and radio observations of local systems, and our models evolve both gas and stars simultaneously. Our regions begin with both clustered and extended distributions of stars, and a gas distribution that can include a filamentary structure in addition to gas surrounding the stellar sub-clusters. We find that the regions become spherical, monolithic, and smooth quite quickly, and that the dynamical evolution is dominated by the gravitational interactions between the stars. In the absence of stellar feedback, the gas moves gently out of the centre of our regions but does not have a significant impact on the motions of the stars at the earliest stages of cluster formation. Our models at later times are consistent with observations of similar regions in the local neighbourhood. We conclude that the evolution of young protostar clusters is relatively insensitive to reasonable choices of initial conditions. Models with more realism, such as an initial population of binary and multiple stars and ongoing star formation, are the next step needed to confirm these findings.

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

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

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

2015-09-14

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

An Introverted Starburst: Gas and SSC Formation in NGC 5253

NASA Astrophysics Data System (ADS)

Turner, J. L.; Beck, S. C.

2004-06-01

High resolution Brackett line spectroscopy with the Keck Telescope reveals relatively narrow recombination lines toward the embedded young super star cluster nebula in NGC 5253. The gas within this nebula is almost certainly gravitationally bound by the massive and compact young star cluster.

Electron interaction with nitromethane embedded in helium droplets: attachment and ionization measurements.

PubMed

Ferreira da Silva, F; Ptasińska, S; Denifl, S; Gschliesser, D; Postler, J; Matias, C; Märk, T D; Limão-Vieira, P; Scheier, P

2011-11-07

Results of a detailed study on electron interactions with nitromethane (CH(3)NO(2)) embedded in helium nanodroplets are reported. Anionic and cationic products formed are analysed by mass spectrometry. When the doped helium droplets are irradiated with low-energy electrons of about 2 eV kinetic energy, exclusively parent cluster anions (CH(3)NO(2))(n)(-) are formed. At 8.5 eV, three anion cluster series are observed, i.e., (CH(3)NO(2))(n)(-), [(CH(3)NO(2))(n)-H](-), and (CH(3)NO(2))(n)NO(2)(-), the latter being the most abundant. The results obtained for anions are compared with previous electron attachment studies with bare nitromethane and nitromethane condensed on a surface. The cation chemistry (induced by electron ionization of the helium matrix at 70 eV and subsequent charge transfer from He(+) to the dopant cluster) is dominated by production of methylated and protonated nitromethane clusters, (CH(3)NO(2))(n)CH(3)(+) and (CH(3)NO(2))(n)H(+).

Potential of transition metal atoms embedded in buckled monolayer g-C3N4 as single-atom catalysts.

PubMed

Li, Shu-Long; Yin, Hui; Kan, Xiang; Gan, Li-Yong; Schwingenschlögl, Udo; Zhao, Yong

2017-11-15

We use first-principles calculations to systematically explore the potential of transition metal atoms (Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Ru, Rh, Pd, Ag, Ir, Pt, and Au) embedded in buckled monolayer g-C 3 N 4 as single-atom catalysts. We show that clustering of Sc and Ti on g-C 3 N 4 is thermodynamically impeded and that V, Cr, Mn, and Cu are much less susceptible to clustering than the other TM atoms under investigation. Strong bonding of the transition metal atoms in the cavities of g-C 3 N 4 and high diffusion barriers together are responsible for single-atom fixation. Analysis of the CO oxidation process indicates that embedding of Cr and Mn in g-C 3 N 4 gives rise to promising single-atom catalysts at low temperature.

Hydrogen-vacancy-dislocation interactions in α-Fe

NASA Astrophysics Data System (ADS)

Tehranchi, A.; Zhang, X.; Lu, G.; Curtin, W. A.

2017-02-01

Atomistic simulations of the interactions between dislocations, hydrogen atoms, and vacancies are studied to assess the viability of a recently proposed mechanism for the formation of nanoscale voids in Fe-based steels in the presence of hydrogen. Quantum-mechanics/molecular-mechanics method calculations confirm molecular statics simulations based on embedded atom method (EAM) potential showing that individual vacancies on the compressive side of an edge dislocation can be transported with the dislocation as it glides. Molecular dynamics simulations based on EAM potential then show, however, that vacancy clusters in the glide plane of an approaching dislocation are annihilated or reduced in size by the creation of a double-jog/climb process that is driven by the huge reduction in energy accompanying vacancy annihilation. The effectiveness of annihilation/reduction processes is not reduced by the presence of hydrogen in the vacancy clusters because typical V-H cluster binding energies are much lower than the vacancy formation energy, except at very high hydrogen content in the cluster. Analysis of a range of configurations indicates that hydrogen plays no special role in stabilizing nanovoids against jog formation processes that shrink voids. Experimental observations of nanovoids on the fracture surfaces of steels must be due to as-yet undetermined processes.

X-ray absorption in insulators with non-Hermitian real-time time-dependent density functional theory.

PubMed

Fernando, Ranelka G; Balhoff, Mary C; Lopata, Kenneth

2015-02-10

Non-Hermitian real-time time-dependent density functional theory was used to compute the Si L-edge X-ray absorption spectrum of α-quartz using an embedded finite cluster model and atom-centered basis sets. Using tuned range-separated functionals and molecular orbital-based imaginary absorbing potentials, the excited states spanning the pre-edge to ∼20 eV above the ionization edge were obtained in good agreement with experimental data. This approach is generalizable to TDDFT studies of core-level spectroscopy and dynamics in a wide range of materials.

A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets.

PubMed

Panta, Sandeep R; Wang, Runtang; Fries, Jill; Kalyanam, Ravi; Speer, Nicole; Banich, Marie; Kiehl, Kent; King, Margaret; Milham, Michael; Wager, Tor D; Turner, Jessica A; Plis, Sergey M; Calhoun, Vince D

2016-01-01

In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI) scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS). We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE) algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets. Finally, we interactively display the output of this approach via a web-page, based on data driven documents (D3) JavaScript library. Two distinct approaches were used to visualize the data. In the first approach, we computed multiple quality control (QC) values from pre-processed data, which were used as inputs to the t-SNE algorithm. This approach helps in assessing the quality of each data set relative to others. In the second case, computed variables of interest (e.g., brain volume or voxel values from segmented gray matter images) were used as inputs to the t-SNE algorithm. This approach helps in identifying interesting patterns in the data sets. We demonstrate these approaches using multiple examples from over 10,000 data sets including (1) quality control measures calculated from phantom data over time, (2) quality control data from human functional MRI data across various studies, scanners, sites, (3) volumetric and density measures from human structural MRI data across various studies, scanners and sites. Results from (1) and (2) show the potential of our approach to combine t-SNE data reduction with interactive color coding of variables of interest to quickly identify visually unique clusters of data (i.e., data sets with poor QC, clustering of data by site) quickly. Results from (3) demonstrate interesting patterns of gray matter and volume, and evaluate how they map onto variables including scanners, age, and gender. In sum, the proposed approach allows researchers to rapidly identify and extract meaningful information from big data sets. Such tools are becoming increasingly important as datasets grow larger.

Topological analysis of group fragmentation in multiagent systems

NASA Astrophysics Data System (ADS)

DeLellis, Pietro; Porfiri, Maurizio; Bollt, Erik M.

2013-02-01

In social animals, the presence of conflicts of interest or multiple leaders can promote the emergence of two or more subgroups. Such subgroups are easily recognizable by human observers, yet a quantitative and objective measure of group fragmentation is currently lacking. In this paper, we explore the feasibility of detecting group fragmentation by embedding the raw data from the individuals' motions on a low-dimensional manifold and analyzing the topological features of this manifold. To perform the embedding, we employ the isomap algorithm, which is a data-driven machine learning tool extensively used in computer vision. We implement this procedure on a data set generated by a modified à la Vicsek model, where agents are partitioned into two or more subsets and an independent leader is assigned to each subset. The dimensionality of the embedding manifold is shown to be a measure of the number of emerging subgroups in the selected observation window and a cluster analysis is proposed to aid the interpretation of these findings. To explore the feasibility of using this approach to characterize group fragmentation in real time and thus reduce the computational cost in data processing and storage, we propose an interpolation method based on an inverse mapping from the embedding space to the original space. The effectiveness of the interpolation technique is illustrated on a test-bed example with potential impact on the regulation of collective behavior of animal groups using robotic stimuli.

CLUSTER DYNAMICS LARGELY SHAPES PROTOPLANETARY DISK SIZES

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

Vincke, Kirsten; Pfalzner, Susanne, E-mail: kvincke@mpifr-bonn.mpg.de

2016-09-01

To what degree the cluster environment influences the sizes of protoplanetary disks surrounding young stars is still an open question. This is particularly true for the short-lived clusters typical for the solar neighborhood, in which the stellar density and therefore the influence of the cluster environment change considerably over the first 10 Myr. In previous studies, the effect of the gas on the cluster dynamics has often been neglected; this is remedied here. Using the code NBody6++, we study the stellar dynamics in different developmental phases—embedded, expulsion, and expansion—including the gas, and quantify the effect of fly-bys on the diskmore » size. We concentrate on massive clusters (M {sub cl} ≥ 10{sup 3}–6 ∗ 10{sup 4} M {sub Sun}), which are representative for clusters like the Orion Nebula Cluster (ONC) or NGC 6611. We find that not only the stellar density but also the duration of the embedded phase matters. The densest clusters react fastest to the gas expulsion and drop quickly in density, here 98% of relevant encounters happen before gas expulsion. By contrast, disks in sparser clusters are initially less affected, but because these clusters expand more slowly, 13% of disks are truncated after gas expulsion. For ONC-like clusters, we find that disks larger than 500 au are usually affected by the environment, which corresponds to the observation that 200 au-sized disks are common. For NGC 6611-like clusters, disk sizes are cut-down on average to roughly 100 au. A testable hypothesis would be that the disks in the center of NGC 6611 should be on average ≈20 au and therefore considerably smaller than those in the ONC.« less

Destructive Clustering of Metal Nanoparticles in Chalcogenide and Oxide Glassy Matrices.

PubMed

Shpotyuk, M V; Shpotyuk, O I; Cebulski, J; Kozyukhin, S

2016-12-01

The energetic χ-criterion is developed to parameterize difference in the origin of high-order optical non-linearity associated with metallic atoms (Cu, Ag, Au) embedded destructively in oxide- and chalcogenide glasses. Within this approach, it is unambiguously proved that covalent-bonded networks of soft semiconductor chalcogenides exemplified by binary As(Ge)-S(Se) glasses differ essentially from those typical for hard dielectric oxides like vitreous silica by impossibility to accommodate pure agglomerates of metallic nanoparticles. In an excellence according to known experimental data, it is suggested that destructive clustering of nanoparticles is possible in Cu-, Ag-, and Au-ion-implanted dielectric oxide glass media, possessing a strongly negative χ-criterion. Some recent speculations trying to ascribe equally this ability to soft chalcogenide glasses despite an obvious difference in the corresponding bond dissociation energies have been disclosed and criticized as inconclusive.

W49A: A Massive Molecular Cloud Forming a Massive Star Cluster in the Galactic Disk

NASA Astrophysics Data System (ADS)

Galvan-Madrid, Roberto; Liu, Hauyu Baobab; Pineda, Jaime E.; Zhang, Zhi-Yu; Ginsburg, Adam; Roman-Zuñiga, Carlos; Peters, Thomas

2015-08-01

I summarize our current results of the MUSCLE survey of W49A, the most luminous star formation region in the Milky Way. Our approach emphasizes multi-scale, multi-resolution imaging in dust, ionized-, and molecular gas, to trace the multiple gas components from <0.1 pc (core scale) all the way up to the scale of the entire giant molecular cloud (GMC), ˜100 pc. The 106 M⊙ GMC is structured in a radial network of filaments that converges toward the central 'hub' with ˜2x105 M⊙, which contains within a few pc a deeply embedded young massive cluster (YMC) of stellar mass ~5x104 M⊙. We also discuss the dynamics of the filamentary network, the role of turbulence in the formation of this YMC, and how objects like W49A can link Milky Way and extragalactic star formation relations.

Molybdenum cluster loaded PLGA nanoparticles: An innovative theranostic approach for the treatment of ovarian cancer.

PubMed

Brandhonneur, N; Hatahet, T; Amela-Cortes, M; Molard, Y; Cordier, S; Dollo, G

2018-04-01

We evaluate poly (d,l-lactide-co-glycolide) (PLGA) nanoparticles embedding inorganic molybdenum octahedral cluster for photodynamic therapy of cancer (PDT). Tetrabutyl ammonium salt of Mo 6 Br 14 cluster unit, (TBA) 2 Mo 6 Br 14 , presents promising photosensitization activity in the destruction of targeted cancer cells. Stable cluster loaded nanoparticles (CNPs) were prepared by solvent displacement method showing spherical shapes, zeta potential values around -30 mV, polydispersity index lower than 0.2 and sizes around 100 nm. FT-IR and DSC analysis revealed the lack of strong chemical interaction between the cluster and the polymer within the nanoparticles. In vitro release study showed that (TBA) 2 Mo 6 Br 14 was totally dissolved in 20 min, while CNPs were able to control the release of encapsulated cluster. In vitro cellular viability studies conducted on A2780 ovarian cancer cell line treated up to 72 h with cluster or CNPs did not show any sign of toxicity in concentrations up to 20 µg/ml. This concentration was selected for photo-activation test on A2780 cells and CNPs were able to generate oxygen singlet resulting in a decrease of the cellular viability up to 50%, respectively compared to non-activated conditions. This work presents (TBA) 2 Mo 6 Br 14 as a novel photosensitizer for PDT and suggests PLGA nanoparticles as an efficient delivery system intended for tumor targeting. Copyright © 2018 Elsevier B.V. All rights reserved.

Data embedding employing degenerate clusters of data having differences less than noise value

DOEpatents

Sanford, II, Maxwell T.; Handel, Theodore G.

1998-01-01

A method of embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user.

Information extraction from dynamic PS-InSAR time series using machine learning

NASA Astrophysics Data System (ADS)

van de Kerkhof, B.; Pankratius, V.; Chang, L.; van Swol, R.; Hanssen, R. F.

2017-12-01

Due to the increasing number of SAR satellites, with shorter repeat intervals and higher resolutions, SAR data volumes are exploding. Time series analyses of SAR data, i.e. Persistent Scatterer (PS) InSAR, enable the deformation monitoring of the built environment at an unprecedented scale, with hundreds of scatterers per km2, updated weekly. Potential hazards, e.g. due to failure of aging infrastructure, can be detected at an early stage. Yet, this requires the operational data processing of billions of measurement points, over hundreds of epochs, updating this data set dynamically as new data come in, and testing whether points (start to) behave in an anomalous way. Moreover, the quality of PS-InSAR measurements is ambiguous and heterogeneous, which will yield false positives and false negatives. Such analyses are numerically challenging. Here we extract relevant information from PS-InSAR time series using machine learning algorithms. We cluster (group together) time series with similar behaviour, even though they may not be spatially close, such that the results can be used for further analysis. First we reduce the dimensionality of the dataset in order to be able to cluster the data, since applying clustering techniques on high dimensional datasets often result in unsatisfying results. Our approach is to apply t-distributed Stochastic Neighbor Embedding (t-SNE), a machine learning algorithm for dimensionality reduction of high-dimensional data to a 2D or 3D map, and cluster this result using Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The results show that we are able to detect and cluster time series with similar behaviour, which is the starting point for more extensive analysis into the underlying driving mechanisms. The results of the methods are compared to conventional hypothesis testing as well as a Self-Organising Map (SOM) approach. Hypothesis testing is robust and takes the stochastic nature of the observations into account, but is time consuming. Therefore, we successively apply our machine learning approach with the hypothesis testing approach in order to benefit from both the reduced computation time of the machine learning approach as from the robust quality metrics of hypothesis testing. We acknowledge support from NASA AISTNNX15AG84G (PI V. Pankratius)

Communication: Biological applications of coupled-cluster frozen-density embedding

NASA Astrophysics Data System (ADS)

Heuser, Johannes; Höfener, Sebastian

2018-04-01

We report the implementation of the Laplace-transform scaled opposite-spin (LT-SOS) resolution-of-the-identity second-order approximate coupled-cluster singles and doubles (RICC2) combined with frozen-density embedding for excitation energies and molecular properties. In the present work, we furthermore employ the Hartree-Fock density for the interaction energy leading to a simplified Lagrangian which is linear in the Lagrangian multipliers. This approximation has the key advantage of a decoupling of the coupled-cluster amplitude and multipliers, leading also to a significant reduction in computation time. Using the new simplified Lagrangian in combination with efficient wavefunction models such as RICC2 or LT-SOS-RICC2 and density-functional theory (DFT) for the environment molecules (CC2-in-DFT) enables the efficient study of biological applications such as the rhodopsin and visual cone pigments using ab initio methods as routine applications.

A YOUNG ECLIPSING BINARY AND ITS LUMINOUS NEIGHBORS IN THE EMBEDDED STAR CLUSTER Sh 2-252E

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

Lester, Kathryn V.; Gies, Douglas R.; Guo, Zhao, E-mail: lester@chara.gsu.edu, E-mail: gies@chara.gsu.edu, E-mail: guo@chara.gsu.edu

We present a photometric and light curve analysis of an eccentric eclipsing binary in the K2 Campaign 0 field, which resides in Sh 2-252E, a young star cluster embedded in an H ii region. We describe a spectroscopic investigation of the three brightest stars in the crowded aperture to identify which is the binary system. We find that none of these stars are components of the eclipsing binary system, which must be one of the fainter nearby stars. These bright cluster members all have remarkable spectra: Sh 2-252a (EPIC 202062176) is a B0.5 V star with razor sharp absorption lines, Sh 2-252b is amore » Herbig A0 star with disk-like emission lines, and Sh 2-252c is a pre-main-sequence star with very red color.« less

Luminescence properties of femtosecond-laser-activated silver oxide nanoparticles embedded in a biopolymer matrix

NASA Astrophysics Data System (ADS)

Gleitsmann, T.; Bernhardt, T. M.; Wöste, L.

2006-01-01

Strong visible luminescence is observed from silver clusters generated by femtosecond-laser-induced reduction of silver oxide nanoparticles embedded in a polymeric gelatin matrix. Light emission from the femtosecond-laser-activated matrix areas considerably exceeds the luminescence intensity of similarly activated bare silver oxide nanoparticle films. Optical spectroscopy of the activated polymer films supports the assignment of the emissive properties to the formation of small silver clusters under focused femtosecond-laser irradiation. The size of the photogenerated clusters is found to sensitively depend on the laser exposure time, eventually leading to the formation of areas of metallic silver in the biopolymer matrix. In this case, luminescence can still be observed in the periphery of the metallic silver structures, emphasizing the importance of the organic matrix for the stabilization of the luminescent nanocluster structures at the metal matrix interface.

Exploring multicollinearity using a random matrix theory approach.

PubMed

Feher, Kristen; Whelan, James; Müller, Samuel

2012-01-01

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.

Reaction Rate of Small Diffusing Molecules on a Cylindrical Membrane

NASA Astrophysics Data System (ADS)

Straube, Ronny; Ward, Michael J.; Falcke, Martin

2007-10-01

Biomembranes consist of a lipid bi-layer into which proteins are embedded to fulfill numerous tasks in localized regions of the membrane. Often, the proteins have to reach these regions by simple diffusion. Motivated by the observation that IP3 receptor channels (IP3R) form clusters on the surface of the endoplasmic reticulum (ER) during ATP-induced calcium release, the reaction rate of small diffusing molecules on a cylindrical membrane is calculated based on the Smoluchowski approach. In this way, the cylindrical topology of the tubular ER is explicitly taken into account. The problem can be reduced to the solution of the diffusion equation on a finite cylindrical surface containing a small absorbing hole. The solution is constructed by matching appropriate `inner' and `outer' asymptotic expansions. The asymptotic results are compared with those from numerical simulations and excellent agreement is obtained. For realistic parameter sets, we find reaction rates in the range of experimentally measured clustering rates of IP3R. This supports the idea that clusters are formed by a purely diffusion limited process.

Weaknesses in Lexical-Semantic Knowledge Among College Students With Specific Learning Disabilities: Evidence From a Semantic Fluency Task

PubMed Central

McGregor, Karla K.; Oleson, Jacob

2017-01-01

Purpose The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. Method One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. Results The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Conclusions Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities. PMID:28267833

Weaknesses in Lexical-Semantic Knowledge Among College Students With Specific Learning Disabilities: Evidence From a Semantic Fluency Task.

PubMed

Hall, Jessica; McGregor, Karla K; Oleson, Jacob

2017-03-01

The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities.

Application of dynamic topic models to toxicogenomics data.

PubMed

Lee, Mikyung; Liu, Zhichao; Huang, Ruili; Tong, Weida

2016-10-06

All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation. In this study, we propose, for the first time, the application of dynamic topic models (DTM) for analyzing time-series gene expression data. A large time-series toxicogenomics dataset was studied. It contains over 3144 microarrays of gene expression data corresponding to rat livers treated with 131 compounds (most are drugs) at two doses (control and high dose) in a repeated schedule containing four separate time points (4-, 8-, 15- and 29-day). We analyzed, with DTM, the topics (consisting of a set of genes) and their biological interpretations over these four time points. We identified hidden patterns embedded in this time-series gene expression profiles. From the topic distribution for compound-time condition, a number of drugs were successfully clustered by their shared mode-of-action such as PPARɑ agonists and COX inhibitors. The biological meaning underlying each topic was interpreted using diverse sources of information such as functional analysis of the pathways and therapeutic uses of the drugs. Additionally, we found that sample clusters produced by DTM are much more coherent in terms of functional categories when compared to traditional clustering algorithms. We demonstrated that DTM, a text mining technique, can be a powerful computational approach for clustering time-series gene expression profiles with the probabilistic representation of their dynamic features along sequential time frames. The method offers an alternative way for uncovering hidden patterns embedded in time series gene expression profiles to gain enhanced understanding of dynamic behavior of gene regulation in the biological system.

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

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

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

2015-05-01

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

Evidence for feedback and stellar-dynamically regulated bursty star cluster formation: the case of the Orion Nebula Cluster

NASA Astrophysics Data System (ADS)

Kroupa, Pavel; Jeřábková, Tereza; Dinnbier, František; Beccari, Giacomo; Yan, Zhiqiang

2018-04-01

A scenario for the formation of multiple co-eval populations separated in age by about 1 Myr in very young clusters (VYCs, ages less than 10 Myr) and with masses in the range 600-20 000 M⊙ is outlined. It rests upon a converging inflow of molecular gas building up a first population of pre-main sequence stars. The associated just-formed O stars ionise the inflow and suppress star formation in the embedded cluster. However, they typically eject each other out of the embedded cluster within 106 yr, that is before the molecular cloud filament can be ionised entirely. The inflow of molecular gas can then resume forming a second population. This sequence of events can be repeated maximally over the life-time of the molecular cloud (about 10 Myr), but is not likely to be possible in VYCs with mass <300 M⊙, because such populations are not likely to contain an O star. Stellar populations heavier than about 2000 M⊙ are likely to have too many O stars for all of these to eject each other from the embedded cluster before they disperse their natal cloud. VYCs with masses in the range 600-2000 M⊙ are likely to have such multi-age populations, while VYCs with masses in the range 2000-20 000 M⊙ can also be composed solely of co-eval, mono-age populations. More massive VYCs are not likely to host sub-populations with age differences of about 1 Myr. This model is applied to the Orion Nebula Cluster (ONC), in which three well-separated pre-main sequences in the colour-magnitude diagram of the cluster have recently been discovered. The mass-inflow history is constrained using this model and the number of OB stars ejected from each population are estimated for verification using Gaia data. As a further consequence of the proposed model, the three runaway O star systems, AE Aur, μ Col and ι Ori, are considered as significant observational evidence for stellar-dynamical ejections of massive stars from the oldest population in the ONC. Evidence for stellar-dynamical ejections of massive stars in the currently forming population is also discussed.

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

Unsupervised image matching based on manifold alignment.

PubMed

Pei, Yuru; Huang, Fengchun; Shi, Fuhao; Zha, Hongbin

2012-08-01

This paper challenges the issue of automatic matching between two image sets with similar intrinsic structures and different appearances, especially when there is no prior correspondence. An unsupervised manifold alignment framework is proposed to establish correspondence between data sets by a mapping function in the mutual embedding space. We introduce a local similarity metric based on parameterized distance curves to represent the connection of one point with the rest of the manifold. A small set of valid feature pairs can be found without manual interactions by matching the distance curve of one manifold with the curve cluster of the other manifold. To avoid potential confusions in image matching, we propose an extended affine transformation to solve the nonrigid alignment in the embedding space. The comparatively tight alignments and the structure preservation can be obtained simultaneously. The point pairs with the minimum distance after alignment are viewed as the matchings. We apply manifold alignment to image set matching problems. The correspondence between image sets of different poses, illuminations, and identities can be established effectively by our approach.

The Limited Role of Number of Nested Syntactic Dependencies in Accounting for Processing Cost: Evidence from German Simplex and Complex Verbal Clusters

PubMed Central

Bader, Markus

2018-01-01

This paper presents three acceptability experiments investigating German verb-final clauses in order to explore possible sources of sentence complexity during human parsing. The point of departure was De Vries et al.'s (2011) generalization that sentences with three or more crossed or nested dependencies are too complex for being processed by the human parsing mechanism without difficulties. This generalization is partially based on findings from Bach et al. (1986) concerning the acceptability of complex verb clusters in German and Dutch. The first experiment tests this generalization by comparing two sentence types: (i) sentences with three nested dependencies within a single clause that contains three verbs in a complex verb cluster; (ii) sentences with four nested dependencies distributed across two embedded clauses, one center-embedded within the other, each containing a two-verb cluster. The results show that sentences with four nested dependencies are judged as acceptable as control sentences with only two nested dependencies, whereas sentences with three nested dependencies are judged as only marginally acceptable. This argues against De Vries et al.'s (2011) claim that the human parser can process no more than two nested dependencies. The results are used to refine the Verb-Cluster Complexity Hypothesis of Bader and Schmid (2009a). The second and the third experiment investigate sentences with four nested dependencies in more detail in order to explore alternative sources of sentence complexity: the number of predicted heads to be held in working memory (storage cost in terms of the Dependency Locality Theory [DLT], Gibson, 2000) and the length of the involved dependencies (integration cost in terms of the DLT). Experiment 2 investigates sentences for which storage cost and integration cost make conflicting predictions. The results show that storage cost outweighs integration cost. Experiment 3 shows that increasing integration cost in sentences with two degrees of center embedding leads to decreased acceptability. Taken together, the results argue in favor of a multifactorial account of the limitations on center embedding in natural languages. PMID:29410633

The Limited Role of Number of Nested Syntactic Dependencies in Accounting for Processing Cost: Evidence from German Simplex and Complex Verbal Clusters.

PubMed

Bader, Markus

2017-01-01

This paper presents three acceptability experiments investigating German verb-final clauses in order to explore possible sources of sentence complexity during human parsing. The point of departure was De Vries et al.'s (2011) generalization that sentences with three or more crossed or nested dependencies are too complex for being processed by the human parsing mechanism without difficulties. This generalization is partially based on findings from Bach et al. (1986) concerning the acceptability of complex verb clusters in German and Dutch. The first experiment tests this generalization by comparing two sentence types: (i) sentences with three nested dependencies within a single clause that contains three verbs in a complex verb cluster; (ii) sentences with four nested dependencies distributed across two embedded clauses, one center-embedded within the other, each containing a two-verb cluster. The results show that sentences with four nested dependencies are judged as acceptable as control sentences with only two nested dependencies, whereas sentences with three nested dependencies are judged as only marginally acceptable. This argues against De Vries et al.'s (2011) claim that the human parser can process no more than two nested dependencies. The results are used to refine the Verb-Cluster Complexity Hypothesis of Bader and Schmid (2009a). The second and the third experiment investigate sentences with four nested dependencies in more detail in order to explore alternative sources of sentence complexity: the number of predicted heads to be held in working memory (storage cost in terms of the Dependency Locality Theory [DLT], Gibson, 2000) and the length of the involved dependencies (integration cost in terms of the DLT). Experiment 2 investigates sentences for which storage cost and integration cost make conflicting predictions. The results show that storage cost outweighs integration cost. Experiment 3 shows that increasing integration cost in sentences with two degrees of center embedding leads to decreased acceptability. Taken together, the results argue in favor of a multifactorial account of the limitations on center embedding in natural languages.

Molecular properties via a subsystem density functional theory formulation: a common framework for electronic embedding.

PubMed

Höfener, Sebastian; Gomes, André Severo Pereira; Visscher, Lucas

2012-01-28

In this article, we present a consistent derivation of a density functional theory (DFT) based embedding method which encompasses wave-function theory-in-DFT (WFT-in-DFT) and the DFT-based subsystem formulation of response theory (DFT-in-DFT) by Neugebauer [J. Neugebauer, J. Chem. Phys. 131, 084104 (2009)] as special cases. This formulation, which is based on the time-averaged quasi-energy formalism, makes use of the variation Lagrangian techniques to allow the use of non-variational (in particular: coupled cluster) wave-function-based methods. We show how, in the time-independent limit, we naturally obtain expressions for the ground-state DFT-in-DFT and WFT-in-DFT embedding via a local potential. We furthermore provide working equations for the special case in which coupled cluster theory is used to obtain the density and excitation energies of the active subsystem. A sample application is given to demonstrate the method. © 2012 American Institute of Physics

Subsystem real-time time dependent density functional theory.

PubMed

Krishtal, Alisa; Ceresoli, Davide; Pavanello, Michele

2015-04-21

We present the extension of Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) to real-time Time Dependent Density Functional Theory (rt-TDDFT). FDE is a DFT-in-DFT embedding method that allows to partition a larger Kohn-Sham system into a set of smaller, coupled Kohn-Sham systems. Additional to the computational advantage, FDE provides physical insight into the properties of embedded systems and the coupling interactions between them. The extension to rt-TDDFT is done straightforwardly by evolving the Kohn-Sham subsystems in time simultaneously, while updating the embedding potential between the systems at every time step. Two main applications are presented: the explicit excitation energy transfer in real time between subsystems is demonstrated for the case of the Na4 cluster and the effect of the embedding on optical spectra of coupled chromophores. In particular, the importance of including the full dynamic response in the embedding potential is demonstrated.

Data embedding employing degenerate clusters of data having differences less than noise value

DOEpatents

Sanford, M.T. II; Handel, T.G.

1998-10-06

A method of embedding auxiliary information into a set of host data, such as a photograph, television signal, facsimile transmission, or identification card. All such host data contain intrinsic noise, allowing pixels in the host data which are nearly identical and which have values differing by less than the noise value to be manipulated and replaced with auxiliary data. As the embedding method does not change the elemental values of the host data, the auxiliary data do not noticeably affect the appearance or interpretation of the host data. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user. 35 figs.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

Dissecting psychiatric spectrum disorders by generative embedding☆☆☆

PubMed Central

Brodersen, Kay H.; Deserno, Lorenz; Schlagenhauf, Florian; Lin, Zhihao; Penny, Will D.; Buhmann, Joachim M.; Stephan, Klaas E.

2013-01-01

This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual–parietal–prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual–parietal–prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification. PMID:24363992

Reduction of the virtual space for coupled-cluster excitation energies of large molecules and embedded systems

PubMed Central

Send, Robert; Kaila, Ville R. I.; Sundholm, Dage

2011-01-01

We investigate how the reduction of the virtual space affects coupled-cluster excitation energies at the approximate singles and doubles coupled-cluster level (CC2). In this reduced-virtual-space (RVS) approach, all virtual orbitals above a certain energy threshold are omitted in the correlation calculation. The effects of the RVS approach are assessed by calculations on the two lowest excitation energies of 11 biochromophores using different sizes of the virtual space. Our set of biochromophores consists of common model systems for the chromophores of the photoactive yellow protein, the green fluorescent protein, and rhodopsin. The RVS calculations show that most of the high-lying virtual orbitals can be neglected without significantly affecting the accuracy of the obtained excitation energies. Omitting all virtual orbitals above 50 eV in the correlation calculation introduces errors in the excitation energies that are smaller than 0.1 eV . By using a RVS energy threshold of 50 eV , the CC2 calculations using triple-ζ basis sets (TZVP) on protonated Schiff base retinal are accelerated by a factor of 6. We demonstrate the applicability of the RVS approach by performing CC2∕TZVP calculations on the lowest singlet excitation energy of a rhodopsin model consisting of 165 atoms using RVS thresholds between 20 eV and 120 eV. The calculations on the rhodopsin model show that the RVS errors determined in the gas-phase are a very good approximation to the RVS errors in the protein environment. The RVS approach thus renders purely quantum mechanical treatments of chromophores in protein environments feasible and offers an ab initio alternative to quantum mechanics∕molecular mechanics separation schemes. PMID:21663351

Reduction of the virtual space for coupled-cluster excitation energies of large molecules and embedded systems.

PubMed

Send, Robert; Kaila, Ville R I; Sundholm, Dage

2011-06-07

We investigate how the reduction of the virtual space affects coupled-cluster excitation energies at the approximate singles and doubles coupled-cluster level (CC2). In this reduced-virtual-space (RVS) approach, all virtual orbitals above a certain energy threshold are omitted in the correlation calculation. The effects of the RVS approach are assessed by calculations on the two lowest excitation energies of 11 biochromophores using different sizes of the virtual space. Our set of biochromophores consists of common model systems for the chromophores of the photoactive yellow protein, the green fluorescent protein, and rhodopsin. The RVS calculations show that most of the high-lying virtual orbitals can be neglected without significantly affecting the accuracy of the obtained excitation energies. Omitting all virtual orbitals above 50 eV in the correlation calculation introduces errors in the excitation energies that are smaller than 0.1 eV. By using a RVS energy threshold of 50 eV, the CC2 calculations using triple-ζ basis sets (TZVP) on protonated Schiff base retinal are accelerated by a factor of 6. We demonstrate the applicability of the RVS approach by performing CC2/TZVP calculations on the lowest singlet excitation energy of a rhodopsin model consisting of 165 atoms using RVS thresholds between 20 eV and 120 eV. The calculations on the rhodopsin model show that the RVS errors determined in the gas-phase are a very good approximation to the RVS errors in the protein environment. The RVS approach thus renders purely quantum mechanical treatments of chromophores in protein environments feasible and offers an ab initio alternative to quantum mechanics/molecular mechanics separation schemes. © 2011 American Institute of Physics

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gómez, D; Baly, A; Benítez, J R; Van der Stuyft, P

2010-01-01

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44 x 10(-3) v 0.29 x 10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial Registration Current Controlled Trials ISRCTN88405796.

Community involvement in dengue vector control: cluster randomised trial.

PubMed

Vanlerberghe, V; Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-06-09

To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Cluster randomised trial. Guantanamo, Cuba. 32 circumscriptions (around 2000 inhabitants each). The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44x10(-3) v 0.29x10(-3). At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Current Controlled Trials ISRCTN88405796.

Reaction-diffusion basis of retroviral infectivity

NASA Astrophysics Data System (ADS)

Sadiq, S. Kashif

2016-11-01

Retrovirus particle (virion) infectivity requires diffusion and clustering of multiple transmembrane envelope proteins (Env3) on the virion exterior, yet is triggered by protease-dependent degradation of a partially occluding, membrane-bound Gag polyprotein lattice on the virion interior. The physical mechanism underlying such coupling is unclear and only indirectly accessible via experiment. Modelling stands to provide insight but the required spatio-temporal range far exceeds current accessibility by all-atom or even coarse-grained molecular dynamics simulations. Nor do such approaches account for chemical reactions, while conversely, reaction kinetics approaches handle neither diffusion nor clustering. Here, a recently developed multiscale approach is considered that applies an ultra-coarse-graining scheme to treat entire proteins at near-single particle resolution, but which also couples chemical reactions with diffusion and interactions. A model is developed of Env3 molecules embedded in a truncated Gag lattice composed of membrane-bound matrix proteins linked to capsid subunits, with freely diffusing protease molecules. Simulations suggest that in the presence of Gag but in the absence of lateral lattice-forming interactions, Env3 diffuses comparably to Gag-absent Env3. Initial immobility of Env3 is conferred through lateral caging by matrix trimers vertically coupled to the underlying hexameric capsid layer. Gag cleavage by protease vertically decouples the matrix and capsid layers, induces both matrix and Env3 diffusion, and permits Env3 clustering. Spreading across the entire membrane surface reduces crowding, in turn, enhancing the effect and promoting infectivity. This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

YSOVAR: MID-INFRARED VARIABILITY OF YOUNG STELLAR OBJECTS AND THEIR DISKS IN THE CLUSTER IRAS 20050+2720

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

Poppenhaeger, K.; Wolk, S. J.; Hora, J. L.

2015-10-15

We present a time-variability study of young stellar objects (YSOs) in the cluster IRAS 20050+2720, performed at 3.6 and 4.5 μm with the Spitzer Space Telescope; this study is part of the Young Stellar Object VARiability (YSOVAR) project. We have collected light curves for 181 cluster members over 60 days. We find a high variability fraction among embedded cluster members of ca. 70%, whereas young stars without a detectable disk display variability less often (in ca. 50% of the cases) and with lower amplitudes. We detect periodic variability for 33 sources with periods primarily in the range of 2–6 days.more » Practically all embedded periodic sources display additional variability on top of their periodicity. Furthermore, we analyze the slopes of the tracks that our sources span in the color–magnitude diagram (CMD). We find that sources with long variability time scales tend to display CMD slopes that are at least partially influenced by accretion processes, while sources with short variability timescales tend to display extinction-dominated slopes. We find a tentative trend of X-ray detected cluster members to vary on longer timescales than the X-ray undetected members.« less

Exact density functional and wave function embedding schemes based on orbital localization

NASA Astrophysics Data System (ADS)

Hégely, Bence; Nagy, Péter R.; Ferenczy, György G.; Kállay, Mihály

2016-08-01

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up the system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.

STAR FORMATION ACROSS THE W3 COMPLEX

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

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

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

Deep near-infrared adaptive-optics observations of a young embedded cluster at the edge of the RCW 41 H II region

NASA Astrophysics Data System (ADS)

Neichel, B.; Samal, M. R.; Plana, H.; Zavagno, A.; Bernard, A.; Fusco, T.

2015-04-01

Aims: We investigate the star formation activity in a young star forming cluster embedded at the edge of the RCW 41 H ii region. As a complementary goal, we aim to demonstrate the gain provided by wide-field adaptive optics (WFAO) instruments to study young clusters. Methods: We used deep, JHKs images from the newly commissioned Gemini-GeMS/GSAOI instrument, complemented with Spitzer IRAC observations, in order to study the photometric properties of the young stellar cluster. GeMS is a WFAO instrument that delivers almost diffraction-limited images over a field of ~2' across. The exquisite angular resolution allows us to reach a limiting magnitude of J ~ 22 for 98% completeness. The combination of the IRAC photometry with our JHKs catalog is used to build color-color diagrams, and select young stellar object (YSO) candidates. The JHKs photometry is also used in conjunction with pre-main sequence evolutionary models to infer masses and ages. The K-band luminosity function is derived, and then used to build the initial mass function (IMF) of the cluster. Results: We detect the presence of 80 YSO candidates. Those YSOs are used to infer the cluster age, which is found to be in the range 1 to 5 Myr. More precisely, we find that 1/3 of the YSOs are in a range between 3 to 5 Myr, while 2/3 of the YSO are ≤3 Myr. When looking at the spatial distribution of these two populations, we find evidence of a potential age gradient across the field that suggests sequential star formation. We construct the IMF and show that we can sample the mass distribution well into the brown dwarf regime (down to ~0.01 M⊙). The logarithmic mass function rises to peak at ~0.3 M⊙, before turning over and declining into the brown dwarf regime. The total cluster mass derived is estimated to be 78 ± 18 M⊙, while the ratio derived of brown dwarfs to star is 18 ± 5%. When comparing it with other young clusters, we find that the IMF shape of the young cluster embedded within RCW 41 is consistent with those of Trapezium, IC 348, or Chamaeleon I, except for the IMF peak, which happens to be at higher mass. This characteristic is also seen in clusters like NGC 6611 or even Taurus. These results suggest that the medium-to-low mass end of the IMF possibly depends on environment.

Lithium cluster anions: photoelectron spectroscopy and ab initio calculations.

PubMed

Alexandrova, Anastassia N; Boldyrev, Alexander I; Li, Xiang; Sarkas, Harry W; Hendricks, Jay H; Arnold, Susan T; Bowen, Kit H

2011-01-28

Structural and energetic properties of small, deceptively simple anionic clusters of lithium, Li(n)(-), n = 3-7, were determined using a combination of anion photoelectron spectroscopy and ab initio calculations. The most stable isomers of each of these anions, the ones most likely to contribute to the photoelectron spectra, were found using the gradient embedded genetic algorithm program. Subsequently, state-of-the-art ab initio techniques, including time-dependent density functional theory, coupled cluster, and multireference configurational interactions methods, were employed to interpret the experimental spectra.

ΛGR Centennial: Cosmic Web in Dark Energy Background

NASA Astrophysics Data System (ADS)

Chernin, A. D.

The basic building blocks of the Cosmic Web are groups and clusters of galaxies, super-clusters (pancakes) and filaments embedded in the universal dark energy background. The background produces antigravity, and the antigravity effect is strong in groups, clusters and superclusters. Antigravity is very weak in filaments where matter (dark matter and baryons) produces gravity dominating in the filament internal dynamics. Gravity-antigravity interplay on the large scales is a grandiose phenomenon predicted by ΛGR theory and seen in modern observations of the Cosmic Web.

Dark Energy and Key Physical Parameters of Clusters of Galaxies

NASA Astrophysics Data System (ADS)

Chernin, A. D.; Bisnovatyi-Kogan, G. S.

We discuss the physics of clusters of galaxies embedded in the cosmic dark energy background and show that 1) the halo cut-off radius of a cluster like the Virgo cluster is practically, if not exactly, equal to the zero-gravity radius at which the dark matter gravity is balanced by the dark energy antigravity; 2) the halo averaged density is equal to two densities of dark energy; 3) the halo edge (cut-off) density is the dark energy density with a numerical factor of the unity order slightly depending on the halo profile.

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

Hégely, Bence; Nagy, Péter R.; Kállay, Mihály, E-mail: kallay@mail.bme.hu

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up themore » system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.« less

Brief Report: Clustered Forward Chaining with Embedded Mastery Probes to Teach Recipe Following

ERIC Educational Resources Information Center

Chazin, Kate T.; Bartelmay, Danielle N.; Lambert, Joseph M.; Houchins-Juárez, Nealetta J.

2017-01-01

This study evaluated the effectiveness of a clustered forward chaining (CFC) procedure to teach a 23-year-old male with autism to follow written recipes. CFC incorporates elements of forward chaining (FC) and total task chaining (TTC) by teaching a small number of steps (i.e., units) using TTC, introducing new units sequentially (akin to FC), and…

A volumetric conformal mapping approach for clustering white matter fibers in the brain

PubMed Central

Gupta, Vikash; Prasad, Gautam; Thompson, Paul

2017-01-01

The human brain may be considered as a genus-0 shape, topologically equivalent to a sphere. Various methods have been used in the past to transform the brain surface to that of a sphere using harmonic energy minimization methods used for cortical surface matching. However, very few methods have studied volumetric parameterization of the brain using a spherical embedding. Volumetric parameterization is typically used for complicated geometric problems like shape matching, morphing and isogeometric analysis. Using conformal mapping techniques, we can establish a bijective mapping between the brain and the topologically equivalent sphere. Our hypothesis is that shape analysis problems are simplified when the shape is defined in an intrinsic coordinate system. Our goal is to establish such a coordinate system for the brain. The efficacy of the method is demonstrated with a white matter clustering problem. Initial results show promise for future investigation in these parameterization technique and its application to other problems related to computational anatomy like registration and segmentation. PMID:29177252

Solutions of the two-dimensional Hubbard model: Benchmarks and results from a wide range of numerical algorithms

DOE PAGES

LeBlanc, J. P. F.; Antipov, Andrey E.; Becca, Federico; ...

2015-12-14

Numerical results for ground-state and excited-state properties (energies, double occupancies, and Matsubara-axis self-energies) of the single-orbital Hubbard model on a two-dimensional square lattice are presented, in order to provide an assessment of our ability to compute accurate results in the thermodynamic limit. Many methods are employed, including auxiliary-field quantum Monte Carlo, bare and bold-line diagrammatic Monte Carlo, method of dual fermions, density matrix embedding theory, density matrix renormalization group, dynamical cluster approximation, diffusion Monte Carlo within a fixed-node approximation, unrestricted coupled cluster theory, and multireference projected Hartree-Fock methods. Comparison of results obtained by different methods allows for the identification ofmore » uncertainties and systematic errors. The importance of extrapolation to converged thermodynamic-limit values is emphasized. Furthermore, cases where agreement between different methods is obtained establish benchmark results that may be useful in the validation of new approaches and the improvement of existing methods.« less

Theoretical study of cathode surfaces and high-temperature superconductors

NASA Technical Reports Server (NTRS)

Mueller, Wolfgang

1995-01-01

Calculations are presented for the work functions of BaO on W, Os, Pt, and alloys of Re-W, Os-W, and Ir-W that are in excellent agreement with experiment. The observed emission enhancement for alloy relative to tungsten dispenser cathodes is attributed to properties of the substrate crystal structure and explained by the smaller depolarization of the surface dipole on hexagonal as compared to cubic substrates. For Ba and BaO on W(100), the geometry of the adsorbates has been determined by a comparison of inverse photoemission spectra with calculated densities of unoccupied states based on the fully relativistic embedded cluster approach. Results are also discussed for models of scandate cathodes and the electronic structure of oxygen on W(100) at room and elevated temperatures. A detailed comparison is made for the surface electronic structure of the high-temperature superconductor YBa2Cu3O7 as obtained with non-, quasi-, and fully relativistic cluster calculations.

XMM-Newton Observations of the Toothbrush and Sausage Clusters

NASA Astrophysics Data System (ADS)

Kara, S.; Mernier, F.; Ezer, C.; Akamatsu, H.; Ercan, E.

2017-10-01

Galaxy clusters are the largest gravitationally-bound objects in the universe. The member galaxies are embedded in a hot X-ray emitting Intra Cluster Medium (ICM) that has been enriched with metals produced by supernovae over the last billion years. Here we report new results from XMM-Newton archival observations of the merging clusters 1RXSJ0603.3+4213 and CIZA J2242.8+5301. These two clusters, also known as the Toothbrush and Sausage clusters, respectively, show a large radio relic associated with a merger shock North of their respective core. We show the distribution of the metal abundances with respect to the merger structures in these two clusters. The results are derived from spatially resolved X-ray spectra from the EPIC instrument on board XMM-Newton.

Impact of a star formation efficiency profile on the evolution of open clusters

NASA Astrophysics Data System (ADS)

Shukirgaliyev, B.; Parmentier, G.; Berczik, P.; Just, A.

2017-09-01

Aims: We study the effect of the instantaneous expulsion of residual star-forming gas on star clusters in which the residual gas has a density profile that is shallower than that of the embedded cluster. This configuration is expected if star formation proceeds with a given star-formation efficiency per free-fall time in a centrally concentrated molecular gas clump. Methods: We performed direct N-body simulations whose initial conditions were generated by the program "mkhalo" from the package "falcON", adapted for our models. Our model clusters initially had a Plummer profile and are in virial equilibrium with the gravitational potential of the cluster-forming clump. The residual gas contribution was computed based on a local-density driven clustered star formation model. Our simulations included mass loss by stellar evolution and the tidal field of a host galaxy. Results: We find that a star cluster with a minimum global star formation efficiency (SFE) of 15 percent is able to survive instantaneous gas expulsion and to produce a bound cluster. Its violent relaxation lasts no longer than 20 Myr, independently of its global SFE and initial stellar mass. At the end of violent relaxation, the bound fractions of the surviving clusters with the same global SFEs are similar, regardless of their initial stellar mass. Their subsequent lifetime in the gravitational field of the Galaxy depends on their bound stellar masses. Conclusions: We therefore conclude that the critical SFE needed to produce a bound cluster is 15 percent, which is roughly half the earlier estimates of 33 percent. Thus we have improved the survival likelihood of young clusters after instantaneous gas expulsion. Young clusters can now survive instantaneous gas expulsion with a global SFEs as low as the SFEs observed for embedded clusters in the solar neighborhood (15-30 percent). The reason is that the star cluster density profile is steeper than that of the residual gas. However, in terms of the effective SFE, measured by the virial ratio of the cluster at gas expulsion, our results are in agreement with previous studies.

Physical conditions in star-forming regions around S235

NASA Astrophysics Data System (ADS)

Kirsanova, M. S.; Wiebe, D. S.; Sobolev, A. M.; Henkel, C.; Tsivilev, A. P.

2014-01-01

Gas density and temperature in star-forming regions around Sh2-235 are derived from ammonia line observations. This information is used to evaluate formation scenarios and to determine evolutionary stages of the young embedded clusters S235 East 1, S235 East 2 and S235 Central. We also estimate the gas mass in the embedded clusters and its ratio to the stellar mass. S235 East 1 appears to be less evolved than S235 East 2 and S235 Central. In S235 East 1 the molecular gas mass exceeds that in the other clusters. Also, this cluster is more embedded in the parent gas cloud than the other two. Comparison with a theoretical model shows that the formation of these three clusters could have been stimulated by the expansion of the Sh2-235 H II region (hereafter S235) via a collect-and-collapse process, provided the density in the surrounding gas exceeds 3 × 103 cm-3, or via collapse of pre-existing clumps. The expansion of S235 cannot be responsible for star formation in the southern S235 A-B region. However, formation of the massive stars in this region might have been triggered by a large-scale supernova shock. Thus, triggered star formation in the studied region may come in three varieties, namely collect-and-collapse and collapse of pre-existing clumps, both initiated by expansion of the local H II regions, and triggered by an external large-scale shock. We argue that the S235 A H II region expands into a highly non-uniform medium with increasing density. It is too young to trigger star formation in its vicinity by a collect-and-collapse process. There is an age spread inside the S235 A-B region. Massive stars in the S235 A-B region are considerably younger than lower mass stars in the same area. This follows from the estimates of their ages and the ages of associated H II regions.

Planet population synthesis driven by pebble accretion in cluster environments

NASA Astrophysics Data System (ADS)

Ndugu, N.; Bitsch, B.; Jurua, E.

2018-02-01

The evolution of protoplanetary discs embedded in stellar clusters depends on the age and the stellar density in which they are embedded. Stellar clusters of young age and high stellar surface density destroy protoplanetary discs by external photoevaporation and stellar encounters. Here, we consider the effect of background heating from newly formed stellar clusters on the structure of protoplanetary discs and how it affects the formation of planets in these discs. Our planet formation model is built on the core accretion scenario, where we take the reduction of the core growth time-scale due to pebble accretion into account. We synthesize planet populations that we compare to observations obtained by radial velocity measurements. The giant planets in our simulations migrate over large distances due to the fast type-II migration regime induced by a high disc viscosity (α = 5.4 × 10-3). Cold Jupiters (rp > 1 au) originate preferably from the outer disc, due to the large-scale planetary migration, while hot Jupiters (rp < 0.1 au) preferably form in the inner disc. We find that the formation of gas giants via pebble accretion is in agreement with the metallicity correlation, meaning that more gas giants are formed at larger metallicity. However, our synthetic population of isolated stars host a significant amount of giant planets even at low metallicity, in contradiction to observations where giant planets are preferably found around high metallicity stars, indicating that pebble accretion is very efficient in the standard pebble accretion framework. On the other hand, discs around stars embedded in cluster environments hardly form any giant planets at low metallicity in agreement with observations, where these changes originate from the increased temperature in the outer parts of the disc, which prolongs the core accretion time-scale of the planet. We therefore conclude that the outer disc structure and the planet's formation location determines the giant planet occurrence rate and the formation efficiency of cold and hot Jupiters.

Community involvement in dengue vector control: cluster randomised trial

PubMed Central

Toledo, M E; Rodríguez, M; Gomez, D; Baly, A; Benitez, J R; Van der Stuyft, P

2009-01-01

Objective To assess the effectiveness of an integrated community based environmental management strategy to control Aedes aegypti, the vector of dengue, compared with a routine strategy. Design Cluster randomised trial. Setting Guantanamo, Cuba. Participants 32 circumscriptions (around 2000 inhabitants each). Interventions The circumscriptions were randomly allocated to control clusters (n=16) comprising routine Aedes control programme (entomological surveillance, source reduction, selective adulticiding, and health education) and to intervention clusters (n=16) comprising the routine Aedes control programme combined with a community based environmental management approach. Main outcome measures The primary outcome was levels of Aedes infestation: house index (number of houses positive for at least one container with immature stages of Ae aegypti per 100 inspected houses), Breteau index (number of containers positive for immature stages of Ae aegypti per 100 inspected houses), and the pupae per inhabitant statistic (number of Ae aegypti pupae per inhabitant). Results All clusters were subjected to the intended intervention; all completed the study protocol up to February 2006 and all were included in the analysis. At baseline the Aedes infestation levels were comparable between intervention and control clusters: house index 0.25% v 0.20%, pupae per inhabitant 0.44×10−3 v 0.29×10−3. At the end of the intervention these indices were significantly lower in the intervention clusters: rate ratio for house indices 0.49 (95% confidence interval 0.27 to 0.88) and rate ratio for pupae per inhabitant 0.27 (0.09 to 0.76). Conclusion A community based environmental management embedded in a routine control programme was effective at reducing levels of Aedes infestation. Trial registration Current Controlled Trials ISRCTN88405796. PMID:19509031

Self-energy behavior away from the Fermi surface in doped Mott insulators.

PubMed

Merino, J; Gunnarsson, O; Kotliar, G

2016-02-03

We analyze self-energies of electrons away from the Fermi surface in doped Mott insulators using the dynamical cluster approximation to the Hubbard model. For large onsite repulsion, U, and hole doping, the magnitude of the self-energy for imaginary frequencies at the top of the band ([Formula: see text]) is enhanced with respect to the self-energy magnitude at the bottom of the band ([Formula: see text]). The self-energy behavior at these two [Formula: see text]-points is switched for electron doping. Although the hybridization is much larger for (0, 0) than for [Formula: see text], we demonstrate that this is not the origin of this difference. Isolated clusters under a downward shift of the chemical potential, [Formula: see text], at half-filling reproduce the overall self-energy behavior at (0, 0) and [Formula: see text] found in low hole doped embedded clusters. This happens although there is no change in the electronic structure of the isolated clusters. Our analysis shows that a downward shift of the chemical potential which weakly hole dopes the Mott insulator can lead to a large enhancement of the [Formula: see text] self-energy for imaginary frequencies which is not associated with electronic correlation effects, even in embedded clusters. Interpretations of the strength of electronic correlations based on self-energies for imaginary frequencies are, in general, misleading for states away from the Fermi surface.

Debugging embedded computer programs. [tactical missile computers

NASA Technical Reports Server (NTRS)

Kemp, G. H.

1980-01-01

Every embedded computer program must complete its debugging cycle using some system that will allow real time debugging. Many of the common items addressed during debugging are listed. Seven approaches to debugging are analyzed to evaluate how well they treat those items. Cost evaluations are also included in the comparison. The results indicate that the best collection of capabilities to cover the common items present in the debugging task occurs in the approach where a minicomputer handles the environment simulation with an emulation of some kind representing the embedded computer. This approach can be taken at a reasonable cost. The case study chosen is an embedded computer in a tactical missile. Several choices of computer for the environment simulation are discussed as well as different approaches to the embedded emulator.

Post-Hartree-Fock studies of the He/Mg(0001) interaction: Anti-corrugation, screening, and pairwise additivity

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

Lara-Castells, María Pilar de, E-mail: Pilar.deLara.Castells@csic.es; Fernández-Perea, Ricardo; Madzharova, Fani

2016-06-28

The adsorption of noble gases on metallic surfaces represents a paradigmatic case of van-der-Waals (vdW) interaction due to the role of screening effects on the corrugation of the interaction potential [J. L. F. Da Silva et al., Phys. Rev. Lett. 90, 066104 (2003)]. The extremely small adsorption energy of He atoms on the Mg(0001) surface (below 3 meV) and the delocalized nature and mobility of the surface electrons make the He/Mg(0001) system particularly challenging, even for state-of-the-art vdW-corrected density functional-based (vdW-DFT) approaches [M. P. de Lara-Castells et al., J. Chem. Phys. 143, 194701 (2015)]. In this work, we meet thismore » challenge by applying two different procedures. First, the dispersion-corrected second-order Möller-Plesset perturbation theory (MP2C) approach is adopted, using bare metal clusters of increasing size. Second, the method of increments [H. Stoll, J. Chem. Phys. 97, 8449 (1992)] is applied at coupled cluster singles and doubles and perturbative triples level, using embedded cluster models of the metal surface. Both approaches provide clear evidences of the anti-corrugation of the interaction potential: the He atom prefers on-top sites, instead of the expected hollow sites. This is interpreted as a signature of the screening of the He atom by the metal for the on-top configuration. The strong screening in the metal is clearly reflected in the relative contribution of successively deeper surface layers to the main dispersion contribution. Aimed to assist future dynamical simulations, a pairwise potential model for the He/surface interaction as a sum of effective He–Mg pair potentials is also presented, as an improvement of the approximation using isolated He–Mg pairs.« less

Post-Hartree-Fock studies of the He/Mg(0001) interaction: Anti-corrugation, screening, and pairwise additivity

NASA Astrophysics Data System (ADS)

de Lara-Castells, María Pilar; Fernández-Perea, Ricardo; Madzharova, Fani; Voloshina, Elena

2016-06-01

The adsorption of noble gases on metallic surfaces represents a paradigmatic case of van-der-Waals (vdW) interaction due to the role of screening effects on the corrugation of the interaction potential [J. L. F. Da Silva et al., Phys. Rev. Lett. 90, 066104 (2003)]. The extremely small adsorption energy of He atoms on the Mg(0001) surface (below 3 meV) and the delocalized nature and mobility of the surface electrons make the He/Mg(0001) system particularly challenging, even for state-of-the-art vdW-corrected density functional-based (vdW-DFT) approaches [M. P. de Lara-Castells et al., J. Chem. Phys. 143, 194701 (2015)]. In this work, we meet this challenge by applying two different procedures. First, the dispersion-corrected second-order Möller-Plesset perturbation theory (MP2C) approach is adopted, using bare metal clusters of increasing size. Second, the method of increments [H. Stoll, J. Chem. Phys. 97, 8449 (1992)] is applied at coupled cluster singles and doubles and perturbative triples level, using embedded cluster models of the metal surface. Both approaches provide clear evidences of the anti-corrugation of the interaction potential: the He atom prefers on-top sites, instead of the expected hollow sites. This is interpreted as a signature of the screening of the He atom by the metal for the on-top configuration. The strong screening in the metal is clearly reflected in the relative contribution of successively deeper surface layers to the main dispersion contribution. Aimed to assist future dynamical simulations, a pairwise potential model for the He/surface interaction as a sum of effective He-Mg pair potentials is also presented, as an improvement of the approximation using isolated He-Mg pairs.

Functionalizing graphene by embedded boron clusters

NASA Astrophysics Data System (ADS)

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

2008-08-01

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

A channel differential EZW coding scheme for EEG data compression.

PubMed

Dehkordi, Vahid R; Daou, Hoda; Labeau, Fabrice

2011-11-01

In this paper, a method is proposed to compress multichannel electroencephalographic (EEG) signals in a scalable fashion. Correlation between EEG channels is exploited through clustering using a k-means method. Representative channels for each of the clusters are encoded individually while other channels are encoded differentially, i.e., with respect to their respective cluster representatives. The compression is performed using the embedded zero-tree wavelet encoding adapted to 1-D signals. Simulations show that the scalable features of the scheme lead to a flexible quality/rate tradeoff, without requiring detailed EEG signal modeling.

Near-Edge X-ray Absorption Fine Structure within Multilevel Coupled Cluster Theory.

PubMed

Myhre, Rolf H; Coriani, Sonia; Koch, Henrik

2016-06-14

Core excited states are challenging to calculate, mainly because they are embedded in a manifold of high-energy valence-excited states. However, their locality makes their determination ideal for local correlation methods. In this paper, we demonstrate the performance of multilevel coupled cluster theory in computing core spectra both within the core-valence separated and the asymmetric Lanczos implementations of coupled cluster linear response theory. We also propose a visualization tool to analyze the excitations using the difference between the ground-state and excited-state electron densities.

Mapping Dark Matter in Simulated Galaxy Clusters

NASA Astrophysics Data System (ADS)

Bowyer, Rachel

2018-01-01

Galaxy clusters are the most massive bound objects in the Universe with most of their mass being dark matter. Cosmological simulations of structure formation show that clusters are embedded in a cosmic web of dark matter filaments and large scale structure. It is thought that these filaments are found preferentially close to the long axes of clusters. We extract galaxy clusters from the simulations "cosmo-OWLS" in order to study their properties directly and also to infer their properties from weak gravitational lensing signatures. We investigate various stacking procedures to enhance the signal of the filaments and large scale structure surrounding the clusters to better understand how the filaments of the cosmic web connect with galaxy clusters. This project was supported in part by the NSF REU grant AST-1358980 and by the Nantucket Maria Mitchell Association.

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

NASA Astrophysics Data System (ADS)

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

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

Probabilistic Analysis of Hierarchical Cluster Protocols for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Kaj, Ingemar

Wireless sensor networks are designed to extract data from the deployment environment and combine sensing, data processing and wireless communication to provide useful information for the network users. Hundreds or thousands of small embedded units, which operate under low-energy supply and with limited access to central network control, rely on interconnecting protocols to coordinate data aggregation and transmission. Energy efficiency is crucial and it has been proposed that cluster based and distributed architectures such as LEACH are particularly suitable. We analyse the random cluster hierarchy in this protocol and provide a solution for low-energy and limited-loss optimization. Moreover, we extend these results to a multi-level version of LEACH, where clusters of nodes again self-organize to form clusters of clusters, and so on.

A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering.

PubMed

Cheng, De; Nie, Feiping; Sun, Jiande; Gong, Yihong

2017-07-01

Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also be of low quality. We address this drawback by allowing the data graph itself to be adaptively adjusted in the clustering procedure. In particular, our proposed weight adaptive Laplacian (WAL) method learns a new data similarity matrix that can adaptively adjust the initial graph according to the similarity weight in the input data graph. We develop three versions of these methods based on the L2-norm, fuzzy entropy regularizer, and another exponential-based weight strategy, that yield three new graph-based clustering objectives. We derive optimization algorithms to solve these objectives. Experimental results on synthetic data sets and real-world benchmark data sets exhibit the effectiveness of these new graph-based clustering methods.

A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY1

PubMed Central

Lee, Ann B.; Luca, Diana; Roeder, Kathryn

2010-01-01

Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic diversity confound efforts to determine the genetic basis of complex disease. Due to technological advances, it is now possible to measure hundreds of thousands of genetic variants per individual across the genome. Principal component analysis (PCA) is routinely used to summarize the genetic similarity between subjects. The eigenvectors are interpreted as dimensions of ancestry. We build on this idea using a spectral graph approach. In the process we draw on connections between multidimensional scaling and spectral kernel methods. Our approach, based on a spectral embedding derived from the normalized Laplacian of a graph, can produce more meaningful delineation of ancestry than by using PCA. The method is stable to outliers and can more easily incorporate different similarity measures of genetic data than PCA. We illustrate a new algorithm for genetic clustering and association analysis on a large, genetically heterogeneous sample. PMID:20689656

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

PubMed

Clark-Langone, Kim M; Wu, Jenny Y; Sangli, Chithra; Chen, Angela; Snable, James L; Nguyen, Anhthu; Hackett, James R; Baker, Joffre; Yothers, Greg; Kim, Chungyeul; Cronin, Maureen T

2007-08-15

Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, S. P.

1984-01-01

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

Dynamical equivalence, the origin of the Galactic field stellar and binary population, and the initial radius-mass relation of embedded clusters

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Kroupa, Pavel; Rocha-Pinto, Helio J.; Giersz, Mirek

2018-03-01

In order to allow a better understanding of the origin of Galactic field populations, dynamical equivalence of stellar-dynamical systems has been postulated by Kroupa and Belloni et al. to allow mapping of solutions of the initial conditions of embedded clusters such that they yield, after a period of dynamical processing, the Galactic field population. Dynamically equivalent systems are defined to initially and finally have the same distribution functions of periods, mass ratios and eccentricities of binary stars. Here, we search for dynamically equivalent clusters using the MOCCA code. The simulations confirm that dynamically equivalent solutions indeed exist. The result is that the solution space is next to identical to the radius-mass relation of Marks & Kroupa, ( r_h/pc )= 0.1^{+0.07}_{-0.04} ( M_ecl/M_{⊙} )^{0.13± 0.04}. This relation is in good agreement with the oIMF. This is achieved by applying a similar procedurebserved density of molecular cloud clumps. According to the solutions, the time-scale to reach dynamical equivalence is about 0.5 Myr which is, interestingly, consistent with the lifetime of ultra-compact H II regions and the time-scale needed for gas expulsion to be active in observed very young clusters as based on their dynamical modelling.

Feature-based component model for design of embedded systems

NASA Astrophysics Data System (ADS)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

New detections of embedded clusters in the Galactic halo

NASA Astrophysics Data System (ADS)

Camargo, D.; Bica, E.; Bonatto, C.

2016-09-01

Context. Until recently it was thought that high Galactic latitude clouds were a non-star-forming ensemble. However, in a previous study we reported the discovery of two embedded clusters (ECs) far away from the Galactic plane (~ 5 kpc). In our recent star cluster catalogue we provided additional high and intermediate latitude cluster candidates. Aims: This work aims to clarify whether our previous detection of star clusters far away from the disc represents just an episodic event or whether star cluster formation is currently a systematic phenomenon in the Galactic halo. We analyse the nature of four clusters found in our recent catalogue and report the discovery of three new ECs each with an unusually high latitude and distance from the Galactic disc midplane. Methods: The analysis is based on 2MASS and WISE colour-magnitude diagrams (CMDs), and stellar radial density profiles (RDPs). The CMDs are built by applying a field-star decontamination procedure, which uncovers the cluster's intrinsic CMD morphology. Results: All of these clusters are younger than 5 Myr. The high-latitude ECs C 932, C 934, and C 939 appear to be related to a cloud complex about 5 kpc below the Galactic disc, under the Local arm. The other clusters are above the disc, C 1074 and C 1100 with a vertical distance of ~3 kpc, C 1099 with ~ 2 kpc, and C 1101 with ~1.8 kpc. Conclusions: According to the derived parameters ECs located below and above the disc occur, which gives evidence of widespread star cluster formation throughout the Galactic halo. This study therefore represents a paradigm shift, by demonstrating that a sterile halo must now be understood as a host for ongoing star formation. The origin and fate of these ECs remain open. There are two possibilities for their origin, Galactic fountains or infall. The discovery of ECs far from the disc suggests that the Galactic halo is more actively forming stars than previously thought. Furthermore, since most ECs do not survive the infant mortality, stars may be raining from the halo into the disc, and/or the halo may be harbouring generations of stars formed in clusters like those detected in our survey.

A Dissemination Methodology for Learning and Teaching Developments through Engaging and Embedding

ERIC Educational Resources Information Center

Treleaven, Lesley; Sykes, Chris; Ormiston, Jarrod

2012-01-01

Dissemination of learning and teaching innovation in higher education requires approaches to change that are socially contextualised, dynamic and self-reflexive. This article, therefore, presents a methodology for dissemination employing an embedding heuristic and engaging in participatory action research. The embedding approach emphasises three…

Embedding methods for the steady Euler equations

NASA Technical Reports Server (NTRS)

Chang, S. H.; Johnson, G. M.

1983-01-01

An approach to the numerical solution of the steady Euler equations is to embed the first-order Euler system in a second-order system and then to recapture the original solution by imposing additional boundary conditions. Initial development of this approach and computational experimentation with it were previously based on heuristic physical reasoning. This has led to the construction of a relaxation procedure for the solution of two-dimensional steady flow problems. The theoretical justification for the embedding approach is addressed. It is proven that, with the appropriate choice of embedding operator and additional boundary conditions, the solution to the embedded system is exactly the one to the original Euler equations. Hence, solving the embedded version of the Euler equations will not produce extraneous solutions.

Embedding a Palliative Approach in Nursing Care Delivery

PubMed Central

Porterfield, Pat; Roberts, Della; Lee, Joyce; Liang, Leah; Reimer-Kirkham, Sheryl; Pesut, Barb; Schalkwyk, Tilly; Stajduhar, Kelli; Tayler, Carolyn; Baumbusch, Jennifer; Thorne, Sally

2017-01-01

A palliative approach involves adapting and integrating principles and values from palliative care into the care of persons who have life-limiting conditions throughout their illness trajectories. The aim of this research was to determine what approaches to nursing care delivery support the integration of a palliative approach in hospital, residential, and home care settings. The findings substantiate the importance of embedding the values and tenets of a palliative approach into nursing care delivery, the roles that nurses have in working with interdisciplinary teams to integrate a palliative approach, and the need for practice supports to facilitate that embedding and integration. PMID:27930401

Nearest neighbor-density-based clustering methods for large hyperspectral images

NASA Astrophysics Data System (ADS)

Cariou, Claude; Chehdi, Kacem

2017-10-01

We address the problem of hyperspectral image (HSI) pixel partitioning using nearest neighbor - density-based (NN-DB) clustering methods. NN-DB methods are able to cluster objects without specifying the number of clusters to be found. Within the NN-DB approach, we focus on deterministic methods, e.g. ModeSeek, knnClust, and GWENN (standing for Graph WatershEd using Nearest Neighbors). These methods only require the availability of a k-nearest neighbor (kNN) graph based on a given distance metric. Recently, a new DB clustering method, called Density Peak Clustering (DPC), has received much attention, and kNN versions of it have quickly followed and showed their efficiency. However, NN-DB methods still suffer from the difficulty of obtaining the kNN graph due to the quadratic complexity with respect to the number of pixels. This is why GWENN was embedded into a multiresolution (MR) scheme to bypass the computation of the full kNN graph over the image pixels. In this communication, we propose to extent the MR-GWENN scheme on three aspects. Firstly, similarly to knnClust, the original labeling rule of GWENN is modified to account for local density values, in addition to the labels of previously processed objects. Secondly, we set up a modified NN search procedure within the MR scheme, in order to stabilize of the number of clusters found from the coarsest to the finest spatial resolution. Finally, we show that these extensions can be easily adapted to the three other NN-DB methods (ModeSeek, knnClust, knnDPC) for pixel clustering in large HSIs. Experiments are conducted to compare the four NN-DB methods for pixel clustering in HSIs. We show that NN-DB methods can outperform a classical clustering method such as fuzzy c-means (FCM), in terms of classification accuracy, relevance of found clusters, and clustering speed. Finally, we demonstrate the feasibility and evaluate the performances of NN-DB methods on a very large image acquired by our AISA Eagle hyperspectral imaging sensor.

Atomistic simulations of the effect of embedded hydrogen and helium on the tensile properties of monocrystalline and nanocrystalline tungsten

NASA Astrophysics Data System (ADS)

Chen, Zhe; Kecskes, Laszlo J.; Zhu, Kaigui; Wei, Qiuming

2016-12-01

Uniaxial tensile properties of monocrystalline tungsten (MC-W) and nanocrystalline tungsten (NC-W) with embedded hydrogen and helium atoms have been investigated using molecular dynamics (MD) simulations in the context of radiation damage evolution. Different strain rates have been imposed to investigate the strain rate sensitivity (SRS) of the samples. Results show that the plastic deformation processes of MC-W and NC-W are dominated by different mechanisms, namely dislocation-based for MC-W and grain boundary-based activities for NC-W, respectively. For MC-W, the SRS increases and a transition appears in the deformation mechanism with increasing embedded atom concentration. However, no obvious embedded atom concentration dependence of the SRS has been observed for NC-W. Instead, in the latter case, the embedded atoms facilitate GB sliding and intergranular fracture. Additionally, a strong strain enhanced He cluster growth has been observed. The corresponding underlying mechanisms are discussed.

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

PubMed

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

2004-02-01

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

A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Rosen, Mark; Madabhushi, Anant

2008-03-01

Current techniques for localization of prostatic adenocarcinoma (CaP) via blinded trans-rectal ultrasound biopsy are associated with a high false negative detection rate. While high resolution endorectal in vivo Magnetic Resonance (MR) prostate imaging has been shown to have improved contrast and resolution for CaP detection over ultrasound, similarity in intensity characteristics between benign and cancerous regions on MR images contribute to a high false positive detection rate. In this paper, we present a novel unsupervised segmentation method that employs manifold learning via consensus schemes for detection of cancerous regions from high resolution 1.5 Tesla (T) endorectal in vivo prostate MRI. A significant contribution of this paper is a method to combine multiple weak, lower-dimensional representations of high dimensional feature data in a way analogous to classifier ensemble schemes, and hence create a stable and accurate reduced dimensional representation. After correcting for MR image intensity artifacts, such as bias field inhomogeneity and intensity non-standardness, our algorithm extracts over 350 3D texture features at every spatial location in the MR scene at multiple scales and orientations. Non-linear dimensionality reduction schemes such as Locally Linear Embedding (LLE) and Graph Embedding (GE) are employed to create multiple low dimensional data representations of this high dimensional texture feature space. Our novel consensus embedding method is used to average object adjacencies from within the multiple low dimensional projections so that class relationships are preserved. Unsupervised consensus clustering is then used to partition the objects in this consensus embedding space into distinct classes. Quantitative evaluation on 18 1.5 T prostate MR data against corresponding histology obtained from the multi-site ACRIN trials show a sensitivity of 92.65% and a specificity of 82.06%, which suggests that our method is successfully able to detect suspicious regions in the prostate.

Merging black holes in non-spherical nuclear star clusters

NASA Astrophysics Data System (ADS)

Petrovich, Cristobal

2018-04-01

The Milky Way and a significant fraction of galaxies are observed to host a central Massive Black Hole (MBH) embedded in a non-spherical nuclear star cluster. I will discuss the orbital evolution of stellar binaries in these environments and argue that their merger rates are expected to be greatly enhanced when the effect from cluster potential is taken into account in the binary-MBH triple system. I will apply our results to compact-object binary mergers mediated by gravitational wave radiation and show that this merger channel can contribute significantly to the LIGO/Virgo detections.

Change in the Embedding Dimension as an Indicator of an Approaching Transition

PubMed Central

Neuman, Yair; Marwan, Norbert; Cohen, Yohai

2014-01-01

Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point. PMID:24979691

A new route to gold nanoflowers

NASA Astrophysics Data System (ADS)

Liebig, Ferenc; Henning, Ricky; Sarhan, Radwan M.; Prietzel, Claudia; Bargheer, Matias; Koetz, Joachim

2018-05-01

Catanionic vesicles spontaneously formed by mixing the anionic surfactant bis(2-ethylhexyl) sulfosuccinate sodium salt with the cationic surfactant cetyltrimethylammonium bromide were used as a reducing medium to produce gold clusters, which are embedded and well-ordered into the template phase. The gold clusters can be used as seeds in the growth process that follows by adding ascorbic acid as a mild reducing component. When the ascorbic acid was added very slowly in an ice bath round-edged gold nanoflowers were produced. When the same experiments were performed at room temperature in the presence of Ag+ ions, sharp-edged nanoflowers could be synthesized. The mechanism of nanoparticle formation can be understood to be a non-diffusion-limited Ostwald ripening process of preordered gold nanoparticles embedded in catanionic vesicle fragments. Surface-enhanced Raman scattering experiments show an excellent enhancement factor of 1.7 · 105 for the nanoflowers deposited on a silicon wafer.

Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae

2016-01-01

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. PMID:27669249

The New 30 Doradus

NASA Astrophysics Data System (ADS)

Walborn, N. R.; Barbá, R. H.

A groundbased, blue-violet spectral classification study of the 30 Doradus stellar content has revealed five spatially and/or temporally distinct components: (1) the central ionizing cluster including R136 (corresponding to the Carina phase of OB cluster evolution with an age of 2-3 Myr); (2) a younger generation in or near the bright nebular filaments west and northeast of R136, containing heavily embedded early-O dwarfs and IR sources, the formation of which was likely triggered by the central cluster (Orion phase, <1 Myr); (3) an older population of late-O and early-B supergiants throughout the central field whose structural relationship, if any, to the younger groups is unclear (Scorpius OB1 phase, 4-6 Myr); (4) a previously known, older still compact cluster 3' northwest of R136, containing A and M supergiants and evidently affecting the nebular dynamics substantially (h and chi Persei phase, 10 Myr); and (5) a newly recognized Sco OB1-phase association surrounding the recently discovered Luminous Blue Variable R143 in the southern part of the Nebula. Evidently, star formation has occurred in discrete events at different epochs in 30 Dor, and there are clear implications for the interpretation of more distant starbursts. This presentation emphasizes the second component above, a new stellar generation currently being formed in 30 Doradus. Groundbased IR images by Rubio et al. and H2 observations by Probst and Rubio show many sources, with detailed relationships to the embedded optical O stars as well as to the nebular microstructures visible in HST/WFPC2 images. Recent observations of these fields with HST/NICMOS reveal an even greater wealth of structural detail, including compact IR multiple systems and clusters, and probable jets associated with two of the embedded early-O systems; one of the latter may also be related to an H2O maser source. These and future IR data will provide new insights into the evolution of starbursts on the scale of 30 Doradus, as well as the early evolution of individual massive stars and compact groups.

An accurate and linear-scaling method for calculating charge-transfer excitation energies and diabatic couplings

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

Pavanello, Michele; Van Voorhis, Troy; Visscher, Lucas

2013-02-07

Quantum-mechanical methods that are both computationally fast and accurate are not yet available for electronic excitations having charge transfer character. In this work, we present a significant step forward towards this goal for those charge transfer excitations that take place between non-covalently bound molecules. In particular, we present a method that scales linearly with the number of non-covalently bound molecules in the system and is based on a two-pronged approach: The molecular electronic structure of broken-symmetry charge-localized states is obtained with the frozen density embedding formulation of subsystem density-functional theory; subsequently, in a post-SCF calculation, the full-electron Hamiltonian and overlapmore » matrix elements among the charge-localized states are evaluated with an algorithm which takes full advantage of the subsystem DFT density partitioning technique. The method is benchmarked against coupled-cluster calculations and achieves chemical accuracy for the systems considered for intermolecular separations ranging from hydrogen-bond distances to tens of Angstroms. Numerical examples are provided for molecular clusters comprised of up to 56 non-covalently bound molecules.« less

An accurate and linear-scaling method for calculating charge-transfer excitation energies and diabatic couplings.

PubMed

Pavanello, Michele; Van Voorhis, Troy; Visscher, Lucas; Neugebauer, Johannes

2013-02-07

Quantum-mechanical methods that are both computationally fast and accurate are not yet available for electronic excitations having charge transfer character. In this work, we present a significant step forward towards this goal for those charge transfer excitations that take place between non-covalently bound molecules. In particular, we present a method that scales linearly with the number of non-covalently bound molecules in the system and is based on a two-pronged approach: The molecular electronic structure of broken-symmetry charge-localized states is obtained with the frozen density embedding formulation of subsystem density-functional theory; subsequently, in a post-SCF calculation, the full-electron Hamiltonian and overlap matrix elements among the charge-localized states are evaluated with an algorithm which takes full advantage of the subsystem DFT density partitioning technique. The method is benchmarked against coupled-cluster calculations and achieves chemical accuracy for the systems considered for intermolecular separations ranging from hydrogen-bond distances to tens of Ångstroms. Numerical examples are provided for molecular clusters comprised of up to 56 non-covalently bound molecules.

A new approach for embedding causal sets into Minkowski space

NASA Astrophysics Data System (ADS)

Liu, He; Reid, David D.

2018-06-01

This paper reports on recent work toward an approach for embedding causal sets into two-dimensional Minkowski space. The main new feature of the present scheme is its use of the spacelike distance measure to construct an ordering of causal set elements within anti-chains of a causal set as an aid to the embedding procedure.

HIGH-ENERGY NEUTRINOS FROM SOURCES IN CLUSTERS OF GALAXIES

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

Fang, Ke; Olinto, Angela V.

2016-09-01

High-energy cosmic rays can be accelerated in clusters of galaxies, by mega-parsec scale shocks induced by the accretion of gas during the formation of large-scale structures, or by powerful sources harbored in clusters. Once accelerated, the highest energy particles leave the cluster via almost rectilinear trajectories, while lower energy ones can be confined by the cluster magnetic field up to cosmological time and interact with the intracluster gas. Using a realistic model of the baryon distribution and the turbulent magnetic field in clusters, we studied the propagation and hadronic interaction of high-energy protons in the intracluster medium. We report themore » cumulative cosmic-ray and neutrino spectra generated by galaxy clusters, including embedded sources, and demonstrate that clusters can contribute a significant fraction of the observed IceCube neutrinos above 30 TeV while remaining undetected in high-energy cosmic rays and γ rays for reasonable choices of parameters and source scenarios.« less

The embedded population around Herbig Ae/Be stars

NASA Astrophysics Data System (ADS)

Testi, L.; Stanga, R. M.; Natta, A.; Palla, F.; Prusti, T.; Baffa, C.; Hunt, L. K.; Lisi, F.

Herbig Ae/Be stars are intermediate mass young stars in the pre-main sequence phase of evolution. There are only few stars of this type known so far, and all of them seem to be relatively isolated, in contrast to their low mass counterparts, the T Tauri stars. A possible explanation of this fact is that other young stars formed near the known YSO are deeply embedded in the molecular cloud environment and are not detectable at optical wavelengths. We used the new ARcetri Near Infrared CAmera (ARNICA) to survey in the J, H and K bands the regions of sky around Herbig stars. The aim of this work is to identify embedded YSO and investigate the clustering properties of these young stars.

Self-consistent calculations for the electronic structure of a vacancy in copper. A solution of the embedding problem

NASA Astrophysics Data System (ADS)

Zeller, R.; Braspenning, P. J.

1982-06-01

The charge density and the local density of states for a vacancy in Cu and for the first shell of Cu neighbours are calculated by the KKR-Green's function technique. The muffin-tin potentials for the vacancy and the neighbour shell atoms are determined self-consistently in the local density approximation of density functional theory. By the use of the proper host Green's function the embedding of this cluster of 13 perturbed muffin-tins into the infinite array of bulk Cu muffin-tin potentials is described rigorously, thus representing a solution of the embedding problem. The calculations demonstrate a rather large charge transfer of 1.1 electrons from the first neighbour shell to the vacancy.

The star-forming complex LMC-N79 as a future rival to 30 Doradus

NASA Astrophysics Data System (ADS)

Ochsendorf, Bram B.; Zinnecker, Hans; Nayak, Omnarayani; Bally, John; Meixner, Margaret; Jones, Olivia C.; Indebetouw, Remy; Rahman, Mubdi

2017-11-01

Within the early Universe, `extreme' star formation may have been the norm rather than the exception1,2. Super star clusters (with masses greater than 105 solar masses) are thought to be the modern-day analogues of globular clusters, relics of a cosmic time (redshift z ≳ 2) when the Universe was filled with vigorously star-forming systems3. The giant H ii region 30 Doradus in the Large Magellanic Cloud is often regarded as a benchmark for studies of extreme star formation4. Here, we report the discovery of a massive embedded star-forming complex spanning about 500 pc in the unexplored southwest region of the Large Magellanic Cloud, which manifests itself as a younger, embedded twin of 30 Doradus. Previously known as N79, this region has a star-formation efficiency greater than that of 30 Doradus, by a factor of about 2, as measured over the past 0.5 Myr. Moreover, at the heart of N79 lies the most luminous infrared compact source discovered with large-scale infrared surveys of the Large Magellanic Cloud and Milky Way, possibly a precursor to the central super star cluster of 30 Doradus, R136. The discovery of a nearby candidate super star cluster may provide invaluable information to understand how extreme star formation proceeds in the current and high-redshift Universe.

A new method to unveil embedded stellar clusters

NASA Astrophysics Data System (ADS)

Lombardi, Marco; Lada, Charles J.; Alves, João

2017-11-01

In this paper we present a novel method to identify and characterize stellar clusters deeply embedded in a dark molecular cloud. The method is based on measuring stellar surface density in wide-field infrared images using star counting techniques. It takes advantage of the differing H-band luminosity functions (HLFs) of field stars and young stellar populations and is able to statistically associate each star in an image as a member of either the background stellar population or a young stellar population projected on or near the cloud. Moreover, the technique corrects for the effects of differential extinction toward each individual star. We have tested this method against simulations as well as observations. In particular, we have applied the method to 2MASS point sources observed in the Orion A and B complexes, and the results obtained compare very well with those obtained from deep Spitzer and Chandra observations where presence of infrared excess or X-ray emission directly determines membership status for every star. Additionally, our method also identifies unobscured clusters and a low resolution version of the Orion stellar surface density map shows clearly the relatively unobscured and diffuse OB 1a and 1b sub-groups and provides useful insights on their spatial distribution.

Weighing the Giants - I. Weak-lensing masses for 51 massive galaxy clusters: project overview, data analysis methods and cluster images

NASA Astrophysics Data System (ADS)

von der Linden, Anja; Allen, Mark T.; Applegate, Douglas E.; Kelly, Patrick L.; Allen, Steven W.; Ebeling, Harald; Burchat, Patricia R.; Burke, David L.; Donovan, David; Morris, R. Glenn; Blandford, Roger; Erben, Thomas; Mantz, Adam

2014-03-01

This is the first in a series of papers in which we measure accurate weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known at redshifts 0.15 ≲ zCl ≲ 0.7, in order to calibrate X-ray and other mass proxies for cosmological cluster experiments. The primary aim is to improve the absolute mass calibration of cluster observables, currently the dominant systematic uncertainty for cluster count experiments. Key elements of this work are the rigorous quantification of systematic uncertainties, high-quality data reduction and photometric calibration, and the `blind' nature of the analysis to avoid confirmation bias. Our target clusters are drawn from X-ray catalogues based on the ROSAT All-Sky Survey, and provide a versatile calibration sample for many aspects of cluster cosmology. We have acquired wide-field, high-quality imaging using the Subaru Telescope and Canada-France-Hawaii Telescope for all 51 clusters, in at least three bands per cluster. For a subset of 27 clusters, we have data in at least five bands, allowing accurate photometric redshift estimates of lensed galaxies. In this paper, we describe the cluster sample and observations, and detail the processing of the SuprimeCam data to yield high-quality images suitable for robust weak-lensing shape measurements and precision photometry. For each cluster, we present wide-field three-colour optical images and maps of the weak-lensing mass distribution, the optical light distribution and the X-ray emission. These provide insights into the large-scale structure in which the clusters are embedded. We measure the offsets between X-ray flux centroids and the brightest cluster galaxies in the clusters, finding these to be small in general, with a median of 20 kpc. For offsets ≲100 kpc, weak-lensing mass measurements centred on the brightest cluster galaxies agree well with values determined relative to the X-ray centroids; miscentring is therefore not a significant source of systematic uncertainty for our weak-lensing mass measurements. In accompanying papers, we discuss the key aspects of our photometric calibration and photometric redshift measurements (Kelly et al.), and measure cluster masses using two methods, including a novel Bayesian weak-lensing approach that makes full use of the photometric redshift probability distributions for individual background galaxies (Applegate et al.). In subsequent papers, we will incorporate these weak-lensing mass measurements into a self-consistent framework to simultaneously determine cluster scaling relations and cosmological parameters.

Fermat's least-time principle and the embedded transparent lens

NASA Astrophysics Data System (ADS)

Kantowski, R.; Chen, B.; Dai, X.

2013-10-01

We present a simplified version of the lowest-order embedded point mass gravitational lens theory and then make the extension of this theory to any embedded transparent lens. Embedding a lens effectively reduces the gravitational potential’s range, i.e., partially shields the lensing potential because the lens mass is made a contributor to the mean mass density of the Universe and not simply superimposed upon it. We give the time-delay function for the embedded point mass lens from which we can derive the simplified lens equation by applying Fermat’s least-time principle. Even though rigorous derivations are only made for the point mass in a flat background, the generalization of the lens equation to lowest order for any distributed lens in any homogeneous background is obvious. We find from this simplified theory that embedding can introduce corrections above the few percent level in weak lensing shears caused by large clusters but only at large impacts. The potential part of the time delay is also affected in strong lensing at the few percent level. Additionally we again confirm that the presence of a cosmological constant alters the gravitational deflection of passing photons.

From molecules to young stellar clusters: the star formation cycle across the disk of M 33

NASA Astrophysics Data System (ADS)

Corbelli, Edvige; Braine, Jonathan; Bandiera, Rino; Brouillet, Nathalie; Combes, Françoise; Druard, Clément; Gratier, Pierre; Mata, Jimmy; Schuster, Karl; Xilouris, Manolis; Palla, Francesco

2017-05-01

Aims: We study the association between giant molecular clouds (GMCs) and young stellar cluster candidates (YSCCs) to shed light on the time evolution of local star formation episodes in the nearby galaxy M 33. Methods: The CO (J = 2-1) IRAM all-disk survey was used to identify and classify 566 GMCs with masses between 2 × 104 and 2 × 106M⊙ across the whole star-forming disk of M 33. In the same area, there are 630 YSCCs that we identified using Spitzer-24 μm data. Some YSCCs are embedded star-forming sites, while the majority have GALEX-UV and Hα counterparts with estimated cluster masses and ages. Results: The GMC classes correspond to different cloud evolutionary stages: inactive clouds are 32% of the total and classified clouds with embedded and exposed star formation are 16% and 52% of the total, respectively. Across the regular southern spiral arm, inactive clouds are preferentially located in the inner part of the arm, possibly suggesting a triggering of star formation as the cloud crosses the arm. The spatial correlation between YSCCs and GMCs is extremely strong, with a typical separation of 17 pc. This is less than half the CO (2-1) beam size and illustrates the remarkable physical link between the two populations. GMCs and YSCCs follow the HI filaments, except in the outermost regions, where the survey finds fewer GMCs than YSCCs, which is most likely due to undetected clouds with low CO luminosity. The distribution of the non-embedded YSCC ages peaks around 5 Myr, with only a few being as old as 8-10 Myr. These age estimates together with the number of GMCs in the various evolutionary stages lead us to conclude that 14 Myr is the typical lifetime of a GMC in M 33 prior to cloud dispersal. The inactive and embedded phases are short, lasting about 4 and 2 Myr, respectively. This underlines that embedded YSCCs rapidly break out from the clouds and become partially visible in Hα or UV long before cloud dispersal. Full Tables 5 and 6 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/601/A146

Small Au clusters on a defective MgO(1 0 0) surface

NASA Astrophysics Data System (ADS)

Barcaro, Giovanni; Fortunelli, Alessandro

2008-05-01

The lowest energy structures of small T]>rndm where rndm is a random number (Metropolis criterion), the new configuration is accepted, otherwise the old configuration is kept, and the process is iterated. For each size we performed 3-5 BH runs, each one composed of 20-25 Monte Carlo steps, using a value of 0.5 eV as kT in the Metropolis criterion. Previous experience [13-15] shows that this is sufficient to single out the global minimum for adsorbed clusters of this size, and that the BH approach is more efficient as a global optimization algorithm than other techniques such as simulated annealing [18]. The MgO support was described via an (Mg 12O 12) cluster embedded in an array of ±2.0 a.u. point charges and repulsive pseudopotentials on the positive charges in direct contact with the cluster (see Ref. [15] for more details on the method). The atoms of the oxide cluster and the point charges were located at the lattice positions of the MgO rock-salt bulk structure using the experimental lattice constant of 4.208 Å. At variance with the ), evaluated by subtracting the energy of the oxide surface and of the metal cluster, both frozen in their interacting configuration, from the value of the total energy of the system, and by taking the absolute value; (ii) the binding energy of the metal cluster (E), evaluated by subtracting the energy of the isolated metal atoms from the total energy of the metal cluster in its interacting configuration, and by taking the absolute value; (iii) the metal cluster distortion energy (E), which corresponds to the difference between the energy of the metal cluster in the configuration interacting with the surface minus the energy of the cluster in its lowest-energy gas-phase configuration (a positive quantity); (iv) the oxide distortion energy (ΔE), evaluated subtracting the energy of the relaxed isolated defected oxide from the energy of the isolated defected oxide in the interacting configuration; and (v) the total binding energy (E), which is the sum of the binding energy of the metal cluster, the adhesion energy and the oxide distortion energy (E=E+E-ΔE). Note that the total binding energy of gas-phase clusters in their global minima can be obtained by summing E+E.

Tracing the Arms of our Milky Way Galaxy

NASA Image and Video Library

2015-06-03

Astronomers using data from NASA's Wide-field Infrared Survey Explorer, or WISE, are helping to trace the shape of our Milky Way galaxy's spiral arms. This illustration shows where WISE data revealed clusters of young stars shrouded in dust, called embedded clusters, which are known to reside in spiral arms. The bars represent uncertainties in the data. The nearly 100 clusters shown here were found in the arms called Perseus, Sagittarius-Carina, and Outer -- three of the galaxy's four proposed primary arms. Our sun resides in a spur to an arm, or a minor arm, called Orion Cygnus. http://photojournal.jpl.nasa.gov/catalog/PIA19341

Melting of Cu nanoclusters by molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Wang, Li; Zhang, Yanning; Bian, Xiufang; Chen, Ying

2003-04-01

We present a detailed molecular dynamics study of the melting of copper nanoclusters with up to 8628 atoms within the framework of the embedded-atom method. The finding indicates that there exists an intermediate nanocrystal regime above 456 atoms. The linear relation between the cluster size and its thermodynamics properties is obeyed in this regime. Melting first occurs at the surface of the clusters, leading to Tm, N= Tm,Bulk- αN-1/3, dropping from Tm,Bulk=1360 K to Tm,456=990 K. In addition, the size, surface energy as well as the root mean square displacement (RMSD) of the clusters in the intermediate regime have been investigated.

The impact of decision aids to enhance shared decision making for diabetes (the DAD study): protocol of a cluster randomized trial.

PubMed

LeBlanc, Annie; Ruud, Kari L; Branda, Megan E; Tiedje, Kristina; Boehmer, Kasey R; Pencille, Laurie J; Van Houten, Holly; Matthews, Marc; Shah, Nilay D; May, Carl R; Yawn, Barbara P; Montori, Victor M

2012-05-28

Shared decision making contributes to high quality healthcare by promoting a patient-centered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient's values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice. We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms. Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices. NCT00388050.

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

PubMed Central

Liu, Wenfen

2017-01-01

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight. PMID:29312447

Dark energy and key physical parameters of clusters of galaxies

NASA Astrophysics Data System (ADS)

Bisnovatyi-Kogan, G. S.; Chernin, A. D.

2012-04-01

We study physics of clusters of galaxies embedded in the cosmic dark energy background. Under the assumption that dark energy is described by the cosmological constant, we show that the dynamical effects of dark energy are strong in clusters like the Virgo cluster. Specifically, the key physical parameters of the dark mater halos in clusters are determined by dark energy: (1) the halo cut-off radius is practically, if not exactly, equal to the zero-gravity radius at which the dark matter gravity is balanced by the dark energy antigravity; (2) the halo averaged density is equal to two densities of dark energy; (3) the halo edge (cut-off) density is the dark energy density with a numerical factor of the unity order slightly depending on the halo profile. The cluster gravitational potential well in which the particles of the dark halo (as well as galaxies and intracluster plasma) move is strongly affected by dark energy: the maximum of the potential is located at the zero-gravity radius of the cluster.

X-Ray Gas Temperatures in the Arc Clusters MS0440+204 and MS0302+1658

NASA Technical Reports Server (NTRS)

Gioia, Isabella M.; White, Nicholas

1997-01-01

The cluster of galaxies MS0440+02, originally discovered through its X-ray emission, was part of an optical observational program to search for arcs and arclets in a complete sample of X-ray luminous, medium-distant clusters of galaxies. Mauna Kea CCD images of MS0440+02 showed a remarkable optical morphology. The core of the cluster contains 6 bright galaxies and numerous fainter ones embedded in a low surface brightness halo. Besides, MS0440+02 is the most spectacular example that we have found of an arc system in a compact condensed cluster, with arcs symmetrically distributed to draw almost perfect circles around the cluster center. Giant arcs are magnified images of distant galaxies, gravitationally distorted by massive foreground clusters. It is of great importance to compare the results of the lensing studies with those derived from X-ray observations, as the two are independent methods of studying the mass distribution. Thus MS0440+02 was the ideal target to obtain temperature measurement with ASCA and good spatial resolution X-ray observations with ROSAT. The X-ray data have been used in conjunction with Hubble Space Telescope observations to put more stringent constrains on the mass estimates. Most of the different wavelength datasets have been reduced and analyzed. Mass determinations have been separately obtained from galaxy virial motions and X-ray profile fitting using the cluster gas temperature as measured by the ASCA satellite. Assuming that the hot gas is in hydrostatic equilibrium and in a spherical potential, we find from the X-ray data a mass distribution profile that is well described by a Beta model. From the multiple images formed by gravitational lensing (HST data) using the modelling of the gravitational lensed arcs, we have derived Beta model. To reconcile the mass estimates we have explored the possibility of having a supercluster surrounding the MOS0440 cluster, that is a model with two isothermal spheres, one embedded inside the other. These results have been published or are in press.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin

2011-12-01

Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis. © 2011 IEEE

Filtering large-scale event collections using a combination of supervised and unsupervised learning for event trigger classification.

PubMed

Mehryary, Farrokh; Kaewphan, Suwisa; Hakala, Kai; Ginter, Filip

2016-01-01

Biomedical event extraction is one of the key tasks in biomedical text mining, supporting various applications such as database curation and hypothesis generation. Several systems, some of which have been applied at a large scale, have been introduced to solve this task. Past studies have shown that the identification of the phrases describing biological processes, also known as trigger detection, is a crucial part of event extraction, and notable overall performance gains can be obtained by solely focusing on this sub-task. In this paper we propose a novel approach for filtering falsely identified triggers from large-scale event databases, thus improving the quality of knowledge extraction. Our method relies on state-of-the-art word embeddings, event statistics gathered from the whole biomedical literature, and both supervised and unsupervised machine learning techniques. We focus on EVEX, an event database covering the whole PubMed and PubMed Central Open Access literature containing more than 40 million extracted events. The top most frequent EVEX trigger words are hierarchically clustered, and the resulting cluster tree is pruned to identify words that can never act as triggers regardless of their context. For rarely occurring trigger words we introduce a supervised approach trained on the combination of trigger word classification produced by the unsupervised clustering method and manual annotation. The method is evaluated on the official test set of BioNLP Shared Task on Event Extraction. The evaluation shows that the method can be used to improve the performance of the state-of-the-art event extraction systems. This successful effort also translates into removing 1,338,075 of potentially incorrect events from EVEX, thus greatly improving the quality of the data. The method is not solely bound to the EVEX resource and can be thus used to improve the quality of any event extraction system or database. The data and source code for this work are available at: http://bionlp-www.utu.fi/trigger-clustering/.

High Performance Molecular Visualization: In-Situ and Parallel Rendering with EGL.

PubMed

Stone, John E; Messmer, Peter; Sisneros, Robert; Schulten, Klaus

2016-05-01

Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications.

Topological structures in the equities market network

PubMed Central

Leibon, Gregory; Pauls, Scott; Rockmore, Daniel; Savell, Robert

2008-01-01

We present a new method for articulating scale-dependent topological descriptions of the network structure inherent in many complex systems. The technique is based on “partition decoupled null models,” a new class of null models that incorporate the interaction of clustered partitions into a random model and generalize the Gaussian ensemble. As an application, we analyze a correlation matrix derived from 4 years of close prices of equities in the New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotation (NASDAQ). In this example, we expose (i) a natural structure composed of 2 interacting partitions of the market that both agrees with and generalizes standard notions of scale (e.g., sector and industry) and (ii) structure in the first partition that is a topological manifestation of a well-known pattern of capital flow called “sector rotation.” Our approach gives rise to a natural form of multiresolution analysis of the underlying time series that naturally decomposes the basic data in terms of the effects of the different scales at which it clusters. We support our conclusions and show the robustness of the technique with a successful analysis on a simulated network with an embedded topological structure. The equities market is a prototypical complex system, and we expect that our approach will be of use in understanding a broad class of complex systems in which correlation structures are resident.

High Performance Molecular Visualization: In-Situ and Parallel Rendering with EGL

PubMed Central

Stone, John E.; Messmer, Peter; Sisneros, Robert; Schulten, Klaus

2016-01-01

Large scale molecular dynamics simulations produce terabytes of data that is impractical to transfer to remote facilities. It is therefore necessary to perform visualization tasks in-situ as the data are generated, or by running interactive remote visualization sessions and batch analyses co-located with direct access to high performance storage systems. A significant challenge for deploying visualization software within clouds, clusters, and supercomputers involves the operating system software required to initialize and manage graphics acceleration hardware. Recently, it has become possible for applications to use the Embedded-system Graphics Library (EGL) to eliminate the requirement for windowing system software on compute nodes, thereby eliminating a significant obstacle to broader use of high performance visualization applications. We outline the potential benefits of this approach in the context of visualization applications used in the cloud, on commodity clusters, and supercomputers. We discuss the implementation of EGL support in VMD, a widely used molecular visualization application, and we outline benefits of the approach for molecular visualization tasks on petascale computers, clouds, and remote visualization servers. We then provide a brief evaluation of the use of EGL in VMD, with tests using developmental graphics drivers on conventional workstations and on Amazon EC2 G2 GPU-accelerated cloud instance types. We expect that the techniques described here will be of broad benefit to many other visualization applications. PMID:27747137

Consequences of realistic embedding for the L 2,3 edge XAS of α-Fe 2 O 3

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

Bagus, Paul S.; Nelin, Connie J.; Sassi, Michel

Cluster models of condensed systems are often used to simulate the core-level spectra obtained with X-ray Photoelectron Spectroscopy, XPS, or with X-ray Absorption Spectroscopy, XAS, especially for near edge features.

Academic Literacies as Cornerstones in Course Design: A Partnership to Develop Programming for Faculty and Teaching Assistants

ERIC Educational Resources Information Center

Bury, Sophie; Sheese, Ron

2016-01-01

We discuss an educational development approach to embedding academic literacies instruction within disciplinary curricula. This developmental, embedded approach contrasts with the generic, extra-curricular, study-skills approach adopted in many universities. Learning Commons partners at York University, including librarians, writing instructors,…

Embedded-Based Graphics Processing Unit Cluster Platform for Multiple Sequence Alignments

PubMed Central

Wei, Jyh-Da; Cheng, Hui-Jun; Lin, Chun-Yuan; Ye, Jin; Yeh, Kuan-Yu

2017-01-01

High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments. PMID:28835734

Embedded-Based Graphics Processing Unit Cluster Platform for Multiple Sequence Alignments.

PubMed

Wei, Jyh-Da; Cheng, Hui-Jun; Lin, Chun-Yuan; Ye, Jin; Yeh, Kuan-Yu

2017-01-01

High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments.

Unsupervised Structure Detection in Biomedical Data.

PubMed

Vogt, Julia E

2015-01-01

A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood comparisons that detects structure in unsupervised data. The method is based on ordering objects in terms of similarity and on the mutual overlap of nearest neighbors. This basic framework was originally introduced in the field of social network analysis to detect actor communities. We demonstrate that the same ideas can successfully be applied to biomedical data sets in order to reveal complex underlying structure. The algorithm is very efficient and works on distance data directly without requiring a vectorial embedding of data. Comprehensive experiments demonstrate the validity of this approach. Comparisons with state-of-the-art clustering methods show that the presented method outperforms hierarchical methods as well as density based clustering methods and model-based clustering. A further advantage of the method is that it simultaneously provides a visualization of the data. Especially in biomedical applications, the visualization of data can be used as a first pre-processing step when analyzing real world data sets to get an intuition of the underlying data structure. We apply this model to synthetic data as well as to various biomedical data sets which demonstrate the high quality and usefulness of the inferred structure.

Identification and classification of hubs in brain networks.

PubMed

Sporns, Olaf; Honey, Christopher J; Kötter, Rolf

2007-10-17

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.

From the tunneling dimer to the onset of microsolvation: Infrared spectroscopy of allyl radical water aggregates in helium nanodroplets

NASA Astrophysics Data System (ADS)

Leicht, Daniel; Kaufmann, Matin; Pal, Nitish; Schwaab, Gerhard; Havenith, Martina

2017-03-01

The infrared spectrum of allyl:water clusters embedded in helium nanodroplets was recorded. Allyl radicals were produced by flash vacuum pyrolysis and trapped in helium droplets. Deuterated water was added to the doped droplets, and the infrared spectrum of the radical water aggregates was recorded in the frequency range 2570-2820 cm-1. Several absorption bands are observed and assigned to 1:1 and 1:2 allyl:D2O clusters, based on pressure dependent measurements and accompanying quantum chemical calculations. The analysis of the 1:1 cluster spectrum revealed a tunneling splitting as well as a combination band. For the 1:2 cluster, we observe a water dimer-like motif that is bound by one π-hydrogen bond to the allyl radical.

Design for the fabrication of high efficiency solar cells

DOEpatents

Simmons, Joseph H.

1998-01-01

A method and apparatus for a photo-active region for generation of free carriers when a first surface is exposed to optical radiation. The photo-active region includes a conducting transparent matrix and clusters of semiconductor materials embedded within the conducting transparent matrix. The clusters are arranged in the matrix material so as to define at least a first distribution of cluster sizes ranging from those with the highest bandgap energy near a light incident surface of the photo-active region to those with the smallest bandgap energy near an opposite second surface of the photo-active region. Also disclosed is a method and apparatus for a solar cell. The solar cell includes a photo-active region containing a plurality of semiconductor clusters of varying sizes as described.

Functionalizing graphene by embedded boron clusters

NASA Astrophysics Data System (ADS)

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

2010-03-01

We present results from an ab initio study of B7 clusters implanted into graphene [1,2]. Our model system consists of an alternating chain of quasiplanar B7 clusters. We show that graphene easily accepts these alternating B7-C6 chains and that the implanted boron components may dramatically modify the electronic properties. This suggests that our model system might serve as a blueprint for the controlled layout of graphene based nanodevices, where the semiconducting properties are supplemented by parts of the graphene matrix itself, and the basic metallic wiring is provided by alternating chains of implanted boron clusters. [1] A. Quandt, C. "Ozdogan, J. Kunstmann, and H. Fehske, Nanotechnology 19, 335707 (2008). [2] A. Quandt, C. "Ozdogan, J. Kunstmann, and H. Fehske, phys. stat. solidi (b) 245, 2077 (2008).

Growth of polymer-metal nanocomposites by pulsed laser deposition

NASA Astrophysics Data System (ADS)

Röder, Johanna; Faupel, Jörg; Krebs, Hans-Ulrich

2008-12-01

Complex polymer-metal nanocomposites have a wide range of applications, e.g. as flexible displays and packaging materials. Pulsed laser deposition was applied to form nanostructured materials consisting of metal clusters (Ag, Au, Pd and Cu) embedded in a polymer (polycarbonate, PC) matrix. The size and amount of the metal clusters are controlled by the number of laser pulses hitting the respective targets. For Cu and Pd, smaller clusters and higher cluster densities are obtained as in the cases of Ag and Au due to a stronger reactivity with the polymers and thus a lower diffusivity. Implantation effects, differences in metal diffusivity and reactivity on the polymer surfaces, and the coalescence properties are discussed with respect to the observed microstructures on PC and compared to the metal growth on poly (methyl methacrylate), PMMA.

New mechanisms of cluster diffusion on metal fcc(100) surfaces

NASA Astrophysics Data System (ADS)

Trushin, Oleg; Salo, Petri; Alatalo, Matti; Ala-Nissila, Tapio

2001-03-01

We have studied atomic mechanisms of the diffusion of small clusters on the fcc(100) metal surfaces using semi-empirical and ab-initio molecular static calculations. Primary goal of these studies was to investigate possible many-body mechanisms of cluster motion which can contribute to low temperature crystal growth. We used embedded atom and Glue potentials in semi-empirical simulations of Cu and Al. Combination of the Nudged Elastic Band and Eigenvector Following methods allowed us to find all the possible transition paths for cluster movements on flat terrace. In case of Cu(001) we have found several new mechanisms for diffusion of clusters, including mechanisms called row-shearing and dimer-rotating in which a whole row inside an island moves according to a concerted jump and a dimer rotates at the periphery of an island, respectively. In some cases these mechanisms yield a lower energy barrier than the standard mechanisms.

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

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

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

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

Chromium: A Stress-Processing Framework for Interactive Rendering on Clusters

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

Humphreys, G,; Houston, M.; Ng, Y.-R.

2002-01-11

We describe Chromium, a system for manipulating streams of graphics API commands on clusters of workstations. Chromium's stream filters can be arranged to create sort-first and sort-last parallel graphics architectures that, in many cases, support the same applications while using only commodity graphics accelerators. In addition, these stream filters can be extended programmatically, allowing the user to customize the stream transformations performed by nodes in a cluster. Because our stream processing mechanism is completely general, any cluster-parallel rendering algorithm can be either implemented on top of or embedded in Chromium. In this paper, we give examples of real-world applications thatmore » use Chromium to achieve good scalability on clusters of workstations, and describe other potential uses of this stream processing technology. By completely abstracting the underlying graphics architecture, network topology, and API command processing semantics, we allow a variety of applications to run in different environments.« less

The split in the ancient cold front in the Perseus cluster

NASA Astrophysics Data System (ADS)

Walker, Stephen A.; ZuHone, John; Fabian, Andy; Sanders, Jeremy

2018-04-01

Sloshing cold fronts in clusters, produced as the dense cluster core moves around in the cluster potential in response to in-falling subgroups, provide a powerful probe of the physics of the intracluster medium and the magnetic fields permeating it1,2. These sharp discontinuities in density and temperature rise gradually outwards with age in a characteristic spiral pattern, embedding into the intracluster medium a record of the minor merging activity of clusters: the further from the cluster centre a cold front is, the older it is. Recently, it was discovered that these cold fronts can survive out to extremely large radii in the Perseus cluster3. Here, we report on high-spatial-resolution Chandra observations of the large-scale cold front in Perseus. We find that rather than broadening through diffusion, the cold front remains extremely sharp (consistent with abrupt jumps in density) and instead is split into two sharp edges. These results show that magnetic draping can suppress diffusion for vast periods of time—around 5 Gyr—even as the cold front expands out to nearly half the cluster virial radius.

Photometric and spectroscopic study of low mass embedded star clusters in reflection nebulae

NASA Astrophysics Data System (ADS)

Soares, J. B.; Bica, E.; Ahumada, A. V.; Clariá, J. J.

2005-02-01

An analysis of the candidate embedded stellar systems in the reflection nebulae vdBH-RN 26, vdBH-RN} 38, vdBH-RN} 53a, GGD 20, ESO 95-RN 18 and NGC 6595 is presented. Optical spectroscopic data from CASLEO (Argentina) in conjunction with near infrared photometry from the 2MASS Point Source Catalogue were employed. The analysis is based on source surface density, colour-colour and colour-magnitude diagrams together with theoretical pre-main sequence isochrones. We take into account the field population affecting the analysis by carrying out a statistical subtraction. The fundamental parameters for the stellar systems were derived. The resulting ages are in the range 1-4 Myr and the objects are dominated by pre-main sequence stars. The observed masses locked in the clusters are less than 25 M⊙. The studied systems have no stars of spectral types earlier than B, indicating that star clusters do not necessarily evolve through an HII region phase. The relatively small locked mass combined with the fact that they are not numerous in catalogues suggests that these low mass clusters are not important donors of stars to the field populations. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina and the National Universities of La Plata, Córdoba and San Juan, Argentina.

Evaluation of optical and electronic properties of silicon nano-agglomerates embedded in SRO: applying density functional theory

PubMed Central

2014-01-01

In systems in atomic scale and nanoscale such as clusters or agglomerates constituted by particles from a few to less than 100 atoms, quantum confinement effects are very important. Their optical and electronic properties are often dependent on the size of the systems and the way in which the atoms in these clusters are bonded. Generally, these nanostructures display optical and electronic properties significantly different to those found in corresponding bulk materials. Silicon agglomerates embedded in silicon rich oxide (SRO) films have optical properties, which have been reported to be directly dependent on silicon nanocrystal size. Furthermore, the room temperature photoluminescence (PL) of SRO has repeatedly generated a huge interest due to its possible applications in optoelectronic devices. However, a plausible emission mechanism has not been widely accepted in the scientific community. In this work, we present a short review about the experimental results on silicon nanoclusters in SRO considering different techniques of growth. We focus mainly on their size, Raman spectra, and photoluminescence spectra. With this as background, we employed the density functional theory with a functional B3LYP and a basis set 6-31G* to calculate the optical and electronic properties of clusters of silicon (constituted by 15 to 20 silicon atoms). With the theoretical calculation of the structural and optical properties of silicon clusters, it is possible to evaluate the contribution of silicon agglomerates in the luminescent emission mechanism, experimentally found in thin SRO films. PMID:25276105

Improved Electrostatic Embedding for Fragment-Based Chemical Shift Calculations in Molecular Crystals.

PubMed

Hartman, Joshua D; Balaji, Ashwin; Beran, Gregory J O

2017-12-12

Fragment-based methods predict nuclear magnetic resonance (NMR) chemical shielding tensors in molecular crystals with high accuracy and computational efficiency. Such methods typically employ electrostatic embedding to mimic the crystalline environment, and the quality of the results can be sensitive to the embedding treatment. To improve the quality of this embedding environment for fragment-based molecular crystal property calculations, we borrow ideas from the embedded ion method to incorporate self-consistently polarized Madelung field effects. The self-consistent reproduction of the Madelung potential (SCRMP) model developed here constructs an array of point charges that incorporates self-consistent lattice polarization and which reproduces the Madelung potential at all atomic sites involved in the quantum mechanical region of the system. The performance of fragment- and cluster-based 1 H, 13 C, 14 N, and 17 O chemical shift predictions using SCRMP and density functionals like PBE and PBE0 are assessed. The improved embedding model results in substantial improvements in the predicted 17 O chemical shifts and modest improvements in the 15 N ones. Finally, the performance of the model is demonstrated by examining the assignment of the two oxygen chemical shifts in the challenging γ-polymorph of glycine. Overall, the SCRMP-embedded NMR chemical shift predictions are on par with or more accurate than those obtained with the widely used gauge-including projector augmented wave (GIPAW) model.

A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Tiwari, Pallavi; Rosen, Mark; Madabhushi, Anant

2008-03-01

Recently, in vivo Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) have emerged as promising new modalities to aid in prostate cancer (CaP) detection. MRI provides anatomic and structural information of the prostate while MRS provides functional data pertaining to biochemical concentrations of metabolites such as creatine, choline and citrate. We have previously presented a hierarchical clustering scheme for CaP detection on in vivo prostate MRS and have recently developed a computer-aided method for CaP detection on in vivo prostate MRI. In this paper we present a novel scheme to develop a meta-classifier to detect CaP in vivo via quantitative integration of multimodal prostate MRS and MRI by use of non-linear dimensionality reduction (NLDR) methods including spectral clustering and locally linear embedding (LLE). Quantitative integration of multimodal image data (MRI and PET) involves the concatenation of image intensities following image registration. However multimodal data integration is non-trivial when the individual modalities include spectral and image intensity data. We propose a data combination solution wherein we project the feature spaces (image intensities and spectral data) associated with each of the modalities into a lower dimensional embedding space via NLDR. NLDR methods preserve the relationships between the objects in the original high dimensional space when projecting them into the reduced low dimensional space. Since the original spectral and image intensity data are divorced from their original physical meaning in the reduced dimensional space, data at the same spatial location can be integrated by concatenating the respective embedding vectors. Unsupervised consensus clustering is then used to partition objects into different classes in the combined MRS and MRI embedding space. Quantitative results of our multimodal computer-aided diagnosis scheme on 16 sets of patient data obtained from the ACRIN trial, for which corresponding histological ground truth for spatial extent of CaP is known, show a marginally higher sensitivity, specificity, and positive predictive value compared to corresponding CAD results with the individual modalities.

Understanding the many-body expansion for large systems. II. Accuracy considerations

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

Lao, Ka Un; Liu, Kuan-Yu; Richard, Ryan M.

2016-04-28

To complement our study of the role of finite precision in electronic structure calculations based on a truncated many-body expansion (MBE, or “n-body expansion”), we examine the accuracy of such methods in the present work. Accuracy may be defined either with respect to a supersystem calculation computed at the same level of theory as the n-body calculations, or alternatively with respect to high-quality benchmarks. Both metrics are considered here. In applications to a sequence of water clusters, (H{sub 2}O){sub N=6−55} described at the B3LYP/cc-pVDZ level, we obtain mean absolute errors (MAEs) per H{sub 2}O monomer of ∼1.0 kcal/mol for two-bodymore » expansions, where the benchmark is a B3LYP/cc-pVDZ calculation on the entire cluster. Three- and four-body expansions exhibit MAEs of 0.5 and 0.1 kcal/mol/monomer, respectively, without resort to charge embedding. A generalized many-body expansion truncated at two-body terms [GMBE(2)], using 3–4 H{sub 2}O molecules per fragment, outperforms all of these methods and affords a MAE of ∼0.02 kcal/mol/monomer, also without charge embedding. GMBE(2) requires significantly fewer (although somewhat larger) subsystem calculations as compared to MBE(4), reducing problems associated with floating-point roundoff errors. When compared to high-quality benchmarks, we find that error cancellation often plays a critical role in the success of MBE(n) calculations, even at the four-body level, as basis-set superposition error can compensate for higher-order polarization interactions. A many-body counterpoise correction is introduced for the GMBE, and its two-body truncation [GMBCP(2)] is found to afford good results without error cancellation. Together with a method such as ωB97X-V/aug-cc-pVTZ that can describe both covalent and non-covalent interactions, the GMBE(2)+GMBCP(2) approach provides an accurate, stable, and tractable approach for large systems.« less

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

PubMed Central

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

2015-01-01

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

Coexistence of two electronic phases in LaTiO3+δ (0.01⩽δ⩽0.12) and their evolution with δ

NASA Astrophysics Data System (ADS)

Zhou, H. D.; Goodenough, J. B.

2005-04-01

Although LaTiO3+δ(0.01⩽δ⩽0.12) is single-phase to powder x-ray diffraction, its properties reveal that a hole-poor strongly correlated electronic phase coexists with a hole-rich itinerant-electron phase. With δ⩽0.03 , the hole-rich phase exists as a minority phase of isolated, mobile itinerant-electron clusters embedded in the hole-poor phase. With δ⩾0.08 , isolated hole-poor clusters are embedded in an itinerant-electron matrix. As δ>0.08 increases, the hole-poor clusters become smaller and more isolated until they are reduced to superparamagnetic strong-correlation fluctuations by δ=0.12 . This behavior is consistent with prediction from the virial theorem of a first-order phase change at the crossover from localized (or strongly correlated) to itinerant electronic behavior, a smaller equilibrium (Ti-O) bond length being in the itinerant-electron phase. Accordingly, the variation of volume with oxidation state does not obey Végard’s law; the itinerant-electron minority phase exerts a compressive force on the hole-poor matrix, and the hole-poor minority phase exerts a tensile stress on the hole-rich matrix.

Constraint Embedding for Multibody System Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2009-01-01

This paper describes a constraint embedding approach for the handling of local closure constraints in multibody system dynamics. The approach uses spatial operator techniques to eliminate local-loop constraints from the system and effectively convert the system into tree-topology systems. This approach allows the direct derivation of recursive O(N) techniques for solving the system dynamics and avoiding the expensive steps that would otherwise be required for handling the closedchain dynamics. The approach is very effective for systems where the constraints are confined to small-subgraphs within the system topology. The paper provides background on the spatial operator O(N) algorithms, the extensions for handling embedded constraints, and concludes with some examples of such constraints.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

PubMed

Xu, Lina; O'Hare, Gregory M P; Collier, Rem

2017-07-05

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks †

PubMed Central

O’Hare, Gregory M. P.; Collier, Rem

2017-01-01

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work—Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity. PMID:28678164

Dynamics of fragment formation in neutron-rich matter

NASA Astrophysics Data System (ADS)

Alcain, P. N.; Dorso, C. O.

2018-01-01

Background: Neutron stars are astronomical systems with nucleons subjected to extreme conditions. Due to the longer range Coulomb repulsion between protons, the system has structural inhomogeneities. Several interactions tailored to reproduce nuclear matter plus a screened Coulomb term reproduce these inhomogeneities known as nuclear pasta. These structural inhomogeneities, located in the crusts of neutron stars, can also arise in expanding systems depending on the thermodynamic conditions (temperature, proton fraction, etc.) and the expansion velocity. Purpose: We aim to find the dynamics of the fragment formation for expanding systems simulated according to the little big bang model. This expansion resembles the evolution of merging neutron stars. Method: We study the dynamics of the nucleons with semiclassical molecular dynamics models. Starting with an equilibrium configuration, we expand the system homogeneously until we arrive at an asymptotic configuration (i.e., very low final densities). We study, with four different cluster recognition algorithms, the fragment distribution throughout this expansion and the dynamics of the cluster formation. Results: Studying the topology of the equilibrium states, before the expansion, we reproduced the known pasta phases plus a novel phase we called pregnocchi, consisting of proton aggregates embedded in a neutron sea. We have identified different fragmentation regimes, depending on the initial temperature and fragment velocity. In particular, for the already mentioned pregnocchi, a neutron cloud surrounds the clusters during the early stages of the expansion, resulting in systems that give rise to configurations compatible with the emergence of the r process. Conclusions: We showed that a proper identification of the cluster distribution is highly dependent on the cluster recognition algorithm chosen, and found that the early cluster recognition algorithm (ECRA) was the most stable one. This approach allowed us to identify the dynamics of the fragment formation. These calculations pave the way to a comparison between Earth experiments and neutron star studies.

Quasi-dynamic earthquake fault systems with rheological heterogeneity

NASA Astrophysics Data System (ADS)

Brietzke, G. B.; Hainzl, S.; Zoeller, G.; Holschneider, M.

2009-12-01

Seismic risk and hazard estimates mostly use pure empirical, stochastic models of earthquake fault systems tuned specifically to the vulnerable areas of interest. Although such models allow for reasonable risk estimates, such models cannot allow for physical statements of the described seismicity. In contrary such empirical stochastic models, physics based earthquake fault systems models allow for a physical reasoning and interpretation of the produced seismicity and system dynamics. Recently different fault system earthquake simulators based on frictional stick-slip behavior have been used to study effects of stress heterogeneity, rheological heterogeneity, or geometrical complexity on earthquake occurrence, spatial and temporal clustering of earthquakes, and system dynamics. Here we present a comparison of characteristics of synthetic earthquake catalogs produced by two different formulations of quasi-dynamic fault system earthquake simulators. Both models are based on discretized frictional faults embedded in an elastic half-space. While one (1) is governed by rate- and state-dependent friction with allowing three evolutionary stages of independent fault patches, the other (2) is governed by instantaneous frictional weakening with scheduled (and therefore causal) stress transfer. We analyze spatial and temporal clustering of events and characteristics of system dynamics by means of physical parameters of the two approaches.

Large magnetovolume effect induced by ferromagnetic-antiferromagnetic competition in a cobaltite perovskite

NASA Astrophysics Data System (ADS)

Miao, Ping; Lin, Xiaohuan; Koda, Akihiro; Lee, Sanghyun; Ishikawa, Yoshihisa; Torii, Shuki; Yonemura, Masao; Mochiku, Takashi; Sagayama, Hajime; Itoh, Shinichi; Wang, Yinxia; Kadono, Ryosuke; Kamiyama, Takashi

Materials that show negative thermal expansion (NTE) have significant industrial merit because they can be used to fabricate composites whose dimensions remain invariant upon heating. In some materials, NTE is concomitant with the spontaneous magnetization, known as the magnetovolume effect (MVE). Here we report a new class of MVE material; namely, a layered perovskite PrBaCo2O5.5+ x (0 <= x <= 0.41),in which strong NTE (β -3.3 × 10-5 K-1 at x = 0.24) is triggered by embedding ferromagnetic (F) clusters into the antiferromagnetic (AF) matrix. The strongest MVE is found near the boundary between F and AF phases in the phase diagram, indicating the essential role of competing interaction between the F-clusters and the AF-matrix. Furthermore, the MVE is not limited to the PrBaCo2O5.5+ x but is also observed in the NdBaCo2O5.5+ x . The present study provides a new approach to obtaining MVE and offers a path to the design of NTE materials. The study was financed by the S-type project (No. 2014S05) of KEK.

Wiggler magnetic field assisted third harmonic generation in expanding clusters

NASA Astrophysics Data System (ADS)

Vij, Shivani

2018-04-01

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

Social networks and links to isolation and loneliness among elderly HCBS clients.

PubMed

Medvene, Louis J; Nilsen, Kari M; Smith, Rachel; Ofei-Dodoo, Samuel; DiLollo, Anthony; Webster, Noah; Graham, Annette; Nance, Anita

2016-01-01

The purpose of this study was to explore the network types of HCBS clients based on the structural characteristics of their social networks. We also examined how the network types were associated with social isolation, relationship quality and loneliness. Forty personal interviews were carried out with HCBS clients to assess the structure of their social networks as indicated by frequency of contact with children, friends, family and participation in religious and community organizations. Hierarchical cluster analysis was conducted to identify network types. Four network types were found including: family (n = 16), diverse (n = 8), restricted (n = 8) and religious (n = 7). Family members comprised almost half of participants' social networks, and friends comprised less than one-third. Clients embedded in family, diverse and religious networks had significantly more positive relationships than clients embedded in restricted networks. Clients embedded in restricted networks had significantly higher social isolation scores and were lonelier than clients in diverse and family networks. The findings suggest that HCBS clients' isolation and loneliness are linked to the types of social networks in which they are embedded. The findings also suggest that clients embedded in restricted networks are at high risk for negative outcomes.

Star formation activity in the southern Galactic H II region G351.63-1.25

NASA Astrophysics Data System (ADS)

Vig, S.; Ghosh, S. K.; Ojha, D. K.; Verma, R. P.; Tamura, M.

2014-06-01

The southern Galactic high-mass star-forming region, G351.63-1.25, is an H II region-molecular cloud complex with a luminosity of ˜2.0 × 105 L⊙, located at a distance of 2.4 kpc from the Sun. In this paper, we focus on the investigation of the associated H II region, embedded cluster and the interstellar medium in the vicinity of G351.63-1.25. We address the identification of exciting source(s) as well as the census of the stellar populations, in an attempt to unfold star formation activity in this region. The ionized gas distribution has been mapped using the Giant Metrewave Radio Telescope, India, at three frequencies: 1280, 610 and 325 MHz. The H II region shows an elongated morphology and the 1280 MHz map comprises six resolved high-density regions encompassed by diffuse emission spanning 1.4 × 1.0 pc2. Based on the measurements of flux densities at multiple radio frequencies, the brightest ultracompact core has electron temperature Te˜7647 {±} 153 K and emission measure, EM˜2.0 {±} 0.8×107 cm-6 pc. The zero-age main-sequence spectral type of the brightest radio core is O7.5. We have carried out near-infrared observations in the JHKs bands using the SIRIUS camera on the 1.4 m Infrared Survey Facility telescope. The near-infrared images reveal the presence of a cluster embedded in nebulous fan-shaped emission. The log-normal slope of the K-band luminosity function of the embedded cluster is found to be ˜0.27 ± 0.03, and the fraction of the near-infrared excess stars is estimated to be 43 per cent. These indicate that the age of the cluster is consistent with ˜1 Myr. Other available data of this region show that the warm (mid-infrared) and cold (millimetre) dust emission peak at different locations indicating progressive stages of star formation process. The champagne flow model from a flat, thin molecular cloud is used to explain the morphology of radio emission with respect to the millimetre cloud and infrared brightness.

The Wicked Problem of Embedding Academic Literacies: Exploring Rhizomatic Ways of Working through an Adaptive Leadership Approach

ERIC Educational Resources Information Center

Benzie, Helen Joy; Pryce, Alison; Smith, Keith

2017-01-01

Embedding academic literacies in higher education courses has been a major focus of the work of learning advisers. A number of studies present the results of embedding in specific courses without discussing the processes of negotiation or the different people involved. This paper is about embedding academic literacies in the Business faculty as…

Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes

PubMed Central

Zhang, Yaoyun; Li, Hee-Jin; Wang, Jingqi; Cohen, Trevor; Roberts, Kirk; Xu, Hua

2018-01-01

Mental health is increasingly recognized an important topic in healthcare. Information concerning psychiatric symptoms is critical for the timely diagnosis of mental disorders, as well as for the personalization of interventions. However, the diversity and sparsity of psychiatric symptoms make it challenging for conventional natural language processing techniques to automatically extract such information from clinical text. To address this problem, this study takes the initiative to use and adapt word embeddings from four source domains – intensive care, biomedical literature, Wikipedia and Psychiatric Forum – to recognize symptoms in the target domain of psychiatry. We investigated four different approaches including 1) only using word embeddings of the source domain, 2) directly combining data of the source and target to generate word embeddings, 3) assigning different weights to word embeddings, and 4) retraining the word embedding model of the source domain using a corpus of the target domain. To the best of our knowledge, this is the first work of adapting multiple word embeddings of external domains to improve psychiatric symptom recognition in clinical text. Experimental results showed that the last two approaches outperformed the baseline methods, indicating the effectiveness of our new strategies to leverage embeddings from other domains. PMID:29888086

NGC 346: Looking in the Cradle of a Massive Star Cluster

NASA Astrophysics Data System (ADS)

Gouliermis, Dimitrios A.; Hony, Sacha

2017-03-01

How does a star cluster of more than few 10,000 solar masses form? We present the case of the cluster NGC 346 in the Small Magellanic Cloud, still embedded in its natal star-forming region N66, and we propose a scenario for its formation, based on observations of the rich stellar populations in the region. Young massive clusters host a high fraction of early-type stars, indicating an extremely high star formation efficiency. The Milky Way galaxy hosts several young massive clusters that fill the gap between young low-mass open clusters and old massive globular clusters. Only a handful, though, are young enough to study their formation. Moreover, the investigation of their gaseous natal environments suffers from contamination by the Galactic disk. Young massive clusters are very abundant in distant starburst and interacting galaxies, but the distance of their hosting galaxies do not also allow a detailed analysis of their formation. The Magellanic Clouds, on the other hand, host young massive clusters in a wide range of ages with the youngest being still embedded in their giant HII regions. Hubble Space Telescope imaging of such star-forming complexes provide a stellar sampling with a high dynamic range in stellar masses, allowing the detailed study of star formation at scales typical for molecular clouds. Our cluster analysis on the distribution of newly-born stars in N66 shows that star formation in the region proceeds in a clumpy hierarchical fashion, leading to the formation of both a dominant young massive cluster, hosting about half of the observed pre-main-sequence population, and a self-similar dispersed distribution of the remaining stars. We investigate the correlation between stellar surface density (and star formation rate derived from star-counts) and molecular gas surface density (derived from dust column density) in order to unravel the physical conditions that gave birth to NGC 346. A power law fit to the data yields a steep correlation between these two parameters with a considerable scatter. The fraction of stellar over the total (gas plus young stars) mass is found to be systematically higher within the central 15 pc (where the young massive cluster is located) than outside, which suggests variations in the star formation efficiency within the same star-forming complex. This trend possibly reflects a change of star formation efficiency in N66 between clustered and non-clustered star formation. Our findings suggest that the formation of NGC 346 is the combined result of star formation regulated by turbulence and of early dynamical evolution induced by the gravitational potential of the dense interstellar medium.

Endohedral gallide cluster superconductors and superconductivity in ReGa5.

PubMed

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-12-22

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures.

Fragmentation dynamics of ionized neon clusters (Ne(n), n=3-14) embedded in helium nanodroplets.

PubMed

Bonhommeau, David; Halberstadt, Nadine; Viel, Alexandra

2006-01-14

We report a theoretical study of the nonadiabatic fragmentation dynamics of ionized neon clusters embedded in helium nanodroplets for cluster sizes up to n=14 atoms. The dynamics of the neon atoms is modeled using the molecular dynamics with quantum transitions method of Tully [J. Chem. Phys. 93, 1061 (1990)] with the nuclei treated classically and transitions between electronic states quantum mechanically. The potential-energy surfaces are derived from a diatomics-in-molecules model to which induced dipole-induced dipole interactions are added. The effect of the spin-orbit interaction is also discussed. The helium environment is modeled by a friction force acting on charged atoms whose speed exceeds the critical Landau velocity. The dependence of the fragment size distribution on the friction strength and on the initial nanodroplet size is investigated. By comparing with the available experimental data obtained for Ne3+ and Ne4+, a reasonable value for the friction coefficient, the only parameter of the model, is deduced. This value is then used to predict the effect of the helium environment on the dissociation dynamics of larger neon clusters, n=5-14. The results show stabilization of larger fragments than in the gas phase, but fragmentation is not completely caged. In addition, two types of dynamics are characterized for Ne4+: fast and explosive, therefore leaving no time for friction to cool down the process when dynamics starts on one of the highest electronic states, and slower, therefore leading to some stabilization by helium when it starts on one of the lowest electronic states.

Key-Node-Separated Graph Clustering and Layouts for Human Relationship Graph Visualization.

PubMed

Itoh, Takayuki; Klein, Karsten

2015-01-01

Many graph-drawing methods apply node-clustering techniques based on the density of edges to find tightly connected subgraphs and then hierarchically visualize the clustered graphs. However, users may want to focus on important nodes and their connections to groups of other nodes for some applications. For this purpose, it is effective to separately visualize the key nodes detected based on adjacency and attributes of the nodes. This article presents a graph visualization technique for attribute-embedded graphs that applies a graph-clustering algorithm that accounts for the combination of connections and attributes. The graph clustering step divides the nodes according to the commonality of connected nodes and similarity of feature value vectors. It then calculates the distances between arbitrary pairs of clusters according to the number of connecting edges and the similarity of feature value vectors and finally places the clusters based on the distances. Consequently, the technique separates important nodes that have connections to multiple large clusters and improves the visibility of such nodes' connections. To test this technique, this article presents examples with human relationship graph datasets, including a coauthorship and Twitter communication network dataset.

Magnetism in Mn-nanowires and -clusters as δ-doped layers in group IV semiconductors (Si, Ge)

NASA Astrophysics Data System (ADS)

Simov, K. R.; Glans, P.-A.; Jenkins, C. A.; Liberati, M.; Reinke, P.

2018-01-01

Mn doping of group-IV semiconductors (Si/Ge) is achieved by embedding nanostructured Mn-layers in group-IV matrix. The Mn-nanostructures are monoatomic Mn-wires or Mn-clusters and capped with an amorphous Si or Ge layer. The precise fabrication of δ-doped Mn-layers is combined with element-specific detection of the magnetic signature with x-ray magnetic circular dichroism. The largest moment (2.5 μB/Mn) is measured for Mn-wires with ionic bonding character and a-Ge overlayer cap; a-Si capping reduces the moment due to variations of bonding in agreement with theoretical predictions. The moments in δ-doped layers dominated by clusters is quenched with an antiferromagnetic component from Mn-Mn bonding.

Curvature and temperature of complex networks.

PubMed

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Vahdat, Amin; Boguñá, Marián

2009-09-01

We show that heterogeneous degree distributions in observed scale-free topologies of complex networks can emerge as a consequence of the exponential expansion of hidden hyperbolic space. Fermi-Dirac statistics provides a physical interpretation of hyperbolic distances as energies of links. The hidden space curvature affects the heterogeneity of the degree distribution, while clustering is a function of temperature. We embed the internet into the hyperbolic plane and find a remarkable congruency between the embedding and our hyperbolic model. Besides proving our model realistic, this embedding may be used for routing with only local information, which holds significant promise for improving the performance of internet routing.

Micromagnetics on high-performance workstation and mobile computational platforms

NASA Astrophysics Data System (ADS)

Fu, S.; Chang, R.; Couture, S.; Menarini, M.; Escobar, M. A.; Kuteifan, M.; Lubarda, M.; Gabay, D.; Lomakin, V.

2015-05-01

The feasibility of using high-performance desktop and embedded mobile computational platforms is presented, including multi-core Intel central processing unit, Nvidia desktop graphics processing units, and Nvidia Jetson TK1 Platform. FastMag finite element method-based micromagnetic simulator is used as a testbed, showing high efficiency on all the platforms. Optimization aspects of improving the performance of the mobile systems are discussed. The high performance, low cost, low power consumption, and rapid performance increase of the embedded mobile systems make them a promising candidate for micromagnetic simulations. Such architectures can be used as standalone systems or can be built as low-power computing clusters.

Promoting Teacher Growth through Lesson Study: A Culturally Embedded Approach

ERIC Educational Resources Information Center

Ebaeguin, Marlon

2015-01-01

Lesson Study has captured the attention of many international educators with its promise of improved student learning and sustained teacher growth. Lesson Study, however, has cultural underpinnings that a simple transference model overlooks. A culturally embedded approach attends to the existing cultural orientations and values of host schools.…

Fragment-Based Electronic Structure Approach for Computing Nuclear Magnetic Resonance Chemical Shifts in Molecular Crystals.

PubMed

Hartman, Joshua D; Beran, Gregory J O

2014-11-11

First-principles chemical shielding tensor predictions play a critical role in studying molecular crystal structures using nuclear magnetic resonance. Fragment-based electronic structure methods have dramatically improved the ability to model molecular crystal structures and energetics using high-level electronic structure methods. Here, a many-body expansion fragment approach is applied to the calculation of chemical shielding tensors in molecular crystals. First, the impact of truncating the many-body expansion at different orders and the role of electrostatic embedding are examined on a series of molecular clusters extracted from molecular crystals. Second, the ability of these techniques to assign three polymorphic forms of the drug sulfanilamide to the corresponding experimental (13)C spectra is assessed. This challenging example requires discriminating among spectra whose (13)C chemical shifts differ by only a few parts per million (ppm) across the different polymorphs. Fragment-based PBE0/6-311+G(2d,p) level chemical shielding predictions correctly assign these three polymorphs and reproduce the sulfanilamide experimental (13)C chemical shifts with 1 ppm accuracy. The results demonstrate that fragment approaches are competitive with the widely used gauge-invariant projector augmented wave (GIPAW) periodic density functional theory calculations.

Using kaizen to improve employee well-being: Results from two organizational intervention studies.

PubMed

von Thiele Schwarz, Ulrica; Nielsen, Karina M; Stenfors-Hayes, Terese; Hasson, Henna

2017-08-01

Participatory intervention approaches that are embedded in existing organizational structures may improve the efficiency and effectiveness of organizational interventions, but concrete tools are lacking. In the present article, we use a realist evaluation approach to explore the role of kaizen, a lean tool for participatory continuous improvement, in improving employee well-being in two cluster-randomized, controlled participatory intervention studies. Case 1 is from the Danish Postal Service, where kaizen boards were used to implement action plans. The results of multi-group structural equation modeling showed that kaizen served as a mechanism that increased the level of awareness of and capacity to manage psychosocial issues, which, in turn, predicted increased job satisfaction and mental health. Case 2 is from a regional hospital in Sweden that integrated occupational health processes with a pre-existing kaizen system. Multi-group structural equation modeling revealed that, in the intervention group, kaizen work predicted better integration of organizational and employee objectives after 12 months, which, in turn, predicted increased job satisfaction and decreased discomfort at 24 months. The findings suggest that participatory and structured problem-solving approaches that are familiar and visual to employees can facilitate organizational interventions.

Using kaizen to improve employee well-being: Results from two organizational intervention studies

PubMed Central

von Thiele Schwarz, Ulrica; Nielsen, Karina M; Stenfors-Hayes, Terese; Hasson, Henna

2016-01-01

Participatory intervention approaches that are embedded in existing organizational structures may improve the efficiency and effectiveness of organizational interventions, but concrete tools are lacking. In the present article, we use a realist evaluation approach to explore the role of kaizen, a lean tool for participatory continuous improvement, in improving employee well-being in two cluster-randomized, controlled participatory intervention studies. Case 1 is from the Danish Postal Service, where kaizen boards were used to implement action plans. The results of multi-group structural equation modeling showed that kaizen served as a mechanism that increased the level of awareness of and capacity to manage psychosocial issues, which, in turn, predicted increased job satisfaction and mental health. Case 2 is from a regional hospital in Sweden that integrated occupational health processes with a pre-existing kaizen system. Multi-group structural equation modeling revealed that, in the intervention group, kaizen work predicted better integration of organizational and employee objectives after 12 months, which, in turn, predicted increased job satisfaction and decreased discomfort at 24 months. The findings suggest that participatory and structured problem-solving approaches that are familiar and visual to employees can facilitate organizational interventions. PMID:28736455

A model for the infrared emission from an OB star cluster environment

NASA Technical Reports Server (NTRS)

Leisawitz, D.

1991-01-01

A model for the infrared emission from the neighborhood of an OB star cluster is described. The distribution of gas and dust around the stars, properties of the dust, and the cluster and interstellar radiation fields are variable. The model can be applied to regions around clusters embedded to various degrees in their parental molecular clouds (i.e., compact H II regions, blister-type H II regions, and the tenuous H II regions ionized by naked O stars). The model is used to simulate IRAS observations of a typical blister H II region. Infrared surface brightness and spectral energy distributions are predicted and the impact of limited spatial resolution is illustrated. The model results are shown to be consistent with observations of the exemplary outer Galaxy OB cluster NGC 7380. It is planned to use the model as a diagnostic tool to probe the physical conditions and dust properties in star-formation regions and, ultimately, in an interpretation of the spectral energy distributions of spiral galaxies.

The organization of prospective thinking: evidence of event clusters in freely generated future thoughts.

PubMed

Demblon, Julie; D'Argembeau, Arnaud

2014-02-01

Recent research suggests that many imagined future events are not represented in isolation, but instead are embedded in broader event sequences-referred to as event clusters. It remains unclear, however, whether the production of event clusters reflects the underlying organizational structure of prospective thinking or whether it is an artifact of the event-cuing task in which participants are explicitly required to provide chains of associated future events. To address this issue, the present study examined whether the occurrence of event clusters in prospective thought is apparent when people are left to think freely about events that might happen in their personal future. The results showed that the succession of events participants spontaneously produced when envisioning their future frequently included event clusters. This finding provides more compelling evidence that prospective thinking involves higher-order autobiographical knowledge structures that organize imagined events in coherent themes and sequences. Copyright © 2014 Elsevier Inc. All rights reserved.

The impact of advertising patient and public involvement on trial recruitment: embedded cluster randomised recruitment trial.

PubMed

Hughes-Morley, Adwoa; Hann, Mark; Fraser, Claire; Meade, Oonagh; Lovell, Karina; Young, Bridget; Roberts, Chris; Cree, Lindsey; More, Donna; O'Leary, Neil; Callaghan, Patrick; Waheed, Waquas; Bower, Peter

2016-12-08

Patient and public involvement in research (PPIR) may improve trial recruitment rates, but it is unclear how. Where trials use PPIR to improve design and conduct, many do not communicate this clearly to potential participants. Better communication of PPIR might encourage patient enrolment, as trials may be perceived as more socially valid, relevant and trustworthy. We aimed to evaluate the impact on recruitment of directly advertising PPIR to potential trial participants. This is a cluster trial, embedded within a host trial ('EQUIP') recruiting service users diagnosed with severe mental illness. The intervention was informed by a systematic review, a qualitative study, social comparison theory and a stakeholder workshop including service users and carers. Adopting Participatory Design approaches, we co-designed the recruitment intervention with PPIR partners using a leaflet to advertise the PPIR in EQUIP and sent potential participants invitations with the leaflet (intervention group) or not (control group). Primary outcome was the proportion of patients enrolled in EQUIP. Secondary outcomes included the proportions of patients who positively responded to the trial invitation. Thirty-four community mental health teams were randomised and 8182 service users invited. For the primary outcome, 4% of patients in the PPIR group were enrolled versus 5.3% of the control group. The intervention was not effective for improving recruitment rates (adjusted OR = 0.75, 95% CI = 0.53 to 1.07, p = 0.113). For the secondary outcome of positive response, the intervention was not effective, with 7.3% of potential participants in the intervention group responding positively versus 7.9% of the control group (adjusted OR = 0.74, 95% CI = 0.53 to 1.04, p = 0.082). We did not find a positive impact of directly advertising PPIR on any other outcomes. To our knowledge, this is the largest ever embedded trial to evaluate a recruitment or PPIR intervention. Advertising PPIR did not improve enrolment rates or any other outcome. It is possible that rather than advertising PPIR being the means to improve recruitment, PPIR may have an alternative impact on trials by making them more attractive, acceptable and patient-centred. We discuss potential reasons for our findings and implications for recruitment practice and research. ISRCTN, ISRCTN16488358 . Registered on 14 May 2014. Study Within A Trial, SWAT-26 . Registered on 21 January 2016.

H II REGIONS, EMBEDDED PROTOSTARS, AND STARLESS CORES IN SHARPLESS 2-157

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

Chen, Chian-Chou; Williams, Jonathan P.; Pandian, Jagadheep D., E-mail: ccchen@ifa.hawaii.edu, E-mail: jpw@ifa.hawaii.edu, E-mail: jagadheep@iist.ac.in

2012-06-20

We present arcsecond resolution 1.4 mm observations of the high-mass star-forming region, Sharpless 2-157, that reveal the cool dust associated with the first stages of star formation. These data are compared with archival images at optical, infrared, and radio wavelengths, and complemented with new arcsecond resolution mid-infrared data. We identify a dusty young H II region, numerous infrared sources within the cluster envelope, and four starless condensations. Three of the cores lie in a line to the south of the cluster peak, but the most massive one is right at the center and associated with a jumble of bright radiomore » and infrared sources. This presents an interesting juxtaposition of high- and low-mass star formation within the same cluster which we compare with similar observations of other high-mass star-forming regions and discuss in the context of cluster formation theory.« less

Local matrix learning in clustering and applications for manifold visualization.

PubMed

Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara

2010-05-01

Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization. 2009 Elsevier Ltd. All rights reserved.

Migration in the shearing sheet and estimates for young open cluster migration

NASA Astrophysics Data System (ADS)

Quillen, Alice C.; Nolting, Eric; Minchev, Ivan; De Silva, Gayandhi; Chiappini, Cristina

2018-04-01

Using tracer particles embedded in self-gravitating shearing sheet N-body simulations, we investigate the distance in guiding centre radius that stars or star clusters can migrate in a few orbital periods. The standard deviations of guiding centre distributions and maximum migration distances depend on the Toomre or critical wavelength and the contrast in mass surface density caused by spiral structure. Comparison between our simulations and estimated guiding radii for a few young supersolar metallicity open clusters, including NGC 6583, suggests that the contrast in mass surface density in the solar neighbourhood has standard deviation (in the surface density distribution) divided by mean of about 1/4 and larger than measured using COBE data by Drimmel and Spergel. Our estimate is consistent with a standard deviation of ˜0.07 dex in the metallicities measured from high-quality spectroscopic data for 38 young open clusters (<1 Gyr) with mean galactocentric radius 7-9 kpc.

Clustering Tree-structured Data on Manifold

PubMed Central

Lu, Na; Miao, Hongyu

2016-01-01

Tree-structured data usually contain both topological and geometrical information, and are necessarily considered on manifold instead of Euclidean space for appropriate data parameterization and analysis. In this study, we propose a novel tree-structured data parameterization, called Topology-Attribute matrix (T-A matrix), so the data clustering task can be conducted on matrix manifold. We incorporate the structure constraints embedded in data into the non-negative matrix factorization method to determine meta-trees from the T-A matrix, and the signature vector of each single tree can then be extracted by meta-tree decomposition. The meta-tree space turns out to be a cone space, in which we explore the distance metric and implement the clustering algorithm based on the concepts like Fréchet mean. Finally, the T-A matrix based clustering (TAMBAC) framework is evaluated and compared using both simulated data and real retinal images to illus trate its efficiency and accuracy. PMID:26660696

Analyzing the anodic reactions for iron surface with a porous Al2O3 cluster with the scanning vibrating electrode

NASA Astrophysics Data System (ADS)

Eliyan, Faysal Fayez

2017-09-01

The Scanning Vibrating Electrode Technique (SVET) was used to analyze the anodic reactions inside and around a porous Al2O3 cluster embedded onto an iron foil. The tests were carried out at -0.7 V vs. Saturated Calomel Electrode, in naturally aerated solutions of 0.1, 0.2, 0.35, and 0.5 M bicarbonate concentration. During 10 h of testing, the SVET showed evidence for a formation of a passive film in and around the cluster, in the scanning area shown in the graphical abstract. In the dilute 0.1 and 0.2 M solutions, the passive films formed slower than those in 0.35 and 0.5 M solutions. In the SVET maps, the passive films showed that they could suppress dissolution to currents comparable to those of slower dissolution under the porous Al2O3 cluster.

Identification of the Viridicatumtoxin and Griseofulvin Gene Clusters from Penicillium aethiopicum

PubMed Central

Chooi, Yit-Heng; Cacho, Ralph; Tang, Yi

2010-01-01

SUMMARY Penicillium aethiopicum produces two structurally interesting and biologically active polyketides: the tetracycline-like viridicatumtoxin 1 and the classic antifungal agent griseofulvin 2. Here, we report the concurrent discovery of the two corresponding biosynthetic gene clusters (vrt and gsf) by 454 shotgun sequencing. Gene deletions confirmed two nonreducing PKSs (NRPKS), vrtA and gsfA, are required for the biosynthesis of 1 and 2, respectively. Both PKSs share similar domain architectures and lack a C-terminal thioesterase domain. We identified gsfI as the chlorinase involved in the biosynthesis of 2, as deletion of gsfI resulted in the accumulation of decholorogriseofulvin 3. Comparative analysis with the P. chrysogenum genome revealed that both clusters are embedded within conserved syntenic regions of P. aethiopicum chromosomes. Discovery of the vrt and gsf clusters provided the basis for genetic and biochemical studies of the pathways. PMID:20534346

A new ATLAS muon CSC readout system with system on chip technology on ATCA platform

DOE PAGES

Claus, R.

2015-10-23

The ATLAS muon Cathode Strip Chamber (CSC) back-end readout system has been upgraded during the LHC 2013-2015 shutdown to be able to handle the higher Level-1 trigger rate of 100 kHz and the higher occupancy at Run 2 luminosity. The readout design is based on the Reconfiguration Cluster Element (RCE) concept for high bandwidth generic DAQ implemented on the ATCA platform. The RCE design is based on the new System on Chip Xilinx Zynq series with a processor-centric architecture with ARM processor embedded in FPGA fabric and high speed I/O resources together with auxiliary memories to form a versatile DAQmore » building block that can host applications tapping into both software and firmware resources. The Cluster on Board (COB) ATCA carrier hosts RCE mezzanines and an embedded Fulcrum network switch to form an online DAQ processing cluster. More compact firmware solutions on the Zynq for G-link, S-link and TTC allowed the full system of 320 G-links from the 32 chambers to be processed by 6 COBs in one ATCA shelf through software waveform feature extraction to output 32 S-links. Furthermore, the full system was installed in Sept. 2014. We will present the RCE/COB design concept, the firmware and software processing architecture, and the experience from the intense commissioning towards LHC Run 2.« less

Efficient active waveguiding properties of Mo6 nano-cluster-doped polymer nanotubes

NASA Astrophysics Data System (ADS)

Bigeon, J.; Huby, N.; Amela-Cortes, M.; Molard, Y.; Garreau, A.; Cordier, S.; Bêche, B.; Duvail, J.-L.

2016-06-01

We investigate 1D nanostructures based on a Mo6@SU8 hybrid nanocomposite in which photoluminescent Mo6 clusters are embedded in the photosensitive SU8 resist. Tens of micrometers long Mo6@SU8-based tubular nanostructures were fabricated by the wetting template method, enabling the control of the inner and outer diameter to about 190 nm and 240 nm respectively, as supported by structural and optical characterizations. The image plane optical study of these nanotubes under optical pumping highlights the efficient waveguiding phenomenon of the red luminescence emitted by the clusters. Moreover, the wave vector distribution in the Fourier plane determined by leakage radiation microscopy gives additional features of the emission and waveguiding. First, the anisotropic red luminescence of the whole system can be attributed to the guided mode along the nanotube. Then, a low-loss propagation behavior is evidenced in the Mo6@SU8-based nanotubes. This result contrasts with the weaker waveguiding signature in the case of UV210-based nanotubes embedding PFO (poly(9,9-di-n-octylfluorenyl-2,7-diyl)). It is attributed to the strong reabsorption phenomenon, owing to overlapping between absorption and emission bands in the semi-conducting conjugated polymer PFO. These results make this Mo6@SU8 original class of nanocomposite a promising candidate as nanosources for submicronic photonic integration.

Efficient active waveguiding properties of Mo6 nano-cluster-doped polymer nanotubes.

PubMed

Bigeon, J; Huby, N; Amela-Cortes, M; Molard, Y; Garreau, A; Cordier, S; Bêche, B; Duvail, J-L

2016-06-24

We investigate 1D nanostructures based on a Mo6@SU8 hybrid nanocomposite in which photoluminescent Mo6 clusters are embedded in the photosensitive SU8 resist. Tens of micrometers long Mo6@SU8-based tubular nanostructures were fabricated by the wetting template method, enabling the control of the inner and outer diameter to about 190 nm and 240 nm respectively, as supported by structural and optical characterizations. The image plane optical study of these nanotubes under optical pumping highlights the efficient waveguiding phenomenon of the red luminescence emitted by the clusters. Moreover, the wave vector distribution in the Fourier plane determined by leakage radiation microscopy gives additional features of the emission and waveguiding. First, the anisotropic red luminescence of the whole system can be attributed to the guided mode along the nanotube. Then, a low-loss propagation behavior is evidenced in the Mo6@SU8-based nanotubes. This result contrasts with the weaker waveguiding signature in the case of UV210-based nanotubes embedding PFO (poly(9,9-di-n-octylfluorenyl-2,7-diyl)). It is attributed to the strong reabsorption phenomenon, owing to overlapping between absorption and emission bands in the semi-conducting conjugated polymer PFO. These results make this Mo6@SU8 original class of nanocomposite a promising candidate as nanosources for submicronic photonic integration.

A new ATLAS muon CSC readout system with system on chip technology on ATCA platform

NASA Astrophysics Data System (ADS)

Claus, R.; ATLAS Collaboration

2016-07-01

The ATLAS muon Cathode Strip Chamber (CSC) back-end readout system has been upgraded during the LHC 2013-2015 shutdown to be able to handle the higher Level-1 trigger rate of 100 kHz and the higher occupancy at Run 2 luminosity. The readout design is based on the Reconfiguration Cluster Element (RCE) concept for high bandwidth generic DAQ implemented on the ATCA platform. The RCE design is based on the new System on Chip Xilinx Zynq series with a processor-centric architecture with ARM processor embedded in FPGA fabric and high speed I/O resources together with auxiliary memories to form a versatile DAQ building block that can host applications tapping into both software and firmware resources. The Cluster on Board (COB) ATCA carrier hosts RCE mezzanines and an embedded Fulcrum network switch to form an online DAQ processing cluster. More compact firmware solutions on the Zynq for G-link, S-link and TTC allowed the full system of 320 G-links from the 32 chambers to be processed by 6 COBs in one ATCA shelf through software waveform feature extraction to output 32 S-links. The full system was installed in Sept. 2014. We will present the RCE/COB design concept, the firmware and software processing architecture, and the experience from the intense commissioning towards LHC Run 2.

A new ATLAS muon CSC readout system with system on chip technology on ATCA platform

NASA Astrophysics Data System (ADS)

Bartoldus, R.; Claus, R.; Garelli, N.; Herbst, R. T.; Huffer, M.; Iakovidis, G.; Iordanidou, K.; Kwan, K.; Kocian, M.; Lankford, A. J.; Moschovakos, P.; Nelson, A.; Ntekas, K.; Ruckman, L.; Russell, J.; Schernau, M.; Schlenker, S.; Su, D.; Valderanis, C.; Wittgen, M.; Yildiz, S. C.

2016-01-01

The ATLAS muon Cathode Strip Chamber (CSC) backend readout system has been upgraded during the LHC 2013-2015 shutdown to be able to handle the higher Level-1 trigger rate of 100 kHz and the higher occupancy at Run-2 luminosity. The readout design is based on the Reconfigurable Cluster Element (RCE) concept for high bandwidth generic DAQ implemented on the Advanced Telecommunication Computing Architecture (ATCA) platform. The RCE design is based on the new System on Chip XILINX ZYNQ series with a processor-centric architecture with ARM processor embedded in FPGA fabric and high speed I/O resources. Together with auxiliary memories, all these components form a versatile DAQ building block that can host applications tapping into both software and firmware resources. The Cluster on Board (COB) ATCA carrier hosts RCE mezzanines and an embedded Fulcrum network switch to form an online DAQ processing cluster. More compact firmware solutions on the ZYNQ for high speed input and output fiberoptic links and TTC allowed the full system of 320 input links from the 32 chambers to be processed by 6 COBs in one ATCA shelf. The full system was installed in September 2014. We will present the RCE/COB design concept, the firmware and software processing architecture, and the experience from the intense commissioning for LHC Run 2.

A new ATLAS muon CSC readout system with system on chip technology on ATCA platform

DOE PAGES

Bartoldus, R.; Claus, R.; Garelli, N.; ...

2016-01-25

The ATLAS muon Cathode Strip Chamber (CSC) backend readout system has been upgraded during the LHC 2013-2015 shutdown to be able to handle the higher Level-1 trigger rate of 100 kHz and the higher occupancy at Run-2 luminosity. The readout design is based on the Reconfigurable Cluster Element (RCE) concept for high bandwidth generic DAQ implemented on the Advanced Telecommunication Computing Architecture (ATCA) platform. The RCE design is based on the new System on Chip XILINX ZYNQ series with a processor-centric architecture with ARM processor embedded in FPGA fabric and high speed I/O resources. Together with auxiliary memories, all ofmore » these components form a versatile DAQ building block that can host applications tapping into both software and firmware resources. The Cluster on Board (COB) ATCA carrier hosts RCE mezzanines and an embedded Fulcrum network switch to form an online DAQ processing cluster. More compact firmware solutions on the ZYNQ for high speed input and output fiberoptic links and TTC allowed the full system of 320 input links from the 32 chambers to be processed by 6 COBs in one ATCA shelf. The full system was installed in September 2014. In conclusion, we will present the RCE/COB design concept, the firmware and software processing architecture, and the experience from the intense commissioning for LHC Run 2.« less

Dynamics of Fractal Cluster Gels with Embedded Active Colloids

NASA Astrophysics Data System (ADS)

Szakasits, Megan E.; Zhang, Wenxuan; Solomon, Michael J.

2017-08-01

We find that embedded active colloids increase the ensemble-averaged mean squared displacement of particles in otherwise passively fluctuating fractal cluster gels. The enhancement in dynamics occurs by a mechanism in which the active colloids contribute to the average dynamics both directly through their own active motion and indirectly through their excitation of neighboring passive colloids in the fractal network. Fractal cluster gels are synthesized by addition of magnesium chloride to an initially stable suspension of 1.0 μ m polystyrene colloids in which a dilute concentration of platinum coated Janus colloids has been dispersed. The Janus colloids are thereby incorporated into the fractal network. We measure the ensemble-averaged mean squared displacement of all colloids in the gel before and after the addition of hydrogen peroxide, a fuel that drives diffusiophoretic motion of the Janus particles. The gel mean squared displacement increases by up to a factor of 3 for an active to passive particle ratio of 1 ∶20 and inputted active energy—defined based on the hydrogen peroxide's effect on colloid swim speed and run length—that is up to 9.5 times thermal energy, on a per particle basis. We model the enhancement in gel particle dynamics as the sum of a direct contribution from the displacement of the Janus particles themselves and an indirect contribution from the strain field that the active colloids induce in the surrounding passive particles.

IN-SYNC. II. Virial Stars from Subvirial Cores—the Velocity Dispersion of Embedded Pre-main-sequence Stars in NGC 1333

NASA Astrophysics Data System (ADS)

Foster, Jonathan B.; Cottaar, Michiel; Covey, Kevin R.; Arce, Héctor G.; Meyer, Michael R.; Nidever, David L.; Stassun, Keivan G.; Tan, Jonathan C.; Chojnowski, S. Drew; da Rio, Nicola; Flaherty, Kevin M.; Rebull, Luisa; Frinchaboy, Peter M.; Majewski, Steven R.; Skrutskie, Michael; Wilson, John C.; Zasowski, Gail

2015-02-01

The initial velocity dispersion of newborn stars is a major unconstrained aspect of star formation theory. Using near-infrared spectra obtained with the APOGEE spectrograph, we show that the velocity dispersion of young (1-2 Myr) stars in NGC 1333 is 0.92 ± 0.12 km s-1 after correcting for measurement uncertainties and the effect of binaries. This velocity dispersion is consistent with the virial velocity of the region and the diffuse gas velocity dispersion, but significantly larger than the velocity dispersion of the dense, star-forming cores, which have a subvirial velocity dispersion of 0.5 km s-1. Since the NGC 1333 cluster is dynamically young and deeply embedded, this measurement provides a strong constraint on the initial velocity dispersion of newly formed stars. We propose that the difference in velocity dispersion between stars and dense cores may be due to the influence of a 70 μG magnetic field acting on the dense cores or be the signature of a cluster with initial substructure undergoing global collapse.

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

Gravitational energy in the framework of embedding and splitting theories

NASA Astrophysics Data System (ADS)

Grad, D. A.; Ilin, R. V.; Paston, S. A.; Sheykin, A. A.

We study various definitions of the gravitational field energy based on the usage of isometric embeddings in the Regge-Teitelboim approach. For the embedding theory, we consider the coordinate translations on the surface as well as the coordinate translations in the flat bulk. In the latter case, the independent definition of gravitational energy-momentum tensor appears as a Noether current corresponding to global inner symmetry. In the field-theoretic form of this approach (splitting theory), we consider Noether procedure and the alternative method of energy-momentum tensor defining by varying the action of the theory with respect to flat bulk metric. As a result, we obtain energy definition in field-theoretic form of embedding theory which, among the other features, gives a nontrivial result for the solutions of embedding theory which are also solutions of Einstein equations. The question of energy localization is also discussed.

Interpreting semantic clustering effects in free recall.

PubMed

Manning, Jeremy R; Kahana, Michael J

2012-07-01

The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organised, and retrieved. One pervasive finding is that when a pair of semantically related words (e.g., "cat" and "dog") is embedded in the studied list, the related words are often recalled successively. This tendency to successively recall semantically related words is termed semantic clustering (Bousfield, 1953; Bousfield & Sedgewick, 1944; Cofer, Bruce, & Reicher, 1966). Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. However, it is often difficult to gain insights into individual participants' internal semantic models, and for this reason researchers typically rely on standardised semantic similarity metrics. Here we use simulations to gain insights into the expected magnitudes of semantic clustering effects given systematic differences between participants' internal similarity models and the similarity metric used to quantify the degree of semantic clustering. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.

Branching points in the low-temperature dipolar hard sphere fluid

NASA Astrophysics Data System (ADS)

Rovigatti, Lorenzo; Kantorovich, Sofia; Ivanov, Alexey O.; Tavares, José Maria; Sciortino, Francesco

2013-10-01

In this contribution, we investigate the low-temperature, low-density behaviour of dipolar hard-sphere (DHS) particles, i.e., hard spheres with dipoles embedded in their centre. We aim at describing the DHS fluid in terms of a network of chains and rings (the fundamental clusters) held together by branching points (defects) of different nature. We first introduce a systematic way of classifying inter-cluster connections according to their topology, and then employ this classification to analyse the geometric and thermodynamic properties of each class of defects, as extracted from state-of-the-art equilibrium Monte Carlo simulations. By computing the average density and energetic cost of each defect class, we find that the relevant contribution to inter-cluster interactions is indeed provided by (rare) three-way junctions and by four-way junctions arising from parallel or anti-parallel locally linear aggregates. All other (numerous) defects are either intra-cluster or associated to low cluster-cluster interaction energies, suggesting that these defects do not play a significant part in the thermodynamic description of the self-assembly processes of dipolar hard spheres.

Active galactic nuclei. IV - Supplying black hole clusters by tidal disruption and by tidal capture of stars

NASA Technical Reports Server (NTRS)

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

1992-01-01

The extent to which individual holes in a cluster of black holes with a mass spectrum can liberate and accrete the resulting material by tidally disrupting stars they encounter, or by capturing stars as binary companions is studied. It is found that the smaller black holes in 'the halo' of such clusters can adequately supply themselves to the level M-dot sub h or greater than 0.0001(M-dot sub h) sub crit, and up to 0.05(M-dot sub h)sub crit for the smallest holes, by tidal disruption, as long as the cluster is embedded in a distribution of stars of relatively high density (not less than 0.1M sub cl/cu pc), and as long as the entire cluster of stars is not too compact (not less than 0.5 pc). Consideration is given to modifications this 'internal' mode of supply introduces in the spectrum emitted by such black hole clusters, and to the current status of their viability as models for AGN and QSOs in light of dynamical studies by Quinlan and Shapiro (1987, 1989).

Complex photonic lattices embedded with tailored intrinsic defects by a dynamically reconfigurable single step interferometric approach

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

Xavier, Jolly, E-mail: jolly.xavierp@physics.iitd.ac.in; Joseph, Joby, E-mail: joby@physics.iitd.ac.in

2014-02-24

We report sculptured diverse photonic lattices simultaneously embedded with intrinsic defects of tunable type, number, shape as well as position by a single-step dynamically reconfigurable fabrication approach based on a programmable phase spatial light modulator-assisted interference lithography. The presented results on controlled formation of intrinsic defects in periodic as well as transversely quasicrystallographic lattices, irrespective and independent of their designed lattice geometry, portray the flexibility and versatility of the approach. The defect-formation in photonic lattices is also experimentally analyzed. Further, we also demonstrate the feasibility of fabrication of such defects-embedded photonic lattices in a photoresist, aiming concrete integrated photonic applications.

Inferring gene ontologies from pairwise similarity data

PubMed Central

Kramer, Michael; Dutkowski, Janusz; Yu, Michael; Bafna, Vineet; Ideker, Trey

2014-01-01

Motivation: While the manually curated Gene Ontology (GO) is widely used, inferring a GO directly from -omics data is a compelling new problem. Recognizing that ontologies are a directed acyclic graph (DAG) of terms and hierarchical relations, algorithms are needed that: analyze a full matrix of gene–gene pairwise similarities from -omics data;infer true hierarchical structure in these data rather than enforcing hierarchy as a computational artifact; andrespect biological pleiotropy, by which a term in the hierarchy can relate to multiple higher level terms. Methods addressing these requirements are just beginning to emerge—none has been evaluated for GO inference. Methods: We consider two algorithms [Clique Extracted Ontology (CliXO), LocalFitness] that uniquely satisfy these requirements, compared with methods including standard clustering. CliXO is a new approach that finds maximal cliques in a network induced by progressive thresholding of a similarity matrix. We evaluate each method’s ability to reconstruct the GO biological process ontology from a similarity matrix based on (a) semantic similarities for GO itself or (b) three -omics datasets for yeast. Results: For task (a) using semantic similarity, CliXO accurately reconstructs GO (>99% precision, recall) and outperforms other approaches (<20% precision, <20% recall). For task (b) using -omics data, CliXO outperforms other methods using two -omics datasets and achieves ∼30% precision and recall using YeastNet v3, similar to an earlier approach (Network Extracted Ontology) and better than LocalFitness or standard clustering (20–25% precision, recall). Conclusion: This study provides algorithmic foundation for building gene ontologies by capturing hierarchical and pleiotropic structure embedded in biomolecular data. Contact: tideker@ucsd.edu PMID:24932003

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations.

PubMed

Fabelo, Himar; Ortega, Samuel; Ravi, Daniele; Kiran, B Ravi; Sosa, Coralia; Bulters, Diederik; Callicó, Gustavo M; Bulstrode, Harry; Szolna, Adam; Piñeiro, Juan F; Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O'Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising, obtaining an accurate delineation of the tumor area.

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations

PubMed Central

Kabwama, Silvester; Madroñal, Daniel; Lazcano, Raquel; J-O’Shanahan, Aruma; Bisshopp, Sara; Hernández, María; Báez, Abelardo; Yang, Guang-Zhong; Stanciulescu, Bogdan; Salvador, Rubén; Juárez, Eduardo; Sarmiento, Roberto

2018-01-01

Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal brain by these tumors makes their accurate identification by the naked eye difficult. Since surgery is the common treatment for brain cancer, an accurate radical resection of the tumor leads to improved survival rates for patients. However, the identification of the tumor boundaries during surgery is challenging. Hyperspectral imaging is a non-contact, non-ionizing and non-invasive technique suitable for medical diagnosis. This study presents the development of a novel classification method taking into account the spatial and spectral characteristics of the hyperspectral images to help neurosurgeons to accurately determine the tumor boundaries in surgical-time during the resection, avoiding excessive excision of normal tissue or unintentionally leaving residual tumor. The algorithm proposed in this study to approach an efficient solution consists of a hybrid framework that combines both supervised and unsupervised machine learning methods. Firstly, a supervised pixel-wise classification using a Support Vector Machine classifier is performed. The generated classification map is spatially homogenized using a one-band representation of the HS cube, employing the Fixed Reference t-Stochastic Neighbors Embedding dimensional reduction algorithm, and performing a K-Nearest Neighbors filtering. The information generated by the supervised stage is combined with a segmentation map obtained via unsupervised clustering employing a Hierarchical K-Means algorithm. The fusion is performed using a majority voting approach that associates each cluster with a certain class. To evaluate the proposed approach, five hyperspectral images of surface of the brain affected by glioblastoma tumor in vivo from five different patients have been used. The final classification maps obtained have been analyzed and validated by specialists. These preliminary results are promising, obtaining an accurate delineation of the tumor area. PMID:29554126

Ground state structure of random magnets

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

Bastea, S.; Duxbury, P.M.

1998-10-01

Using exact optimization methods, we find all of the ground states of ({plus_minus}h) random-field Ising magnets (RFIM) and of dilute antiferromagnets in a field (DAFF). The degenerate ground states are usually composed of isolated clusters (two-level systems) embedded in a frozen background. We calculate the paramagnetic response (sublattice response) and the ground state entropy for the RFIM (DAFF) due to these clusters. In both two and three dimensions there is a broad regime in which these quantities are strictly positive, even at irrational values of h/J (J is the exchange constant). {copyright} {ital 1998} {ital The American Physical Society}

Brief Report: Clustered Forward Chaining with Embedded Mastery Probes to Teach Recipe Following.

PubMed

Chazin, Kate T; Bartelmay, Danielle N; Lambert, Joseph M; Houchins-Juárez, Nealetta J

2017-04-01

This study evaluated the effectiveness of a clustered forward chaining (CFC) procedure to teach a 23-year-old male with autism to follow written recipes. CFC incorporates elements of forward chaining (FC) and total task chaining (TTC) by teaching a small number of steps (i.e., units) using TTC, introducing new units sequentially (akin to FC), and prompting through untrained steps. Results indicated that CFC was effective for teaching the participant to follow written recipes. Results maintained with therapist support for 3-5 weeks for all recipes, and maintained when therapist support was removed.

Further Structural Intelligence for Sensors Cluster Technology in Manufacturing

PubMed Central

Mekid, Samir

2006-01-01

With the ever increasing complex sensing and actuating tasks in manufacturing plants, intelligent sensors cluster in hybrid networks becomes a rapidly expanding area. They play a dominant role in many fields from macro and micro scale. Global object control and the ability to self organize into fault-tolerant and scalable systems are expected for high level applications. In this paper, new structural concepts of intelligent sensors and networks with new intelligent agents are presented. Embedding new functionalities to dynamically manage cooperative agents for autonomous machines are interesting key enabling technologies most required in manufacturing for zero defects production.

Dust and gas environment of the young embedded cluster IRAS 18511+0146

NASA Astrophysics Data System (ADS)

Vig, S.; Testi, L.; Walmsley, C. M.; Cesaroni, R.; Molinari, S.

2017-03-01

Context. Since massive and intermediate mass stars form in clusters, a comparative investigation of the environments of the young embedded cluster members can reveal significant information about the conditions under which stars form and evolve. Aims: IRAS 18511+0146 is a young embedded (proto)cluster located at 3.5 kpc surrounding what appears to be an intermediate mass protostar. Here, we investigate the nature of cluster members (two of which are believed to be the most massive and luminous) using imaging and spectroscopy in the near and mid-infrared. In particular, we examine the three brightest mid-infrared objects, two of which are believed to be the most massive ones driving the luminosity of this region. Methods: Near-infrared spectroscopy of nine objects (bright in K-bands) towards IRAS 18511+0146 has been carried out. Several cluster members have also been investigated in the mid-infrared using spectroscopic and imaging with VISIR on the VLT. Far-infrared images from the Herschel Hi-GAL survey have been used to construct the column density and temperature maps of the region. Results: The brightest point-like object associated with IRAS 18511+0146 is referred to as S7 in the present work (designated UGPS J185337.88+015030.5 in the UKIRT Galactic Plane survey). S7 is likely the most luminous object in the cluster as it is bright at all wavelengths ranging from the near-infrared to millimetre. Seven of the nine objects show rising spectral energy distributions in the near-infrared, with four objects showing Br-γ emission. Three members: S7, S10 (also UGPS J185338.37+015015.3) and S11 (also UGPS J185338.72+015013.5) are bright in mid-infrared with diffuse emission being detected in the vicinity of S11 in PAH bands. Silicate absorption is detected towards these three objects, with an absorption maximum between 9.6 and 9.7 μm, large optical depths (1.8-3.2), and profile widths of 1.6-2.1μm. The silicate profiles of S7 and S10 are similar, in contrast to S11 (which has the largest width and optical depth). The cold dust emission peaks at S7, with temperature at 26 K and column density N(H2) 7 × 1022 cm-2. The bolometric luminosity of IRAS 18511 region is L 1.8 × 104L⊙. S7 is the main contributor to the bolometric luminosity, with L (S7) ≳104L⊙. Conclusions: S7 is a high-mass protostellar object with ionised stellar winds, evident from the correlation between radio and bolometric luminosity, as well as the asymmetric Br-γ profile. The differences in silicate profiles of S7 and S11 could be due to different radiation environments as we believe the former to be more massive and in an earlier phase than the latter.

Embedding Enterprise in Science and Engineering Departments

ERIC Educational Resources Information Center

Handscombe, Robert D.; Rodriguez-Falcon, Elena; Patterson, Eann A.

2008-01-01

Purpose: This paper aims to focus on the attempts to implement the challenges of teaching enterprise to science and engineering students by the embedding approach chosen by the White Rose Centre for Enterprise (WRCE), one of the centres formed under the Science Engineering Challenge in the UK. Design/methodology/approach: WRCE's objective was to…

Moving from Introverted to Extraverted Embedded Librarian Services: An Example of a Proactive Model

ERIC Educational Resources Information Center

Knight, Valerie R.; Loftis, Charissa

2012-01-01

Librarians at Wayne State College have developed an extraverted online embedded librarian model whereby librarians proactively push out content to students at time-appropriate moments. This article outlines why extraverted approaches are more effective than introverted approaches. It also details how to develop an extraverted program. First,…

SLLE for predicting membrane protein types.

PubMed

Wang, Meng; Yang, Jie; Xu, Zhi-Jie; Chou, Kuo-Chen

2005-01-07

Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.

Energy and charge transfer in ionized argon coated water clusters.

PubMed

Kočišek, J; Lengyel, J; Fárník, M; Slavíček, P

2013-12-07

We investigate the electron ionization of clusters generated in mixed Ar-water expansions. The electron energy dependent ion yields reveal the neutral cluster composition and structure: water clusters fully covered with the Ar solvation shell are formed under certain expansion conditions. The argon atoms shield the embedded (H2O)n clusters resulting in the ionization threshold above ≈15 eV for all fragments. The argon atoms also mediate more complex reactions in the clusters: e.g., the charge transfer between Ar(+) and water occurs above the threshold; at higher electron energies above ~28 eV, an excitonic transfer process between Ar(+)* and water opens leading to new products Ar(n)H(+) and (H2O)(n)H(+). On the other hand, the excitonic transfer from the neutral Ar* state at lower energies is not observed although this resonant process was demonstrated previously in a photoionization experiment. Doubly charged fragments (H2O)(n)H2(2+) and (H2O)(n)(2+) ions are observed and Intermolecular Coulomb decay (ICD) processes are invoked to explain their thresholds. The Coulomb explosion of the doubly charged cluster formed within the ICD process is prevented by the stabilization effect of the argon solvent.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

PubMed

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data

PubMed Central

Fernandez, Nicolas F.; Gundersen, Gregory W.; Rahman, Adeeb; Grimes, Mark L.; Rikova, Klarisa; Hornbeck, Peter; Ma’ayan, Avi

2017-01-01

Most tools developed to visualize hierarchically clustered heatmaps generate static images. Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations. Clustergrammer can be used to generate shareable interactive visualizations by uploading a data table to a web-site, or by embedding Clustergrammer in Jupyter Notebooks. The Clustergrammer core libraries can also be used as a toolkit by developers to generate visualizations within their own applications. Clustergrammer is demonstrated using gene expression data from the cancer cell line encyclopedia (CCLE), original post-translational modification data collected from lung cancer cells lines by a mass spectrometry approach, and original cytometry by time of flight (CyTOF) single-cell proteomics data from blood. Clustergrammer enables producing interactive web based visualizations for the analysis of diverse biological data. PMID:28994825

Extending Quantum Chemistry of Bound States to Electronic Resonances

NASA Astrophysics Data System (ADS)

Jagau, Thomas-C.; Bravaya, Ksenia B.; Krylov, Anna I.

2017-05-01

Electronic resonances are metastable states with finite lifetime embedded in the ionization or detachment continuum. They are ubiquitous in chemistry, physics, and biology. Resonances play a central role in processes as diverse as DNA radiolysis, plasmonic catalysis, and attosecond spectroscopy. This review describes novel equation-of-motion coupled-cluster (EOM-CC) methods designed to treat resonances and bound states on an equal footing. Built on complex-variable techniques such as complex scaling and complex absorbing potentials that allow resonances to be associated with a single eigenstate of the molecular Hamiltonian rather than several continuum eigenstates, these methods extend electronic-structure tools developed for bound states to electronic resonances. Selected examples emphasize the formal advantages as well as the numerical accuracy of EOM-CC in the treatment of electronic resonances. Connections to experimental observables such as spectra and cross sections, as well as practical aspects of implementing complex-valued approaches, are also discussed.

Inhomogeneity compensation for MR brain image segmentation using a multi-stage FCM-based approach.

PubMed

Szilágyi, László; Szilágyi, Sándor M; Dávid, László; Benyó, Zoltán

2008-01-01

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a multiple stage fuzzy c-means (FCM) based algorithm for the estimation and compensation of the slowly varying additive or multiplicative noise, supported by a pre-filtering technique for Gaussian and impulse noise elimination. The slowly varying behavior of the bias or gain field is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show, that the proposed method provides accurate segmentation. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Communication: Density functional theory embedding with the orthogonality constrained basis set expansion procedure

NASA Astrophysics Data System (ADS)

Culpitt, Tanner; Brorsen, Kurt R.; Hammes-Schiffer, Sharon

2017-06-01

Density functional theory (DFT) embedding approaches have generated considerable interest in the field of computational chemistry because they enable calculations on larger systems by treating subsystems at different levels of theory. To circumvent the calculation of the non-additive kinetic potential, various projector methods have been developed to ensure the orthogonality of molecular orbitals between subsystems. Herein the orthogonality constrained basis set expansion (OCBSE) procedure is implemented to enforce this subsystem orbital orthogonality without requiring a level shifting parameter. This scheme is a simple alternative to existing parameter-free projector-based schemes, such as the Huzinaga equation. The main advantage of the OCBSE procedure is that excellent convergence behavior is attained for DFT-in-DFT embedding without freezing any of the subsystem densities. For the three chemical systems studied, the level of accuracy is comparable to or higher than that obtained with the Huzinaga scheme with frozen subsystem densities. Allowing both the high-level and low-level DFT densities to respond to each other during DFT-in-DFT embedding calculations provides more flexibility and renders this approach more generally applicable to chemical systems. It could also be useful for future extensions to embedding approaches combining wavefunction theories and DFT.

Practical Pedagogy for Embedding ESD in Science, Technology, Engineering and Mathematics Curricula

ERIC Educational Resources Information Center

Hopkinson, Peter; James, Peter

2010-01-01

Purpose--The purpose of this paper is to review and highlight some recent examples of embedding education for sustainable development (ESD), within science and related curricula in ways that are meaningful and relevant to staff and students and reflect on different embedding strategies and discourses. Design/methodology/approach--A review of…

Critical Friendship and Critical Orphanship: Embedded Research of an English Local Authority Initiative

ERIC Educational Resources Information Center

Duggan, James R.

2014-01-01

The article engages with the opportunities and constraints raised by embedded research during times of rapid and extensive organisational change. Embedded research is an increasingly common approach for funding PhD studentships. The rapid and extensive reforms of the English public sector pose significant and underexplored challenges for embedded…

Optical absorption spectra and g factor of MgO: Mn2+explored by ab initio and semi empirical methods

NASA Astrophysics Data System (ADS)

Andreici Eftimie, E.-L.; Avram, C. N.; Brik, M. G.; Avram, N. M.

2018-02-01

In this paper we present a methodology for calculations of the optical absorption spectra, ligand field parameters and g factor for the Mn2+ (3d5) ions doped in MgO host crystal. The proposed technique combines two methods: the ab initio multireference (MR) and the semi empirical ligand field (LF) in the framework of the exchange charge model (ECM) respectively. Both methods of calculations are applied to the [MnO6]10-cluster embedded in an extended point charge field of host matrix ligands based on Gellé-Lepetit procedure. The first step of such investigations was the full optimization of the cubic structure of perfect MgO crystal, followed by the structural optimization of the doped of MgO:Mn2+ system, using periodic density functional theory (DFT). The ab initio MR wave functions approaches, such as complete active space self-consistent field (CASSCF), N-electron valence second order perturbation theory (NEVPT2) and spectroscopy oriented configuration interaction (SORCI), are used for the calculations. The scalar relativistic effects have also been taken into account through the second order Douglas-Kroll-Hess (DKH2) procedure. Ab initio ligand field theory (AILFT) allows to extract all LF parameters and spin-orbit coupling constant from such calculations. In addition, the ECM of ligand field theory (LFT) has been used for modelling theoptical absorption spectra. The perturbation theory (PT) was employed for the g factor calculation in the semi empirical LFT. The results of each of the aforementioned types of calculations are discussed and the comparisons between the results obtained and the experimental results show a reasonable agreement, which justifies this new methodology based on the simultaneous use of both methods. This study establishes fundamental principles for the further modelling of larger embedded cluster models of doped metal oxides.

Molecular dynamics study of the melting of a supported 887-atom Pd decahedron.

PubMed

Schebarchov, D; Hendy, S C; Polak, W

2009-04-08

We employ classical molecular dynamics simulations to investigate the melting behaviour of a decahedral Pd(887) cluster on a single layer of graphite (graphene). The interaction between Pd atoms is modelled with an embedded-atom potential, while the adhesion of Pd atoms to the substrate is approximated with a Lennard-Jones potential. We find that the decahedral structure persists at temperatures close to the melting point, but that just below the melting transition, the cluster accommodates to the substrate by means of complete melting and then recrystallization into an fcc structure. These structural changes are in qualitative agreement with recently proposed models, and they verify the existence of an energy barrier preventing softly deposited clusters from 'wetting' the substrate at temperatures below the melting point.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method.

PubMed

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-11-27

A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method

PubMed Central

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-01-01

Background A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Results Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Conclusion Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries. PMID:18047705

Endohedral gallide cluster superconductors and superconductivity in ReGa5

PubMed Central

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F.; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-01-01

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures. PMID:26644566

Performance analysis of clustering techniques over microarray data: A case study

NASA Astrophysics Data System (ADS)

Dash, Rasmita; Misra, Bijan Bihari

2018-03-01

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

Metallic-nanoparticles-enhanced fluorescence from individual micron-sized aerosol particles on-the-fly.

PubMed

Sivaprakasam, Vasanthi; Hart, Matthew B; Jain, Vaibhav; Eversole, Jay D

2014-08-11

Fluorescence spectra from individual aerosol particles that were either coated or embedded with metallic nanoparticles (MNPs) was acquired on-the-fly using 266 nm and 355 nm excitation. Using aqueous suspensions of MNPs with either polystyrene latex (PSL) spheres or dissolved proteins (tryptophan or ovalbumin), we generated PSL spheres coated with MNPs, or protein clusters embedded with MNPs as aerosols. Both enhanced and quenched fluorescence intensities were observed as a function of MNP concentration. Optimizing MNP material, size and spacing should yield enhanced sensitivity for specific aerosol materials that could be exploited to improve detection limits of single-particle, on-the-fly fluorescence or Raman based spectroscopic sensors.

Embedding EfS in Teacher Education through a Multi-Level Systems Approach: Lessons from Queensland

ERIC Educational Resources Information Center

Evans, Neus; Ferreira, Jo-Anne; Davis, Julie; Stevenson, Robert B.

2016-01-01

This article reports on the fourth stage of an evolving study to develop a systems model for embedding education for sustainability (EfS) into preservice teacher education. The fourth stage trialled the extension of the model to a comprehensive state-wide systems approach involving representatives from all eight Queensland teacher education…

Monitoring and Fostering Learning through Games and Embedded Assessments. Research Report. ETS RR-08-69

ERIC Educational Resources Information Center

Shute, Valerie J.; Ventura, Matthew; Bauer, Malcolm; Zapata-Rivera, Diego

2008-01-01

To reveal what is being learned during the gaming experience, this report proposes an approach for embedding assessments in immersive games, drawing on recent advances in assessment design. Key to this approach are formative assessment to guide instructional experiences and evidence-centered design to systematically analyze the assessment argument…

Globular cluster formation with multiple stellar populations from hierarchical star cluster complexes

NASA Astrophysics Data System (ADS)

Bekki, Kenji

2017-05-01

Most old globular clusters (GCs) in the Galaxy are observed to have internal chemical abundance spreads in light elements. We discuss a new GC formation scenario based on hierarchical star formation within fractal molecular clouds. In the new scenario, a cluster of bound and unbound star clusters ('star cluster complex', SCC) that have a power-law cluster mass function with a slope (β) of 2 is first formed from a massive gas clump developed in a dwarf galaxy. Such cluster complexes and β = 2 are observed and expected from hierarchical star formation. The most massive star cluster ('main cluster'), which is the progenitor of a GC, can accrete gas ejected from asymptotic giant branch (AGB) stars initially in the cluster and other low-mass clusters before the clusters are tidally stripped or destroyed to become field stars in the dwarf. The SCC is initially embedded in a giant gas hole created by numerous supernovae of the SCC so that cold gas outside the hole can be accreted on to the main cluster later. New stars formed from the accreted gas have chemical abundances that are different from those of the original SCC. Using hydrodynamical simulations of GC formation based on this scenario, we show that the main cluster with the initial mass as large as [2-5] × 105 M⊙ can accrete more than 105 M⊙ gas from AGB stars of the SCC. We suggest that merging of hierarchical SSCs can play key roles in stellar halo formation around GCs and self-enrichment processes in the early phase of GC formation.

Ionized Gas Motions and the Structure of Feedback near a Forming Globular Cluster in NGC 5253

NASA Astrophysics Data System (ADS)

Cohen, Daniel P.; Turner, Jean L.; Consiglio, S. Michelle; Martin, Emily C.; Beck, Sara C.

2018-06-01

We observed Brackett α 4.05 μm emission toward the supernebula in NGC 5253 with NIRSPEC on Keck II in adaptive optics mode, NIRSPAO, to probe feedback from its exciting embedded super star cluster (SSC). NIRSPEC's Slit-viewing Camera was simultaneously used to image the K-band continuum at ∼0.″1 resolution. We register the IR continuum with HST imaging, and find that the visible clusters are offset from the K-band peak, which coincides with the Brα peak of the supernebula and its associated molecular cloud. The spectra of the supernebula exhibit Brα emission with a strong, narrow core. The linewidths are 65–76 km s‑1, FWHM, comparable to those around individual ultra-compact H II regions within our Galaxy. A weak, broad (FWHM ≃ 150–175 km s‑1) component is detected on the base of the line, which could trace a population of sources with high-velocity winds. The core velocity of Brα emission shifts by +13 km s‑1 from NE to SW across the supernebula, possibly indicating a bipolar outflow from an embedded object or a link to a foreground redshifted gas filament. The results can be explained if the supernebula comprises thousands of ionized wind regions around individual massive stars, stalled in their expansion due to critical radiative cooling and unable to merge to drive a coherent cluster wind. Based on the absence of an outflow with large mass loss, we conclude that feedback is currently ineffective at dispersing gas, and the SSC retains enriched material out of which it may continue to form stars.

H{sub 2} MOLECULAR CLUSTERS WITH EMBEDDED MOLECULES AND ATOMS AS THE SOURCE OF THE DIFFUSE INTERSTELLAR BANDS

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

Bernstein, L. S.; Clark, F. O.; Lynch, D. K., E-mail: larry@spectral.com, E-mail: dave@thulescientific.com

2013-05-01

We suggest that the diffuse interstellar bands (DIBs) arise from absorption lines of electronic transitions in molecular clusters primarily composed of a single molecule, atom, or ion ({sup s}eed{sup )}, embedded in a single-layer shell of H{sub 2} molecules. Less abundant variants of the cluster, including two seed molecules and/or a two-layer shell of H{sub 2} molecules, may also occur. The lines are broadened, blended, and wavelength-shifted by interactions between the seed and surrounding H{sub 2} shell. We refer to these clusters as contaminated H{sub 2} clusters (CHCs). We show that CHC spectroscopy matches the diversity of observed DIB spectralmore » profiles and provides good fits to several DIB profiles based on a rotational temperature of 10 K. CHCs arise from {approx}centimeter-sized, dirty H{sub 2} ice balls, called contaminated H{sub 2} ice macro-particles (CHIMPs), formed in cold, dense, giant molecular clouds (GMCs), and later released into the interstellar medium (ISM) upon GMC disruption. Attractive interactions, arising from Van der Waals and ion-induced dipole potentials, between the seeds and H{sub 2} molecules enable CHIMPs to attain centimeter-sized dimensions. When an ultraviolet (UV) photon is absorbed in the outer layer of a CHIMP, it heats the icy matrix and expels CHCs into the ISM. While CHCs are quickly destroyed by absorbing UV photons, they are replenished by the slowly eroding CHIMPs. Since CHCs require UV photons for their release, they are most abundant at, but not limited to, the edges of UV-opaque molecular clouds, consistent with the observed, preferred location of DIBs. An inherent property of CHCs, which can be characterized as nanometer size, spinning, dipolar dust grains, is that they emit in the radio-frequency region. We also show that the CHCs offer a natural explanation for the anomalous microwave emission feature in the {approx}10-100 GHz spectral region.« less

Formation of Very Young Massive Clusters and Implications for Globular Clusters

NASA Astrophysics Data System (ADS)

Banerjee, Sambaran; Kroupa, Pavel

How Very Young Massive star Clusters (VYMCs; also known as "starburst" clusters), which typically are of ≳ 104 M ⊙ and are a few Myr old, form out of Giant Molecular Clouds is still largely an open question. Increasingly detailed observations of young star clusters and star-forming molecular clouds and computational studies provide clues about their formation scenarios and the underlying physical processes involved. This chapter is focused on reviewing the decade-long studies that attempt to computationally reproduce the well-observed nearby VYMCs, such as the Orion Nebula Cluster, R136 and NGC 3603 young cluster, thereby shedding light on birth conditions of massive star clusters, in general. On this regard, focus is given on direct N-body modelling of real-sized massive star clusters, with a monolithic structure and undergoing residual gas expulsion, which have consistently reproduced the observed characteristics of several VYMCs and also of young star clusters, in general. The connection of these relatively simplified model calculations with the structural richness of dense molecular clouds and the complexity of hydrodynamic calculations of star cluster formation is presented in detail. Furthermore, the connections of such VYMCs with globular clusters, which are nearly as old as our Universe, is discussed. The chapter is concluded by addressing long-term deeply gas-embedded (at least apparently) and substructured systems like W3 Main. While most of the results are quoted from existing and up-to-date literature, in an integrated fashion, several new insights and discussions are provided.

Probing Globular Cluster Formation in Low Metallicity Dwarf Galaxies

NASA Astrophysics Data System (ADS)

Johnson, Kelsey E.; Hunt, Leslie K.; Reines, Amy E.

2008-12-01

The ubiquitous presence of globular clusters around massive galaxies today suggests that these extreme star clusters must have been formed prolifically in the earlier universe in low-metallicity galaxies. Numerous adolescent and massive star clusters are already known to be present in a variety of galaxies in the local universe; however most of these systems have metallicities of 12 + log(O/H) > 8, and are thus not representative of the galaxies in which today's ancient globular clusters were formed. In order to better understand the formation and evolution of these massive clusters in environments with few heavy elements, we have targeted several low-metallicity dwarf galaxies with radio observations, searching for newly-formed massive star clusters still embedded in their birth material. The galaxies in this initial study are HS 0822+3542, UGC 4483, Pox 186, and SBS 0335-052, all of which have metallicities of 12 + log(O/H) < 7.75. While no thermal radio sources, indicative of natal massive star clusters, are found in three of the four galaxies, SBS 0335-052 hosts two such objects, which are incredibly luminous. The radio spectral energy distributions of these intense star-forming regions in SBS 0335-052 suggest the presence of ~12,000 equivalent O-type stars, and the implied star formation rate is nearing the maximum starburst intensity limit.

The mass function and dynamical mass of young star clusters: why their initial crossing-time matters crucially

NASA Astrophysics Data System (ADS)

Parmentier, Geneviève; Baumgardt, Holger

2012-12-01

We highlight the impact of cluster-mass-dependent evolutionary rates upon the evolution of the cluster mass function during violent relaxation, that is, while clusters dynamically respond to the expulsion of their residual star-forming gas. Mass-dependent evolutionary rates arise when the mean volume density of cluster-forming regions is mass-dependent. In that case, even if the initial conditions are such that the cluster mass function at the end of violent relaxation has the same shape as the embedded-cluster mass function (i.e. infant weight-loss is mass-independent), the shape of the cluster mass function does change transiently during violent relaxation. In contrast, for cluster-forming regions of constant mean volume density, the cluster mass function shape is preserved all through violent relaxation since all clusters then evolve at the same mass-independent rate. On the scale of individual clusters, we model the evolution of the ratio of the dynamical mass to luminous mass of a cluster after gas expulsion. Specifically, we map the radial dependence of the time-scale for a star cluster to return to equilibrium. We stress that fields of view a few pc in size only, typical of compact clusters with rapid evolutionary rates, are likely to reveal cluster regions which have returned to equilibrium even if the cluster experienced a major gas expulsion episode a few Myr earlier. We provide models with the aperture and time expressed in units of the initial half-mass radius and initial crossing-time, respectively, so that our results can be applied to clusters with initial densities, sizes, and apertures different from ours.

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

PubMed

Arpino, Bruno; Cannas, Massimo

2016-05-30

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

Design and fabrication of memory devices based on nanoscale polyoxometalate clusters

NASA Astrophysics Data System (ADS)

Busche, Christoph; Vilà-Nadal, Laia; Yan, Jun; Miras, Haralampos N.; Long, De-Liang; Georgiev, Vihar P.; Asenov, Asen; Pedersen, Rasmus H.; Gadegaard, Nikolaj; Mirza, Muhammad M.; Paul, Douglas J.; Poblet, Josep M.; Cronin, Leroy

2014-11-01

Flash memory devices--that is, non-volatile computer storage media that can be electrically erased and reprogrammed--are vital for portable electronics, but the scaling down of metal-oxide-semiconductor (MOS) flash memory to sizes of below ten nanometres per data cell presents challenges. Molecules have been proposed to replace MOS flash memory, but they suffer from low electrical conductivity, high resistance, low device yield, and finite thermal stability, limiting their integration into current MOS technologies. Although great advances have been made in the pursuit of molecule-based flash memory, there are a number of significant barriers to the realization of devices using conventional MOS technologies. Here we show that core-shell polyoxometalate (POM) molecules can act as candidate storage nodes for MOS flash memory. Realistic, industry-standard device simulations validate our approach at the nanometre scale, where the device performance is determined mainly by the number of molecules in the storage media and not by their position. To exploit the nature of the core-shell POM clusters, we show, at both the molecular and device level, that embedding [(Se(IV)O3)2]4- as an oxidizable dopant in the cluster core allows the oxidation of the molecule to a [Se(V)2O6]2- moiety containing a {Se(V)-Se(V)} bond (where curly brackets indicate a moiety, not a molecule) and reveals a new 5+ oxidation state for selenium. This new oxidation state can be observed at the device level, resulting in a new type of memory, which we call `write-once-erase'. Taken together, these results show that POMs have the potential to be used as a realistic nanoscale flash memory. Also, the configuration of the doped POM core may lead to new types of electrical behaviour. This work suggests a route to the practical integration of configurable molecules in MOS technologies as the lithographic scales approach the molecular limit.

A Spectroscopic Study of Young Stellar Objects in the Serpens Cloud Core and NGC 1333

NASA Astrophysics Data System (ADS)

Winston, E.; Megeath, S. T.; Wolk, S. J.; Hernandez, J.; Gutermuth, R.; Muzerolle, J.; Hora, J. L.; Covey, K.; Allen, L. E.; Spitzbart, B.; Peterson, D.; Myers, P.; Fazio, G. G.

2009-06-01

We present spectral observations of 130 young stellar objects (YSOs) in the Serpens Cloud Core and NGC 1333 embedded clusters. The observations consist of near-IR spectra in the H and K bands from SpeX on the IRTF and far-red spectra (6000-9000 Å) from Hectospec on the Multi-Mirror Telescope. These YSOs were identified in previous Spitzer and Chandra observations, and the evolutionary classes of the YSOs were determined from the Spitzer mid-IR photometry. With these spectra we search for corroborating evidence for the pre-main-sequence nature of the objects, study the properties of the detected emission lines as a function of evolutionary class, and obtain spectral types for the observed YSOs. The temperatures implied by the spectral types are combined with luminosities determined from the near-IR photometry to construct Hertzsprung-Russell (H-R) diagrams for the clusters. By comparing the positions of the YSOs in the H-R diagrams with the pre-main-sequence tracks of Baraffe (1998), we determine the ages of the embedded sources and study the relative ages of the YSOs with and without optically thick circumstellar disks. The apparent isochronal ages of the YSOs in both clusters range from less than 1 Myr to 10 Myr, with most objects below 3 Myr. The observed distributions of ages for the Class II and Class III objects are statistically indistinguishable. We examine the spatial distribution and extinction of the YSOs as a function of their isochronal ages. We find the sources <3 Myr to be concentrated in the molecular cloud gas, while the older sources are spatially dispersed and are not deeply embedded. Nonetheless, the sources with isochronal ages >3 Myr show all the characteristics of YSOs in their spectra, their IR spectral energy distributions, and their X-ray emission; we find no evidence that they are contaminating background giants or foreground dwarfs. However, we find no corresponding decrease in the fraction of sources with infrared excess with isochronal age; this suggests that the older isochronal ages may not measure the true age of the >3 Myr YSOs. Thus, the nature of the apparently older sources and their implications for cluster formation remain unresolved.

The Effect of an Embedded Pedagogical Agent on the Students' Science Achievement

ERIC Educational Resources Information Center

Kizilkaya, Gonca; Askar, Petek

2008-01-01

Purpose: The purpose of this paper is to investigate the effect of an embedded pedagogical agent into a tutorial on achievement. Design/methodology/approach: Research methodology is designed according to the post test control group model in which the experimental group (69 students) was exposed to a tutorial with an embedded pedagogical agent;…

Combining frozen-density embedding with the conductor-like screening model using Lagrangian techniques for response properties.

PubMed

Schieschke, Nils; Di Remigio, Roberto; Frediani, Luca; Heuser, Johannes; Höfener, Sebastian

2017-07-15

We present the explicit derivation of an approach to the multiscale description of molecules in complex environments that combines frozen-density embedding (FDE) with continuum solvation models, in particular the conductor-like screening model (COSMO). FDE provides an explicit atomistic description of molecule-environment interactions at reduced computational cost, while the outer continuum layer accounts for the effect of long-range isotropic electrostatic interactions. Our treatment is based on a variational Lagrangian framework, enabling rigorous derivations of ground- and excited-state response properties. As an example of the flexibility of the theoretical framework, we derive and discuss FDE + COSMO analytical molecular gradients for excited states within the Tamm-Dancoff approximation (TDA) and for ground states within second-order Møller-Plesset perturbation theory (MP2) and a second-order approximate coupled cluster with singles and doubles (CC2). It is shown how this method can be used to describe vertical electronic excitation (VEE) energies and Stokes shifts for uracil in water and carbostyril in dimethyl sulfoxide (DMSO), respectively. In addition, VEEs for some simplified protein models are computed, illustrating the performance of this method when applied to larger systems. The interaction terms between the FDE subsystem densities and the continuum can influence excitation energies up to 0.3 eV and, thus, cannot be neglected for general applications. We find that the net influence of the continuum in presence of the first FDE shell on the excitation energy amounts to about 0.05 eV for the cases investigated. The present work is an important step toward rigorously derived ab initio multilayer and multiscale modeling approaches. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Efficient clustering aggregation based on data fragments.

PubMed

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

2012-06-01

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

Array-based DNA-methylation profiling in sarcomas with small blue round cell histology provides valuable diagnostic information.

PubMed

Koelsche, Christian; Hartmann, Wolfgang; Schrimpf, Daniel; Stichel, Damian; Jabar, Susanne; Ranft, Andreas; Reuss, David E; Sahm, Felix; Jones, David T W; Bewerunge-Hudler, Melanie; Trautmann, Marcel; Klingebiel, Thomas; Vokuhl, Christian; Gessler, Manfred; Wardelmann, Eva; Petersen, Iver; Baumhoer, Daniel; Flucke, Uta; Antonescu, Cristina; Esteller, Manel; Fröhling, Stefan; Kool, Marcel; Pfister, Stefan M; Mechtersheimer, Gunhild; Dirksen, Uta; von Deimling, Andreas

2018-03-23

Undifferentiated solid tumors with small blue round cell histology and expression of CD99 mostly resemble Ewing sarcoma. However, they also may include other tumors such as mesenchymal chondrosarcoma, synovial sarcoma, or small cell osteosarcoma. Definitive classification usually requires detection of entity-specific mutations. While this approach identifies the majority of Ewing sarcomas, a subset of lesions remains unclassified and, therefore, has been termed "Ewing-like sarcomas" or small blue round cell tumors not otherwise specified. We developed an approach for further characterization of small blue round cell tumors not otherwise specified using an array-based DNA-methylation profiling approach. Data were analyzed by unsupervised clustering and t-distributed stochastic neighbor embedding analysis and compared with a reference methylation data set of 460 well-characterized prototypical sarcomas encompassing 18 subtypes. Verification was performed by additional FISH analyses, RNA sequencing from formalin-fixed paraffin-embedded material or immunohistochemical marker analyses. In a cohort of more than 1,000 tumors assumed to represent Ewing sarcomas, 30 failed to exhibit the typical EWS translocation. These tumors were subjected to methylation profiling and could be assigned to Ewing sarcoma in 14 (47%), to small blue round cell tumors with CIC alteration in 6 (20%), to small blue round cell tumors with BCOR alteration in 4 (13%), to synovial sarcoma and to malignant rhabdoid tumor in 2 cases each. One single case each was allotted to mesenchymal chondrosarcoma and adamantinoma. 12/14 tumors classified as Ewing sarcoma could be verified by demonstrating either a canonical EWS translocation evading initial testing, by identifying rare breakpoints or fusion partners. The methylation-based assignment of the remaining small blue round cell tumors not otherwise specified also could be verified by entity-specific molecular alterations in 13/16 cases. In conclusion, array-based DNA-methylation analysis of undifferentiated tumors with small blue round cell histology is a powerful tool for precisely classifying this diagnostically challenging tumor group.

Telling Stories, Landing Planes and Getting Them Moving--A Holistic Approach to Developing Students' Statistical Literacy

ERIC Educational Resources Information Center

Jones, Julie Scott; Goldring, John E.

2017-01-01

The issue of poor statistical literacy amongst undergraduates in the United Kingdom is well documented. At university level, where poor statistics skills impact particularly on social science programmes, embedding is often used as a remedy. However, embedding represents a surface approach to the problem. It ignores the barriers to learning that…

Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering.

PubMed

Wang, Yang; Wu, Lin

2018-07-01

Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optical properties of embedded metal nanoparticles at low temperatures

NASA Astrophysics Data System (ADS)

Heilmann, A.; Kreibig, U.

2000-06-01

Metal nanoparticles (gold, silver, copper) that are embedded in an insulating organic host material exhibit optical plasma resonance absorption in the visible and near-infrared region. The spectral position, the half width and the intensity of the plasma resonance absorption all depend on the particle size, the particle shape, and the optical behavior of the cluster and the host material. The optical extinction of various gold, silver or copper particle assemblies embedded in plasma polymer or gelatin was measured at 4.2 K and 1.2 K as well as at room temperature. The packing density of several samples was high enough to resolve a reversible increase of the plasma resonance absorption intensity towards lower temperatures. Additionally, at larger silver particles D_m > 50 nm a significant blue shift of the plasma resonance absorption was measured. Particle size and shape distribution were determined by transmission electron microscopy (TEM). For the first time, simultaneous measurements of the electrical and optical properties at one and the same particle assembly were performed at low temperatures. Contrary to the increasing optical extinction, the d.c. conductivity decreased to two orders of magnitude. At silver particles embedded in a plasma polymer made from thiophene a significant photocurrent was measured.

Electronic structure and orientation relationship of Li nanoclusters embedded in MgO studied by depth-selective positron annihilation two-dimensional angular correlation

NASA Astrophysics Data System (ADS)

Falub, C. V.; Mijnarends, P. E.; Eijt, S. W.; van Huis, M. A.; van Veen, A.; Schut, H.

2002-08-01

Quantum-confined positrons are sensitive probes for determining the electronic structure of nanoclusters embedded in materials. In this work, a depth-selective positron annihilation 2D-ACAR (two-dimensional angular correlation of annihilation radiation) method is used to determine the electronic structure of Li nanoclusters formed by implantation of 1016-cm-2 30-keV 6Li ions in MgO (100) and (110) crystals and by subsequent annealing at 950 K. Owing to the difference between the positron affinities of lithium and MgO, the Li nanoclusters act as quantum dots for positrons. 2D-ACAR distributions for different projections reveal a semicoherent fitting of the embedded metallic Li nanoclusters to the host MgO lattice. Ab initio Korringa-Kohn-Rostoker calculations of the momentum density show that the anisotropies of the experimental distributions are consistent with an fcc crystal structure of the Li nanoclusters. The observed reduction of the width of the experimental 2D-ACAR distribution is attributed to positron trapping in vacancies associated with Li clusters. This work proposes a method for studying the electronic structure of metallic quantum dots embedded in an insulating material.

Interlaced coarse-graining for the dynamical cluster approximation

NASA Astrophysics Data System (ADS)

Haehner, Urs; Staar, Peter; Jiang, Mi; Maier, Thomas; Schulthess, Thomas

The negative sign problem remains a challenging limiting factor in quantum Monte Carlo simulations of strongly correlated fermionic many-body systems. The dynamical cluster approximation (DCA) makes this problem less severe by coarse-graining the momentum space to map the bulk lattice to a cluster embedded in a dynamical mean-field host. Here, we introduce a new form of an interlaced coarse-graining and compare it with the traditional coarse-graining. We show that it leads to more controlled results with weaker cluster shape and smoother cluster size dependence, which with increasing cluster size converge to the results obtained using the standard coarse-graining. In addition, the new coarse-graining reduces the severity of the fermionic sign problem. Therefore, it enables calculations on much larger clusters and can allow the evaluation of the exact infinite cluster size result via finite size scaling. To demonstrate this, we study the hole-doped two-dimensional Hubbard model and show that the interlaced coarse-graining in combination with the DCA+ algorithm permits the determination of the superconducting Tc on cluster sizes, for which the results can be fitted with the Kosterlitz-Thouless scaling law. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program, and of the Swiss National Supercomputing Center. OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

Tensor Train Neighborhood Preserving Embedding

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

2018-05-01

In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.

Multiferroic and magnetoelectric nanocomposites for data processing

NASA Astrophysics Data System (ADS)

Kleemann, Wolfgang

2017-06-01

Recent progress in preparing and understanding composite magnetoelectrics is highlighted. Apart from optimized standard solutions novel methods of switching magnetism with electric fields and vice versa with focus on magnetoelectric (ME) data processing in multiferroic and magnetoelectric nanocomposites deserve particular interest. First, we report on the patented MERAM, which uses the electric field control of exchange bias in a layered composite via an epitaxial magnetoelectric Cr2O3 layer exchange coupled to a Pt/Co/Pt trilayer. It promises to crucially reduce Joule energy losses in RAM devices. Second, magnetic switching of the electric polarization by a transverse magnetic field in a composite of CoFe2O4 nanopillars embedded in a vertically poled BaTiO3 thick film produces a regular surface polarization pattern with rectangular local symmetry. Its possible use for data processing is discussed. Third, in the relaxor ferroelectric single-phase compound (BiFe0.9Co0.1O3)0.4-(Bi1/2K1/2TiO3)0.6 polar nanoregions emerging from ferrimagnetic Bi(Fe,Co)O3 regions embedded in a Bi1/2K1/2TiO3 relaxor component transform into ferroelectric clusters and simultaneously enable congruent magnetic clusters. The local polarization and magnetization couple with record-high direct and converse magnetoelectric coupling coefficients, α  ≈  1.0  ×  10-5 s m-1. These ‘multiferroic’ clusters are promising for applications in data storage or processing devices.

Letter to Russia

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

Tobin, J G

Below is the referee report. It is not as bad as it seems at first. The manuscript has not been rejected. Instead, the referee is 'not recommending publication.' On the APS website, the status is 'with authors,' instead of 'not under consideration.' Thus, this manuscript is still alive, but we will need to work on it. Please take a look at what the referee says below and let me know how you would respond. I will do the same. Hopefully, we will be able to respond well and find a way for this manuscript to get into PRB. According tomore » the introduction of their manuscript, the authors intend to study the electronic structure of clusters of Pu atoms and, among other things, to illustrate how the properties of the cluster's central region approach those of the bulk Pu metal as the cluster size increases. It is then somewhat surprising to find out that all the 'cluster' calculations discussed in the paper are in fact set up in such a way that they model the bulk properties - the clusters are embedded in a kind of mean field that is designed to approximate the rest of an infinite lattice (the authors call it the extended cluster scheme). Consequently, all the observed finite-size effects are essentially artificial since they represent the inaccuracies of the embedding procedure. The results for the finite clusters themselves do not carry a direct physical meaning (which contradicts authors statements from the introduction), only the extrapolation to the infinite cluster would, if done properly. The authors propose that the number of 5f electrons n{_}5f is a linear function of the cubic root of N, where N is the number of atoms in the cluster. This function fits the calculated data well (Fig. 8), but, as the authors indeed note, it cannot hold for very large N where n{_}5f must saturate at a finite value. The calculated data show no sign of such saturation (Fig. 8), which indicates that the considered clusters are too small to draw conclusions about the bulk properties. I find it puzzling that the authors nonetheless claim in their conclusions that 'An evaluation of state occupations supports the proposal that the occupation of the 5f levels in bulk Pu must be near 5'. Apart from the aforementioned conceptual inconsistencies, there are a number of more technical aspects that are not discussed in sufficient detail. Among these are: (1) The authors use LDA to approximate the electron correlations. A lively debate takes place in the literature whether this approximation can adequately describe the electronic structure of Pu metal or not, yet the authors do not discuss the choice of the approximation at all, which they should, in my opinion. They should also specify if their solutions are spin polarized or whether they use spin-restricted LDA. (2) The quality of the employed basis set is not clear. Are the results converged with respect to the basis size? What is the estimated magnitude of the residual errors? (3) There are statements in the manuscript indicating that the cluster calculations depend somehow on the calculations of the diatomic molecule. Namely: 'Underpinning these calculations, there is a geometry optimization of diatomic molecules...' and 'Underlying the Pu cluster simulations is the calculation of the electronic structure of a Pu2 dimer with the bond length 3.28 {angstrom} corresponding to the inter-atomic distances in delta-Pu.' What does this underpinning/underlying mean in more technical terms? What role does the geometry optimization play when the cluster calculations seem to be performed at a fixed geometry corresponding to the delta-Pu? Lastly, the manuscript contains a lot of material that was previously (and often multiple times) published elsewhere, including the Physical Review journals. For instance, the experimental part of Fig. 2 was shown already in Refs. 26, 27 and 28 in essentially the same graphical form; the top part of Fig. 9 appeared in Refs. 19, 4 and in PRL 90, 196404 (2003). I think that reprinting these results is not necessary and just referencing the earlier papers would be sufficient.« less

A Deep Near-Infrared Survey of the N 49 Region around the Soft Gamma-Ray Repeater 0526-66

NASA Technical Reports Server (NTRS)

Klose, S.; Henden, A. A.; Geppert, U.; Greiner, J.; Guetter, H. H.; Hartmann, D. H.; Kouveliotou, C.; Luginbuhl, C. B.; Stecklurn, B.; Vrba, F. J.

2004-01-01

We report the results of a deep near-infrared survey of the vicinity of supernova remnant N49 in the Large Magellanic Cloud (LMC), which contains the soft gamma-ray repeater (SGR) 0526-66. Two of the four confirmed SGRs are potentially associated with compact stellar clusters. We thus searched for a similar association of SGR0526-66, and find the unexplored young stellar cluster SL 463 at a projected distance of approx. 30 pc from the SGR. This constitutes the third cluster-SGR link, and lends support to scenarios in which SGR progenitors originate in young, embedded clusters. If real, the cluster-SGR association constrains the age and thus the initial mass of these stars. In addition, our high-resolution images of the super- nova remnant N49 reveal an area of excess K-band flux in the southeastern part of the SNR. This feature coincides with the maximum flux area at 8.28 microns as detected by the Midcourse Space Experiment (MSX satellite), which we identify with IRAS 052594607.

Regulation of star formation in giant galaxies by precipitation, feedback and conduction.

PubMed

Voit, G M; Donahue, M; Bryan, G L; McDonald, M

2015-03-12

The Universe's largest galaxies reside at the centres of galaxy clusters and are embedded in hot gas that, if left undisturbed, would cool quickly and create many more new stars than are actually observed. Cooling can be regulated by feedback from accretion of cooling gas onto the central black hole, but requires an accretion rate finely tuned to the thermodynamic state of the hot gas. Theoretical models in which cold clouds precipitate out of the hot gas via thermal instability and accrete onto the black hole exhibit the necessary tuning. Recent observational evidence shows that the abundance of cold gas in the centres of clusters increases rapidly near the predicted threshold for instability. Here we report observations showing that this precipitation threshold extends over a large range in cluster radius, cluster mass and cosmic time. We incorporate the precipitation threshold into a framework of theoretical models for the thermodynamic state of hot gas in galaxy clusters. According to that framework, precipitation regulates star formation in some giant galaxies, while thermal conduction prevents star formation in others if it can compensate for radiative cooling and shut off precipitation.

Nuclear Rings in the IR: Hidden Super Star Clusters

NASA Astrophysics Data System (ADS)

Maoz, Dan

1997-07-01

We propose NICMOS broad-band {F160W, F187W} and Paschen Alpha {F187N} imaging of nuclear starburst rings in two nearby galaxies. We already have UV {F220W} FOC data, and are scheduled to obtain WFPC2 images in U, V, I, and Halpha+[NII] of these rings. The rings contain large populations of super star clusters similar to those recently discovered in other types of starburst systems. Nuclear rings contain large numbers of these clusters in relatively unobscured starburst environments. Measurement of the age, size, and stellar contents of the clusters can test the hypothesis that super star clusters are young globular clusters. Together with our UV and optical data, NICMOS images will provide the SED of numerous super star clusters over a decade in wavelength. Our already-approved observations will allow us to estimate, by comparison with evolutionary synthesis models, the masses and ages of the clusters. The proposed IR data will be sensitive to the number of supergiants {1.6 micron} and O-stars {Paschen Alpha} in each of the clusters. The observations will provide an independent determination of the reddening, mass, and age of each cluster. We expect to see in the IR numerous clusters that are obscured in the UV and optical. These clusters may be the younger ones, which are still embedded in their molecular clouds. By measuring the mass, age, and size of a large number of clusters, we can actually obtain an evolutionary picture of these objects at different stages in their lives.

Efficient architecture for spike sorting in reconfigurable hardware.

PubMed

Hwang, Wen-Jyi; Lee, Wei-Hao; Lin, Shiow-Jyu; Lai, Sheng-Ying

2013-11-01

This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.

Radiation-induced microcrystal shape change as a mechanism of wasteform degradation

NASA Astrophysics Data System (ADS)

Ojovan, Michael I.; Burakov, Boris E.; Lee, William E.

2018-04-01

Experiments with actinide-containing insulating wasteforms such as devitrified glasses containing 244Cm, Ti-pyrochlore, single-phase La-monazite, Pu-monazite ceramics, Eu-monazite and zircon single crystals containing 238Pu indicate that mechanical self-irradiation-induced destruction may not reveal itself for many years (even decades). The mechanisms causing these slowly-occurring changes remain unknown therefore in addition to known mechanisms of wasteform degradation such as matrix swelling and loss of solid solution we have modelled the damaging effects of electrical fields induced by the decay of radionuclides in clusters embedded in a non-conducting matrix. Three effects were important: (i) electric breakdown; (ii) cluster shape change due to dipole interaction, and (iii) cluster shape change due to polarisation interaction. We reveal a critical size of radioactive clusters in non-conducting matrices so that the matrix material can be damaged if clusters are larger than this critical size. The most important parameters that control the matrix integrity are the radioactive cluster (inhomogeneity) size, specific radioactivity, and effective matrix electrical conductivity. We conclude that the wasteform should be as homogeneous as possible and even electrically conductive to avoid potential damage caused by electrical charges induced by radioactive decay.

Highly efficient star formation in NGC 5253 possibly from stream-fed accretion.

PubMed

Turner, J L; Beck, S C; Benford, D J; Consiglio, S M; Ho, P T P; Kovács, A; Meier, D S; Zhao, J-H

2015-03-19

Gas clouds in present-day galaxies are inefficient at forming stars. Low star-formation efficiency is a critical parameter in galaxy evolution: it is why stars are still forming nearly 14 billion years after the Big Bang and why star clusters generally do not survive their births, instead dispersing to form galactic disks or bulges. Yet the existence of ancient massive bound star clusters (globular clusters) in the Milky Way suggests that efficiencies were higher when they formed ten billion years ago. A local dwarf galaxy, NGC 5253, has a young star cluster that provides an example of highly efficient star formation. Here we report the detection of the J = 3→2 rotational transition of CO at the location of the massive cluster. The gas cloud is hot, dense, quiescent and extremely dusty. Its gas-to-dust ratio is lower than the Galactic value, which we attribute to dust enrichment by the embedded star cluster. Its star-formation efficiency exceeds 50 per cent, tenfold that of clouds in the Milky Way. We suggest that high efficiency results from the force-feeding of star formation by a streamer of gas falling into the galaxy.

The outskirts of the Coma cluster

NASA Astrophysics Data System (ADS)

Gavazzi, Giuseppe

Evolved Coma-like clusters of galaxies are constituted of relaxed cores composed of ''old'' early-type galaxies, embedded in large-scale structures, mostly constituted of unevolved (late-type) systems. According to the hierarchical theory of cluster formation the central regions are being fed with unevolved, low-mass systems infalling from the surroundings that are gradually transformed into elliptical/S0 galaxies by tidal galaxy-galaxy and galaxy-cluster interactions, taking place at some boundary distance. The Coma cluster, the most studied of all local clusters, provides us with the ideal test-bed for such an evolutionary study because of the completeness of the photometric and kinematic information already at hands. The field of view of the planned GALEX observations is not big enough to include the boundary interface where most transformations processes are expected to take place, including the truncation of the current star formation. We propose to complete the outskirt of Coma with an additional corona of 11 GALEX imaging fields of 1500 sec exposure each, matching the deepness (UV_{AB}=23.5 mag) of the fields observed in guarantee time. Given the priority of the target, we also propose one optional Central pointing that includes one bright star marginally exceeding the detector brightness limit.

Electrostatically Embedded Many-Body Expansion for Neutral and Charged Metalloenzyme Model Systems.

PubMed

Kurbanov, Elbek K; Leverentz, Hannah R; Truhlar, Donald G; Amin, Elizabeth A

2012-01-10

The electrostatically embedded many-body (EE-MB) method has proven accurate for calculating cohesive and conformational energies in clusters, and it has recently been extended to obtain bond dissociation energies for metal-ligand bonds in positively charged inorganic coordination complexes. In the present paper, we present four key guidelines that maximize the accuracy and efficiency of EE-MB calculations for metal centers. Then, following these guidelines, we show that the EE-MB method can also perform well for bond dissociation energies in a variety of neutral and negatively charged inorganic coordination systems representing metalloenzyme active sites, including a model of the catalytic site of the zinc-bearing anthrax toxin lethal factor, a popular target for drug development. In particular, we find that the electrostatically embedded three-body (EE-3B) method is able to reproduce conventionally calculated bond-breaking energies in a series of pentacoordinate and hexacoordinate zinc-containing systems with an average absolute error (averaged over 25 cases) of only 0.98 kcal/mol.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Field O stars: formed in situ or as runaways?

NASA Astrophysics Data System (ADS)

Gvaramadze, V. V.; Weidner, C.; Kroupa, P.; Pflamm-Altenburg, J.

2012-08-01

A significant fraction of massive stars in the Milky Way and other galaxies are located far from star clusters and star-forming regions. It is known that some of these stars are runaways, i.e. possess high space velocities (determined through the proper motion and/or radial velocity measurements), and therefore most likely were formed in embedded clusters and then ejected into the field because of dynamical few-body interactions or binary-supernova explosions. However, there exists a group of field O stars whose runaway status is difficult to prove via direct proper motion measurements (e.g. in the Magellanic Clouds) or whose (measured) low space velocities and/or young ages appear to be incompatible with their large separation from known star clusters. The existence of this group led some authors to believe that field O stars can form in situ. Since the question of whether or not O stars can form in isolation is of crucial importance for star formation theory, it is important to thoroughly test candidates of such stars in order to improve the theory. In this paper, we examine the runaway status of the best candidates for isolated formation of massive stars in the Milky Way and the Magellanic Clouds by searching for bow shocks around them, by using the new reduction of the Hipparcos data, and by searching for stellar systems from which they could originate within their lifetimes. We show that most of the known O stars thought to have formed in isolation are instead very likely runaways. We show also that the field must contain a population of O stars whose low space velocities and/or young ages are in apparent contradiction to the large separation of these stars from their parent clusters and/or the ages of these clusters. These stars (the descendants of runaway massive binaries) cannot be traced back to their parent clusters and therefore can be mistakenly considered as having formed in situ. We argue also that some field O stars could be detected in optical wavelengths only because they are runaways, while their cousins residing in the deeply embedded parent clusters might still remain totally obscured. The main conclusion of our study is that there is no significant evidence whatsoever in support of the in situ proposal on the origin of massive stars.

The sparkling Universe: clustering of voids and void clumps

NASA Astrophysics Data System (ADS)

Lares, Marcelo; Ruiz, Andrés N.; Luparello, Heliana E.; Ceccarelli, Laura; Garcia Lambas, Diego; Paz, Dante J.

2017-07-01

We analyse the clustering of cosmic voids using a numerical simulation and the main galaxy sample from the Sloan Digital Sky Survey. We take into account the classification of voids into two types that resemble different evolutionary modes: those with a rising integrated density profile (void-in-void mode or R-type) and voids with shells (void-in-cloud mode or S-type). The results show that voids of the same type have stronger clustering than the full sample. We use the correlation analysis to define void clumps, associations with at least two voids separated by a distance of at most the mean void separation. In order to study the spatial configuration of void clumps, we compute the minimal spanning tree and analyse their multiplicity, maximum length and elongation parameter. We further study the dynamics of the smaller sphere that enclose all the voids in each clump. Although the global densities of void clumps are different according to their member-void types, the bulk motions of these spheres are remarkably lower than those of randomly placed spheres with the same radius distribution. In addition, the coherence of pairwise void motions does not strongly depend on whether voids belong to the same clump. Void clumps are useful to analyse the large-scale flows around voids, since voids embedded in large underdense regions are mostly in the void-in-void regime, where the expansion of the larger region produces the separation of voids. Similarly, voids around overdense regions form clumps that are in collapse, as reflected in the relative velocities of voids that are mostly approaching.

A graph-theoretical analysis algorithm for quantifying the transition from sensory input to motor output by an emotional stimulus.

PubMed

Karmonik, Christof; Fung, Steve H; Dulay, M; Verma, A; Grossman, Robert G

2013-01-01

Graph-theoretical analysis algorithms have been used for identifying subnetworks in the human brain during the Default Mode State. Here, these methods are expanded to determine the interaction of the sensory and the motor subnetworks during the performance of an approach-avoidance paradigm utilizing the correlation strength between the signal intensity time courses as measure of synchrony. From functional magnetic resonance imaging (fMRI) data of 9 healthy volunteers, two signal time courses, one from the primary visual cortex (sensory input) and one from the motor cortex (motor output) were identified and a correlation difference map was calculated. Graph networks were created from this map and visualized with spring-embedded layouts and 3D layouts in the original anatomical space. Functional clusters in these networks were identified with the MCODE clustering algorithm. Interactions between the sensory sub-network and the motor sub-network were quantified through the interaction strengths of these clusters. The percentages of interactions involving the visual cortex ranged from 85 % to 18 % and the motor cortex ranged from 40 % to 9 %. Other regions with high interactions were: frontal cortex (19 ± 18 %), insula (17 ± 22 %), cuneus (16 ± 15 %), supplementary motor area (SMA, 11 ± 18 %) and subcortical regions (11 ± 10 %). Interactions between motor cortex, SMA and visual cortex accounted for 12 %, between visual cortex and cuneus for 8 % and between motor cortex, SMA and cuneus for 6 % of all interactions. These quantitative findings are supported by the visual impressions from the 2D and 3D network layouts.

Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes.

PubMed

Cannistraci, Carlo Vittorio; Ravasi, Timothy; Montevecchi, Franco Maria; Ideker, Trey; Alessio, Massimo

2010-09-15

Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space. 'Minimum Curvilinearity' (MC) is a principle that-for small datasets-suggests the approximation of curvilinear sample distances in the feature space by pair-wise distances over their minimum spanning tree (MST), and thus avoids the introduction of any tuning parameter. MC is used to design two novel forms of nonlinear machine learning (NML): Minimum Curvilinear embedding (MCE) for DR, and Minimum Curvilinear affinity propagation (MCAP) for clustering. Compared with several other unsupervised and supervised algorithms, MCE and MCAP, whether individually or combined in H2P, overcome the limits of classical approaches. High performance was attained in the visualization and classification of: (i) pain patients (proteomic measurements) in peripheral neuropathy; (ii) human organ tissues (genomic transcription factor measurements) on the basis of their embryological origin. MC provides a valuable framework to estimate nonlinear distances in small datasets. Its extension to large datasets is prefigured for novel NMLs. Classification of neuropathic pain by proteomic profiles offers new insights for future molecular and systems biology characterization of pain. Improvements in tissue embryological classification refine results obtained in an earlier study, and suggest a possible reinterpretation of skin attribution as mesodermal. https://sites.google.com/site/carlovittoriocannistraci/home.

Commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al.

ERIC Educational Resources Information Center

Timms, Mike

2014-01-01

In his commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al., Mike Timms writes that his own research has involved the use of embedded assessments using simulations in interactive learning environments, and the Evidence Centered Design (ECD) approach has provided a solid…

Minimizing embedding impact in steganography using trellis-coded quantization

NASA Astrophysics Data System (ADS)

Filler, Tomáš; Judas, Jan; Fridrich, Jessica

2010-01-01

In this paper, we propose a practical approach to minimizing embedding impact in steganography based on syndrome coding and trellis-coded quantization and contrast its performance with bounds derived from appropriate rate-distortion bounds. We assume that each cover element can be assigned a positive scalar expressing the impact of making an embedding change at that element (single-letter distortion). The problem is to embed a given payload with minimal possible average embedding impact. This task, which can be viewed as a generalization of matrix embedding or writing on wet paper, has been approached using heuristic and suboptimal tools in the past. Here, we propose a fast and very versatile solution to this problem that can theoretically achieve performance arbitrarily close to the bound. It is based on syndrome coding using linear convolutional codes with the optimal binary quantizer implemented using the Viterbi algorithm run in the dual domain. The complexity and memory requirements of the embedding algorithm are linear w.r.t. the number of cover elements. For practitioners, we include detailed algorithms for finding good codes and their implementation. Finally, we report extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel.

Electron-induced hydrogen loss in uracil in a water cluster environment

NASA Astrophysics Data System (ADS)

Smyth, M.; Kohanoff, J.; Fabrikant, I. I.

2014-05-01

Low-energy electron-impact hydrogen loss due to dissociative electron attachment (DEA) to the uracil and thymine molecules in a water cluster environment is investigated theoretically. Only the A'-resonance contribution, describing the near-threshold behavior of DEA, is incorporated. Calculations are based on the nonlocal complex potential theory and the multiple scattering theory, and are performed for a model target with basic properties of uracil and thymine, surrounded by five water molecules. The DEA cross section is strongly enhanced when the attaching molecule is embedded in a water cluster. This growth is due to two effects: the increase of the resonance lifetime and the negative shift in the resonance position due to interaction of the intermediate negative ion with the surrounding water molecules. A similar effect was earlier found in DEA to chlorofluorocarbons.

An empirical potential for simulating vacancy clusters in tungsten.

PubMed

Mason, D R; Nguyen-Manh, D; Becquart, C S

2017-12-20

We present an empirical interatomic potential for tungsten, particularly well suited for simulations of vacancy-type defects. We compare energies and structures of vacancy clusters generated with the empirical potential with an extensive new database of values computed using density functional theory, and show that the new potential predicts low-energy defect structures and formation energies with high accuracy. A significant difference to other popular embedded-atom empirical potentials for tungsten is the correct prediction of surface energies. Interstitial properties and short-range pairwise behaviour remain similar to the Ackford-Thetford potential on which it is based, making this potential well-suited to simulations of microstructural evolution following irradiation damage cascades. Using atomistic kinetic Monte Carlo simulations, we predict vacancy cluster dissociation in the range 1100-1300 K, the temperature range generally associated with stage IV recovery.

Study on the structural transition of CoNi nanoclusters using molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Xia, J. H.; Gao, Xue-Mei

2018-04-01

In this work, the segregation and structural transitions of CoNi clusters, between 1500 and 300 K, have been investigated using molecular dynamics simulations with the embedded atom method potential. The radial distribution function was used to analyze the segregation during the cooling processes. It is found that Co atoms segregate to the inside and Ni atoms preferably to the surface during the cooling processes, the Co147Ni414 cluster becomes a core-shell structure. We discuss the structural transition according to the pair-correction function and pair-analysis technique, and finally the liquid Co147Ni414 crystallizes into the coexistence of hcp and fcc structure at 300 K. At the same time, it is found that the frozen structure of CoNi cluster is strongly related to the Co concentration.

National forest economic clusters: a new model for assessing national-forest-based natural resources products and services.

Treesearch

Thomas D. Rojas

2007-01-01

National forest lands encompass numerous rural and urban communities. Some national-forest-based communities lie embedded within national forests, and others reside just outside the official boundaries of national forests. The urban and rural communities within or near national forest lands include a wide variety of historical traditions and cultural values that affect...

Direct synthesis of antimicrobial coatings based on tailored bi-elemental nanoparticles

NASA Astrophysics Data System (ADS)

Benetti, Giulio; Cavaliere, Emanuele; Canteri, Adalberto; Landini, Giulia; Rossolini, Gian Maria; Pallecchi, Lucia; Chiodi, Mirco; Van Bael, Margriet J.; Winckelmans, Naomi; Bals, Sara; Gavioli, Luca

2017-03-01

Ultrathin coatings based on bi-elemental nanoparticles (NPs) are very promising to limit the surface-related spread of bacterial pathogens, particularly in nosocomial environments. However, tailoring the synthesis, composition, adhesion to substrate, and antimicrobial spectrum of the coating is an open challenge. Herein, we report on a radically new nanostructured coating, obtained by a one-step gas-phase deposition technique, and composed of bi-elemental Janus type Ag/Ti NPs. The NPs are characterized by a cluster-in-cluster mixing phase with metallic Ag nano-crystals embedded in amorphous TiO2 and present a promising antimicrobial activity including also multidrug resistant strains. We demonstrate the flexibility of the method to tune the embedded Ag nano-crystals dimension, the total relative composition of the coating, and the substrate type, opening the possibility of tailoring the dimension, composition, antimicrobial spectrum, and other physical/chemical properties of such multi-elemental systems. This work is expected to significantly spread the range of applications of NPs coatings, not only as an effective tool in the prevention of healthcare-associated infections but also in other technologically relevant fields like sensors or nano-/micro joining.

High resolution far-infrared observations of the evolved H II region M16

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

McBreen, B.; Fazio, G.G.; Jaffe, D.T.

1982-03-01

M16 is an evolved, extremely density bounded H II region, which now consists only of a series of ionization fronts at molecular cloud boundaries. The source of ionization is the OB star cluster (NGC 6611) which is about 5 x 10/sup 6/ years old. We used the CFA/UA 102 cm balloon-borne telescope to map this region and detected three far-infrared (far-IR) sources embedded in an extended ridge of emission. Source I is an unresolved far-IR source embedded in a molecular cloud near a sharp ionization front. An H/sub 2/O maser is associated with this source, but no radio continuum emissionmore » has been observed. The other two far-IR sources (II and III) are associated with ionized gas-molecular cloud interfaces, with the far-IR radiation arising from dust at the boundary heated by the OB cluster. Source II is located at the southern prominent neutral intrusion with its associated bright rims and dark ''elephant trunk'' globules that delineate the current progress of the ionization front into the neutral material, and Source III arises at the interface of the northern molecular cloud fragment.« less

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

NASA Technical Reports Server (NTRS)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

Formation of metallic clusters in oxide insulators by means of ion beam mixing

NASA Astrophysics Data System (ADS)

Talut, G.; Potzger, K.; Mücklich, A.; Zhou, Shengqiang

2008-04-01

The intermixing and near-interface cluster formation of Pt and FePt thin films deposited on different oxide surfaces by means of Pt+ ion irradiation and subsequent annealing was investigated. Irradiated as well as postannealed samples were investigated using high resolution transmission electron microscopy. In MgO and Y :ZrO2 covered with Pt, crystalline clusters with mean sizes of 2 and 3.5nm were found after the Pt+ irradiations with 8×1015 and 2×1016cm-2 and subsequent annealing, respectively. In MgO samples covered with FePt, clusters with mean sizes of 1 and 2nm were found after the Pt+ irradiations with 8×1015 and 2×1016cm-2 and subsequent annealing, respectively. In Y :ZrO2 samples covered with FePt, clusters up to 5nm in size were found after the Pt+ irradiation with 2×1016cm-2 and subsequent annealing. In LaAlO3 the irradiation was accompanied by a full amorphization of the host matrix and appearance of embedded clusters of different sizes. The determination of the lattice constant and thus the kind of the clusters in samples covered by FePt was hindered due to strong deviation of the electron beam by the ferromagnetic FePt.

Streptomyces scabies 87-22 contains a coronafacic acid-like biosynthetic cluster that contributes to plant-microbe interactions.

PubMed

Bignell, Dawn R D; Seipke, Ryan F; Huguet-Tapia, José C; Chambers, Alan H; Parry, Ronald J; Loria, Rosemary

2010-02-01

Plant-pathogenic Streptomyces spp. cause scab disease on economically important root and tuber crops, the most important of which is potato. Key virulence determinants produced by these species include the cellulose synthesis inhibitor, thaxtomin A, and the secreted Nec1 protein that is required for colonization of the plant host. Recently, the genome sequence of Streptomyces scabies 87-22 was completed, and a biosynthetic cluster was identified that is predicted to synthesize a novel compound similar to coronafacic acid (CFA), a component of the virulence-associated coronatine phytotoxin produced by the plant-pathogenic bacterium Pseudomonas syringae. Southern analysis indicated that the cfa-like cluster in S. scabies 87-22 is likely conserved in other strains of S. scabies but is absent from two other pathogenic streptomycetes, S. turgidiscabies and S. acidiscabies. Transcriptional analyses demonstrated that the cluster is expressed during plant-microbe interactions and that expression requires a transcriptional regulator embedded in the cluster as well as the bldA tRNA. A knockout strain of the biosynthetic cluster displayed a reduced virulence phenotype on tobacco seedlings compared with the wild-type strain. Thus, the cfa-like biosynthetic cluster is a newly discovered locus in S. scabies that contributes to host-pathogen interactions.

The doubling of stellar black hole nuclei

NASA Astrophysics Data System (ADS)

Kazandjian, Mher V.; Touma, J. R.

2013-04-01

It is strongly believed that Andromeda's double nucleus signals a disc of stars revolving around its central supermassive black hole on eccentric Keplerian orbits with nearly aligned apsides. A self-consistent stellar dynamical origin for such apparently long-lived alignment has so far been lacking, with indications that cluster self-gravity is capable of sustaining such lopsided configurations if and when stimulated by external perturbations. Here, we present results of N-body simulations which show unstable counter-rotating stellar clusters around supermassive black holes saturating into uniformly precessing lopsided nuclei. The double nucleus in our featured experiment decomposes naturally into a thick eccentric disc of apo-apse aligned stars which is embedded in a lighter triaxial cluster. The eccentric disc reproduces key features of Keplerian disc models of Andromeda's double nucleus; the triaxial cluster has a distinctive kinematic signature which is evident in Hubble Space Telescope observations of Andromeda's double nucleus, and has been difficult to reproduce with Keplerian discs alone. Our simulations demonstrate how the combination of an eccentric disc and a triaxial cluster arises naturally when a star cluster accreted over a preexisting and counter-rotating disc of stars drives disc and cluster into a mutually destabilizing dance. Such accretion events are inherent to standard galaxy formation scenarios. They are here shown to double stellar black hole nuclei as they feed them.

Extreme learning machine based optimal embedding location finder for image steganography

PubMed Central

Aljeroudi, Yazan

2017-01-01

In image steganography, determining the optimum location for embedding the secret message precisely with minimum distortion of the host medium remains a challenging issue. Yet, an effective approach for the selection of the best embedding location with least deformation is far from being achieved. To attain this goal, we propose a novel approach for image steganography with high-performance, where extreme learning machine (ELM) algorithm is modified to create a supervised mathematical model. This ELM is first trained on a part of an image or any host medium before being tested in the regression mode. This allowed us to choose the optimal location for embedding the message with best values of the predicted evaluation metrics. Contrast, homogeneity, and other texture features are used for training on a new metric. Furthermore, the developed ELM is exploited for counter over-fitting while training. The performance of the proposed steganography approach is evaluated by computing the correlation, structural similarity (SSIM) index, fusion matrices, and mean square error (MSE). The modified ELM is found to outperform the existing approaches in terms of imperceptibility. Excellent features of the experimental results demonstrate that the proposed steganographic approach is greatly proficient for preserving the visual information of an image. An improvement in the imperceptibility as much as 28% is achieved compared to the existing state of the art methods. PMID:28196080

Dark energy and the structure of the Coma cluster of galaxies

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Tales from the frontline: the experiences of early childhood practitioners working with an 'embedded' research team.

PubMed

Wong, Sandie

2009-05-01

In late 2006, SDN Children's Services, an Australian not-for-profit provider of services for children, families and communities, engaged a research team that was 'embedded' within the organisation for 1 year. This action represented a significant investment of resources, such as staff time and organisational funds, and demonstrates SDN's strong commitment to research and evaluation as a means of supporting organisational learning and development. This paper highlights the innovative nature of the approach by positioning the role of the embedded researcher within the current theoretical and socio-political context. It also provides evidence of the success of the approach by reporting on the findings of a study that investigated staff's experiences of being involved in this type of collaborative investigation of their work. I argue that the employment of an embedded researcher can have positive benefits both for the organisation and the practitioners--but who the researchers are really matters.

Cell-Averaged discretization for incompressible Navier-Stokes with embedded boundaries and locally refined Cartesian meshes: a high-order finite volume approach

NASA Astrophysics Data System (ADS)

Bhalla, Amneet Pal Singh; Johansen, Hans; Graves, Dan; Martin, Dan; Colella, Phillip; Applied Numerical Algorithms Group Team

2017-11-01

We present a consistent cell-averaged discretization for incompressible Navier-Stokes equations on complex domains using embedded boundaries. The embedded boundary is allowed to freely cut the locally-refined background Cartesian grid. Implicit-function representation is used for the embedded boundary, which allows us to convert the required geometric moments in the Taylor series expansion (upto arbitrary order) of polynomials into an algebraic problem in lower dimensions. The computed geometric moments are then used to construct stencils for various operators like the Laplacian, divergence, gradient, etc., by solving a least-squares system locally. We also construct the inter-level data-transfer operators like prolongation and restriction for multi grid solvers using the same least-squares system approach. This allows us to retain high-order of accuracy near coarse-fine interface and near embedded boundaries. Canonical problems like Taylor-Green vortex flow and flow past bluff bodies will be presented to demonstrate the proposed method. U.S. Department of Energy, Office of Science, ASCR (Award Number DE-AC02-05CH11231).

Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

PubMed

Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

2017-01-01

Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

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

PubMed

Jeng, Jin-Tsong

2006-06-01

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

The GALAH survey: chemical tagging of star clusters and new members in the Pleiades

NASA Astrophysics Data System (ADS)

Kos, Janez; Bland-Hawthorn, Joss; Freeman, Ken; Buder, Sven; Traven, Gregor; De Silva, Gayandhi M.; Sharma, Sanjib; Asplund, Martin; Duong, Ly; Lin, Jane; Lind, Karin; Martell, Sarah; Simpson, Jeffrey D.; Stello, Dennis; Zucker, Daniel B.; Zwitter, Tomaž; Anguiano, Borja; Da Costa, Gary; D'Orazi, Valentina; Horner, Jonathan; Kafle, Prajwal R.; Lewis, Geraint; Munari, Ulisse; Nataf, David M.; Ness, Melissa; Reid, Warren; Schlesinger, Katie; Ting, Yuan-Sen; Wyse, Rosemary

2018-02-01

The technique of chemical tagging uses the elemental abundances of stellar atmospheres to 'reconstruct' chemically homogeneous star clusters that have long since dispersed. The GALAH spectroscopic survey - which aims to observe one million stars using the Anglo-Australian Telescope - allows us to measure up to 30 elements or dimensions in the stellar chemical abundance space, many of which are not independent. How to find clustering reliably in a noisy high-dimensional space is a difficult problem that remains largely unsolved. Here, we explore t-distributed stochastic neighbour embedding (t-SNE) - which identifies an optimal mapping of a high-dimensional space into fewer dimensions - whilst conserving the original clustering information. Typically, the projection is made to a 2D space to aid recognition of clusters by eye. We show that this method is a reliable tool for chemical tagging because it can: (i) resolve clustering in chemical space alone, (ii) recover known open and globular clusters with high efficiency and low contamination, and (iii) relate field stars to known clusters. t-SNE also provides a useful visualization of a high-dimensional space. We demonstrate the method on a data set of 13 abundances measured in the spectra of 187 000 stars by the GALAH survey. We recover seven of the nine observed clusters (six globular and three open clusters) in chemical space with minimal contamination from field stars and low numbers of outliers. With chemical tagging, we also identify two Pleiades supercluster members (which we confirm kinematically), one as far as 6° - one tidal radius away from the cluster centre.

THE PREVALENCE AND IMPACT OF WOLF–RAYET STARS IN EMERGING MASSIVE STAR CLUSTERS

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

Sokal, Kimberly R.; Johnson, Kelsey E.; Indebetouw, Rémy

We investigate Wolf–Rayet (WR) stars as a source of feedback contributing to the removal of natal material in the early evolution of massive star clusters. Despite previous work suggesting that massive star clusters clear out their natal material before the massive stars evolve into the WR phase, WR stars have been detected in several emerging massive star clusters. These detections suggest that the timescale for clusters to emerge can be at least as long as the time required to produce WR stars (a few million years), and could also indicate that WR stars may be providing the tipping point inmore » the combined feedback processes that drive a massive star cluster to emerge. We explore the potential overlap between the emerging phase and the WR phase with an observational survey to search for WR stars in emerging massive star clusters hosting WR stars. We select candidate emerging massive star clusters from known radio continuum sources with thermal emission and obtain optical spectra with the 4 m Mayall Telescope at Kitt Peak National Observatory and the 6.5 m MMT.{sup 4} We identify 21 sources with significantly detected WR signatures, which we term “emerging WR clusters.” WR features are detected in ∼50% of the radio-selected sample, and thus we find that WR stars are commonly present in currently emerging massive star clusters. The observed extinctions and ages suggest that clusters without WR detections remain embedded for longer periods of time, and may indicate that WR stars can aid, and therefore accelerate, the emergence process.« less

Characterization of Omega-WINGS galaxy clusters. I. Stellar light and mass profiles

NASA Astrophysics Data System (ADS)

Cariddi, S.; D'Onofrio, M.; Fasano, G.; Poggianti, B. M.; Moretti, A.; Gullieuszik, M.; Bettoni, D.; Sciarratta, M.

2018-02-01

Context. Galaxy clusters are the largest virialized structures in the observable Universe. Knowledge of their properties provides many useful astrophysical and cosmological information. Aims: Our aim is to derive the luminosity and stellar mass profiles of the nearby galaxy clusters of the Omega-WINGS survey and to study the main scaling relations valid for such systems. Methods: We merged data from the WINGS and Omega-WINGS databases, sorted the sources according to the distance from the brightest cluster galaxy (BCG), and calculated the integrated luminosity profiles in the B and V bands, taking into account extinction, photometric and spatial completeness, K correction, and background contribution. Then, by exploiting the spectroscopic sample we derived the stellar mass profiles of the clusters. Results: We obtained the luminosity profiles of 46 galaxy clusters, reaching r200 in 30 cases, and the stellar mass profiles of 42 of our objects. We successfully fitted all the integrated luminosity growth profiles with one or two embedded Sérsic components, deriving the main clusters parameters. Finally, we checked the main scaling relation among the clusters parameters in comparison with those obtained for a selected sample of early-type galaxies (ETGs) of the same clusters. Conclusions: We found that the nearby galaxy clusters are non-homologous structures such as ETGs and exhibit a color-magnitude (CM) red-sequence relation very similar to that observed for galaxies in clusters. These properties are not expected in the current cluster formation scenarios. In particular the existence of a CM relation for clusters, shown here for the first time, suggests that the baryonic structures grow and evolve in a similar way at all scales.

Embedded WENO: A design strategy to improve existing WENO schemes

NASA Astrophysics Data System (ADS)

van Lith, Bart S.; ten Thije Boonkkamp, Jan H. M.; IJzerman, Wilbert L.

2017-02-01

Embedded WENO methods utilise all adjacent smooth substencils to construct a desirable interpolation. Conventional WENO schemes under-use this possibility close to large gradients or discontinuities. We develop a general approach for constructing embedded versions of existing WENO schemes. Embedded methods based on the WENO schemes of Jiang and Shu [1] and on the WENO-Z scheme of Borges et al. [2] are explicitly constructed. Several possible choices are presented that result in either better spectral properties or a higher order of convergence for sufficiently smooth solutions. However, these improvements carry over to discontinuous solutions. The embedded methods are demonstrated to be indeed improvements over their standard counterparts by several numerical examples. All the embedded methods presented have no added computational effort compared to their standard counterparts.

Real time UNIX in embedded control-a case study within the context of LynxOS

NASA Astrophysics Data System (ADS)

Kleines, H.; Zwoll, K.

1996-02-01

Intelligent communication controllers for a layered protocol profile are a typical example of an embedded control application, where the classical approach for the software development is based on a proprietary real-time operating system kernel under which the individual layers are implemented as tasks. Based on the exemplary implementation of a derivative of MAP 3.0, an unusual and innovative approach is presented, where the protocol software is implemented under the UNIX-compatible real-time operating system LynxOS. The overall design of the embedded control application is presented under a more general view and economical implications as well as aspects of the development environment and performance are discussed

Dark Matter and Extragalactic Gas Clouds in the NGC 4532/DDO 137 System

NASA Technical Reports Server (NTRS)

Hoffman, G. L.; Lu, N. Y.; Salpeter, E. E.; Connell, B. M.

1998-01-01

H I synthesis mapping of NGC 4532 and DDO 137, a pair of Sm galaxies on the edge of the Virgo cluster, is used to determine rotation curves for each of the galaxies and to resolve the structure and kinematics of three extragalactic H I clouds embedded in an extended envelope of diffuse HI discovered in earlier Arecibo studies of the system.

Low-Rank Discriminant Embedding for Multiview Learning.

PubMed

Li, Jingjing; Wu, Yue; Zhao, Jidong; Lu, Ke

2017-11-01

This paper focuses on the specific problem of multiview learning where samples have the same feature set but different probability distributions, e.g., different viewpoints or different modalities. Since samples lying in different distributions cannot be compared directly, this paper aims to learn a latent subspace shared by multiple views assuming that the input views are generated from this latent subspace. Previous approaches usually learn the common subspace by either maximizing the empirical likelihood, or preserving the geometric structure. However, considering the complementarity between the two objectives, this paper proposes a novel approach, named low-rank discriminant embedding (LRDE), for multiview learning by taking full advantage of both sides. By further considering the duality between data points and features of multiview scene, i.e., data points can be grouped based on their distribution on features, while features can be grouped based on their distribution on the data points, LRDE not only deploys low-rank constraints on both sample level and feature level to dig out the shared factors across different views, but also preserves geometric information in both the ambient sample space and the embedding feature space by designing a novel graph structure under the framework of graph embedding. Finally, LRDE jointly optimizes low-rank representation and graph embedding in a unified framework. Comprehensive experiments in both multiview manner and pairwise manner demonstrate that LRDE performs much better than previous approaches proposed in recent literatures.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

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.

The Acquisition of Neg-V and V-Neg Order in Embedded Clauses in Swedish: A Microparametric Approach

ERIC Educational Resources Information Center

Waldmann, Christian

2014-01-01

This article examines the acquisition of embedded verb placement in Swedish children, focusing on Neg-V and V-Neg order. It is proposed that a principle of economy of movement creates an overuse of V-Neg order in embedded clauses and that the low frequency of the target-consistent Neg-V order in child-directed speech obstructs children from…

A hardware-in-the-loop simulation program for ground-based radar

NASA Astrophysics Data System (ADS)

Lam, Eric P.; Black, Dennis W.; Ebisu, Jason S.; Magallon, Julianna

2011-06-01

A radar system created using an embedded computer system needs testing. The way to test an embedded computer system is different from the debugging approaches used on desktop computers. One way to test a radar system is to feed it artificial inputs and analyze the outputs of the radar. More often, not all of the building blocks of the radar system are available to test. This will require the engineer to test parts of the radar system using a "black box" approach. A common way to test software code on a desktop simulation is to use breakpoints so that is pauses after each cycle through its calculations. The outputs are compared against the values that are expected. This requires the engineer to use valid test scenarios. We will present a hardware-in-the-loop simulator that allows the embedded system to think it is operating with real-world inputs and outputs. From the embedded system's point of view, it is operating in real-time. The hardware in the loop simulation is based on our Desktop PC Simulation (PCS) testbed. In the past, PCS was used for ground-based radars. This embedded simulation, called Embedded PCS, allows a rapid simulated evaluation of ground-based radar performance in a laboratory environment.

Stretchable nanocomposite electrodes with tunable mechanical properties by supersonic cluster beam implantation in elastomers

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

Borghi, F.; Podestà, A.; Milani, P., E-mail: pmilani@mi.infn.it

We demonstrate the fabrication of gold-polydimethylsiloxane nanocomposite electrodes, by supersonic cluster beam implantation, with tunable Young's modulus depending solely on the amount of metal clusters implanted in the elastomeric matrix. We show both experimentally and by atomistic simulations that the mechanical properties of the nanocomposite can be maintained close to that of the bare elastomer for significant metal volume concentrations. Moreover, the elastic properties of the nanocomposite, as experimentally characterized by nanoindentation and modeled with molecular dynamics simulations, are also well described by the Guth-Gold classical model for nanoparticle-filled rubbers, which depends on the presence, concentration, and aspect ratio ofmore » metal nanoparticles, and not on the physical and chemical modification of the polymeric matrix due to the embedding process. The elastic properties of the nanocomposite can therefore be determined and engineered a priori, by controlling only the nanoparticle concentration.« less

Dynamic and Contextual Information in HMM Modeling for Handwritten Word Recognition.

PubMed

Bianne-Bernard, Anne-Laure; Menasri, Farès; Al-Hajj Mohamad, Rami; Mokbel, Chafic; Kermorvant, Christopher; Likforman-Sulem, Laurence

2011-10-01

This study aims at building an efficient word recognition system resulting from the combination of three handwriting recognizers. The main component of this combined system is an HMM-based recognizer which considers dynamic and contextual information for a better modeling of writing units. For modeling the contextual units, a state-tying process based on decision tree clustering is introduced. Decision trees are built according to a set of expert-based questions on how characters are written. Questions are divided into global questions, yielding larger clusters, and precise questions, yielding smaller ones. Such clustering enables us to reduce the total number of models and Gaussians densities by 10. We then apply this modeling to the recognition of handwritten words. Experiments are conducted on three publicly available databases based on Latin or Arabic languages: Rimes, IAM, and OpenHart. The results obtained show that contextual information embedded with dynamic modeling significantly improves recognition.

Modelling the growth of plants with a uniform growth logistics.

PubMed

Kilian, H G; Bartkowiak, D; Kazda, M; Kaufmann, D

2014-05-21

The increment model has previously been used to describe the growth of plants in general. Here, we examine how the same logistics enables the development of different superstructures. Data from the literature are analyzed with the increment model. Increments are growth-invariant molecular clusters, treated as heuristic particles. This approach formulates the law of mass action for multi-component systems, describing the general properties of superstructures which are optimized via relaxation processes. The daily growth patterns of hypocotyls can be reproduced implying predetermined growth invariant model parameters. In various species, the coordinated formation and death of fine roots are modeled successfully. Their biphasic annual growth follows distinct morphological programs but both use the same logistics. In tropical forests, distributions of the diameter in breast height of trees of different species adhere to the same pattern. Beyond structural fluctuations, competition and cooperation within and between the species may drive optimization. All superstructures of plants examined so far could be reproduced with our approach. With genetically encoded growth-invariant model parameters (interaction with the environment included) perfect morphological development runs embedded in the uniform logistics of the increment model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Trajectory Based Behavior Analysis for User Verification

NASA Astrophysics Data System (ADS)

Pao, Hsing-Kuo; Lin, Hong-Yi; Chen, Kuan-Ta; Fadlil, Junaidillah

Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden patterns embedded in the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior in the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The method can also be applied for the task of recognition, predicting the trajectory type without pre-defined identity. Given a trajectory input, the results show that the proposed method can accurately verify the user identity, or suggest whom owns the trajectory if the input identity is not provided.

Bose-Einstein condensate & degenerate Fermi cored dark matter halos

NASA Astrophysics Data System (ADS)

Chung, W.-J.; Nelson, L. A.

2018-06-01

There has been considerable interest in the last several years in support of the idea that galaxies and clusters could have highly condensed cores of dark matter (DM) within their central regions. In particular, it has been suggested that dark matter could form Bose-Einstein condensates (BECs) or degenerate Fermi cores. We examine these possibilities under the assumption that the core consists of highly condensed DM (either bosons or fermions) that is embedded in a diffuse envelope (e.g., isothermal sphere). The novelty of our approach is that we invoke composite polytropes to model spherical collisionless structures in a way that is physically intuitive and can be generalized to include other equations of state (EOSs). Our model is very amenable to the analysis of BEC cores (composed of ultra-light bosons) that have been proposed to resolve small-scale CDM anomalies. We show that the analysis can readily be applied to bosons with or without small repulsive self-interactions. With respect to degenerate Fermi cores, we confirm that fermionic particle masses between 1—1000 keV are not excluded by the observations. Finally, we note that this approach can be extended to include a wide range of EOSs in addition to multi-component collisionless systems.

Participación científica del Nodo La Plata en el Proyecto VVV

NASA Astrophysics Data System (ADS)

Baume, G.; Fernández Lajús, E.; Feinstein, C.; Gamen, R.; Fariña, C.

We present here the main research lines related to the survey Vista Variables in the Vía Láctea (VVV) being carried out at "Node La Plata". These lines involve the study of stellar clusters and eclipsing systems. In this frame- work raises the following studies: a) An preliminar analysis of a group of embedded stellar clusters located in the fourth Galactic quadrant by estimat- ing their fundamental parameters using VVV data supplemented with data from other published catalogs. b) The provided methodology for the deter- mination of the eclipsing binary stars parameters for those ones detected in the survey from their light curves, including also extrasolar planets transits. FULL TEXT IN SPANISH

Scalable cluster administration - Chiba City I approach and lessons learned.

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

Navarro, J. P.; Evard, R.; Nurmi, D.

2002-07-01

Systems administrators of large clusters often need to perform the same administrative activity hundreds or thousands of times. Often such activities are time-consuming, especially the tasks of installing and maintaining software. By combining network services such as DHCP, TFTP, FTP, HTTP, and NFS with remote hardware control, cluster administrators can automate all administrative tasks. Scalable cluster administration addresses the following challenge: What systems design techniques can cluster builders use to automate cluster administration on very large clusters? We describe the approach used in the Mathematics and Computer Science Division of Argonne National Laboratory on Chiba City I, a 314-node Linuxmore » cluster; and we analyze the scalability, flexibility, and reliability benefits and limitations from that approach.« less

Star formation towards the southern cometary H II region IRAS 17256-3631

NASA Astrophysics Data System (ADS)

Veena, V. S.; Vig, S.; Tej, A.; Varricatt, W. P.; Ghosh, S. K.; Chandrasekhar, T.; Ashok, N. M.

2016-03-01

IRAS 17256-3631 is a southern Galactic massive star-forming region located at a distance of 2 kpc. In this paper, we present a multiwavelength investigation of the embedded cluster, the H II region, as well as the parent cloud. Radio images at 325, 610 and 1372 MHz were obtained using Giant Metrewave Radio Telescope, India while the near-infrared imaging and spectroscopy were carried out using United Kingdom Infrared Telescope and Mt. Abu Infrared Telescope, India. The near-infrared K-band image reveals the presence of a partially embedded infrared cluster. The spectral features of the brightest star in the cluster, IRS-1, spectroscopically agree with a late O or early B star and could be the driving source of this region. Filamentary H2 emission detected towards the outer envelope indicates the presence of highly excited gas. The parent cloud is investigated at far-infrared to millimetre wavelengths and 18 dust clumps have been identified. The spectral energy distributions of these clumps have been fitted as modified blackbodies and the best-fitting peak temperatures are found to range from 14 to 33 K, while the column densities vary from 0.7 to 8.5 × 1022 cm-2. The radio maps show a cometary morphology for the distribution of ionized gas that is density bounded towards the north-west and ionization bounded towards the south-east. This morphology is better explained with the champagne flow model as compared to the bow-shock model. Using observations at near-, mid- and far-infrared, submillimetre and radio wavelengths, we examine the evolutionary stages of various clumps.

A methodological study of genome-wide DNA methylation analyses using matched archival formalin-fixed paraffin embedded and fresh frozen breast tumors.

PubMed

Espinal, Allyson C; Wang, Dan; Yan, Li; Liu, Song; Tang, Li; Hu, Qiang; Morrison, Carl D; Ambrosone, Christine B; Higgins, Michael J; Sucheston-Campbell, Lara E

2017-02-28

DNA from archival formalin-fixed and paraffin embedded (FFPE) tissue is an invaluable resource for genome-wide methylation studies although concerns about poor quality may limit its use. In this study, we compared DNA methylation profiles of breast tumors using DNA from fresh-frozen (FF) tissues and three types of matched FFPE samples. For 9/10 patients, correlation and unsupervised clustering analysis revealed that the FF and FFPE samples were consistently correlated with each other and clustered into distinct subgroups. Greater than 84% of the top 100 loci previously shown to differentiate ER+ and ER- tumors in FF tissues were also FFPE DML. Weighted Correlation Gene Network Analyses (WCGNA) grouped the DML loci into 16 modules in FF tissue, with ~85% of the module membership preserved across tissue types. Restored FFPE and matched FF samples were profiled using the Illumina Infinium HumanMethylation450K platform. Methylation levels (β-values) across all loci and the top 100 loci previously shown to differentiate tumors by estrogen receptor status (ER+ or ER-) in a larger FF study, were compared between matched FF and FFPE samples using Pearson's correlation, hierarchical clustering and WCGNA. Positive predictive values and sensitivity levels for detecting differentially methylated loci (DML) in FF samples were calculated in an independent FFPE cohort. FFPE breast tumors samples show lower overall detection of DMLs versus FF, however FFPE and FF DMLs compare favorably. These results support the emerging consensus that the 450K platform can be employed to investigate epigenetics in large sets of archival FFPE tissues.

Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches

PubMed Central

Boyack, Kevin W.; Newman, David; Duhon, Russell J.; Klavans, Richard; Patek, Michael; Biberstine, Joseph R.; Schijvenaars, Bob; Skupin, André; Ma, Nianli; Börner, Katy

2011-01-01

Background We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis. The few comparisons of clustering results from different similarity approaches have focused on small literature sets and have given conflicting results. Our study was designed to seek a robust answer to the question of which similarity approach would generate the most coherent clusters of a biomedical literature set of over two million documents. Methodology We used a corpus of 2.15 million recent (2004-2008) records from MEDLINE, and generated nine different document-document similarity matrices from information extracted from their bibliographic records, including titles, abstracts and subject headings. The nine approaches were comprised of five different analytical techniques with two data sources. The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models – BM25 and PMRA (PubMed Related Articles). The two data sources were a) MeSH subject headings, and b) words from titles and abstracts. Each similarity matrix was filtered to keep the top-n highest similarities per document and then clustered using a combination of graph layout and average-link clustering. Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE. Conclusions PubMed's own related article approach (PMRA) generated the most coherent and most concentrated cluster solution of the nine text-based similarity approaches tested, followed closely by the BM25 approach using titles and abstracts. Approaches using only MeSH subject headings were not competitive with those based on titles and abstracts. PMID:21437291

Integrated embedded frequency selective surface sensors for structural health monitoring.

DOT National Transportation Integrated Search

2014-08-01

The objective of this project is to design an embedded sensor element capable of characterizing mechanical properties including shear strain. This element will be designed using a Frequency Selective Surface (FSS) approach, and will be intended for i...

Simulating radiative feedback and star cluster formation in GMCs - II. Mass dependence of cloud destruction and cluster properties

NASA Astrophysics Data System (ADS)

Howard, Corey S.; Pudritz, Ralph E.; Harris, William E.

2017-09-01

The process of radiative feedback in giant molecular clouds (GMCs) is an important mechanism for limiting star cluster formation through the heating and ionization of the surrounding gas. We explore the degree to which radiative feedback affects early (≲5 Myr) cluster formation in GMCs having masses that range from 104 to 106 M⊙ using the flash code. The inclusion of radiative feedback lowers the efficiency of cluster formation by 20-50 per cent relative to hydrodynamic simulations. Two models in particular - 5 × 104 and 105 M⊙ - show the largest suppression of the cluster formation efficiency, corresponding to a factor of ˜2. For these clouds only, the internal energy, a measure of the energy injected by radiative feedback, exceeds the gravitational potential for a significant amount of time. We find a clear relation between the maximum cluster mass, Mc,max, formed in a GMC and the mass of the GMC itself, MGMC: Mc,max ∝ M_{GMC}^{0.81}. This scaling result suggests that young globular clusters at the necessary scale of 106 M⊙ form within host GMCs of masses near ˜5 × 107 M⊙. We compare simulated cluster mass distributions to the observed embedded cluster mass function [d log (N)/dlog (M) ∝ Mβ where β = -1] and find good agreement (β = -0.99 ± 0.14) only for simulations including radiative feedback, indicating this process is important in controlling the growth of young clusters. However, the high star formation efficiencies, which range from 16 to 21 per cent, and high star formation rates compared to locally observed regions suggest other feedback mechanisms are also important during the formation and growth of stellar clusters.

Nature's polyoxometalate chemistry: X-ray structure of the Mo storage protein loaded with discrete polynuclear Mo-O clusters.

PubMed

Kowalewski, Björn; Poppe, Juliane; Demmer, Ulrike; Warkentin, Eberhard; Dierks, Thomas; Ermler, Ulrich; Schneider, Klaus

2012-06-13

Some N(2)-fixing bacteria prolong the functionality of nitrogenase in molybdenum starvation by a special Mo storage protein (MoSto) that can store more than 100 Mo atoms. The presented 1.6 Å X-ray structure of MoSto from Azotobacter vinelandii reveals various discrete polyoxomolybdate clusters, three covalently and three noncovalently bound Mo(8), three Mo(5-7), and one Mo(3) clusters, and several low occupied, so far undefinable clusters, which are embedded in specific pockets inside a locked cage-shaped (αβ)(3) protein complex. The structurally identical Mo(8) clusters (three layers of two, four, and two MoO(n) octahedra) are distinguishable from the [Mo(8)O(26)](4-) cluster formed in acidic solutions by two displaced MoO(n) octahedra implicating three kinetically labile terminal ligands. Stabilization in the covalent Mo(8) cluster is achieved by Mo bonding to Hisα156-N(ε2) and Gluα129-O(ε1). The absence of covalent protein interactions in the noncovalent Mo(8) cluster is compensated by a more extended hydrogen-bond network involving three pronounced histidines. One displaced MoO(n) octahedron might serve as nucleation site for an inhomogeneous Mo(5-7) cluster largely surrounded by bulk solvent. In the Mo(3) cluster located on the 3-fold axis, the three accurately positioned His140-N(ε2) atoms of the α subunits coordinate to the Mo atoms. The formed polyoxomolybdate clusters of MoSto, not detectable in bulk solvent, are the result of an interplay between self- and protein-driven assembly processes that unite inorganic supramolecular and protein chemistry in a host-guest system. Template, nucleation/protection, and catalyst functions of the polypeptide as well as perspectives for designing new clusters are discussed.

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

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

2011-02-01

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

Bottom-up strategies for the assembling of magnetic systems using nanoclusters

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

Improved Spectra for MALDI MSI of Peptides Using Ammonium Phosphate Monobasic in MALDI Matrix.

PubMed

Ucal, Yasemin; Ozpinar, Aysel

2018-05-10

MALDI mass spectrometry imaging (MSI) enables analysis of peptides along with histology. However, there are several critical steps in MALDI MSI of peptides, one of which is spectral quality. Suppression of MALDI matrix clusters by the aid of ammonium salts in MALDI experiments is well-known. It is asserted that addition of ammonium salts dissociates potential matrix adducts and thereafter decreases matrix cluster formation. Consequently, MALDI MS sensitivity and mass accuracy increases. Up to our knowledge, a limited number of MALDI MSI studies used ammonium salts as matrix additives to suppress matrix clusters and enhance peptide signals. In this work, we investigated the effect of ammonium phosphate monobasic (AmP) as alpha-cyano-4-hydroxycinnamic acid (α-CHCA) matrix additive in MALDI MSI of peptides. Prior to MALDI MSI, the effect of varying concentrations of AmP in α-CHCA were assessed in bovine serum albumin (BSA) tryptic digests and compared with the control (α-CHCA without AmP). Based on our data, the addition of AmP as matrix additive decreased matrix cluster formation regardless of its concentration and, specifically 8 mM AmP and 10 mM AmP increased BSA peptide signal intensities. In MALDI MSI of peptides, both 8 mM, and 10 mM AmP in α-CHCA improved peptide signals especially in the mass range of m/z 2000 to 3000. In particular, 9 peptide signals were found to have differential intensities within the tissues deposited with AmP in α-CHCA (AUC>0.60). To the best of our knowledge, this is the first MALDI MSI of peptides work investigating different concentrations of AmP as α-CHCA matrix additive in order to enhance peptide signals in formalin fixed paraffin embedded (FFPE) tissues. Further, AmP as part of α-CHCA matrix could enhance protein identifications and support MALDI MSI based proteomic approaches. This article is protected by copyright. All rights reserved.

The galaxy cluster outskirts probed by Chandra

NASA Astrophysics Data System (ADS)

Morandi, Andrea; Sun, Ming; Forman, William; Jones, Christine

2015-08-01

Exploring the virialization region of galaxy clusters has recently raised the attention of the scientific community, offering a direct view of structure formation. In this talk, I will present recent results on the physical properties of the intracluster medium in the outer volumes of a sample of 320 clusters (0.056 3 keV) in the Chandra archive, with a total integration time of ~20 Ms. We stacked the emission measure profiles of the clusters to detect a signal out to R_{100}. We then measured the average emission measure, gas density and gas fraction, which scale according to the self-similar model of cluster formation. We observe a steepening of the density profiles beyond R_{500} with slope beta ~ 0.68 at R_{500} and beta ~ 1 at R_{200} and beyond. By tracking the direction of the cosmic filaments where the clusters are embedded, we report that galaxy clusters deviate from spherical symmetry. We also did not find evolution of the gas density with redshift, confirming the self-similar evolution of the gas density. The value of the baryon fraction reaches the cosmic value at R_{200}: however, systematics due to non-thermal pressure support and clumpiness might enhance the measured gas fraction, leading to an actual deficit of the baryon budget with respect to the primordial value). This novel method, the stacking the X-ray signal of cluster outskirts, has the capacity to provide a generational leap forward in our understanding of cluster physics and formation, and the use of clusters as cosmological probes.

Scalable Methods for Electronic Excitations and Optical Responses of Nanostructures: Mathematics to Algorithms to Observables

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

Carter, Emily A

2013-02-02

Kohn-Sham density functional theory (DFT) is a powerful, well-established tool for the study of condensed phase electronic structure. However, there are still a number of situations where its applicability is limited. The basic theme of our research is the development of first principles electronic structure approaches for condensed matter that goes beyond what can currently be done with standard implementations ofKohn-Sham DFT. Our efforts to this end have focused on two classes or' methods. The first addresses the well-lmown inability of DFT to handle strong, many-body electron correlation effects. Our approach is a DFT -based embedding theory, to treat localizedmore » features (e.g. impurity, adsorbate, vacancy, etc.) embedded in a periodic, metallic crystal. A description for the embedded region is provided by explicitly correlated, ab initio wave function methods. DFT, as a fo1n1ally ground state theory, does not give a good description of excited states; an additional feature of our approach is the ability to obtain excitations localized in this region. We apply our method to a first-principles study of the adsorption of a single magnetic Co ada tom on non-magnetic Cu( 111 ), a known Kondo system whose behavior is governed by strong electron correlation. The second class of methods that we are developing is an orbital-free density functional theory (OFDFT), which addresses the speed limitations ofKohn-Sham DFT. OFDFT is a powerful, O(N) scaling method for electronic structure calculations. Unlike Kohn-Sham DFT, OFDFT goes back to the original Hohenberg-Kohn idea of directly optimizing an energy functional which is an explicit functional of the density, without invoking an orbital description. This eliminates the need to manipulate orbitals, which leads to O(N{sup 3}) scaling in the Kahn-Sham approach. The speed of OFDFT allows direct electronic structure calculations on large systems on the order of thousands to tens of thousands of atoms, an expensive feat within Kohn-Sham. Due to our incomplete knowledge of the exact, universal energy density functional, this speedup comes at the cost of some accuracy with respect to Kohn-Sham methods. However, OFDFT has been shown to be remarkably accurate with respect to Kohn-Sham when used in the study of nearly-free-electron-like metals, e.g., AI, for which good density functionals have been derived. Examples of past applications of OFDFT include the prediction of properties of bulk crystals, surfaces, vacancies, vacancy clusters, nanoclusters, and dislocations, as well as OFDFT -based multiscale simulations of nanoindentation in AI and Al-Mg alloys.« less

Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization.

PubMed

Neustetter, M; Jabbour Al Maalouf, E; Limão-Vieira, P; Denifl, S

2016-08-07

Electron ionization of neat tungsten hexacarbonyl (W(CO)6) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO)6 clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO)n (+) (0 ≤ n ≤ 6) and W2(CO)n (+) (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO)n (+) (0 ≤ n ≤ 3) and W2C(CO)n (+) (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.

Rigidity of transmembrane proteins determines their cluster shape

NASA Astrophysics Data System (ADS)

Jafarinia, Hamidreza; Khoshnood, Atefeh; Jalali, Mir Abbas

2016-01-01

Protein aggregation in cell membrane is vital for the majority of biological functions. Recent experimental results suggest that transmembrane domains of proteins such as α -helices and β -sheets have different structural rigidities. We use molecular dynamics simulation of a coarse-grained model of protein-embedded lipid membranes to investigate the mechanisms of protein clustering. For a variety of protein concentrations, our simulations under thermal equilibrium conditions reveal that the structural rigidity of transmembrane domains dramatically affects interactions and changes the shape of the cluster. We have observed stable large aggregates even in the absence of hydrophobic mismatch, which has been previously proposed as the mechanism of protein aggregation. According to our results, semiflexible proteins aggregate to form two-dimensional clusters, while rigid proteins, by contrast, form one-dimensional string-like structures. By assuming two probable scenarios for the formation of a two-dimensional triangular structure, we calculate the lipid density around protein clusters and find that the difference in lipid distribution around rigid and semiflexible proteins determines the one- or two-dimensional nature of aggregates. It is found that lipids move faster around semiflexible proteins than rigid ones. The aggregation mechanism suggested in this paper can be tested by current state-of-the-art experimental facilities.

A Photometrically Detected Forming Cluster of Galaxies at Redshift 1.6 in the GOODS Field

NASA Astrophysics Data System (ADS)

Castellano, M.; Salimbeni, S.; Trevese, D.; Grazian, A.; Pentericci, L.; Fiore, F.; Fontana, A.; Giallongo, E.; Santini, P.; Cristiani, S.; Nonino, M.; Vanzella, E.

2007-12-01

We report the discovery of a localized overdensity at z~1.6 in the GOODS-South field, presumably a poor cluster in the process of formation. The three-dimensional galaxy density has been estimated on the basis of well-calibrated photometric redshifts from the multiband photometric GOODS-MUSIC catalog using the (2+1)-dimensional technique. The density peak is embedded in the larger scale overdensity of galaxies known to exist at z=1.61 in the area. The properties of the member galaxies are compared to those of the surrounding field, and we find that the two populations are significantly different, supporting the reality of the structure. The reddest galaxies, once evolved according to their best-fit models, have colors consistent with the red sequence of lower redshift clusters. The estimated M200 total mass of the cluster is in the range 1.3×1014-5.7×1014 Msolar, depending on the assumed bias factor b. An upper limit for the 2-10 keV X-ray luminosity, based on the 1 Ms Chandra observations, is LX=0.5×1043 erg s-1, suggesting that the cluster has not yet reached the virial equilibrium.

Cluster Formation of Anchored Proteins Induced by Membrane-Mediated Interaction

PubMed Central

Li, Shuangyang; Zhang, Xianren; Wang, Wenchuan

2010-01-01

Abstract Computer simulations were used to study the cluster formation of anchored proteins in a membrane. The rate and extent of clustering was found to be dependent upon the hydrophobic length of the anchored proteins embedded in the membrane. The cluster formation mechanism of anchored proteins in our work was ascribed to the different local perturbations on the upper and lower monolayers of the membrane and the intermonolayer coupling. Simulation results demonstrated that only when the penetration depth of anchored proteins was larger than half the membrane thickness, could the structure of the lower monolayer be significantly deformed. Additionally, studies on the local structures of membranes indicated weak perturbation of bilayer thickness for a shallowly inserted protein, while there was significant perturbation for a more deeply inserted protein. The origin of membrane-mediated protein-protein interaction is therefore due to the local perturbation of the membrane thickness, and the entropy loss—both of which are caused by the conformation restriction on the lipid chains and the enhanced intermonolayer coupling for a deeply inserted protein. Finally, in this study we addressed the difference of cluster formation mechanisms between anchored proteins and transmembrane proteins. PMID:20513399

Dehydration, Dehydrogenation, and Condensation of Alcohols on Supported Oxide Catalysts Based on Cyclic (WO3)3 and (MoO3)3 Clusters

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

Rousseau, Roger J.; Dixon, David A.; Kay, Bruce D.

2014-01-01

Supported early transition metal oxides have important applications in numerous catalytic reactions. In this article we review preparation and activity of well-defined model WO3 and MoO3 catalysts prepared via deposition of cyclic gas-phase (WO3)3 and (MoO3)3 clusters generated by sublimation of WO3 and MoO3 powders. Conversion of small aliphatic alcohols to alkenes, aldehydes/ketons, and ethers is employed to probe the structure-activity relationships on model WO3 and MoO3 catalysts ranging from unsupported (WO3)3 and (MoO3)3 clusters embedded in alcohol matrices, to (WO3)3 clusters supported on surfaces of other oxides, and epitaxial and nanoporous WO3 films. Detailed theoretical calculations reveal the underlyingmore » reaction mechanisms and provide insight into the origin of the differences in the WO3 and MoO3 reactivity. For the range of interrogated (WO3)3 they further shed light into the role structure and binding of (WO3)3 clusters with the support play in determining their catalytic activity.« less

Ab initio model potential calculations on the electronic spectrum of Ni2 + -doped MgO including correlation, spin-orbit and embedding effects

NASA Astrophysics Data System (ADS)

Llusar, Rosa; Casarrubios, Marcos; Barandiarán, Zoila; Seijo, Luis

1996-10-01

An ab initio theoretical study of the optical absorption spectrum of Ni2+-doped MgO has been conducted by means of calculations in a MgO-embedded (NiO6)10-cluster. The calculations include long- and short-range embedding effects of electrostatic and quantum nature brought about by the MgO crystalline lattice, as well as electron correlation and spin-orbit effects within the (NiO6)10- cluster. The spin-orbit calculations have been performed using the spin-orbit-CI WB-AIMP method [Chem. Phys. Lett. 147, 597 (1988); J. Chem. Phys. 102, 8078 (1995)] which has been recently proposed and is applied here for the first time to the field of impurities in crystals. The WB-AIMP method is extended in order to handle correlation effects which, being necessary to produce accurate energy differences between spin-free states, are not needed for the proper calculation of spin-orbit couplings. The extension of the WB-AIMP method, which is also aimed at keeping the size of the spin-orbit-CI within reasonable limits, is based on the use of spin-free-state shifting operators. It is shown that the unreasonable spin-orbit splittings obtained for MgO:Ni2+ in spin-orbit-CI calculations correlating only 8 electrons become correct when the proposed extension is applied, so that the same CI space is used but energy corrections due to correlating up to 26 electrons are included. The results of the ligand field spectrum of MgO:Ni2+ show good overall agreement with the experimental measurements and a reassignment of the observed Eg(b3T1g) excited state is proposed and discussed.

Nonschematic drawing recognition: a new approach based on attributed graph grammar with flexible embedding

NASA Astrophysics Data System (ADS)

Lee, Kyu J.; Kunii, T. L.; Noma, T.

1993-01-01

In this paper, we propose a syntactic pattern recognition method for non-schematic drawings, based on a new attributed graph grammar with flexible embedding. In our graph grammar, the embedding rule permits the nodes of a guest graph to be arbitrarily connected with the nodes of a host graph. The ambiguity caused by this flexible embedding is controlled with the evaluation of synthesized attributes and the check of context sensitivity. To integrate parsing with the synthesized attribute evaluation and the context sensitivity check, we also develop a bottom up parsing algorithm.

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

McDonald, M.; Allen, S. W.; Bayliss, M.

We present the results of a Chandra X-ray survey of the 8 most massive galaxy clusters at z>1.2 in the South Pole Telescope 2500 deg^2 survey. We combine this sample with previously-published Chandra observations of 49 massive X-ray-selected clusters at 00.2R500 scaling like E(z)^2. In the centers of clusters (r<0.1R500), we find significant deviations from self similarity (n_e ~ E(z)^{0.1+/-0.5}), consistent with no redshift dependence. When we isolate clusters with over-dense cores (i.e., cool cores), we find that the average over-density profile has not evolved with redshift -- that is, cool cores have not changed in size, density, or totalmore » mass over the past ~9-10 Gyr. We show that the evolving "cuspiness" of clusters in the X-ray, reported by several previous studies, can be understood in the context of a cool core with fixed properties embedded in a self similarly-evolving cluster. We find no measurable evolution in the X-ray morphology of massive clusters, seemingly in tension with the rapidly-rising (with redshift) rate of major mergers predicted by cosmological simulations. We show that these two results can be brought into agreement if we assume that the relaxation time after a merger is proportional to the crossing time, since the latter is proportional to H(z)^(-1).« less

Numerical analysis of the vibroacoustic properties of plates with embedded grids of acoustic black holes.

PubMed

Conlon, Stephen C; Fahnline, John B; Semperlotti, Fabio

2015-01-01

The concept of an Acoustic Black Hole (ABH) has been developed and exploited as an approach for passively attenuating structural vibration. The basic principle of the ABH relies on proper tailoring of the structure geometrical properties in order to produce a gradual reduction of the flexural wave speed, theoretically approaching zero. For practical systems the idealized "zero" wave speed condition cannot be achieved so the structural areas of low wave speed are treated with surface damping layers to allow the ABH to approach the idealized dissipation level. In this work, an investigation was conducted to assess the effects that distributions of ABHs embedded in plate-like structures have on both vibration and structure radiated sound, focusing on characterizing and improving low frequency performance. Finite Element and Boundary Element models were used to assess the vibration response and radiated sound power performance of several plate configurations, comparing baseline uniform plates with embedded periodic ABH designs. The computed modal loss factors showed the importance of the ABH unit cell low order modes in the overall vibration reduction effectiveness of the embedded ABH plates at low frequencies where the free plate bending wavelengths are longer than the scale of the ABH.

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

A spatial multi-objective optimization model for sustainable urban wastewater system layout planning.

PubMed

Dong, X; Zeng, S; Chen, J

2012-01-01

Design of a sustainable city has changed the traditional centralized urban wastewater system towards a decentralized or clustering one. Note that there is considerable spatial variability of the factors that affect urban drainage performance including urban catchment characteristics. The potential options are numerous for planning the layout of an urban wastewater system, which are associated with different costs and local environmental impacts. There is thus a need to develop an approach to find the optimal spatial layout for collecting, treating, reusing and discharging the municipal wastewater of a city. In this study, a spatial multi-objective optimization model, called Urban wastewateR system Layout model (URL), was developed. It is solved by a genetic algorithm embedding Monte Carlo sampling and a series of graph algorithms. This model was illustrated by a case study in a newly developing urban area in Beijing, China. Five optimized system layouts were recommended to the local municipality for further detailed design.

Efficient design of clinical trials and epidemiological research: is it possible?

PubMed

Lauer, Michael S; Gordon, David; Wei, Gina; Pearson, Gail

2017-08-01

Randomized clinical trials and large-scale, cohort studies continue to have a critical role in generating evidence in cardiovascular medicine; however, the increasing concern is that ballooning costs threaten the clinical trial enterprise. In this Perspectives article, we discuss the changing landscape of clinical research, and clinical trials in particular, focusing on reasons for the increasing costs and inefficiencies. These reasons include excessively complex design, overly restrictive inclusion and exclusion criteria, burdensome regulations, excessive source-data verification, and concerns about the effect of clinical research conduct on workflow. Thought leaders have called on the clinical research community to consider alternative, transformative business models, including those models that focus on simplicity and leveraging of digital resources. We present some examples of innovative approaches by which some investigators have successfully conducted large-scale, clinical trials at relatively low cost. These examples include randomized registry trials, cluster-randomized trials, adaptive trials, and trials that are fully embedded within digital clinical care or administrative platforms.

Direct Integration of Red-NIR Emissive Ceramic-like An M6 Xi8 Xa6 Metal Cluster Salts in Organic Copolymers Using Supramolecular Interactions.

PubMed

Robin, Malo; Dumait, Noée; Amela-Cortes, Maria; Roiland, Claire; Harnois, Maxime; Jacques, Emmanuel; Folliot, Hervé; Molard, Yann

2018-04-03

Hybrid nanomaterials made of inorganic nanocomponents dispersed in an organic host raise an increasing interest as low-cost solution-processable functional materials. However, preventing phase segregation while allowing a high inorganic doping content remains a major challenge, and usual methods require a functionalization step prior integration. Herein, we report a new approach to design such nanocomposite in which ceramic-like metallic nanocluster compounds are embedded at 10 wt % in organic copolymers, without any functionalization. Dispersion homogeneity and stability are ensured by weak interactions occurring between the copolymer lateral chains and the nanocluster compound. Hybrids could be ink-jet printed and casted on a blue LED. This proof-of-concept device emits in the red-NIR area and generates singlet oxygen, O 2 ( 1 Δg), of particular interest for lights, display, sensors or photodynamic based therapy applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Full-potential KKR calculations for vacancies in Al : Screening effect and many-body interactions

NASA Astrophysics Data System (ADS)

Hoshino, T.; Asato, M.; Zeller, R.; Dederichs, P. H.

2004-09-01

We give ab initio calculations for vacancies in Al . The calculations are based on the generalized-gradient approximation in the density-functional theory and employ the all-electron full-potential Korringa-Kohn-Rostoker Green’s function method for point defects, which guarantees the correct embedding of the cluster of point defects in an otherwise perfect crystal. First, we confirm the recent calculated results of Carling [Phys. Rev. Lett. 85, 3862 (2000)], i.e., repulsion of the first-nearest-neighbor (1NN) divacancy in Al , and elucidate quantitatively the micromechanism of repulsion. Using the calculated results for vacancy formation energies and divacancy binding energies in Na , Mg , Al , and Si of face-centered-cubic, we show that the single vacancy in nearly free-electron systems becomes very stable with increasing free-electron density, due to the screening effect, and that the formation of divacancy destroys the stable electron distribution around the single vacancy, resulting in a repulsion of two vacancies on 1NN sites, so that the 1NN divacancy is unstable. Second, we show that the cluster expansion converges rapidly for the binding energies of vacancy agglomerates in Al . The binding energy of 13 vacancies consisting of a central vacancy and its 12 nearest neighbors, is reproduced within the error of 0.002eV per vacancy, if many-body interaction energies up to the four-body terms are taken into account in the cluster expansion, being compared with the average error (>0.1eV) of the glue models which are very often used to provide interatomic potentials for computer simulations. For the cluster expansion of the binding energies of impurities, we get the same convergence as that obtained for vacancies. Thus, the present cluster-expansion approach for the binding energies of agglomerates of vacancies and impurities in Al may provide accurate data to construct the interaction-parameter model for computer simulations which are strongly requested to study the dynamical process in the initial stage of the formation of the so-called Guinier-Preston zones of low-concentrated Al -based alloys such as Al1-cXc ( X=Cu , Zn ; c<0.05 ).

A possibilistic approach to clustering

NASA Technical Reports Server (NTRS)

Krishnapuram, Raghu; Keller, James M.

1993-01-01

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Embedded security system for multi-modal surveillance in a railway carriage

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Audigier, Romaric; Ambellouis, Sébastien; Capman, François; Benhadda, Hamid; Joudrier, Stéphanie; Sodoyer, David; Lamarque, Thierry

2015-10-01

Public transport security is one of the main priorities of the public authorities when fighting against crime and terrorism. In this context, there is a great demand for autonomous systems able to detect abnormal events such as violent acts aboard passenger cars and intrusions when the train is parked at the depot. To this end, we present an innovative approach which aims at providing efficient automatic event detection by fusing video and audio analytics and reducing the false alarm rate compared to classical stand-alone video detection. The multi-modal system is composed of two microphones and one camera and integrates onboard video and audio analytics and fusion capabilities. On the one hand, for detecting intrusion, the system relies on the fusion of "unusual" audio events detection with intrusion detections from video processing. The audio analysis consists in modeling the normal ambience and detecting deviation from the trained models during testing. This unsupervised approach is based on clustering of automatically extracted segments of acoustic features and statistical Gaussian Mixture Model (GMM) modeling of each cluster. The intrusion detection is based on the three-dimensional (3D) detection and tracking of individuals in the videos. On the other hand, for violent events detection, the system fuses unsupervised and supervised audio algorithms with video event detection. The supervised audio technique detects specific events such as shouts. A GMM is used to catch the formant structure of a shout signal. Video analytics use an original approach for detecting aggressive motion by focusing on erratic motion patterns specific to violent events. As data with violent events is not easily available, a normality model with structured motions from non-violent videos is learned for one-class classification. A fusion algorithm based on Dempster-Shafer's theory analyses the asynchronous detection outputs and computes the degree of belief of each probable event.

Imparting functionality to biocatalysts via embedding enzymes into nanoporous materials by a de novo approach: size-selective sheltering of catalase in metal-organic framework microcrystals.

PubMed

Shieh, Fa-Kuen; Wang, Shao-Chun; Yen, Chia-I; Wu, Chang-Cheng; Dutta, Saikat; Chou, Lien-Yang; Morabito, Joseph V; Hu, Pan; Hsu, Ming-Hua; Wu, Kevin C-W; Tsung, Chia-Kuang

2015-04-08

We develop a new concept to impart new functions to biocatalysts by combining enzymes and metal-organic frameworks (MOFs). The proof-of-concept design is demonstrated by embedding catalase molecules into uniformly sized ZIF-90 crystals via a de novo approach. We have carried out electron microscopy, X-ray diffraction, nitrogen sorption, electrophoresis, thermogravimetric analysis, and confocal microscopy to confirm that the ~10 nm catalase molecules are embedded in 2 μm single-crystalline ZIF-90 crystals with ~5 wt % loading. Because catalase is immobilized and sheltered by the ZIF-90 crystals, the composites show activity in hydrogen peroxide degradation even in the presence of protease proteinase K.

Real time UNIX in embedded control -- A case study within context of LynxOS

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

Kleines, H.; Zwoll, K.

1996-02-01

Intelligent communication controllers for a layered protocol profile are a typical example of an embedded control application, where the classical approach for the software development is based on a proprietary real-time operating system kernel under which the individual layers are implemented as tasks. Based on the exemplary implementation of a derivative of MAP 3.0, an unusual and innovative approach is presented, where the protocol software is implemented under the UNIX-compatible real-time operating system LynxOS. The overall design of the embedded control application is presented under a more general view and economical implications as well as aspects of the development environmentmore » and performance are discussed.« less

Cluster ensemble based on Random Forests for genetic data.

PubMed

Alhusain, Luluah; Hafez, Alaaeldin M

2017-01-01

Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data. One application is population structure analysis, which aims to group individuals into subpopulations based on shared genetic variations, such as single nucleotide polymorphisms. Advances in DNA sequencing technology have facilitated the obtainment of genetic datasets with exceptional sizes. Genetic data usually contain hundreds of thousands of genetic markers genotyped for thousands of individuals, making an efficient means for handling such data desirable. Random Forests (RFs) has emerged as an efficient algorithm capable of handling high-dimensional data. RFs provides a proximity measure that can capture different levels of co-occurring relationships between variables. RFs has been widely considered a supervised learning method, although it can be converted into an unsupervised learning method. Therefore, RF-derived proximity measure combined with a clustering technique may be well suited for determining the underlying structure of unlabeled data. This paper proposes, RFcluE, a cluster ensemble approach for determining the underlying structure of genetic data based on RFs. The approach comprises a cluster ensemble framework to combine multiple runs of RF clustering. Experiments were conducted on high-dimensional, real genetic dataset to evaluate the proposed approach. The experiments included an examination of the impact of parameter changes, comparing RFcluE performance against other clustering methods, and an assessment of the relationship between the diversity and quality of the ensemble and its effect on RFcluE performance. This paper proposes, RFcluE, a cluster ensemble approach based on RF clustering to address the problem of population structure analysis and demonstrate the effectiveness of the approach. The paper also illustrates that applying a cluster ensemble approach, combining multiple RF clusterings, produces more robust and higher-quality results as a consequence of feeding the ensemble with diverse views of high-dimensional genetic data obtained through bagging and random subspace, the two key features of the RF algorithm.

Benchmark fragment-based 1H, 13C, 15N and 17O chemical shift predictions in molecular crystals†

PubMed Central

Hartman, Joshua D.; Kudla, Ryan A.; Day, Graeme M.; Mueller, Leonard J.; Beran, Gregory J. O.

2016-01-01

The performance of fragment-based ab initio 1H, 13C, 15N and 17O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. 1H, 13C, 15N, and 17O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same 1H, 13C, 15N, and 17O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tertbutyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2. PMID:27431490

Benchmark fragment-based (1)H, (13)C, (15)N and (17)O chemical shift predictions in molecular crystals.

PubMed

Hartman, Joshua D; Kudla, Ryan A; Day, Graeme M; Mueller, Leonard J; Beran, Gregory J O

2016-08-21

The performance of fragment-based ab initio(1)H, (13)C, (15)N and (17)O chemical shift predictions is assessed against experimental NMR chemical shift data in four benchmark sets of molecular crystals. Employing a variety of commonly used density functionals (PBE0, B3LYP, TPSSh, OPBE, PBE, TPSS), we explore the relative performance of cluster, two-body fragment, and combined cluster/fragment models. The hybrid density functionals (PBE0, B3LYP and TPSSh) generally out-perform their generalized gradient approximation (GGA)-based counterparts. (1)H, (13)C, (15)N, and (17)O isotropic chemical shifts can be predicted with root-mean-square errors of 0.3, 1.5, 4.2, and 9.8 ppm, respectively, using a computationally inexpensive electrostatically embedded two-body PBE0 fragment model. Oxygen chemical shieldings prove particularly sensitive to local many-body effects, and using a combined cluster/fragment model instead of the simple two-body fragment model decreases the root-mean-square errors to 7.6 ppm. These fragment-based model errors compare favorably with GIPAW PBE ones of 0.4, 2.2, 5.4, and 7.2 ppm for the same (1)H, (13)C, (15)N, and (17)O test sets. Using these benchmark calculations, a set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided and their robustness assessed using statistical cross-validation. We demonstrate the utility of these approaches and the reported scaling parameters on applications to 9-tert-butyl anthracene, several histidine co-crystals, benzoic acid and the C-nitrosoarene SnCl2(CH3)2(NODMA)2.

Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks.

PubMed

Grimes, Mark; Hall, Benjamin; Foltz, Lauren; Levy, Tyler; Rikova, Klarisa; Gaiser, Jeremiah; Cook, William; Smirnova, Ekaterina; Wheeler, Travis; Clark, Neil R; Lachmann, Alexander; Zhang, Bin; Hornbeck, Peter; Ma'ayan, Avi; Comb, Michael

2018-05-22

Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive "OR" gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein-mediated control of gene expression. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

A genetic graph-based approach for partitional clustering.

PubMed

Menéndez, Héctor D; Barrero, David F; Camacho, David

2014-05-01

Clustering is one of the most versatile tools for data analysis. In the recent years, clustering that seeks the continuity of data (in opposition to classical centroid-based approaches) has attracted an increasing research interest. It is a challenging problem with a remarkable practical interest. The most popular continuity clustering method is the spectral clustering (SC) algorithm, which is based on graph cut: It initially generates a similarity graph using a distance measure and then studies its graph spectrum to find the best cut. This approach is sensitive to the parameters of the metric, and a correct parameter choice is critical to the quality of the cluster. This work proposes a new algorithm, inspired by SC, that reduces the parameter dependency while maintaining the quality of the solution. The new algorithm, named genetic graph-based clustering (GGC), takes an evolutionary approach introducing a genetic algorithm (GA) to cluster the similarity graph. The experimental validation shows that GGC increases robustness of SC and has competitive performance in comparison with classical clustering methods, at least, in the synthetic and real dataset used in the experiments.

Panchromatic observations of dwarf starburst galaxies: Infant super star clusters and a low-luminosity AGN

NASA Astrophysics Data System (ADS)

Reines, Amy Ellen

2011-01-01

Globular star clusters and supermassive black holes are fundamental components of today's massive galaxies, with origins dating back to the very early universe. Both globular clusters and the seeds of supermassive black holes are believed to have formed in the progenitors of modern massive galaxies, although the details are poorly understood. Direct observations of these low-mass, distant, and hence faint systems are unobtainable with current capabilities. However, gas-rich dwarf starburst galaxies in the local universe, analogous in many ways to protogalaxies at high-redshift, can provide critical insight into the early stages of galaxy evolution including the formation of globular clusters and massive black holes. This thesis presents a panchromatic study of nearby dwarf starburst galaxies harboring nascent globular clusters still embedded in their birth material. Infant clusters are identified via their production of thermal radio emission at centimeter wavelengths, which comes from dense gas ionized by young massive stars. By combining radio observations with complementary data at ultraviolet, optical and infrared wavelengths, we obtain a comprehensive view of massive clusters emerging from their gaseous and dusty birth cocoons. This thesis also presents the first example of a nearby dwarf starburst galaxy hosting an actively accreting massive central black hole. The black hole in this dwarf galaxy is unusual in that it is not associated with a bulge, a nuclear star cluster, or any other well-defined nucleus, likely reflecting an early phase of black hole and galaxy evolution that has not been previously observed.

AGES OF STAR CLUSTERS IN THE TIDAL TAILS OF MERGING GALAXIES

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

Mulia, A. J.; Chandar, R.; Whitmore, B. C.

We study the stellar content in the tidal tails of three nearby merging galaxies, NGC 520, NGC 2623, and NGC 3256, using BVI imaging taken with the Advanced Camera for Surveys on board the Hubble Space Telescope. The tidal tails in all three systems contain compact and fairly massive young star clusters, embedded in a sea of diffuse, unresolved stellar light. We compare the measured colors and luminosities with predictions from population synthesis models to estimate cluster ages and find that clusters began forming in tidal tails during or shortly after the formation of the tails themselves. We find amore » lack of very young clusters (≤10 Myr old), implying that eventually star formation shuts off in the tails as the gas is used up or dispersed. There are a few clusters in each tail with estimated ages that are older than the modeled tails themselves, suggesting that these may have been stripped out from the original galaxy disks. The luminosity function of the tail clusters can be described by a single power-law, dN/dL ∝ L{sup α}, with −2.6 < α < −2.0. We find a stellar age gradient across some of the tidal tails, which we interpret as a superposition of (1) newly formed stars and clusters along the dense center of the tail and (2) a sea of broadly distributed, older stellar material ejected from the progenitor galaxies.« less

The Remarkable Similarity of Massive Galaxy Clusters from z ~ 0 to z ~ 1.9

DOE PAGES

McDonald, M.; Allen, S. W.; Bayliss, M.; ...

2017-06-28

We present the results of a Chandra X-ray survey of the 8 most massive galaxy clusters at z>1.2 in the South Pole Telescope 2500 deg^2 survey. We combine this sample with previously-published Chandra observations of 49 massive X-ray-selected clusters at 00.2R500 scaling like E(z)^2. In the centers of clusters (r<0.1R500), we find significant deviations from self similarity (n_e ~ E(z)^{0.1+/-0.5}), consistent with no redshift dependence. When we isolate clusters with over-dense cores (i.e., cool cores), we find that the average over-density profile has not evolved with redshift -- that is, cool cores have not changed in size, density, or totalmore » mass over the past ~9-10 Gyr. We show that the evolving "cuspiness" of clusters in the X-ray, reported by several previous studies, can be understood in the context of a cool core with fixed properties embedded in a self similarly-evolving cluster. We find no measurable evolution in the X-ray morphology of massive clusters, seemingly in tension with the rapidly-rising (with redshift) rate of major mergers predicted by cosmological simulations. We show that these two results can be brought into agreement if we assume that the relaxation time after a merger is proportional to the crossing time, since the latter is proportional to H(z)^(-1).« less

Connecting the small scale to the large scale: young massive stars and their environments from the Red MSX Source Survey.

NASA Astrophysics Data System (ADS)

Figura, Charles C.; Urquhart, James S.; Morgan, Lawrence

2015-01-01

We have conducted a detailed multi-wavelength investigation of a variety of massive star forming regions in order to characterise the impact of the interactions between the substructure of the dense protostellar clumps and their local environment, including feedback from the embedded proto-cluster.A selection of 70 MYSOs and HII regions identified by the RMS survey have been followed up with observations of the ammonia (1,1) and (2,2) inversion transitions made with the KFPA on the GBT. These maps have been combined with archival CO data to investigate the thermal and kinematic structure of the extended envelopes down to the dense clumps. We complement this larger-scale picture with high resolution near- and mid-infrared images to probe the properties of the embedded objects themselves.We present an overview of several sources from this sample that illustrate some of the the interactions that we observe. We find that high molecular column densities and kinetic temperatures are coincident with embedded sources and with shocks and outflows as exhibited in gas kinematics.

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

Olshevsky, Vyacheslav; Lapenta, Giovanni; Divin, Andrey

We use kinetic particle-in-cell and MHD simulations supported by an observational data set to investigate magnetic reconnection in clusters of null points in space plasma. The magnetic configuration under investigation is driven by fast adiabatic flux rope compression that dissipates almost half of the initial magnetic field energy. In this phase powerful currents are excited producing secondary instabilities, and the system is brought into a state of “intermittent turbulence” within a few ion gyro-periods. Reconnection events are distributed all over the simulation domain and energy dissipation is rather volume-filling. Numerous spiral null points interconnected via their spines form null linesmore » embedded into magnetic flux ropes; null point pairs demonstrate the signatures of torsional spine reconnection. However, energy dissipation mainly happens in the shear layers formed by adjacent flux ropes with oppositely directed currents. In these regions radial null pairs are spontaneously emerging and vanishing, associated with electron streams and small-scale current sheets. The number of spiral nulls in the simulation outweighs the number of radial nulls by a factor of 5–10, in accordance with Cluster observations in the Earth's magnetosheath. Twisted magnetic fields with embedded spiral null points might indicate the regions of major energy dissipation for future space missions such as the Magnetospheric Multiscale Mission.« less

Developing a New Wireless Sensor Network Platform and Its Application in Precision Agriculture

PubMed Central

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of “smart dust” offer great advantages due to their small size, low power consumption, easy integration and support for “green” applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network. PMID:22346622

Developing a new wireless sensor network platform and its application in precision agriculture.

PubMed

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of "smart dust" offer great advantages due to their small size, low power consumption, easy integration and support for "green" applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network.

Collaboration patterns in the German political science co-authorship network.

PubMed

Leifeld, Philip; Wankmüller, Sandra; Berger, Valentin T Z; Ingold, Karin; Steiner, Christiane

2017-01-01

Research on social processes in the production of scientific output suggests that the collective research agenda of a discipline is influenced by its structural features, such as "invisible colleges" or "groups of collaborators" as well as academic "stars" that are embedded in, or connect, these research groups. Based on an encompassing dataset that takes into account multiple publication types including journals and chapters in edited volumes, we analyze the complete co-authorship network of all 1,339 researchers in German political science. Through the use of consensus graph clustering techniques and descriptive centrality measures, we identify the ten largest research clusters, their research topics, and the most central researchers who act as bridges and connect these clusters. We also aggregate the findings at the level of research organizations and consider the inter-university co-authorship network. The findings indicate that German political science is structured by multiple overlapping research clusters with a dominance of the subfields of international relations, comparative politics and political sociology. A small set of well-connected universities takes leading roles in these informal research groups.

Collaboration patterns in the German political science co-authorship network

PubMed Central

Wankmüller, Sandra; Berger, Valentin T. Z.; Ingold, Karin; Steiner, Christiane

2017-01-01

Research on social processes in the production of scientific output suggests that the collective research agenda of a discipline is influenced by its structural features, such as “invisible colleges” or “groups of collaborators” as well as academic “stars” that are embedded in, or connect, these research groups. Based on an encompassing dataset that takes into account multiple publication types including journals and chapters in edited volumes, we analyze the complete co-authorship network of all 1,339 researchers in German political science. Through the use of consensus graph clustering techniques and descriptive centrality measures, we identify the ten largest research clusters, their research topics, and the most central researchers who act as bridges and connect these clusters. We also aggregate the findings at the level of research organizations and consider the inter-university co-authorship network. The findings indicate that German political science is structured by multiple overlapping research clusters with a dominance of the subfields of international relations, comparative politics and political sociology. A small set of well-connected universities takes leading roles in these informal research groups. PMID:28388621

On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model

NASA Astrophysics Data System (ADS)

Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin

2018-01-01

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.

Thermodynamic Behavior of Nano-sized Gold Clusters on the (001) Surface

NASA Technical Reports Server (NTRS)

Paik, Sun M.; Yoo, Sung M.; Namkung, Min; Wincheski, Russell A.; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

We have studied thermal expansion of the surface layers of the hexagonally reconstructed Au (001) surface using a classical Molecular Dynamics (MD) simulation technique with an Embedded Atomic Method (EAM) type many-body potential. We find that the top-most hexagonal layer contracts as temperature increases, whereas the second layer expands or contracts depending on the system size. The magnitude of expansion coefficient of the top layer is much larger than that of the other layers. The calculated thermal expansion coefficients of the top-most layer are about -4.93 x 10(exp -5)Angstroms/Kelvin for the (262 x 227)Angstrom cluster and -3.05 x 10(exp -5)Angstroms/Kelvin for (101 x 87)Angstrom cluster. The Fast Fourier Transform (FFT) image of the atomic density shows that there exists a rotated domain of the top-most hexagonal cluster with rotation angle close to 1 degree at temperature T less than 1000Kelvin. As the temperature increases this domain undergoes a surface orientational phase transition. These predictions are in good agreement with previous phenomenological theories and experimental studies.

Accessing the Vibrational Signatures of Amino Acid Ions Embedded in Water Clusters

DOE PAGES

Voss, Jonathan M.; Fischer, Kaitlyn C.; Garand, Etienne

2018-04-16

We present an infrared predissociation (IRPD) study of microsolvated GlyH +(H 2O) n and GlyH +(D 2O) n clusters, formed inside of a cryogenic ion trap via condensation of H 2O or D 2O onto the protonated glycine ions. The resulting IRPD spectra, showing characteristic O–H and O–D stretches, indicate that H/D exchange reactions are quenched when the ion trap is held at 80 K, minimizing the presence of isotopomers. Comparisons of GlyH +(H 2O) n and GlyH +(D 2O) n spectra clearly highlight and distinguish the vibrational signatures of the water solvent molecules from those of the core GlyHmore » + ion, allowing for quick assessment of solvation structures. Without the aid of calculations, we can already infer solvation motifs and the presence of multiple conformations. Furthermore, the use of a cryogenic ion trap to cluster solvent molecules around ions of interest and control H/D exchange reactions is broadly applicable and should be extendable to studies of more complex peptidic ions in large solvated clusters.« less

Accessing the Vibrational Signatures of Amino Acid Ions Embedded in Water Clusters

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

Voss, Jonathan M.; Fischer, Kaitlyn C.; Garand, Etienne

We present an infrared predissociation (IRPD) study of microsolvated GlyH +(H 2O) n and GlyH +(D 2O) n clusters, formed inside of a cryogenic ion trap via condensation of H 2O or D 2O onto the protonated glycine ions. The resulting IRPD spectra, showing characteristic O–H and O–D stretches, indicate that H/D exchange reactions are quenched when the ion trap is held at 80 K, minimizing the presence of isotopomers. Comparisons of GlyH +(H 2O) n and GlyH +(D 2O) n spectra clearly highlight and distinguish the vibrational signatures of the water solvent molecules from those of the core GlyHmore » + ion, allowing for quick assessment of solvation structures. Without the aid of calculations, we can already infer solvation motifs and the presence of multiple conformations. Furthermore, the use of a cryogenic ion trap to cluster solvent molecules around ions of interest and control H/D exchange reactions is broadly applicable and should be extendable to studies of more complex peptidic ions in large solvated clusters.« less

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Integrating powdered activated carbon into wastewater tertiary filter for micro-pollutant removal.

PubMed

Hu, Jingyi; Aarts, Annelies; Shang, Ran; Heijman, Bas; Rietveld, Luuk

2016-07-15

Integrating powdered activated carbon (PAC) into wastewater tertiary treatment is a promising technology to reduce organic micro-pollutant (OMP) discharge into the receiving waters. To take advantage of the existing tertiary filter, PAC was pre-embedded inside the filter bed acting as a fixed-bed adsorber. The pre-embedding (i.e. immobilization) of PAC was realized by direct dosing a PAC solution on the filter top, which was then promoted to penetrate into the filter media by a down-flow of tap water. In order to examine the effectiveness of this PAC pre-embedded filter towards OMP removal, batch adsorption tests, representing PAC contact reactor (with the same PAC mass-to-treated water volume ratio as in the PAC pre-embedded filter) were performed as references. Moreover, as a conventional dosing option, PAC was dosed continuously with the filter influent (i.e. the wastewater secondary effluent with the investigated OMPs). Comparative results confirmed a higher OMP removal efficiency associated with the PAC pre-embedded filter, as compared to the batch system with a practical PAC residence time. Furthermore, over a filtration period of 10 h (approximating a realistic filtration cycle for tertiary filters), the continuous dosing approach resulted in less OMP removal. Therefore, it was concluded that the pre-embedding approach can be preferentially considered when integrating PAC into the wastewater tertiary treatment for OMP elimination. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cluster randomized evaluation of Adolescent Girls Empowerment Programme (AGEP): study protocol.

PubMed

Hewett, Paul C; Austrian, Karen; Soler-Hampejsek, Erica; Behrman, Jere R; Bozzani, Fiammetta; Jackson-Hachonda, Natalie A

2017-05-05

Adolescents in less developed countries such as Zambia often face multi-faceted challenges for achieving successful transitions through adolescence to early adulthood. The literature has noted the need to introduce interventions during this period, particularly for adolescent girls, with the perspective that such investments have significant economic, social and health returns to society. The Adolescent Girls Empowerment Programme (AGEP) was an intervention designed as a catalyst for change for adolescent girls through themselves, to their family and community. AGEP was a multi-sectoral intervention targeting over 10,000 vulnerable adolescent girls ages 10-19 in rural and urban areas, in four of the ten provinces of Zambia. At the core of AGEP were mentor-led, weekly girls' group meetings of 20 to 30 adolescent girls participating over two years. Three curricula - sexual and reproductive health and lifeskills, financial literacy, and nutrition - guided the meetings. An engaging and participatory pedagogical approach was used. Two additional program components, a health voucher and a bank account, were offered to some girls to provide direct mechanisms to improve access to health and financial services. Embedded within AGEP was a rigorous multi-arm randomised cluster trial with randomization to different combinations of programme arms. The study was powered to assess the impact across a set of key longer-term outcomes, including early marriage and first birth, contraceptive use, educational attainment and acquisition of HIV and HSV-2. Baseline behavioural surveys and biological specimen collection were initiated in 2013. Impact was evaluated immediately after the program ended in 2015 and will be evaluated again after two additional years of follow-up in 2017. The primary analysis is intent-to-treat. Qualitative data are being collected in 2013, 2015 and 2017 to inform the programme implementation and the quantitative findings. An economic evaluation will evaluate the incremental cost-effectiveness of each component of the intervention. The AGEP program and embedded evaluation will provide detailed information regarding interventions for adolescent girls in developing country settings. It will provide a rich information and data source on adolescent girls and its related findings will inform policy-makers, health professionals, donors and other stakeholders. ISRCTN29322231 . March 04 2016; retrospectively registered.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

PubMed Central

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-01-01

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

Merging with the path not taken: Wilhelm Wundt's work as a precursor to the embedded-processes approach to memory, attention, and consciousness.

PubMed

Cowan, Nelson; Rachev, Nikolay R

2018-06-04

Early research on memory was dominated by two researchers forging different paths: Hermann Ebbinghaus, interested in principles of learning and recall, and Wilhelm Wundt, founder of the first formal laboratory of experimental psychology, who was interested in empirical evidence to interpret conscious experience. Whereas the work of Ebbinghaus is a much-heralded precursor of modern research on long-term memory, the work of Wundt appears to be a mostly-forgotten precursor to research on working memory. We show how his scientific perspective is germane to more recent investigations, with emphasis on the embedded-processes approaches of Nelson Cowan and Klaus Oberauer, and how it is in contrast with most other recent theoretical approaches. This investigation is important because the embedded-process theorists, apparently like most modern researchers, have recognized few of Wundt's specific contributions. We explore commonalities between the approaches and suggest that an appreciation of these commonalities might enrich the field going forward. Copyright © 2018 Elsevier Inc. All rights reserved.

Embedded high-contrast distributed grating structures

DOEpatents

Zubrzycki, Walter J.; Vawter, Gregory A.; Allerman, Andrew A.

2002-01-01

A new class of fabrication methods for embedded distributed grating structures is claimed, together with optical devices which include such structures. These new methods are the only known approach to making defect-free high-dielectric contrast grating structures, which are smaller and more efficient than are conventional grating structures.

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.

A Deep X-ray Survey of Low-Mass PMS Stars in NGC 2264

NASA Technical Reports Server (NTRS)

Simon, Theodore

2005-01-01

Two X-ray images were obtained with the XMM-Newton spacecraft of more than 300 members of the NGC 2264 Open Cluster and its associated molecular cloud in order to investigate their magnetic activity. The X-ray fluxes extracted from those observations were used to study the dependence of stellar dynamo activity upon age and rotation for the optically revealed T Tauri stars and to place empirical constraints on theoretical models of angular momentum/dynamo evolution. The observations were also used to study the role of magnetic fields in the formation of low mass stars through the observation of very young protostars that are deeply embedded in the molecular cloud located behind the visible open cluster.

DNS and Embedded DNS as Tools for Investigating Unsteady Heat Transfer Phenomena in Turbines

NASA Technical Reports Server (NTRS)

vonTerzi, Dominic; Bauer, H.-J.

2010-01-01

DNS is a powerful tool with high potential for investigating unsteady heat transfer and fluid flow phenomena, in particular for cases involving transition to turbulence and/or large coherent structures. - DNS of idealized configurations related to turbomachinery components is already possible. - For more realistic configurations and the inclusion of more effects, reduction of computational cost is key issue (e.g., hybrid methods). - Approach pursued here: Embedded DNS ( segregated coupling of DNS with LES and/or RANS). - Embedded DNS is an enabling technology for many studies. - Pre-transitional heat transfer and trailing-edge cutback film-cooling are good candidates for (embedded) DNS studies.

Measuring glomerular number from kidney MRI images

NASA Astrophysics Data System (ADS)

Thiagarajan, Jayaraman J.; Natesan Ramamurthy, Karthikeyan; Kanberoglu, Berkay; Frakes, David; Bennett, Kevin; Spanias, Andreas

2016-03-01

Measuring the glomerular number in the entire, intact kidney using non-destructive techniques is of immense importance in studying several renal and systemic diseases. Commonly used approaches either require destruction of the entire kidney or perform extrapolation from measurements obtained from a few isolated sections. A recent magnetic resonance imaging (MRI) method, based on the injection of a contrast agent (cationic ferritin), has been used to effectively identify glomerular regions in the kidney. In this work, we propose a robust, accurate, and low-complexity method for estimating the number of glomeruli from such kidney MRI images. The proposed technique has a training phase and a low-complexity testing phase. In the training phase, organ segmentation is performed on a few expert-marked training images, and glomerular and non-glomerular image patches are extracted. Using non-local sparse coding to compute similarity and dissimilarity graphs between the patches, the subspace in which the glomerular regions can be discriminated from the rest are estimated. For novel test images, the image patches extracted after pre-processing are embedded using the discriminative subspace projections. The testing phase is of low computational complexity since it involves only matrix multiplications, clustering, and simple morphological operations. Preliminary results with MRI data obtained from five kidneys of rats show that the proposed non-invasive, low-complexity approach performs comparably to conventional approaches such as acid maceration and stereology.

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2013-09-25

The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

Semantic Clustering of Search Engine Results

PubMed Central

Soliman, Sara Saad; El-Sayed, Maged F.; Hassan, Yasser F.

2015-01-01

This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision. PMID:26933673

A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

PubMed Central

Nguyen, Nha; Vo, An; Choi, Inchan

2015-01-01

Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

Hamiltonian vs Lagrangian Embedding of a Massive Spin-One Theory Involving Two-Form Field

NASA Astrophysics Data System (ADS)

Harikumar, E.; Sivakumar, M.

We consider the Hamiltonian and Lagrangian embedding of a first-order, massive spin-one, gauge noninvariant theory involving antisymmetric tensor field. We apply the BFV-BRST generalized canonical approach to convert the model to a first class system and construct nilpotent BFV-BRST charge and a unitarizing Hamiltonian. The canonical analysis of the Stückelberg formulation of this model is presented. We bring out the contrasting feature in the constraint structure, specifically with respect to the reducibility aspect, of the Hamiltonian and the Lagrangian embedded model. We show that to obtain manifestly covariant Stückelberg Lagrangian from the BFV embedded Hamiltonian, phase space has to be further enlarged and show how the reducible gauge structure emerges in the embedded model.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks.

PubMed

Gholami, Mohammad; Brennan, Robert W

2016-01-06

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.

A Comparison of Alternative Distributed Dynamic Cluster Formation Techniques for Industrial Wireless Sensor Networks

PubMed Central

Gholami, Mohammad; Brennan, Robert W.

2016-01-01

In this paper, we investigate alternative distributed clustering techniques for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on: (1) the development of a novel distributed management approach for tracking mobile nodes in an industrial wireless sensor network; and (2) an objective comparison of alternative cluster management approaches for wireless sensor networks. To perform this comparison, we focus on two main clustering approaches proposed in the literature: pre-defined clusters and ad hoc clusters. These approaches are compared in the context of their reconfigurability: more specifically, we investigate the trade-off between the cost and the effectiveness of competing strategies aimed at adapting to changes in the sensing environment. To support this work, we introduce three new metrics: a cost/efficiency measure, a performance measure, and a resource consumption measure. The results of our experiments show that ad hoc clusters adapt more readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency. PMID:26751447

Measurement of surface roughness changes of unpolished and polished enamel following erosion

PubMed Central

Austin, Rupert S.; Parkinson, Charles R.; Hasan, Adam; Bartlett, David W.

2017-01-01

Objectives To determine if Sa roughness data from measuring one central location of unpolished and polished enamel were representative of the overall surfaces before and after erosion. Methods Twenty human enamel sections (4x4 mm) were embedded in bis-acryl composite and randomised to either a native or polishing enamel preparation protocol. Enamel samples were subjected to an acid challenge (15 minutes 100 mL orange juice, pH 3.2, titratable acidity 41.3mmol OH/L, 62.5 rpm agitation, repeated for three cycles). Median (IQR) surface roughness [Sa] was measured at baseline and after erosion from both a centralised cluster and four peripheral clusters. Within each cluster, five smaller areas (0.04 mm2) provided the Sa roughness data. Results For both unpolished and polished enamel samples there were no significant differences between measuring one central cluster or four peripheral clusters, before and after erosion. For unpolished enamel the single central cluster had a median (IQR) Sa roughness of 1.45 (2.58) μm and the four peripheral clusters had a median (IQR) of 1.32 (4.86) μm before erosion; after erosion there were statistically significant reductions to 0.38 (0.35) μm and 0.34 (0.49) μm respectively (p<0.0001). Polished enamel had a median (IQR) Sa roughness 0.04 (0.17) μm for the single central cluster and 0.05 (0.15) μm for the four peripheral clusters which statistically significantly increased after erosion to 0.27 (0.08) μm for both (p<0.0001). Conclusion Measuring one central cluster of unpolished and polished enamel was representative of the overall enamel surface roughness, before and after erosion. PMID:28771562

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

NASA Astrophysics Data System (ADS)

Titantah, John T.; Karttunen, Mikko

2016-05-01

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

A Fast Implementation of the ISODATA Clustering Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mount, David M.; Netanyahu, Nathan S.; LeMoigne, Jacqueline

2005-01-01

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to ISODATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

A Fast Implementation of the Isodata Clustering Algorithm

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Le Moigne, Jacqueline; Mount, David M.; Netanyahu, Nathan S.

2007-01-01

Clustering is central to many image processing and remote sensing applications. ISODATA is one of the most popular and widely used clustering methods in geoscience applications, but it can run slowly, particularly with large data sets. We present a more efficient approach to IsoDATA clustering, which achieves better running times by storing the points in a kd-tree and through a modification of the way in which the algorithm estimates the dispersion of each cluster. We also present an approximate version of the algorithm which allows the user to further improve the running time, at the expense of lower fidelity in computing the nearest cluster center to each point. We provide both theoretical and empirical justification that our modified approach produces clusterings that are very similar to those produced by the standard ISODATA approach. We also provide empirical studies on both synthetic data and remotely sensed Landsat and MODIS images that show that our approach has significantly lower running times.

Composite anion-exchangers modified with nanoparticles of hydrated oxides of multivalent metals

NASA Astrophysics Data System (ADS)

Maltseva, T. V.; Kolomiets, E. O.; Dzyazko, Yu. S.; Scherbakov, S.

2018-02-01

Organic-inorganic composite ion-exchangers based on anion exchange resins have been obtained. Particles of one-component and two-component modifier were embedded using the approach, which allows us to realize purposeful control of a size of the embedded particles. The approach is based on Ostwald-Freundlich equation, which was adapted to deposition in ion exchange matrix. The equation was obtained experimentally. Hydrated oxides of zirconium and iron were applied to modification, concentration of the reagents were varied. The embedded particles accelerate sorption, the rate of which is fitted by the model equation of chemical reactions of pseudo-second order. When sorption of arsenate ions from very diluted solution (50 µg dm-3) occurs, the composites show higher distribution coefficients comparing with the pristine resin.

A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

PubMed Central

Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

2012-01-01

Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

Embedded correlated wavefunction schemes: theory and applications.

PubMed

Libisch, Florian; Huang, Chen; Carter, Emily A

2014-09-16

Conspectus Ab initio modeling of matter has become a pillar of chemical research: with ever-increasing computational power, simulations can be used to accurately predict, for example, chemical reaction rates, electronic and mechanical properties of materials, and dynamical properties of liquids. Many competing quantum mechanical methods have been developed over the years that vary in computational cost, accuracy, and scalability: density functional theory (DFT), the workhorse of solid-state electronic structure calculations, features a good compromise between accuracy and speed. However, approximate exchange-correlation functionals limit DFT's ability to treat certain phenomena or states of matter, such as charge-transfer processes or strongly correlated materials. Furthermore, conventional DFT is purely a ground-state theory: electronic excitations are beyond its scope. Excitations in molecules are routinely calculated using time-dependent DFT linear response; however applications to condensed matter are still limited. By contrast, many-electron wavefunction methods aim for a very accurate treatment of electronic exchange and correlation. Unfortunately, the associated computational cost renders treatment of more than a handful of heavy atoms challenging. On the other side of the accuracy spectrum, parametrized approaches like tight-binding can treat millions of atoms. In view of the different (dis-)advantages of each method, the simulation of complex systems seems to force a compromise: one is limited to the most accurate method that can still handle the problem size. For many interesting problems, however, compromise proves insufficient. A possible solution is to break up the system into manageable subsystems that may be treated by different computational methods. The interaction between subsystems may be handled by an embedding formalism. In this Account, we review embedded correlated wavefunction (CW) approaches and some applications. We first discuss our density functional embedding theory, which is formally exact. We show how to determine the embedding potential, which replaces the interaction between subsystems, at the DFT level. CW calculations are performed using a fixed embedding potential, that is, a non-self-consistent embedding scheme. We demonstrate this embedding theory for two challenging electron transfer phenomena: (1) initial oxidation of an aluminum surface and (2) hot-electron-mediated dissociation of hydrogen molecules on a gold surface. In both cases, the interaction between gas molecules and metal surfaces were treated by sophisticated CW techniques, with the remainder of the extended metal surface being treated by DFT. Our embedding approach overcomes the limitations of conventional Kohn-Sham DFT in describing charge transfer, multiconfigurational character, and excited states. From these embedding simulations, we gained important insights into fundamental processes that are crucial aspects of fuel cell catalysis (i.e., O2 reduction at metal surfaces) and plasmon-mediated photocatalysis by metal nanoparticles. Moreover, our findings agree very well with experimental observations, while offering new views into the chemistry. We finally discuss our recently formulated potential-functional embedding theory that provides a seamless, first-principles way to include back-action onto the environment from the embedded region.

An Approach to Embedded Training for Future Leaders and Staff

DTIC Science & Technology

2009-10-01

13. SUPPLEMENTARY NOTES See also ADA562526. RTO-MP-HFM-169 Human Dimensions in Embedded Virtual Simulation (Les dimensions humaines dans la...order to better capitalize on follow-on operations. 4.10 Theme 7: Sustain Unit Operations Theme 7 is defined as the ability of Soldiers and

Job-Embedded Professional Development: Its Impact on Teacher Self-Efficacy and Student Performance

ERIC Educational Resources Information Center

Althauser, Krista

2015-01-01

A quantitative approach was used to investigate the impact of a district-wide, job-embedded mathematics professional development program on elementary teachers' general and personal efficacy. This investigation was based on the principles of mathematics professional development, efficacy theory, and student achievement. It was designed to…

Global detection approach for clustered microcalcifications in mammograms using a deep learning network.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-04-01

In computerized detection of clustered microcalcifications (MCs) from mammograms, the traditional approach is to apply a pattern detector to locate the presence of individual MCs, which are subsequently grouped into clusters. Such an approach is often susceptible to the occurrence of false positives (FPs) caused by local image patterns that resemble MCs. We investigate the feasibility of a direct detection approach to determining whether an image region contains clustered MCs or not. Toward this goal, we develop a deep convolutional neural network (CNN) as the classifier model to which the input consists of a large image window ([Formula: see text] in size). The multiple layers in the CNN classifier are trained to automatically extract image features relevant to MCs at different spatial scales. In the experiments, we demonstrated this approach on a dataset consisting of both screen-film mammograms and full-field digital mammograms. We evaluated the detection performance both on classifying image regions of clustered MCs using a receiver operating characteristic (ROC) analysis and on detecting clustered MCs from full mammograms by a free-response receiver operating characteristic analysis. For comparison, we also considered a recently developed MC detector with FP suppression. In classifying image regions of clustered MCs, the CNN classifier achieved 0.971 in the area under the ROC curve, compared to 0.944 for the MC detector. In detecting clustered MCs from full mammograms, at 90% sensitivity, the CNN classifier obtained an FP rate of 0.69 clusters/image, compared to 1.17 clusters/image by the MC detector. These results indicate that using global image features can be more effective in discriminating clustered MCs from FPs caused by various sources, such as linear structures, thereby providing a more accurate detection of clustered MCs on mammograms.

Configurational coupled cluster approach with applications to magnetic model systems

NASA Astrophysics Data System (ADS)

Wu, Siyuan; Nooijen, Marcel

2018-05-01

A general exponential, coupled cluster like, approach is discussed to extract an effective Hamiltonian in configurational space, as a sum of 1-body, 2-body up to n-body operators. The simplest two-body approach is illustrated by calculations on simple magnetic model systems. A key feature of the approach is that equations up to a certain rank do not depend on higher body cluster operators.

Hub-filament System in IRAS 05480+2545: Young Stellar Cluster and 6.7 GHz Methanol Maser

NASA Astrophysics Data System (ADS)

Dewangan, L. K.; Ojha, D. K.; Baug, T.

2017-07-01

To probe the star formation (SF) process, we present a multi-wavelength study of IRAS 05480+2545 (hereafter I05480+2545). Analysis of Herschel data reveals a massive clump (M clump ˜ 1875 {M}⊙ ; peak N(H2) ˜ 4.8 × 1022 cm-2 A V ˜ 51 mag) containing the 6.7 GHz methanol maser and I05480+2545, which is also depicted in a temperature range of 18-26 K. Several noticeable parsec-scale filaments are detected in the Herschel 250 μm image and seem to be radially directed to the massive clump. It resembles more of a “hub-filament” system. Deeply embedded young stellar objects (YSOs) have been identified using the 1-5 μm photometric data, and a significant fraction of YSOs and their clustering are spatially found toward the massive clump, revealing the intense SF activities. An infrared counterpart (IRc) of the maser is investigated in the Spitzer 3.6-4.5 μm images. The IRc does not appear as a point-like source and is most likely associated with the molecular outflow. Based on the 1.4 GHz and Hα continuum images, the ionized emission is absent toward the IRc, indicating that the massive clump harbors an early phase of a massive protostar before the onset of an ultracompact H II region. Together, the I05480+2545 is embedded in a very similar “hub-filament” system to those seen in the Rosette Molecular Cloud. The outcome of the present work indicates the role of filaments in the formation of the massive star-forming clump and cluster of YSOs, which might help channel material to the central hub configuration and the clump/core.

A methodological study of genome-wide DNA methylation analyses using matched archival formalin-fixed paraffin embedded and fresh frozen breast tumors

PubMed Central

Yan, Li; Liu, Song; Tang, Li; Hu, Qiang; Morrison, Carl D.; Ambrosone, Christine B.; Higgins, Michael J.; Sucheston-Campbell, Lara E.

2017-01-01

Background DNA from archival formalin-fixed and paraffin embedded (FFPE) tissue is an invaluable resource for genome-wide methylation studies although concerns about poor quality may limit its use. In this study, we compared DNA methylation profiles of breast tumors using DNA from fresh-frozen (FF) tissues and three types of matched FFPE samples. Results For 9/10 patients, correlation and unsupervised clustering analysis revealed that the FF and FFPE samples were consistently correlated with each other and clustered into distinct subgroups. Greater than 84% of the top 100 loci previously shown to differentiate ER+ and ER– tumors in FF tissues were also FFPE DML. Weighted Correlation Gene Network Analyses (WCGNA) grouped the DML loci into 16 modules in FF tissue, with ~85% of the module membership preserved across tissue types. Materials and Methods Restored FFPE and matched FF samples were profiled using the Illumina Infinium HumanMethylation450K platform. Methylation levels (β-values) across all loci and the top 100 loci previously shown to differentiate tumors by estrogen receptor status (ER+ or ER−) in a larger FF study, were compared between matched FF and FFPE samples using Pearson's correlation, hierarchical clustering and WCGNA. Positive predictive values and sensitivity levels for detecting differentially methylated loci (DML) in FF samples were calculated in an independent FFPE cohort. Conclusions FFPE breast tumors samples show lower overall detection of DMLs versus FF, however FFPE and FF DMLs compare favorably. These results support the emerging consensus that the 450K platform can be employed to investigate epigenetics in large sets of archival FFPE tissues. PMID:28118602

Formation of large-scale structure from cosmic strings and massive neutrinos

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.; Melott, Adrian L.; Bertschinger, Edmund

1989-01-01

Numerical simulations of large-scale structure formation from cosmic strings and massive neutrinos are described. The linear power spectrum in this model resembles the cold-dark-matter power spectrum. Galaxy formation begins early, and the final distribution consists of isolated density peaks embedded in a smooth background, leading to a natural bias in the distribution of luminous matter. The distribution of clustered matter has a filamentary appearance with large voids.

Fuzzy Document Clustering Approach using WordNet Lexical Categories

NASA Astrophysics Data System (ADS)

Gharib, Tarek F.; Fouad, Mohammed M.; Aref, Mostafa M.

Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. This area is growing rapidly mainly because of the strong need for analysing the huge and large amount of textual data that reside on internal file systems and the Web. Text document clustering provides an effective navigation mechanism to organize this large amount of data by grouping their documents into a small number of meaningful classes. In this paper we proposed a fuzzy text document clustering approach using WordNet lexical categories and Fuzzy c-Means algorithm. Some experiments are performed to compare efficiency of the proposed approach with the recently reported approaches. Experimental results show that Fuzzy clustering leads to great performance results. Fuzzy c-means algorithm overcomes other classical clustering algorithms like k-means and bisecting k-means in both clustering quality and running time efficiency.

Convalescing Cluster Configuration Using a Superlative Framework

PubMed Central

Sabitha, R.; Karthik, S.

2015-01-01

Competent data mining methods are vital to discover knowledge from databases which are built as a result of enormous growth of data. Various techniques of data mining are applied to obtain knowledge from these databases. Data clustering is one such descriptive data mining technique which guides in partitioning data objects into disjoint segments. K-means algorithm is a versatile algorithm among the various approaches used in data clustering. The algorithm and its diverse adaptation methods suffer certain problems in their performance. To overcome these issues a superlative algorithm has been proposed in this paper to perform data clustering. The specific feature of the proposed algorithm is discretizing the dataset, thereby improving the accuracy of clustering, and also adopting the binary search initialization method to generate cluster centroids. The generated centroids are fed as input to K-means approach which iteratively segments the data objects into respective clusters. The clustered results are measured for accuracy and validity. Experiments conducted by testing the approach on datasets from the UC Irvine Machine Learning Repository evidently show that the accuracy and validity measure is higher than the other two approaches, namely, simple K-means and Binary Search method. Thus, the proposed approach proves that discretization process will improve the efficacy of descriptive data mining tasks. PMID:26543895

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

PubMed

Xu, Peng; Gordon, Mark S

2014-09-04

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

Algorithms of maximum likelihood data clustering with applications

NASA Astrophysics Data System (ADS)

Giada, Lorenzo; Marsili, Matteo

2002-12-01

We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any possible cluster structure. The likelihood in turn depends only on the Pearson's coefficient of the data. We discuss clustering algorithms that provide a fast and reliable approximation to maximum likelihood configurations. Compared to standard clustering methods, our approach has the advantages that (i) it is parameter free, (ii) the number of clusters need not be fixed in advance and (iii) the interpretation of the results is transparent. In order to test our approach and compare it with standard clustering algorithms, we analyze two very different data sets: time series of financial market returns and gene expression data. We find that different maximization algorithms produce similar cluster structures whereas the outcome of standard algorithms has a much wider variability.

SUZAKU OBSERVATIONS OF THE X-RAY BRIGHTEST FOSSIL GROUP ESO 3060170

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

Su, Yuanyuan; White, Raymond E. III; Miller, Eric D., E-mail: ysu@crimson.ua.edu

2013-10-01

'Fossil' galaxy groups, each dominated by a relatively isolated giant elliptical galaxy, have many properties intermediate between groups and clusters of galaxies. We used the Suzaku X-ray observatory to observe the X-ray brightest fossil group, ESO 3060170, out to R{sub 200}, in order to better elucidate the relation between fossil groups, normal groups, and clusters. We determined the intragroup gas temperature, density, and metal abundance distributions and derived the entropy, pressure, and mass profiles for this group. The entropy and pressure profiles in the outer regions are flatter than in simulated clusters, similar to what is seen in observations ofmore » massive clusters. This may indicate that the gas is clumpy and/or the gas has been redistributed. Assuming hydrostatic equilibrium, the total mass is estimated to be ∼1.7 × 10{sup 14} M{sub ☉} within a radius R{sub 200} of ∼1.15 Mpc, with an enclosed baryon mass fraction of 0.13. The integrated iron mass-to-light ratio of this fossil group is larger than in most groups and comparable to those of clusters, indicating that this fossil group has retained the bulk of its metals. A galaxy luminosity density map on a scale of 25 Mpc shows that this fossil group resides in a relatively isolated environment, unlike the filamentary structures in which typical groups and clusters are embedded.« less

Bright Young Star Clusters in NGC5253 with LEGUS

NASA Astrophysics Data System (ADS)

Calzetti, Daniela; Johnson, Kelsey E.; Adamo, Angela; Gallagher, John S.; Andrews, Jennifer E.; Smith, Linda J.; Clayton, Geoffrey C.; Lee, Janice C.; Sabbi, Elena; Ubeda, Leonardo; Kim, Hwihyun; Ryon, Jenna E.; Thilker, David A.; Bright, Stacey N.; Zackrisson, Erik; Kennicutt, Robert; de Mink, Selma E.; Whitmore, Bradley C.; Aloisi, Alessandra; Chandar, Rupali; Cignoni, Michele; Cook, David; Dale, Daniel A.; Elmegreen, Bruce; Elmegreen, Debra M.; Evans, Aaron S.; Fumagalli, Michele; Gouliermis, Dimitrios; Grasha, Kathryn; Grebel, Eva; Krumholz, Mark R.; Walterbos, Rene A. M.; Wofford, Aida; Brown, Thomas M.; Christian, Carol A.; Dobbs, Claire; Herrero-Davo`, Artemio; Kahre, Lauren; Messa, Matteo; Nair, Preethi; Nota, Antonella; Östlin, Göran; Pellerin, Anne; Sacchi, Elena; Schaerer, Daniel; Tosi, Monica

2016-01-01

Using UV-to-H broad and narrow-band HST imaging, we derive the ages and masses of the 11 brightest star clusters in the dwarf galaxy NGC5253. This galaxy, located at ~3 Mpc, hosts an intense starburst, which includes a centrally-concentrated dusty region with strong thermal radio emission (the `radio nebula'). The HST imaging includes data from the Cycle 21 Treasury Program LEGUS (Legacy ExtraGalactic UV Survey), in addition to narrow--band H-alpha (6563 A), P-beta (12820 A), and P-alpha (18756 A). The bright clusters have ages ~1-15 Myr and masses ~1E4 - 2.5E5 Msun. Two of the 11 star clusters are located within the radio nebula, and suffer from significant dust attenuation. Both are extremely young, with a best-fit age around 1 Myr, and masses ~7.5E4 and ~2.5E5 Msun, respectively. The most massive of the two `radio nebula' clusters is 2-4 times less massive than previously estimated and is embedded within a cloud of dust with A_V~50 mag. The two clusters account for about half of the ionizing photon rate in the radio nebula, and will eventually supply about 2/3 of the mechanical energy in present-day shocks. Additional sources are required to supply the remaining ionizing radiation, and may include very massive stars.

Revisiting the monster: the mass profile of the galaxy cluster Abell 3827 using dynamical and strong lensing constrains

NASA Astrophysics Data System (ADS)

Rodrigo Carrasco Damele, Eleazar; Verdugo, Tomas

2018-01-01

The galaxy cluster Abell 3827 is one of the most massive clusters know at z ≦ 0.1 (Richness class 2, BM typeI, X-ray LX = 2.4 x 1044 erg s-1). The Brightest Cluster Galaxy (BCG) in Abell 3827 is perhaps the most extreme example of ongoing galaxy cannibalism. The multi-component BCG hosts the stellar remnants nuclei of at least four bright elliptical galaxies embedded in a common assymetric halo extended up to 15 kpc. The most notorious characteristic of the BCG is the existence of a unique strong gravitational lens system located within the inner 15 kpc region. A mass estimation of the galaxy based on strong lensing model was presented in Carrasco et al (2010, ApJL, 715, 160). Moreover, the exceptional strong lensing lens system in Abell 3827 and the location of the four bright galaxies has been used to measure for the first time small physical separations between dark and ordinary matter (Williams et al. 2011, MNRAS, 415, 448, Massey et al. 2015, MNRAS, 449, 3393). In this contribution, we present a detailed strong lensing and dynamical analysis of the cluster Abell 3827 based on spectroscopic redshift of the lensed features and from ~70 spectroscopically confirmed member galaxies inside 0.5 x 0.5 Mpc from the cluster center.

A roadmap of clustering algorithms: finding a match for a biomedical application.

PubMed

Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

Automating Embedded Analysis Capabilities and Managing Software Complexity in Multiphysics Simulation, Part I: Template-Based Generic Programming

DOE PAGES

Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.

2012-01-01

An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering.

Enhancing quantum annealing performance for the molecular similarity problem

NASA Astrophysics Data System (ADS)

Hernandez, Maritza; Aramon, Maliheh

2017-05-01

Quantum annealing is a promising technique which leverages quantum mechanics to solve hard optimization problems. Considerable progress has been made in the development of a physical quantum annealer, motivating the study of methods to enhance the efficiency of such a solver. In this work, we present a quantum annealing approach to measure similarity among molecular structures. Implementing real-world problems on a quantum annealer is challenging due to hardware limitations such as sparse connectivity, intrinsic control error, and limited precision. In order to overcome the limited connectivity, a problem must be reformulated using minor-embedding techniques. Using a real data set, we investigate the performance of a quantum annealer in solving the molecular similarity problem. We provide experimental evidence that common practices for embedding can be replaced by new alternatives which mitigate some of the hardware limitations and enhance its performance. Common practices for embedding include minimizing either the number of qubits or the chain length and determining the strength of ferromagnetic couplers empirically. We show that current criteria for selecting an embedding do not improve the hardware's performance for the molecular similarity problem. Furthermore, we use a theoretical approach to determine the strength of ferromagnetic couplers. Such an approach removes the computational burden of the current empirical approaches and also results in hardware solutions that can benefit from simple local classical improvement. Although our results are limited to the problems considered here, they can be generalized to guide future benchmarking studies.

Stochastic coupled cluster theory: Efficient sampling of the coupled cluster expansion

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Dynamic kinetic energy potential for orbital-free density functional theory.

PubMed

Neuhauser, Daniel; Pistinner, Shlomo; Coomar, Arunima; Zhang, Xu; Lu, Gang

2011-04-14

A dynamic kinetic energy potential (DKEP) is developed for time-dependent orbital-free (TDOF) density function theory applications. This potential is constructed to affect only the dynamical (ω ≠ 0) response of an orbital-free electronic system. It aims at making the orbital-free simulation respond in the same way as that of a noninteracting homogenous electron gas (HEG), as required by a correct kinetic energy, therefore enabling extension of the success of orbital-free density functional theory in the static case (e.g., for embedding and description of processes in bulk materials) to dynamic processes. The potential is constructed by expansions of terms, each of which necessitates only simple time evolution (concurrent with the TDOF evolution) and a spatial convolution at each time-step. With 14 such terms a good fit is obtained to the response of the HEG at a large range of frequencies, wavevectors, and densities. The method is demonstrated for simple jellium spheres, approximating Na(9)(+) and Na(65)(+) clusters. It is applicable both to small and large (even ultralarge) excitations and the results converge (i.e., do not blow up) as a function of time. An extension to iterative frequency-resolved extraction is briefly outlined, as well as possibly numerically simpler expansions. The approach could also be extended to fit, instead of the HEG susceptibility, either an experimental susceptibility or a theoretically derived one for a non-HEG system. The DKEP potential should be a powerful tool for embedding a dynamical system described by a more accurate method (such as time-dependent density functional theory, TDDFT) in a large background described by TDOF with a DKEP potential. The type of expansions used and envisioned should be useful for other approaches, such as memory functionals in TDDFT. Finally, an appendix details the formal connection between TDOF and TDDFT.

A comprehensive grid to evaluate case management's expected effectiveness for community-dwelling frail older people: results from a multiple, embedded case study.

PubMed

Van Durme, Thérèse; Schmitz, Olivier; Cès, Sophie; Anthierens, Sibyl; Maggi, Patrick; Delye, Sam; De Almeida Mello, Johanna; Declercq, Anja; Macq, Jean; Remmen, Roy; Aujoulat, Isabelle

2015-06-18

Case management is a type of intervention expected to improve the quality of care and therefore the quality of life of frail, community-dwelling older people while delaying institutionalisation in nursing homes. However, the heterogeneity, multidimensionality and complexity of these interventions make their evaluation by the means of classical approaches inadequate. Our objective was twofold: (i) to propose a tool allowing for the identification of the key components that explain the success of case management for this population and (ii) to propose a typology based on the results of this tool. The process started with a multiple embedded case study design in order to identify the key components of case management. Based on the results of this first step, data were collected among 22 case management interventions, in order to evaluate their expected effectiveness. Finally, multiple correspondence analyses was conducted to propose a typology of case management. The overall approach was informed by Wagner's Chronic Care Model and the theory of complexity. The study identified a total of 23 interacting key components. Based on the clustering of response patterns of the 22 case management projects included in our study, three types of case management programmes were evidenced, situated on a continuum from a more "socially-oriented" type towards a more "clinically-oriented" type of case management. The type of feedback provided to the general practitioner about both the global geriatric assessment and the result of the intervention turned out to be the most discriminant component between the types. The study design allowed to produce a tool that can be used to distinguish between different types of case management interventions and further evaluate their effect on frail older people in terms of the delaying institutionalisation, functional and cognitive status, quality of life and societal costs.

Pt/Au nanoalloy supported on alumina and chlorided alumina: DFT and experimental analysis

NASA Astrophysics Data System (ADS)

Sharifi, N.; Falamaki, C.; Ghorbanzadeh Ahangari, M.

2018-04-01

Density functional theory (DFT) was used to explore the adsorption of Pt/Au nanoalloy onto a pure and chlorided γ-Al2O3(110) surface, which has been applied in numerous catalytic reactions. First, we considered the adsorption properties of Pt clusters (n ≤ 5) onto the Al2O3(110) surface to determine the most stable Pt cluster on alumina surface in reforming processes. After full structural relaxations of Pt clusters at various configurations on alumina, our computed results expressed that the minimum binding energy (‑5.67 eV) is accrued for Pt4 cluster and the distance between the nearest Pt atom in the cluster to the alumina surface is equal to 1.13 Å. Then, we investigated the binding energies, geometries, and electronic properties of adsorbed Aun clusters (n ≤ 6) on the γ-Al2O3(110) surface. Our studied showed that Au5 was the most thermodynamically stable structure on γ-Al2O3. Finally, we inspected these properties for adsorbed Au clusters onto the Pt4-decorated alumina (Aun/Pt4-alumina) system. The binding energy of the Au4/Pt4-alumina system was ‑5.01 eV, and the distance between Au4 cluster and Pt4-alumina was 1.33 Å. The Au4/Pt4alumina system was found to be the most stable nanometer-sized catalyst design. At last, our first-principles calculations predicted that the best position of embedment Cl on the Au4/Pt4-alumina.

A Constraint on the Formation Timescale of the Young Open Cluster NGC 2264: Lithium Abundance of Pre-main Sequence Stars

NASA Astrophysics Data System (ADS)

Lim, Beomdu; Sung, Hwankyung; Kim, Jinyoung S.; Bessell, Michael S.; Hwang, Narae; Park, Byeong-Gon

2016-11-01

The timescale of cluster formation is an essential parameter in order to understand the formation process of star clusters. Pre-main sequence (PMS) stars in nearby young open clusters reveal a large spread in brightness. If the spread were considered to be a result of a real spread in age, the corresponding cluster formation timescale would be about 5-20 Myr. Hence it could be interpreted that star formation in an open cluster is prolonged for up to a few tens of Myr. However, difficulties in reddening correction, observational errors, and systematic uncertainties introduced by imperfect evolutionary models for PMS stars can result in an artificial age spread. Alternatively, we can utilize Li abundance as a relative age indicator of PMS star to determine the cluster formation timescale. The optical spectra of 134 PMS stars in NGC 2264 have been obtained with MMT/Hectochelle. The equivalent widths have been measured for 86 PMS stars with a detectable Li line (3500\\lt {T}{eff}[{{K}}]≤slant 6500). Li abundance under the condition of local thermodynamic equilibrium (LTE) was derived using the conventional curve of growth method. After correction for non-LTE effects, we find that the initial Li abundance of NGC 2264 is A({Li})=3.2+/- 0.2. From the distribution of the Li abundances, the underlying age spread of the visible PMS stars is estimated to be about 3-4 Myr and this, together with the presence of embedded populations in NGC 2264, suggests that the cluster formed on a timescale shorter than 5 Myr.

Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization

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

Neustetter, M.; Jabbour Al Maalouf, E.; Denifl, S., E-mail: Stephan.Denifl@uibk.ac.at, E-mail: plimaovieira@fct.unl.pt

2016-08-07

Electron ionization of neat tungsten hexacarbonyl (W(CO){sub 6}) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO){sub 6} clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO){sub n}{sup +} (0 ≤ n ≤ 6) and W{sub 2}(CO){sub n}{sup +} (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO){sub n}{sup +} (0 ≤more » n ≤ 3) and W{sub 2}C(CO){sub n}{sup +} (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.« less

Track propagation methods for the correlation of charged tracks with clusters in the calorimeter of the bar PANDA experiment

NASA Astrophysics Data System (ADS)

Nasawasd, T.; Simantathammakul, T.; Herold, C.; Stockmanns, T.; Ritman, J.; Kobdaj, C.

2018-02-01

To classify clusters of hits in the electromagnetic calorimeter (EMC) of bar PANDA (antiProton ANnihilation at DArmstadt), one has to match these EMC clusters with tracks of charged particles reconstructed from hits in the tracking system. Therefore the tracks are propagated to the surface of the EMC and associated with EMC clusters which are nearby and below a cut parameter. In this work, we propose a helix propagator to extrapolate the track from the Straw Tube Tracker (STT) to the inner surface of the EMC instead of the GEANE propagator which is already embedded within the PandaRoot computational framework. The results for both propagation methods show a similar quality, with a 30% gain in CPU time when using the helix propagator. We use Monte-Carlo truth information to compare the particle ID of the EMC clusters with the ID of the extrapolated points, thus deciding upon the correctness of the matches. By varying the cut parameter as a function of transverse momentum and particle type, our simulations show that the purity can be increased by 3-5% compared to the default value which is a constant cut in the bar PANDA simulation framework PandaRoot.

Dimensionality reduction of collective motion by principal manifolds

NASA Astrophysics Data System (ADS)

Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.

2015-01-01

While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.

A probabilistic method for determining the volume fraction of pre-embedded capsules in self-healing materials

NASA Astrophysics Data System (ADS)

Lv, Zhong; Chen, Huisu

2014-10-01

Autonomous healing of cracks using pre-embedded capsules containing healing agent is becoming a promising approach to restore the strength of damaged structures. In addition to the material properties, the size and volume fraction of capsules influence crack healing in the matrix. Understanding the crack and capsule interaction is critical in the development and design of structures made of self-healing materials. Assuming that the pre-embedded capsules are randomly dispersed we theoretically model flat ellipsoidal crack interaction with capsules and determine the probability of a crack intersecting the pre-embedded capsules i.e. the self-healing probability. We also develop a probabilistic model of a crack simultaneously meeting with capsules and catalyst carriers in two-component self-healing system matrix. Using a risk-based healing approach, we determine the volume fraction and size of the pre-embedded capsules that are required to achieve a certain self-healing probability. To understand the effect of the shape of the capsules on self-healing we theoretically modeled crack interaction with spherical and cylindrical capsules. We compared the results of our theoretical model with Monte-Carlo simulations of crack interaction with capsules. The formulae presented in this paper will provide guidelines for engineers working with self-healing structures in material selection and sustenance.

Metric Optimization for Surface Analysis in the Laplace-Beltrami Embedding Space

PubMed Central

Lai, Rongjie; Wang, Danny J.J.; Pelletier, Daniel; Mohr, David; Sicotte, Nancy; Toga, Arthur W.

2014-01-01

In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects. PMID:24686245

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY.

PubMed

Rackauckas, Christopher; Nie, Qing

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs.

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY

PubMed Central

Rackauckas, Christopher

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs. PMID:29527134

Observation of correlated electronic decay in expanding clusters triggered by near-infrared fields

PubMed Central

Schütte, B.; Arbeiter, M.; Fennel, T.; Jabbari, G.; Kuleff, A.I.; Vrakking, M.J.J.; Rouzée, A.

2015-01-01

When an excited atom is embedded into an environment, novel relaxation pathways can emerge that are absent for isolated atoms. A well-known example is interatomic Coulombic decay, where an excited atom relaxes by transferring its excess energy to another atom in the environment, leading to its ionization. Such processes have been observed in clusters ionized by extreme-ultraviolet and X-ray lasers. Here, we report on a correlated electronic decay process that occurs following nanoplasma formation and Rydberg atom generation in the ionization of clusters by intense, non-resonant infrared laser fields. Relaxation of the Rydberg states and transfer of the available electronic energy to adjacent electrons in Rydberg states or quasifree electrons in the expanding nanoplasma leaves a distinct signature in the electron kinetic energy spectrum. These so far unobserved electron-correlation-driven energy transfer processes may play a significant role in the response of any nano-scale system to intense laser light. PMID:26469997

What drives the formation of massive stars and clusters?

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

II Zw 40 - 30 Doradus on Steroids

NASA Astrophysics Data System (ADS)

Leitherer, Claus; Lee, Janice C.; Levesque, Emily M.

2017-11-01

We obtained HST COS G140L spectra of the enigmatic nearby blue compact dwarf galaxy II Zw 40. The galaxy hosts a nuclear super star cluster embedded in a radio-bright nebula, similar to those observed in the related blue compact dwarfs NGC 5253 and Henize 2-10. The ultraviolet spectrum of II Zw 40 is exceptional in terms of the strength of He II 1640, O III] 1666 and C III] 1909. We determined reddening, age, and the cluster mass from the ultraviolet data. The super nebula and the ionizing cluster exceed the ionizing luminosity and stellar mass of the local benchmark 30 Doradus by an order of magnitude. Comparison with stellar evolution models accounting for rotation reveals serious short-comings: these models do not account for the presence of Wolf-Rayet-like stars at young ages observed in II Zw 40. Photoionization modeling is used to probe the origin of the nebular lines and determine gas phase abundances. C/O is solar, in agreement with the result of the stellar-wind modeling.

The effect of the subprime crisis on the credit risk in global scale

NASA Astrophysics Data System (ADS)

Lee, Sangwook; Kim, Min Jae; Lee, Sun Young; Kim, Soo Yong; Ban, Joon Hwa

2013-05-01

Credit default swap (CDS) has become one of the most actively traded credit derivatives, and its importance in finance markets has increased after the subprime crisis. In this study, we analyzed the correlation structure of credit risks embedded in CDS and the influence of the subprime crisis on this topological space. We found that the correlation was stronger in the cluster constructed according to the location of the CDS reference companies than in the one constructed according to their industries. The correlation both within a given cluster and between different clusters became significantly stronger after the subprime crisis. The causality test shows that the lead lag effect between the portfolios (into which reference companies are grouped by the continent where each of them is located) is reversed in direction because the portion of non-investable and investable reference companies in each portfolio has changed since then. The effect of a single impulse has increased and the response time relaxation has become prolonged after the crisis as well.

Sampling methods for stellar masses and the mmax-Mecl relation in the starburst dwarf galaxy NGC 4214

NASA Astrophysics Data System (ADS)

Weidner, Carsten; Kroupa, Pavel; Pflamm-Altenburg, Jan

2014-07-01

It has been claimed in the recent literature that a non-trivial relation between the mass of the most-massive star, mmax, in a star cluster and its embedded star cluster mass (the mmax - Mecl relation) is falsified by observations of the most-massive stars and the Hα luminosity of young star clusters in the starburst dwarf galaxy NGC 4214. Here, it is shown by comparing the NGC 4214 results with observations from the Milky Way that NGC 4214 agrees very well with the predictions of the mmax - Mecl relation and with the integrated galactic stellar initial mass function theory. The difference in conclusions is based on a high degree of degeneracy between expectations from random sampling and those from the mmax - Mecl relation, but are also due to interpreting mmax as a truncation mass in a randomly sampled initial mass function. Additional analysis of galaxies with lower SFRs than those currently presented in the literature will be required to break this degeneracy.

A non cool-core 4.6-keV cluster around the bright nearby radio galaxy PKS B1416-493

NASA Astrophysics Data System (ADS)

Worrall, D. M.; Birkinshaw, M.

2017-05-01

We present new X-ray (Chandra) and radio (ATCA) observations of the z = 0.09 radio galaxy PKS B1416-493, a member of the southern equivalent of the 3CRR sample. We find the source to be embedded in a previously unrecognized bright kT = 4.6-keV non cool-core cluster. The discovery of new clusters of such high temperature and luminosity within z = 0.1 is rare. The radio source was chosen for observation based on its intermediate FR I/II morphology. We identify a cavity coincident with the northeast lobe, and excess counts associated with the southwest lobe that we interpret as inverse-Compton X-ray emission. The jet power, at 5.3 × 1044 erg s-1, when weighted by radio source density, supports suggestions that radio sources of intermediate morphology and radio power may dominate radio-galaxy heating in the local Universe.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

Steganographic embedding in containers-images

NASA Astrophysics Data System (ADS)

Nikishova, A. V.; Omelchenko, T. A.; Makedonskij, S. A.

2018-05-01

Steganography is one of the approaches to ensuring the protection of information transmitted over the network. But a steganographic method should vary depending on a used container. According to statistics, the most widely used containers are images and the most common image format is JPEG. Authors propose a method of data embedding into a frequency area of images in format JPEG 2000. It is proposed to use the method of Benham-Memon- Yeo-Yeung, in which instead of discrete cosine transform, discrete wavelet transform is used. Two requirements for images are formulated. Structure similarity is chosen to obtain quality assessment of data embedding. Experiments confirm that requirements satisfaction allows achieving high quality assessment of data embedding.

Query Results Clustering by Extending SPARQL with CLUSTER BY

NASA Astrophysics Data System (ADS)

Ławrynowicz, Agnieszka

The task of dynamic clustering of the search results proved to be useful in the Web context, where the user often does not know the granularity of the search results in advance. The goal of this paper is to provide a declarative way for invoking dynamic clustering of the results of queries submitted over Semantic Web data. To achieve this goal the paper proposes an approach that extends SPARQL by clustering abilities. The approach introduces a new statement, CLUSTER BY, into the SPARQL grammar and proposes semantics for such extension.

Accuracy of Protein Embedding Potentials: An Analysis in Terms of Electrostatic Potentials.

PubMed

Olsen, Jógvan Magnus Haugaard; List, Nanna Holmgaard; Kristensen, Kasper; Kongsted, Jacob

2015-04-14

Quantum-mechanical embedding methods have in recent years gained significant interest and may now be applied to predict a wide range of molecular properties calculated at different levels of theory. To reach a high level of accuracy in embedding methods, both the electronic structure model of the active region and the embedding potential need to be of sufficiently high quality. In fact, failures in quantum mechanics/molecular mechanics (QM/MM)-based embedding methods have often been associated with the QM/MM methodology itself; however, in many cases the reason for such failures is due to the use of an inaccurate embedding potential. In this paper, we investigate in detail the quality of the electronic component of embedding potentials designed for calculations on protein biostructures. We show that very accurate explicitly polarizable embedding potentials may be efficiently designed using fragmentation strategies combined with single-fragment ab initio calculations. In fact, due to the self-interaction error in Kohn-Sham density functional theory (KS-DFT), use of large full-structure quantum-mechanical calculations based on conventional (hybrid) functionals leads to less accurate embedding potentials than fragment-based approaches. We also find that standard protein force fields yield poor embedding potentials, and it is therefore not advisable to use such force fields in general QM/MM-type calculations of molecular properties other than energies and structures.

A Comparison of Activity-Based Intervention and Embedded Direct Instruction When Teaching Emergent Literacy Skills

ERIC Educational Resources Information Center

Botts, Dawn C.; Losardo, Angela S.; Tillery, Christina Y.; Werts, Margaret G.

2014-01-01

This replication study focused on the effectiveness of two different intervention approaches, activity-based intervention and embedded direct instruction, on the acquisition, generalization, and maintenance of phonological awareness, a key area of emergent literacy, by preschool children with language delays. Five male preschool participants with…

Researching into a MOOC Embedded Flipped Classroom Model for College English Reading and Writing Course

ERIC Educational Resources Information Center

Xinying, Zhang

2017-01-01

There is obvious pressure for higher education institutions to undergo transformation now in China. Reflecting this, the computer and information technology give rise to the development of a Massive Open Online Course (MOOC) embedded flipped classroom. Flipped classroom approaches replace the traditional transmissive teaching with engaging…

Web Service Architecture Framework for Embedded Devices

ERIC Educational Resources Information Center

Yanzick, Paul David

2009-01-01

The use of Service Oriented Architectures, namely web services, has become a widely adopted method for transfer of data between systems across the Internet as well as the Enterprise. Adopting a similar approach to embedded devices is also starting to emerge as personal devices and sensor networks are becoming more common in the industry. This…

Architecture of an E-Learning System with Embedded Authoring Support.

ERIC Educational Resources Information Center

Baudry, Andreas; Bungenstock, Michael; Mertsching, Barbel

This paper introduces an architecture for an e-learning system with an embedded authoring system. Based on the metaphor of a construction kit, this approach offers a general solution for specific content creation and publication. The learning resources are IMS "Content Packages" with a special structure to separate content and presentation. These…

Embedding an Indigenous Graduate Attribute into University of Western Sydney's Courses

ERIC Educational Resources Information Center

Anning, Berice

2010-01-01

The paper reports on embedding an Indigenous graduate attribute into courses at the University of Western Sydney (UWS), providing the background to the development and implementation of a holistic and individual Indigenous graduate attribute. It details the approach taken by the Badanami Centre for Indigenous Education in advising the UWS staff on…

Building Staff Capacity through Reflecting on Collaborative Development of Embedded Academic Literacies Curricula

ERIC Educational Resources Information Center

Thies, Linda C.

2016-01-01

Most Australian universities articulate some policies around the integration of graduate learning outcomes in courses. This paper draws on a Federal Government funded project that adopted a developmental approach to students' acquisition of course learning outcomes, through the embedding of academic literacies in course curricula. The project was…

Embedding Marketing in International Campus Development: Lessons from UK Universities

ERIC Educational Resources Information Center

Lewis, Vicky

2016-01-01

This paper provides recommendations for embedding a market- and marketing-informed approach within the development process for a new international campus. It includes a brief outline of the current global profile of international campuses (as one form of transnational education) before highlighting the role of marketing at key stages of campus…

Embedded Multiprocessor Technology for VHSIC Insertion

NASA Technical Reports Server (NTRS)

Hayes, Paul J.

1990-01-01

Viewgraphs on embedded multiprocessor technology for VHSIC insertion are presented. The objective was to develop multiprocessor system technology providing user-selectable fault tolerance, increased throughput, and ease of application representation for concurrent operation. The approach was to develop graph management mapping theory for proper performance, model multiprocessor performance, and demonstrate performance in selected hardware systems.

The Gaia-ESO Survey and CSI 2264: Substructures, disks, and sequential star formation in the young open cluster NGC 2264

NASA Astrophysics Data System (ADS)

Venuti, L.; Prisinzano, L.; Sacco, G. G.; Flaccomio, E.; Bonito, R.; Damiani, F.; Micela, G.; Guarcello, M. G.; Randich, S.; Stauffer, J. R.; Cody, A. M.; Jeffries, R. D.; Alencar, S. H. P.; Alfaro, E. J.; Lanzafame, A. C.; Pancino, E.; Bayo, A.; Carraro, G.; Costado, M. T.; Frasca, A.; Jofré, P.; Morbidelli, L.; Sousa, S. G.; Zaggia, S.

2018-01-01

Context. Reconstructing the structure and history of young clusters is pivotal to understanding the mechanisms and timescales of early stellar evolution and planet formation. Recent studies suggest that star clusters often exhibit a hierarchical structure, possibly resulting from several star formation episodes occurring sequentially rather than a monolithic cloud collapse. Aims: We aim to explore the structure of the open cluster and star-forming region NGC 2264 ( 3 Myr), which is one of the youngest, richest and most accessible star clusters in the local spiral arm of our Galaxy; we link the spatial distribution of cluster members to other stellar properties such as age and evolutionary stage to probe the star formation history within the region. Methods: We combined spectroscopic data obtained as part of the Gaia-ESO Survey (GES) with multi-wavelength photometric data from the Coordinated Synoptic Investigation of NGC 2264 (CSI 2264) campaign. We examined a sample of 655 cluster members, with masses between 0.2 and 1.8 M⊙ and including both disk-bearing and disk-free young stars. We used Teff estimates from GES and g,r,i photometry from CSI 2264 to derive individual extinction and stellar parameters. Results: We find a significant age spread of 4-5 Myr among cluster members. Disk-bearing objects are statistically associated with younger isochronal ages than disk-free sources. The cluster has a hierarchical structure, with two main blocks along its latitudinal extension. The northern half develops around the O-type binary star S Mon; the southern half, close to the tip of the Cone Nebula, contains the most embedded regions of NGC 2264, populated mainly by objects with disks and ongoing accretion. The median ages of objects at different locations within the cluster, and the spatial distribution of disked and non-disked sources, suggest that star formation began in the north of the cluster, over 5 Myr ago, and was ignited in its southern region a few Myr later. Star formation is likely still ongoing in the most embedded regions of the cluster, while the outer regions host a widespread population of more evolved objects; these may be the result of an earlier star formation episode followed by outward migration on timescales of a few Myr. We find a detectable lag between the typical age of disk-bearing objects and that of accreting objects in the inner regions of NGC 2264: the first tend to be older than the second, but younger than disk-free sources at similar locations within the cluster. This supports earlier findings that the characteristic timescales of disk accretion are shorter than those of disk dispersal, and smaller than the average age of NGC 2264 (i.e., ≲3 Myr). At the same time, we note that disks in the north of the cluster tend to be shorter-lived ( 2.5 Myr) than elsewhere; this may reflect the impact of massive stars within the region (notably S Mon), that trigger rapid disk dispersal. Conclusions: Our results, consistent with earlier studies on NGC 2264 and other young clusters, support the idea of a star formation process that takes place sequentially over a prolonged span in a given region. A complete understanding of the dynamics of formation and evolution of star clusters requires accurate astrometric and kinematic characterization of its population; significant advance in this field is foreseen in the upcoming years thanks to the ongoing Gaia mission, coupled with extensive ground-based surveys like GES. Full Table B.1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/609/A10

Status in calculating electronic excited states in transition metal oxides from first principles.

PubMed

Bendavid, Leah Isseroff; Carter, Emily Ann

2014-01-01

Characterization of excitations in transition metal oxides is a crucial step in the development of these materials for photonic and optoelectronic applications. However, many transition metal oxides are considered to be strongly correlated materials, and their complex electronic structure is challenging to model with many established quantum mechanical techniques. We review state-of-the-art first-principles methods to calculate charged and neutral excited states in extended materials, and discuss their application to transition metal oxides. We briefly discuss developments in density functional theory (DFT) to calculate fundamental band gaps, and introduce time-dependent DFT, which can model neutral excitations. Charged excitations can be described within the framework of many-body perturbation theory based on Green's functions techniques, which predominantly employs the GW approximation to the self-energy to facilitate a feasible solution to the quasiparticle equations. We review the various implementations of the GW approximation and evaluate each approach in its calculation of fundamental band gaps of many transition metal oxides. We also briefly review the related Bethe-Salpeter equation (BSE), which introduces an electron-hole interaction between GW-derived quasiparticles to describe accurately neutral excitations. Embedded correlated wavefunction theory is another framework used to model localized neutral or charged excitations in extended materials. Here, the electronic structure of a small cluster is modeled within correlated wavefunction theory, while its coupling to its environment is represented by an embedding potential. We review a number of techniques to represent this background potential, including electrostatic representations and electron density-based methods, and evaluate their application to transition metal oxides.

The rise and fall of star formation in z ~ 0.2 merging galaxy clusters

DOE PAGES

Stroe, Andra; Sobral, David; Dawson, William; ...

2015-04-20

CIZA J2242.8+5301 (‘Sausage’) and 1RXS J0603.3+4213 (‘Toothbrush’) are two low-redshift (z ~ 0.2), massive (~2 × 10 15 M ⊙), post-core passage merging clusters, which host-shock waves traced by diffuse radio emission. To study their star formation properties, we uniformly survey the ‘Sausage’ and ‘Toothbrush’ clusters in broad- and narrow-band filters and select a sample of 201 and 463 line emitters, down to a rest-frame equivalent width (13 Å). Here, we robustly separate between Hα and higher redshift emitters using a combination of optical multiband (B, g, V, r, i, z) and spectroscopic data. We build Hα luminosity functions formore » the entire cluster region, near the shock fronts, and away from the shock fronts and find striking differences between the two clusters. In the dynamically younger, 1 Gyr old ‘Sausage’ cluster we find numerous (59) Hα emitters above a star formation rate (SFR) of 0.17 M ⊙ yr -1 surprisingly located in close proximity to the shock fronts, embedded in very hot intracluster medium plasma. The SFR density for the cluster population is at least at the level of typical galaxies at z ~ 2. Down to the same SFR, the possibly dynamically more evolved ‘Toothbrush’ cluster has only nine Hα galaxies. The cluster Hα galaxies fall on the SFR–stellar mass relation z ~ 0.2 for the field. However, the ‘Sausage’ cluster has an Hα emitter density >20 times that of blank fields. If the shock passes through gas-rich cluster galaxies, the compressed gas could collapse into dense clouds and excite star formation for a few 100 Myr. Finally, this process ultimately leads to a rapid consumption of the molecular gas, accelerating the transformation of gas-rich field spirals into cluster S0s or ellipticals.« less

Platypus globin genes and flanking loci suggest a new insertional model for beta-globin evolution in birds and mammals.

PubMed

Patel, Vidushi S; Cooper, Steven J B; Deakin, Janine E; Fulton, Bob; Graves, Tina; Warren, Wesley C; Wilson, Richard K; Graves, Jennifer A M

2008-07-25

Vertebrate alpha (alpha)- and beta (beta)-globin gene families exemplify the way in which genomes evolve to produce functional complexity. From tandem duplication of a single globin locus, the alpha- and beta-globin clusters expanded, and then were separated onto different chromosomes. The previous finding of a fossil beta-globin gene (omega) in the marsupial alpha-cluster, however, suggested that duplication of the alpha-beta cluster onto two chromosomes, followed by lineage-specific gene loss and duplication, produced paralogous alpha- and beta-globin clusters in birds and mammals. Here we analyse genomic data from an egg-laying monotreme mammal, the platypus (Ornithorhynchus anatinus), to explore haemoglobin evolution at the stem of the mammalian radiation. The platypus alpha-globin cluster (chromosome 21) contains embryonic and adult alpha- globin genes, a beta-like omega-globin gene, and the GBY globin gene with homology to cytoglobin, arranged as 5'-zeta-zeta'-alphaD-alpha3-alpha2-alpha1-omega-GBY-3'. The platypus beta-globin cluster (chromosome 2) contains single embryonic and adult globin genes arranged as 5'-epsilon-beta-3'. Surprisingly, all of these globin genes were expressed in some adult tissues. Comparison of flanking sequences revealed that all jawed vertebrate alpha-globin clusters are flanked by MPG-C16orf35 and LUC7L, whereas all bird and mammal beta-globin clusters are embedded in olfactory genes. Thus, the mammalian alpha- and beta-globin clusters are orthologous to the bird alpha- and beta-globin clusters respectively. We propose that alpha- and beta-globin clusters evolved from an ancient MPG-C16orf35-alpha-beta-GBY-LUC7L arrangement 410 million years ago. A copy of the original beta (represented by omega in marsupials and monotremes) was inserted into an array of olfactory genes before the amniote radiation (>315 million years ago), then duplicated and diverged to form orthologous clusters of beta-globin genes with different expression profiles in different lineages.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE PAGES

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

2017-04-17

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

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

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Clustering analysis strategies for electron energy loss spectroscopy (EELS).

PubMed

Torruella, Pau; Estrader, Marta; López-Ortega, Alberto; Baró, Maria Dolors; Varela, Maria; Peiró, Francesca; Estradé, Sònia

2018-02-01

In this work, the use of cluster analysis algorithms, widely applied in the field of big data, is proposed to explore and analyze electron energy loss spectroscopy (EELS) data sets. Three different data clustering approaches have been tested both with simulated and experimental data from Fe 3 O 4 /Mn 3 O 4 core/shell nanoparticles. The first method consists on applying data clustering directly to the acquired spectra. A second approach is to analyze spectral variance with principal component analysis (PCA) within a given data cluster. Lastly, data clustering on PCA score maps is discussed. The advantages and requirements of each approach are studied. Results demonstrate how clustering is able to recover compositional and oxidation state information from EELS data with minimal user input, giving great prospects for its usage in EEL spectroscopy. Copyright © 2017 Elsevier B.V. All rights reserved.

Time-Dependent Thomas-Fermi Approach for Electron Dynamics in Metal Clusters

NASA Astrophysics Data System (ADS)

Domps, A.; Reinhard, P.-G.; Suraud, E.

1998-06-01

We propose a time-dependent Thomas-Fermi approach to the (nonlinear) dynamics of many-fermion systems. The approach relies on a hydrodynamical picture describing the system in terms of collective flow. We investigate in particular an application to electron dynamics in metal clusters. We make extensive comparisons with fully fledged quantal dynamical calculations and find overall good agreement. The approach thus provides a reliable and inexpensive scheme to study the electronic response of large metal clusters.