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Sample records for large-scale correlation function

  1. Large-scale 3D galaxy correlation function and non-Gaussianity

    SciTech Connect

    Raccanelli, Alvise; Doré, Olivier; Bertacca, Daniele; Maartens, Roy E-mail: daniele.bertacca@gmail.com E-mail: roy.maartens@gmail.com

    2014-08-01

    We investigate the properties of the 2-point galaxy correlation function at very large scales, including all geometric and local relativistic effects --- wide-angle effects, redshift space distortions, Doppler terms and Sachs-Wolfe type terms in the gravitational potentials. The general three-dimensional correlation function has a nonzero dipole and octupole, in addition to the even multipoles of the flat-sky limit. We study how corrections due to primordial non-Gaussianity and General Relativity affect the multipolar expansion, and we show that they are of similar magnitude (when f{sub NL} is small), so that a relativistic approach is needed. Furthermore, we look at how large-scale corrections depend on the model for the growth rate in the context of modified gravity, and we discuss how a modified growth can affect the non-Gaussian signal in the multipoles.

  2. A large-scale study of the world wide web: network correlation functions with scale-invariant boundaries

    NASA Astrophysics Data System (ADS)

    Ludueña, Guillermo A.; Meixner, Harald; Kaczor, Gregor; Gros, Claudius

    2013-08-01

    We performed a large-scale crawl of the world wide web, covering 6.9 million domains and 57 million subdomains, including all high-traffic sites of the internet. We present a study of the correlations found between quantities measuring the structural relevance of each node in the network (the in- and out-degree, the local clustering coefficient, the first-neighbor in-degree and the Alexa rank). We find that some of these properties show strong correlation effects and that the dependencies occurring out of these correlations follow power laws not only for the averages, but also for the boundaries of the respective density distributions. In addition, these scale-free limits do not follow the same exponents as the corresponding averages. In our study we retain the directionality of the hyperlinks and develop a statistical estimate for the clustering coefficient of directed graphs. We include in our study the correlations between the in-degree and the Alexa traffic rank, a popular index for the traffic volume, finding non-trivial power-law correlations. We find that sites with more/less than about 103 links from different domains have remarkably different statistical properties, for all correlation functions studied, indicating towards an underlying hierarchical structure of the world wide web.

  3. Large-scale quantization from local correlations in space plasmas

    NASA Astrophysics Data System (ADS)

    Livadiotis, George; McComas, David J.

    2014-05-01

    This study examines the large-scale quantization that can characterize the phase space of certain physical systems. Plasmas are such systems where large-scale quantization, ħ*, is caused by Debye shielding that structures correlations between particles. The value of ħ* is constant—some 12 orders of magnitude larger than the Planck constant—across a wide range of space plasmas, from the solar wind in the inner heliosphere to the distant plasma in the inner heliosheath and the local interstellar medium. This paper develops the foundation and advances the understanding of the concept of plasma quantization; in particular, we (i) show the analogy of plasma to Planck quantization, (ii) show the key points of plasma quantization, (iii) construct some basic quantum mechanical concepts for the large-scale plasma quantization, (iv) investigate the correlation between plasma parameters that implies plasma quantization, when it is approximated by a relation between the magnetosonic energy and the plasma frequency, (v) analyze typical space plasmas throughout the heliosphere and show the constancy of plasma quantization over many orders of magnitude in plasma parameters, (vi) analyze Advanced Composition Explorer (ACE) solar wind measurements to develop another measurement of the value of ħ*, and (vii) apply plasma quantization to derive unknown plasma parameters when some key observable is missing.

  4. Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

    SciTech Connect

    Dodge, D. A.; Harris, D. B.

    2016-03-15

    Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlation detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.

  5. Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

    DOE PAGES

    Dodge, D. A.; Harris, D. B.

    2016-03-15

    Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

  6. Structure and function of large-scale brain systems.

    PubMed

    Koziol, Leonard F; Barker, Lauren A; Joyce, Arthur W; Hrin, Skip

    2014-01-01

    This article introduces the functional neuroanatomy of large-scale brain systems. Both the structure and functions of these brain networks are presented. All human behavior is the result of interactions within and between these brain systems. This system of brain function completely changes our understanding of how cognition and behavior are organized within the brain, replacing the traditional lesion model. Understanding behavior within the context of brain network interactions has profound implications for modifying abstract constructs such as attention, learning, and memory. These constructs also must be understood within the framework of a paradigm shift, which emphasizes ongoing interactions within a dynamically changing environment.

  7. Development of Large-Scale Functional Brain Networks in Children

    PubMed Central

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-01-01

    The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

  8. Phase Correlations and Topological Measures of Large-Scale Structure

    NASA Astrophysics Data System (ADS)

    Coles, P.

    The process of gravitational instability initiated by small primordial density perturbations is a vital ingredient of cosmological models that attempt to explain how galaxies and large-scale structure formed in the Universe. In the standard picture (the "concordance" model), a period of accelerated expansion ("inflation") generated density fluctuations with simple statistical properties through quantum processes (Starobinsky [82], [83], [84]; Guth [39]; Guth & Pi [40]; Albrecht & Steinhardt [2]; Linde [55]). In this scenario the primordial density field is assumed to form a statistically homogeneous and isotropic Gaussian random field (GRF). Over years of observational scrutiny this paradigm has strengthened its hold in the minds of cosmologists and has survived many tests, culminating in those furnished by the Wilkinson Microwave Anisotropy Probe (WMAP; Bennett et al. [7]; Hinshaw et al. [45].

  9. A large-scale evaluation of computational protein function prediction.

    PubMed

    Radivojac, Predrag; Clark, Wyatt T; Oron, Tal Ronnen; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kaßner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Boehm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas A; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-03-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

  10. A large-scale evaluation of computational protein function prediction

    PubMed Central

    Radivojac, Predrag; Clark, Wyatt T; Ronnen Oron, Tal; Schnoes, Alexandra M; Wittkop, Tobias; Sokolov, Artem; Graim, Kiley; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa; Pandey, Gaurav; Yunes, Jeffrey M; Talwalkar, Ameet S; Repo, Susanna; Souza, Michael L; Piovesan, Damiano; Casadio, Rita; Wang, Zheng; Cheng, Jianlin; Fang, Hai; Gough, Julian; Koskinen, Patrik; Törönen, Petri; Nokso-Koivisto, Jussi; Holm, Liisa; Cozzetto, Domenico; Buchan, Daniel W A; Bryson, Kevin; Jones, David T; Limaye, Bhakti; Inamdar, Harshal; Datta, Avik; Manjari, Sunitha K; Joshi, Rajendra; Chitale, Meghana; Kihara, Daisuke; Lisewski, Andreas M; Erdin, Serkan; Venner, Eric; Lichtarge, Olivier; Rentzsch, Robert; Yang, Haixuan; Romero, Alfonso E; Bhat, Prajwal; Paccanaro, Alberto; Hamp, Tobias; Kassner, Rebecca; Seemayer, Stefan; Vicedo, Esmeralda; Schaefer, Christian; Achten, Dominik; Auer, Florian; Böhm, Ariane; Braun, Tatjana; Hecht, Maximilian; Heron, Mark; Hönigschmid, Peter; Hopf, Thomas; Kaufmann, Stefanie; Kiening, Michael; Krompass, Denis; Landerer, Cedric; Mahlich, Yannick; Roos, Manfred; Björne, Jari; Salakoski, Tapio; Wong, Andrew; Shatkay, Hagit; Gatzmann, Fanny; Sommer, Ingolf; Wass, Mark N; Sternberg, Michael J E; Škunca, Nives; Supek, Fran; Bošnjak, Matko; Panov, Panče; Džeroski, Sašo; Šmuc, Tomislav; Kourmpetis, Yiannis A I; van Dijk, Aalt D J; ter Braak, Cajo J F; Zhou, Yuanpeng; Gong, Qingtian; Dong, Xinran; Tian, Weidong; Falda, Marco; Fontana, Paolo; Lavezzo, Enrico; Di Camillo, Barbara; Toppo, Stefano; Lan, Liang; Djuric, Nemanja; Guo, Yuhong; Vucetic, Slobodan; Bairoch, Amos; Linial, Michal; Babbitt, Patricia C; Brenner, Steven E; Orengo, Christine; Rost, Burkhard; Mooney, Sean D; Friedberg, Iddo

    2013-01-01

    Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based Critical Assessment of protein Function Annotation (CAFA) experiment. Fifty-four methods representing the state-of-the-art for protein function prediction were evaluated on a target set of 866 proteins from eleven organisms. Two findings stand out: (i) today’s best protein function prediction algorithms significantly outperformed widely-used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is significant need for improvement of currently available tools. PMID:23353650

  11. Applications of large-scale density functional theory in biology

    NASA Astrophysics Data System (ADS)

    Cole, Daniel J.; Hine, Nicholas D. M.

    2016-10-01

    Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

  12. Large scale cross-correlations in Internet traffic.

    PubMed

    Barthélemy, Marc; Gondran, Bernard; Guichard, Eric

    2002-11-01

    The Internet is a complex network of interconnected routers, and the existence of a collective behavior such as congestion suggests that the correlations between the different connections play a crucial role. It is thus critical to measure and quantify these correlations. We use methods of random matrix theory (RMT) to analyze the cross-correlation matrix C of information flow changes of 650 connections between 26 routers of the French scientific network "Renater." We find that C has the universal properties of the Gaussian orthogonal ensemble of random matrices: The distribution of eigenvalues-up to a rescaling that exhibits a typical correlation time of the order of 10 min-and the spacing distribution follow the predictions of RMT. There are some deviations for large eigenvalues which contain network-specific information and which identify genuine correlations between the connections. The study of the most correlated connections reveals the existence of "active centers" that are exchanging information with a large number of routers thereby inducing correlations between the corresponding connections. These strong correlations could be a reason for the observed self-similarity in the world-wide web traffic.

  13. Large scale cross-correlations in Internet traffic

    NASA Astrophysics Data System (ADS)

    Barthélemy, Marc; Gondran, Bernard; Guichard, Eric

    2002-11-01

    The Internet is a complex network of interconnected routers, and the existence of a collective behavior such as congestion suggests that the correlations between the different connections play a crucial role. It is thus critical to measure and quantify these correlations. We use methods of random matrix theory (RMT) to analyze the cross-correlation matrix C of information flow changes of 650 connections between 26 routers of the French scientific network ``Renater.'' We find that C has the universal properties of the Gaussian orthogonal ensemble of random matrices: The distribution of eigenvalues-up to a rescaling that exhibits a typical correlation time of the order of 10 min-and the spacing distribution follow the predictions of RMT. There are some deviations for large eigenvalues which contain network-specific information and which identify genuine correlations between the connections. The study of the most correlated connections reveals the existence of ``active centers'' that are exchanging information with a large number of routers thereby inducing correlations between the corresponding connections. These strong correlations could be a reason for the observed self-similarity in the world-wide web traffic.

  14. Embedding based on function approximation for large scale image search.

    PubMed

    Do, Thanh-Toan; Cheung, Ngai-Man

    2017-03-23

    The objective of this paper is to design an embedding method that maps local features describing an image (e.g. SIFT) to a higher dimensional representation useful for the image retrieval problem. First, motivated by the relationship between the linear approximation of a nonlinear function in high dimensional space and the stateof- the-art feature representation used in image retrieval, i.e., VLAD, we propose a new approach for the approximation. The embedded vectors resulted by the function approximation process are then aggregated to form a single representation for image retrieval. Second, in order to make the proposed embedding method applicable to large scale problem, we further derive its fast version in which the embedded vectors can be efficiently computed, i.e., in the closed-form. We compare the proposed embedding methods with the state of the art in the context of image search under various settings: when the images are represented by medium length vectors, short vectors, or binary vectors. The experimental results show that the proposed embedding methods outperform existing the state of the art on the standard public image retrieval benchmarks.

  15. THREE-POINT PHASE CORRELATIONS: A NEW MEASURE OF NONLINEAR LARGE-SCALE STRUCTURE

    SciTech Connect

    Wolstenhulme, Richard; Bonvin, Camille; Obreschkow, Danail

    2015-05-10

    We derive an analytical expression for a novel large-scale structure observable: the line correlation function. The line correlation function, which is constructed from the three-point correlation function of the phase of the density field, is a robust statistical measure allowing the extraction of information in the nonlinear and non-Gaussian regime. We show that, in perturbation theory, the line correlation is sensitive to the coupling kernel F{sub 2}, which governs the nonlinear gravitational evolution of the density field. We compare our analytical expression with results from numerical simulations and find a 1σ agreement for separations r ≳ 30 h{sup −1} Mpc. Fitting formulae for the power spectrum and the nonlinear coupling kernel at small scales allow us to extend our prediction into the strongly nonlinear regime, where we find a 1σ agreement with the simulations for r ≳ 2 h{sup −1} Mpc. We discuss the advantages of the line correlation relative to standard statistical measures like the bispectrum. Unlike the latter, the line correlation is independent of the bias, in the regime where the bias is local and linear. Furthermore, the variance of the line correlation is independent of the Gaussian variance on the modulus of the density field. This suggests that the line correlation can probe more precisely the nonlinear regime of gravity, with less contamination from the power spectrum variance.

  16. The three-point function as a probe of models for large-scale structure

    NASA Technical Reports Server (NTRS)

    Frieman, Joshua A.; Gaztanaga, Enrique

    1994-01-01

    We analyze the consequences of models of structure formation for higher order (n-point) galaxy correlation functions in the mildly nonlinear regime. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations have recently been introduced to obtain more power on large scales, R(sub p) is approximately 20/h Mpc, e.g., low matter-density (nonzero cosmological constant) models, 'tilted' primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower et al. We show that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale dependence leads to a dramatic decrease of the the hierarchical amplitudes Q(sub J) at large scales, r is greater than or approximately R(sub p). Current observational constraints on the three-point amplitudes Q(sub 3) and S(sub 3) can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales.

  17. Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

    PubMed

    Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

    2016-02-01

    Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

  18. Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

    NASA Astrophysics Data System (ADS)

    Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

    2012-02-01

    Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

  19. Sustaining evidence-based prevention programs: correlates in a large-scale dissemination initiative.

    PubMed

    Cooper, Brittany Rhoades; Bumbarger, Brian K; Moore, Julia E

    2015-01-01

    Over the past four decades, significant strides have been made in the science of preventing youth problem behaviors. Subsequently, policymakers and funders have begun to insist on the use of evidence-based programs (EBPs) as a requirement for funding. However, unless practitioners are able to sustain these programs beyond initial seed funding, they are unlikely to achieve their ultimate goal of broad public health impact. Despite its obvious importance, sustainability has received relatively little attention in prevention science until recently. Moreover, there have been few opportunities to study the correlates of sustainability in large-scale, multi-year initiatives involving multiple programs. The present study examined rates of sustainment of a wide range of proven-effective prevention and intervention programs; identified factors related to organizational support and readiness, program and implementer characteristics, and sustainability planning that distinguished sustained programs; and examined variability in these associations across classroom-based, community/mentoring, family-focused prevention, and family treatment program types within the context of a state-wide EBP dissemination initiative in Pennsylvania over 4 years. The majority of EBPs sustained functioning 2 years or more beyond their initial funding. In general, sustained programs reported greater community coalition functioning, communication to key stakeholders, knowledge of the program's logical model, communication with the trainer or program developer, and sustainability planning. In addition to these universal correlates, important program-specific correlates emerged as well. Implications for the technical assistance and support necessary to promote the sustainability of EBPs in nonresearch contexts are also discussed.

  20. Cross-correlation of diffuse synchrotron and large-scale structures

    NASA Astrophysics Data System (ADS)

    Brown, Shea; Farnsworth, Damon; Rudnick, Lawrence

    2010-02-01

    We explore for the first time the method of cross-correlation of radio synchrotron emission and tracers of large-scale structure in order to detect the warm-hot intergalactic medium (WHIM). We performed a cross-correlation of a 34° × 34° area of Two-Micron All-Sky Survey (2MASS) galaxies for two redshift slices (0.03 < z < 0.04 and 0.06 < z < 0.07) with the corresponding region of the 1.4 GHz Bonn survey. For this analysis, we assumed that the synchrotron surface brightness is linearly proportional to surface density of galaxies. We also sampled the cross-correlation function (CCF) using 24 distant fields of the same size from the Bonn survey, to better assess the noise properties. Though we obtained a null result, we found that by adding a signal weighted by the 2MASS image with a filament (peak) surface brightness of 1 (7) and 7 (49) mK would produce a 3σ positive correlation for the 0.03 < z < 0.04 and 0.06 < z < 0.07 redshift slices, respectively. These detection thresholds correspond to minimum energy magnetic fields as low as 0.2 μG, close to some theoretical expectations for filament field values. This injected signal is also below the rms noise of the Bonn survey, and demonstrates the power of this technique and its utility for upcoming sensitive continuum surveys such as those planned with the Murchison Widefield Array.

  1. Correlation of CMB with large-scale structure. II. Weak lensing

    SciTech Connect

    Hirata, Christopher M.; Padmanabhan, Nikhil; Seljak, Uros

    2008-08-15

    We investigate the correlation of gravitational lensing of the cosmic microwave background (CMB) with several tracers of large-scale structure, including luminous red galaxies (LRGs), quasars, and radio sources. The lensing field is reconstructed based on the CMB maps from the Wilkinson Microwave Anisotropy Probe (WMAP) satellite; the LRGs and quasars are observed by the Sloan Digital Sky Survey (SDSS); and the radio sources are observed in the NRAO VLA Sky Survey (NVSS). Combining all three large-scale structure samples, we find evidence for a positive cross correlation at the 2.5{sigma} level (1.8{sigma} for the SDSS samples and 2.1{sigma} for NVSS); the cross correlation amplitude is 1.06{+-}0.42 times that expected for the WMAP cosmological parameters. Our analysis extends other recent analyses in that we carefully determine bias-weighted redshift distribution of the sources, which is needed for a meaningful cosmological interpretation of the detected signal. We investigate contamination of the signal by galactic emission, extragalactic radio and infrared sources, thermal and kinetic Sunyaev-Zel'dovich effects, and the Rees-Sciama effect, and find all of them to be negligible.

  2. A correlation between the cosmic microwave background and large-scale structure in the Universe.

    PubMed

    Boughn, Stephen; Crittenden, Robert

    2004-01-01

    Observations of distant supernovae and the fluctuations in the cosmic microwave background (CMB) indicate that the expansion of the Universe may be accelerating under the action of a 'cosmological constant' or some other form of 'dark energy'. This dark energy now appears to dominate the Universe and not only alters its expansion rate, but also affects the evolution of fluctuations in the density of matter, slowing down the gravitational collapse of material (into, for example, clusters of galaxies) in recent times. Additional fluctuations in the temperature of CMB photons are induced as they pass through large-scale structures and these fluctuations are necessarily correlated with the distribution of relatively nearby matter. Here we report the detection of correlations between recent CMB data and two probes of large-scale structure: the X-ray background and the distribution of radio galaxies. These correlations are consistent with those predicted by dark energy, indicating that we are seeing the imprint of dark energy on the growth of structure in the Universe.

  3. Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

    PubMed

    Yuan, Yinyin; Li, Chang-Tsun; Windram, Oliver

    2011-04-06

    Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC) method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/).

  4. Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy.

    PubMed

    Zhang, Zhiqiang; Liao, Wei; Chen, Huafu; Mantini, Dante; Ding, Ju-Rong; Xu, Qiang; Wang, Zhengge; Yuan, Cuiping; Chen, Guanghui; Jiao, Qing; Lu, Guangming

    2011-10-01

    The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings

  5. Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

    PubMed

    Hero, Alfred O; Rajaratnam, Bala

    2016-01-01

    When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

  6. Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

    PubMed Central

    Hero, Alfred O.; Rajaratnam, Bala

    2015-01-01

    When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

  7. Nonlinear Seismic Correlation Analysis of the JNES/NUPEC Large-Scale Piping System Tests.

    SciTech Connect

    Nie,J.; DeGrassi, G.; Hofmayer, C.; Ali, S.

    2008-06-01

    The Japan Nuclear Energy Safety Organization/Nuclear Power Engineering Corporation (JNES/NUPEC) large-scale piping test program has provided valuable new test data on high level seismic elasto-plastic behavior and failure modes for typical nuclear power plant piping systems. The component and piping system tests demonstrated the strain ratcheting behavior that is expected to occur when a pressurized pipe is subjected to cyclic seismic loading. Under a collaboration agreement between the US and Japan on seismic issues, the US Nuclear Regulatory Commission (NRC)/Brookhaven National Laboratory (BNL) performed a correlation analysis of the large-scale piping system tests using derailed state-of-the-art nonlinear finite element models. Techniques are introduced to develop material models that can closely match the test data. The shaking table motions are examined. The analytical results are assessed in terms of the overall system responses and the strain ratcheting behavior at an elbow. The paper concludes with the insights about the accuracy of the analytical methods for use in performance assessments of highly nonlinear piping systems under large seismic motions.

  8. Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

    NASA Technical Reports Server (NTRS)

    Grujic, L. T.; Siljak, D. D.

    1973-01-01

    The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

  9. Correlated primordial perturbations in light of CMB and large scale structure data

    SciTech Connect

    Kurki-Suonio, Hannu; Muhonen, Vesa; Vaeliviita, Jussi

    2005-03-15

    We use cosmic microwave background (CMB) and large scale structure data to constrain cosmological models where the primordial perturbations have both an adiabatic and a cold dark matter (CDM) isocurvature component. We allow for a possible correlation between the adiabatic and isocurvature modes, and for different spectral indices for the power in each mode and for their correlation. We do a likelihood analysis with 11 independent parameters and discuss the effect of choosing the pivot scale for the definition of amplitude parameters. The upper limit to the isocurvature fraction is 18% around a pivot scale k=0.01 Mpc{sup -1}. For smaller pivot wavenumbers the limit stays about the same. For larger pivot wavenumbers, very large values of the isocurvature spectral index are favored, which makes the analysis problematic, but larger isocurvature fractions seem to be allowed. For large isocurvature spectral indices n{sub iso}>2 a positive correlation between the adiabatic and isocurvature mode is favored, and for n{sub iso}<2 a negative correlation is favored. The upper limit to the nonadiabatic contribution to the CMB temperature variance is 7.5%. Of the standard cosmological parameters, determination of the CDM density {omega}{sub c} and the sound horizon angle {theta} (or the Hubble constant H{sub 0}) are affected most by a possible presence of a correlated isocurvature contribution. The baryon density {omega}{sub b} nearly retains its 'adiabatic value'.

  10. A Bayesian Estimate of the CMB-Large-scale Structure Cross-correlation

    NASA Astrophysics Data System (ADS)

    Moura-Santos, E.; Carvalho, F. C.; Penna-Lima, M.; Novaes, C. P.; Wuensche, C. A.

    2016-08-01

    Evidences for late-time acceleration of the universe are provided by multiple probes, such as Type Ia supernovae, the cosmic microwave background (CMB), and large-scale structure (LSS). In this work, we focus on the integrated Sachs-Wolfe (ISW) effect, i.e., secondary CMB fluctuations generated by evolving gravitational potentials due to the transition between, e.g., the matter and dark energy (DE) dominated phases. Therefore, assuming a flat universe, DE properties can be inferred from ISW detections. We present a Bayesian approach to compute the CMB-LSS cross-correlation signal. The method is based on the estimate of the likelihood for measuring a combined set consisting of a CMB temperature and galaxy contrast maps, provided that we have some information on the statistical properties of the fluctuations affecting these maps. The likelihood is estimated by a sampling algorithm, therefore avoiding the computationally demanding techniques of direct evaluation in either pixel or harmonic space. As local tracers of the matter distribution at large scales, we used the Two Micron All Sky Survey galaxy catalog and, for the CMB temperature fluctuations, the ninth-year data release of the Wilkinson Microwave Anisotropy Probe (WMAP9). The results show a dominance of cosmic variance over the weak recovered signal, due mainly to the shallowness of the catalog used, with systematics associated with the sampling algorithm playing a secondary role as sources of uncertainty. When combined with other complementary probes, the method presented in this paper is expected to be a useful tool to late-time acceleration studies in cosmology.

  11. Explorative Function in Williams Syndrome Analyzed through a Large-Scale Task with Multiple Rewards

    ERIC Educational Resources Information Center

    Foti, F.; Petrosini, L.; Cutuli, D.; Menghini, D.; Chiarotti, F.; Vicari, S.; Mandolesi, L.

    2011-01-01

    This study aimed to evaluate spatial function in subjects with Williams syndrome (WS) by using a large-scale task with multiple rewards and comparing the spatial abilities of WS subjects with those of mental age-matched control children. In the present spatial task, WS participants had to explore an open space to search nine rewards placed in…

  12. The Matching Criterion Purification for Differential Item Functioning Analyses in a Large-Scale Assessment

    ERIC Educational Resources Information Center

    Lee, HyeSun; Geisinger, Kurt F.

    2016-01-01

    The current study investigated the impact of matching criterion purification on the accuracy of differential item functioning (DIF) detection in large-scale assessments. The three matching approaches for DIF analyses (block-level matching, pooled booklet matching, and equated pooled booklet matching) were employed with the Mantel-Haenszel…

  13. The large-scale quasar-Lyman α forest cross-correlation from BOSS

    SciTech Connect

    Font-Ribera, Andreu; Arnau, Eduard; Miralda-Escudé, Jordi E-mail: edu.arnau.lazaro@gmail.com; and others

    2013-05-01

    We measure the large-scale cross-correlation of quasars with the Lyα forest absorption in redshift space, using ∼ 60000 quasar spectra from Data Release 9 (DR9) of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is detected over a wide range of scales, up to comoving separations r of 80 h{sup −1}Mpc. For r > 15 h{sup −1}Mpc, we show that the cross-correlation is well fitted by the linear theory prediction for the mean overdensity around a quasar host halo in the standard ΛCDM model, with the redshift distortions indicative of gravitational evolution detected at high confidence. Using previous determinations of the Lyα forest bias factor obtained from the Lyα autocorrelation, we infer the quasar bias factor to be b{sub q} = 3.64{sup +0.13}{sub −0.15} at a mean redshift z = 2.38, in agreement with previous measurements from the quasar auto-correlation. We also obtain a new estimate of the Lyα forest redshift distortion factor, β{sub F} = 1.1±0.15, slightly larger than but consistent with the previous measurement from the Lyα forest autocorrelation. The simple linear model we use fails at separations r < 15h{sup −1}Mpc, and we show that this may reasonably be due to the enhanced ionization due to radiation from the quasars. We also provide the expected correction that the mass overdensity around the quasar implies for measurements of the ionizing radiation background from the line-of-sight proximity effect.

  14. Modeling dynamic functional information flows on large-scale brain networks.

    PubMed

    Lv, Peili; Guo, Lei; Hu, Xintao; Li, Xiang; Jin, Changfeng; Han, Junwei; Li, Lingjiang; Liu, Tianming

    2013-01-01

    Growing evidence from the functional neuroimaging field suggests that human brain functions are realized via dynamic functional interactions on large-scale structural networks. Even in resting state, functional brain networks exhibit remarkable temporal dynamics. However, it has been rarely explored to computationally model such dynamic functional information flows on large-scale brain networks. In this paper, we present a novel computational framework to explore this problem using multimodal resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) data. Basically, recent literature reports including our own studies have demonstrated that the resting state brain networks dynamically undergo a set of distinct brain states. Within each quasi-stable state, functional information flows from one set of structural brain nodes to other sets of nodes, which is analogous to the message package routing on the Internet from the source node to the destination. Therefore, based on the large-scale structural brain networks constructed from DTI data, we employ a dynamic programming strategy to infer functional information transition routines on structural networks, based on which hub routers that most frequently participate in these routines are identified. It is interesting that a majority of those hub routers are located within the default mode network (DMN), revealing a possible mechanism of the critical functional hub roles played by the DMN in resting state. Also, application of this framework on a post trauma stress disorder (PTSD) dataset demonstrated interesting difference in hub router distributions between PTSD patients and healthy controls.

  15. Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

    PubMed

    Chen, Rong; Nixon, Erika; Herskovits, Edward

    2016-04-01

    Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

  16. Predicting protein functions from redundancies in large-scale protein interaction networks

    NASA Technical Reports Server (NTRS)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

  17. Intensive Working Memory Training Produces Functional Changes in Large-scale Frontoparietal Networks.

    PubMed

    Thompson, Todd W; Waskom, Michael L; Gabrieli, John D E

    2016-04-01

    Working memory is central to human cognition, and intensive cognitive training has been shown to expand working memory capacity in a given domain. It remains unknown, however, how the neural systems that support working memory are altered through intensive training to enable the expansion of working memory capacity. We used fMRI to measure plasticity in activations associated with complex working memory before and after 20 days of training. Healthy young adults were randomly assigned to train on either a dual n-back working memory task or a demanding visuospatial attention task. Training resulted in substantial and task-specific expansion of dual n-back abilities accompanied by changes in the relationship between working memory load and activation. Training differentially affected activations in two large-scale frontoparietal networks thought to underlie working memory: the executive control network and the dorsal attention network. Activations in both networks linearly scaled with working memory load before training, but training dissociated the role of the two networks and eliminated this relationship in the executive control network. Load-dependent functional connectivity both within and between these two networks increased following training, and the magnitudes of increased connectivity were positively correlated with improvements in task performance. These results provide insight into the adaptive neural systems that underlie large gains in working memory capacity through training.

  18. Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone

    PubMed Central

    Kraguljac, Nina Vanessa; White, David Matthew; Hadley, Jennifer Ann; Visscher, Kristina; Knight, David; ver Hoef, Lawrence; Falola, Blessing; Lahti, Adrienne Carol

    2015-01-01

    Objective To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. Material and methods 34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps. Results In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone. Conclusions Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity. PMID:26793436

  19. Inference of functional properties from large-scale analysis of enzyme superfamilies.

    PubMed

    Brown, Shoshana D; Babbitt, Patricia C

    2012-01-02

    As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.

  20. Optical correlator using very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators

    NASA Technical Reports Server (NTRS)

    Turner, Richard M.; Jared, David A.; Sharp, Gary D.; Johnson, Kristina M.

    1993-01-01

    The use of 2-kHz 64 x 64 very-large-scale integrated circuit/ferroelectric-liquid-crystal electrically addressed spatial light modulators as the input and filter planes of a VanderLugt-type optical correlator is discussed. Liquid-crystal layer thickness variations that are present in the devices are analyzed, and the effects on correlator performance are investigated through computer simulations. Experimental results from the very-large-scale-integrated / ferroelectric-liquid-crystal optical-correlator system are presented and are consistent with the level of performance predicted by the simulations.

  1. Energetics and Structural Characterization of the large-scale Functional Motion of Adenylate Kinase

    NASA Astrophysics Data System (ADS)

    Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

    2015-02-01

    Adenylate Kinase (AK) is a signal transducing protein that regulates cellular energy homeostasis balancing between different conformations. An alteration of its activity can lead to severe pathologies such as heart failure, cancer and neurodegenerative diseases. A comprehensive elucidation of the large-scale conformational motions that rule the functional mechanism of this enzyme is of great value to guide rationally the development of new medications. Here using a metadynamics-based computational protocol we elucidate the thermodynamics and structural properties underlying the AK functional transitions. The free energy estimation of the conformational motions of the enzyme allows characterizing the sequence of events that regulate its action. We reveal the atomistic details of the most relevant enzyme states, identifying residues such as Arg119 and Lys13, which play a key role during the conformational transitions and represent druggable spots to design enzyme inhibitors. Our study offers tools that open new areas of investigation on large-scale motion in proteins.

  2. Searching for a correlation between cosmic-ray sources above 10{sup 19} eV and large scale structure

    SciTech Connect

    Kashti, Tamar; Waxman, Eli E-mail: eli.waxman@weizmann.ac.il

    2008-05-15

    We study the anisotropy signature which is expected if the sources of ultrahigh energy, >10{sup 19} eV, cosmic rays (UHECRs) are extra-galactic and trace the large scale distribution of luminous matter. Using the PSCz galaxy catalog as a tracer of the large scale structure (LSS), we derive the expected all sky angular distribution of the UHECR intensity. We define a statistic that measures the correlation between the predicted and observed UHECR arrival direction distributions, and show that it is more sensitive to the expected anisotropy signature than the power spectrum and the two-point correlation function. The distribution of the correlation statistic is not sensitive to the unknown redshift evolution of UHECR source density and to the unknown strength and structure of inter-galactic magnetic fields. We show, using this statistic, that recently published >5.7 Multiplication-Sign 10{sup 19} eV Auger data are inconsistent with isotropy at Asymptotically-Equal-To 98% CL, and consistent with a source distribution that traces LSS, with some preference for a source distribution that is biased with respect to the galaxy distribution. The anisotropy signature should be detectable also at lower energy, >4 Multiplication-Sign 10{sup 19} eV. A few-fold increase of the Auger exposure is likely to increase the significance to >99% CL, but not to>99.9% CL (unless the UHECR source density is comparable to or larger than that of galaxies). In order to distinguish between different bias models, the systematic uncertainty in the absolute energy calibration of the experiments should be reduced to well below the current Asymptotically-Equal-To 25%.

  3. Large-Scale Brain Networks of the Human Left Temporal Pole: A Functional Connectivity MRI Study

    PubMed Central

    Pascual, Belen; Masdeu, Joseph C.; Hollenbeck, Mark; Makris, Nikos; Insausti, Ricardo; Ding, Song-Lin; Dickerson, Bradford C.

    2015-01-01

    The most rostral portion of the human temporal cortex, the temporal pole (TP), has been described as “enigmatic” because its functional neuroanatomy remains unclear. Comparative anatomy studies are only partially helpful, because the human TP is larger and cytoarchitectonically more complex than in nonhuman primates. Considered by Brodmann as a single area (BA 38), the human TP has been recently parceled into an array of cytoarchitectonic subfields. In order to clarify the functional connectivity of subregions of the TP, we undertook a study of 172 healthy adults using resting-state functional connectivity MRI. Remarkably, a hierarchical cluster analysis performed to group the seeds into distinct subsystems according to their large-scale functional connectivity grouped 87.5% of the seeds according to the recently described cytoarchitectonic subregions of the TP. Based on large-scale functional connectivity, there appear to be 4 major subregions of the TP: 1) dorsal, with predominant connectivity to auditory/somatosensory and language networks; 2) ventromedial, predominantly connected to visual networks; 3) medial, connected to paralimbic structures; and 4) anterolateral, connected to the default-semantic network. The functional connectivity of the human TP, far more complex than its known anatomic connectivity in monkey, is concordant with its hypothesized role as a cortical convergence zone. PMID:24068551

  4. Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection.

    PubMed

    Fornito, Alex; Harrison, Ben J; Zalesky, Andrew; Simons, Jon S

    2012-07-31

    Analyses of functional interactions between large-scale brain networks have identified two broad systems that operate in apparent competition or antagonism with each other. One system, termed the default mode network (DMN), is thought to support internally oriented processing. The other system acts as a generic external attention system (EAS) and mediates attention to exogenous stimuli. Reports that the DMN and EAS show anticorrelated activity across a range of experimental paradigms suggest that competition between these systems supports adaptive behavior. Here, we used functional MRI to characterize functional interactions between the DMN and different EAS components during performance of a recollection task known to coactivate regions of both networks. Using methods to isolate task-related, context-dependent changes in functional connectivity between these systems, we show that increased cooperation between the DMN and a specific right-lateralized frontoparietal component of the EAS is associated with more rapid memory recollection. We also show that these cooperative dynamics are facilitated by a dynamic reconfiguration of the functional architecture of the DMN into core and transitional modules, with the latter serving to enhance integration with frontoparietal regions. In particular, the right posterior cingulate cortex may act as a critical information-processing hub that provokes these context-dependent reconfigurations from an intrinsic or default state of antagonism. Our findings highlight the dynamic, context-dependent nature of large-scale brain dynamics and shed light on their contribution to individual differences in behavior.

  5. Large-scale photonic integration for advanced all-optical routing functions

    NASA Astrophysics Data System (ADS)

    Nicholes, Steven C.

    Advanced InP-based photonic integrated circuits are a critical technology to manage the increasing bandwidth demands of next-generation all-optical networks. Integrating many of the discrete functions required in optical networks into a single device provides a reduction in system footprint and optical losses by eliminating the fiber coupling junctions between components. This translates directly into increased system reliability and cost savings. Although many key network components have been realized via InP-based monolithic integration over the years, truly large-scale photonic ICs have only recently emerged in the marketplace. This lag-time has been mostly due to historically low device yields. In all-optical routing applications, large-scale photonic ICs may be able to address two of the key roadblocks associated with scaling modern electronic routers to higher capacities---namely, power and size. If the functions of dynamic wavelength conversion and routing are moved to the optical layer, we can eliminate the need for power-hungry optical-to-electrical (O/E) and electrical-to-optical (E/O) data conversions at each router node. Additionally, large-scale photonic ICs could reduce the footprint of such a system by combining the similar functions of each port onto a single chip. However, robust design and manufacturing techniques that will enable high-yield production of these chips must be developed. In this work, we demonstrate a monolithic tunable optical router (MOTOR) chip consisting of an array of eight 40-Gbps wavelength converters and a passive arrayed-waveguide grating router that functions as the packet-forwarding switch fabric of an all-optical router. The device represents one of the most complex InP photonic ICs ever reported, with more than 200 integrated functional elements in a single chip. Single-channel 40 Gbps wavelength conversion and channel switching using 231-1 PRBS data showed a power penalty as low as 4.5 dB with less than 2 W drive power

  6. Effective Boolean dynamics analysis to identify functionally important genes in large-scale signaling networks.

    PubMed

    Trinh, Hung-Cuong; Kwon, Yung-Keun

    2015-11-01

    Efficiently identifying functionally important genes in order to understand the minimal requirements of normal cellular development is challenging. To this end, a variety of structural measures have been proposed and their effectiveness has been investigated in recent literature; however, few studies have shown the effectiveness of dynamics-based measures. This led us to investigate a dynamic measure to identify functionally important genes, and the effectiveness of which was verified through application on two large-scale human signaling networks. We specifically consider Boolean sensitivity-based dynamics against an update-rule perturbation (BSU) as a dynamic measure. Through investigations on two large-scale human signaling networks, we found that genes with relatively high BSU values show slower evolutionary rate and higher proportions of essential genes and drug targets than other genes. Gene-ontology analysis showed clear differences between the former and latter groups of genes. Furthermore, we compare the identification accuracies of essential genes and drug targets via BSU and five well-known structural measures. Although BSU did not always show the best performance, it effectively identified the putative set of genes, which is significantly different from the results obtained via the structural measures. Most interestingly, BSU showed the highest synergy effect in identifying the functionally important genes in conjunction with other measures. Our results imply that Boolean-sensitive dynamics can be used as a measure to effectively identify functionally important genes in signaling networks.

  7. Functional models for large-scale gene regulation networks: realism and fiction.

    PubMed

    Lagomarsino, Marco Cosentino; Bassetti, Bruno; Castellani, Gastone; Remondini, Daniel

    2009-04-01

    High-throughput experiments are shedding light on the topology of large regulatory networks and at the same time their functional states, namely the states of activation of the nodes (for example transcript or protein levels) in different conditions, times, environments. We now possess a certain amount of information about these two levels of description, stored in libraries, databases and ontologies. A current challenge is to bridge the gap between topology and function, i.e. developing quantitative models aimed at characterizing the expression patterns of large sets of genes. However, approaches that work well for small networks become impossible to master at large scales, mainly because parameters proliferate. In this review we discuss the state of the art of large-scale functional network models, addressing the issue of what can be considered as "realistic" and what the main limitations may be. We also show some directions for future work, trying to set the goals that future models should try to achieve. Finally, we will emphasize the possible benefits in the understanding of biological mechanisms underlying complex multifactorial diseases, and in the development of novel strategies for the description and the treatment of such pathologies.

  8. Aberrant intra-salience network dynamic functional connectivity impairs large-scale network interactions in schizophrenia.

    PubMed

    Wang, Xiangpeng; Zhang, Wenwen; Sun, Yujing; Hu, Min; Chen, Antao

    2016-12-01

    Aberrant functional interactions between several large-scale networks, especially the central executive network (CEN), the default mode network (DMN) and the salience network (SN), have been postulated as core pathophysiologic features of schizophrenia; however, the attributing factors of which remain unclear. The study employed resting-state fMRI with 77 participants (42 patients and 35 controls). We performed dynamic functional connectivity (DFC) and functional connectivity (FC) analyses to explore the connectivity patterns of these networks. Furthermore, we performed a structural equation model (SEM) analysis to explore the possible role of the SN in modulating network interactions. The results were as follows: (1) The inter-network connectivity showed decreased connectivity strength and increased time-varying instability in schizophrenia; (2) The SN manifested schizophrenic intra-network dysfunctions in both the FC and DFC patterns; (3) The connectivity properties of the SN were effective in discriminating controls from patients; (4) In patients, the dynamic intra-SN connectivity negatively predicted the inter-network FC, and this effect was mediated by intra-SN connectivity strength. These findings suggest that schizophrenia show systematic deficits in temporal stability of large-scale network connectivity. Furthermore, aberrant network interactions in schizophrenia could be attributed to instable intra-SN connectivity and the dysfunction of the SN may be an intrinsic biomarker of the disease.

  9. Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

    PubMed Central

    Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

    2015-01-01

    Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

  10. A Large-Scale Functional Screen to Identify Epigenetic Repressors of Retrotransposon Expression.

    PubMed

    Ecco, Gabriela; Rowe, Helen M; Trono, Didier

    2016-01-01

    Deposition of epigenetic marks is an important layer of the transcriptional control of retrotransposons, especially during early embryogenesis. Krüppel-associated box domain zinc finger proteins (KRAB-ZFPs) are one of the largest families of transcription factors, and collectively partake in this process by tethering to thousands of retroelement-containing genomic loci their cofactor KAP1, which acts as a scaffold for a heterochromatin-inducing machinery. However, while the sequence-specific DNA binding potential of the poly-zinc finger-containing KRAB-ZFPs is recognized, very few members of the family have been assigned specific targets. In this chapter, we describe a large-scale functional screen to identify the retroelements bound by individual murine KRAB-ZFPs. Our method is based on the automated transfection of a library of mouse KRAB-ZFP-containing vectors into 293T cells modified to express GFP from a PGK promoter harboring in its immediate vicinity a KAP1-recruiting retroelement-derived sequence. Analysis is then performed by plate reader and flow cytometry fluorescence readout. Such large-scale DNA-centered functional approach can not only help to identify the trans-acting factors responsible for silencing retrotransposons, but also serve as a model for dissecting the transcriptional networks influenced by retroelement-derived cis-acting sequences.

  11. Large-scale resting state network correlates of cognitive impairment in Parkinson's disease and related dopaminergic deficits

    PubMed Central

    Lebedev, Alexander V.; Westman, Eric; Simmons, Andrew; Lebedeva, Aleksandra; Siepel, Françoise J.; Pereira, Joana B.; Aarsland, Dag

    2014-01-01

    Cognitive impairment is a common non-motor feature of Parkinson's disease (PD). Understanding the neural mechanisms of this deficit is crucial for the development of efficient methods for treatment monitoring and augmentation of cognitive functions in PD patients. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson's Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with 123I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox (BCT) was used to extract nodal strength from all ROIs, and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable (LV) scores were matched with the performances in the three cognitive domains (memory, visuospatial, and executive) and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on the modularity of the “cognitive network” was analyzed. For the range of deficits studied, better executive performance was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This profile was also characterized by a relative preservation of nigrostriatal dopaminergic function. The profile associated with better memory performance correlated with increased

  12. GenASiS Basics: Object-oriented utilitarian functionality for large-scale physics simulations

    DOE PAGES

    Cardall, Christian Y.; Budiardja, Reuben D.

    2015-06-11

    Aside from numerical algorithms and problem setup, large-scale physics simulations on distributed-memory supercomputers require more basic utilitarian functionality, such as physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. Here we describe and make available Fortran 2003 classes furnishing extensible object-oriented implementations of this sort of rudimentary functionality, along with individual `unit test' programs and larger example problems demonstrating their use. Lastly, these classes compose the Basics division of our developing astrophysics simulation code GenASiS (General Astrophysical Simulation System), but their fundamental nature makes themmore » useful for physics simulations in many fields.« less

  13. GENASIS Basics: Object-oriented utilitarian functionality for large-scale physics simulations

    NASA Astrophysics Data System (ADS)

    Cardall, Christian Y.; Budiardja, Reuben D.

    2015-11-01

    Aside from numerical algorithms and problem setup, large-scale physics simulations on distributed-memory supercomputers require more basic utilitarian functionality, such as physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. Here we describe and make available Fortran 2003 classes furnishing extensible object-oriented implementations of this sort of rudimentary functionality, along with individual 'unit test' programs and larger example problems demonstrating their use. These classes compose the Basics division of our developing astrophysics simulation code GENASIS (General Astrophysical Simulation System), but their fundamental nature makes them useful for physics simulations in many fields.

  14. GenASiS Basics: Object-oriented utilitarian functionality for large-scale physics simulations

    SciTech Connect

    Cardall, Christian Y.; Budiardja, Reuben D.

    2015-06-11

    Aside from numerical algorithms and problem setup, large-scale physics simulations on distributed-memory supercomputers require more basic utilitarian functionality, such as physical units and constants; display to the screen or standard output device; message passing; I/O to disk; and runtime parameter management and usage statistics. Here we describe and make available Fortran 2003 classes furnishing extensible object-oriented implementations of this sort of rudimentary functionality, along with individual `unit test' programs and larger example problems demonstrating their use. Lastly, these classes compose the Basics division of our developing astrophysics simulation code GenASiS (General Astrophysical Simulation System), but their fundamental nature makes them useful for physics simulations in many fields.

  15. Gravity at the horizon: on relativistic effects, CMB-LSS correlations and ultra-large scales in Horndeski's theory

    NASA Astrophysics Data System (ADS)

    Renk, Janina; Zumalacárregui, Miguel; Montanari, Francesco

    2016-07-01

    We address the impact of consistent modifications of gravity on the largest observable scales, focusing on relativistic effects in galaxy number counts and the cross-correlation between the matter large scale structure (LSS) distribution and the cosmic microwave background (CMB). Our analysis applies to a very broad class of general scalar-tensor theories encoded in the Horndeski Lagrangian and is fully consistent on linear scales, retaining the full dynamics of the scalar field and not assuming quasi-static evolution. As particular examples we consider self-accelerating Covariant Galileons, Brans-Dicke theory and parameterizations based on the effective field theory of dark energy, using the hi class code to address the impact of these models on relativistic corrections to LSS observables. We find that especially effects which involve integrals along the line of sight (lensing convergence, time delay and the integrated Sachs-Wolfe effect—ISW) can be considerably modified, and even lead to O(1000%) deviations from General Relativity in the case of the ISW effect for Galileon models, for which standard probes such as the growth function only vary by O(10%). These effects become dominant when correlating galaxy number counts at different redshifts and can lead to ~ 50% deviations in the total signal that might be observable by future LSS surveys. Because of their integrated nature, these deep-redshift cross-correlations are sensitive to modifications of gravity even when probing eras much before dark energy domination. We further isolate the ISW effect using the cross-correlation between LSS and CMB temperature anisotropies and use current data to further constrain Horndeski models. Forthcoming large-volume galaxy surveys using multiple-tracers will search for all these effects, opening a new window to probe gravity and cosmic acceleration at the largest scales available in our universe.

  16. Large-scale structure after COBE: Peculiar velocities and correlations of cold dark matter halos

    NASA Technical Reports Server (NTRS)

    Zurek, Wojciech H.; Quinn, Peter J.; Salmon, John K.; Warren, Michael S.

    1994-01-01

    Large N-body simulations on parallel supercomputers allow one to simultaneously investigate large-scale structure and the formation of galactic halos with unprecedented resolution. Our study shows that the masses as well as the spatial distribution of halos on scales of tens of megaparsecs in a cold dark matter (CDM) universe with the spectrum normalized to the anisotropies detected by Cosmic Background Explorer (COBE) is compatible with the observations. We also show that the average value of the relative pairwise velocity dispersion sigma(sub v) - used as a principal argument against COBE-normalized CDM models-is significantly lower for halos than for individual particles. When the observational methods of extracting sigma(sub v) are applied to the redshift catalogs obtained from the numerical experiments, estimates differ significantly between different observation-sized samples and overlap observational estimates obtained following the same procedure.

  17. The HI Content of Galaxies as a Function of Local Density and Large-Scale Environment

    NASA Astrophysics Data System (ADS)

    Thoreen, Henry; Cantwell, Kelly; Maloney, Erin; Cane, Thomas; Brough Morris, Theodore; Flory, Oscar; Raskin, Mark; Crone-Odekon, Mary; ALFALFA Team

    2017-01-01

    We examine the HI content of galaxies as a function of environment, based on a catalogue of 41527 galaxies that are part of the 70% complete Arecibo Legacy Fast-ALFA (ALFALFA) survey. We use nearest-neighbor methods to characterize local environment, and a modified version of the algorithm developed for the Galaxy and Mass Assembly (GAMA) survey to classify large-scale environment as group, filament, tendril, or void. We compare the HI content in these environments using statistics that include both HI detections and the upper limits on detections from ALFALFA. The large size of the sample allows to statistically compare the HI content in different environments for early-type galaxies as well as late-type galaxies. This work is supported by NSF grants AST-1211005 and AST-1637339, the Skidmore Faculty-Student Summer Research program, and the Schupf Scholars program.

  18. ERRATUM: Correlations at Large Scales and the Onset of Turbulence in the Fast Solar Wind

    NASA Technical Reports Server (NTRS)

    Wicks, R. T.; Roberts, D. A.; Mallet, A.; Schekochihin, A. A.; Horbury, T. S.; Chen, C. H. K.

    2014-01-01

    We show that the scaling of structure functions of magnetic and velocity fields in a mostly highly Alfvenic fast solar wind stream depends strongly on the joint distribution of the dimensionless measures of cross helicity and residual energy. Already at very low frequencies, fluctuations that are both more balanced (cross helicity approx. 0) and equipartitioned (residual energy approx.0) have steep structure functions reminiscent of "turbulent" scalings usually associated with the inertial range. Fluctuations that are magnetically dominated (residual energy approx. –1), and so have closely anti-aligned Elsasser-field vectors, or are imbalanced (cross helicity approx. 1), and so have closely aligned magnetic and velocity vectors, have wide "1/f" ranges typical of fast solar wind. We conclude that the strength of nonlinear interactions of individual fluctuations within a stream, diagnosed by the degree of correlation in direction and magnitude of magnetic and velocity fluctuations, determines the extent of the 1/f region observed, and thus the onset scale for the turbulent cascade.

  19. Correlations at large scales and the onset of turbulence in the fast solar wind

    SciTech Connect

    Wicks, R. T.; Roberts, D. A.; Mallet, A.; Schekochihin, A. A.; Horbury, T. S.; Chen, C. H. K.

    2013-12-01

    We show that the scaling of structure functions of magnetic and velocity fields in a mostly highly Alfvénic fast solar wind stream depends strongly on the joint distribution of the dimensionless measures of cross helicity and residual energy. Already at very low frequencies, fluctuations that are both more balanced (cross helicity ∼0) and equipartitioned (residual energy ∼0) have steep structure functions reminiscent of 'turbulent' scalings usually associated with the inertial range. Fluctuations that are magnetically dominated (residual energy ∼–1), and so have closely anti-aligned Elsasser-field vectors, or are imbalanced (cross helicity ∼1), and so have closely aligned magnetic and velocity vectors, have wide '1/f' ranges typical of fast solar wind. We conclude that the strength of nonlinear interactions of individual fluctuations within a stream, diagnosed by the degree of correlation in direction and magnitude of magnetic and velocity fluctuations, determines the extent of the 1/f region observed, and thus the onset scale for the turbulent cascade.

  20. Large-scale All-electron Density Functional Theory Calculations using Enriched Finite Element Method

    NASA Astrophysics Data System (ADS)

    Kanungo, Bikash; Gavini, Vikram

    We present a computationally efficient method to perform large-scale all-electron density functional theory calculations by enriching the Lagrange polynomial basis in classical finite element (FE) discretization with atom-centered numerical basis functions, which are obtained from the solutions of the Kohn-Sham (KS) problem for single atoms. We term these atom-centered numerical basis functions as enrichment functions. The integrals involved in the construction of the discrete KS Hamiltonian and overlap matrix are computed using an adaptive quadrature grid based on gradients in the enrichment functions. Further, we propose an efficient scheme to invert the overlap matrix by exploiting its LDL factorization and employing spectral finite elements along with Gauss-Lobatto quadrature rules. Finally, we use a Chebyshev polynomial based acceleration technique to compute the occupied eigenspace in each self-consistent iteration. We demonstrate the accuracy, efficiency and scalability of the proposed method on various metallic and insulating benchmark systems, with systems ranging in the order of 10,000 electrons. We observe a 50-100 fold reduction in the overall computational time when compared to classical FE calculations while being commensurate with the desired chemical accuracy. We acknowledge the support of NSF (Grant No. 1053145) and ARO (Grant No. W911NF-15-1-0158) in conducting this work.

  1. FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data.

    PubMed

    Uchiyama, Takeru; Irie, Mitsuru; Mori, Hiroshi; Kurokawa, Ken; Yamada, Takuji

    2015-01-01

    Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree), a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the "Functional Tree map", a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree's analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree's capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree's capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research.

  2. Galaxy clustering on large scales.

    PubMed Central

    Efstathiou, G

    1993-01-01

    I describe some recent observations of large-scale structure in the galaxy distribution. The best constraints come from two-dimensional galaxy surveys and studies of angular correlation functions. Results from galaxy redshift surveys are much less precise but are consistent with the angular correlations, provided the distortions in mapping between real-space and redshift-space are relatively weak. The galaxy two-point correlation function, rich-cluster two-point correlation function, and galaxy-cluster cross-correlation function are all well described on large scales ( greater, similar 20h-1 Mpc, where the Hubble constant, H0 = 100h km.s-1.Mpc; 1 pc = 3.09 x 10(16) m) by the power spectrum of an initially scale-invariant, adiabatic, cold-dark-matter Universe with Gamma = Omegah approximately 0.2. I discuss how this fits in with the Cosmic Background Explorer (COBE) satellite detection of large-scale anisotropies in the microwave background radiation and other measures of large-scale structure in the Universe. PMID:11607400

  3. Large-scale Granger causality analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  4. DGDFT: A massively parallel method for large scale density functional theory calculations

    SciTech Connect

    Hu, Wei Yang, Chao; Lin, Lin

    2015-09-28

    We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10{sup −4} Hartree/atom in terms of the error of energy and 6.2 × 10{sup −4} Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

  5. DGDFT: A massively parallel method for large scale density functional theory calculations.

    PubMed

    Hu, Wei; Lin, Lin; Yang, Chao

    2015-09-28

    We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) method, for efficient large-scale Kohn-Sham DFT based electronic structure calculations. The DGDFT method uses adaptive local basis (ALB) functions generated on-the-fly during the self-consistent field iteration to represent the solution to the Kohn-Sham equations. The use of the ALB set provides a systematic way to improve the accuracy of the approximation. By using the pole expansion and selected inversion technique to compute electron density, energy, and atomic forces, we can make the computational complexity of DGDFT scale at most quadratically with respect to the number of electrons for both insulating and metallic systems. We show that for the two-dimensional (2D) phosphorene systems studied here, using 37 basis functions per atom allows us to reach an accuracy level of 1.3 × 10(-4) Hartree/atom in terms of the error of energy and 6.2 × 10(-4) Hartree/bohr in terms of the error of atomic force, respectively. DGDFT can achieve 80% parallel efficiency on 128,000 high performance computing cores when it is used to study the electronic structure of 2D phosphorene systems with 3500-14 000 atoms. This high parallel efficiency results from a two-level parallelization scheme that we will describe in detail.

  6. Multifractal Detrended Cross-Correlation Analysis for Large-Scale Warehouse-Out Behaviors

    NASA Astrophysics Data System (ADS)

    Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou

    2015-09-01

    Based on cross-correlation algorithm, we analyze the correlation property of warehouse-out quantity of different warehouses, respectively, and different products of each warehouse. Our study identifies that significant cross-correlation relationship for warehouse-out quantity exists among different warehouses and different products of a warehouse. Further, we take multifractal detrended cross-correlation analysis for warehouse-out quantity among different warehouses and different products of a warehouse. The results show that for the warehouse-out behaviors of total amount, different warehouses and different products of a warehouse significantly follow multifractal property. Specifically for each warehouse, the coupling relationships of rebar and wire rod reveal long-term memory characteristics, no matter for large fluctuation or small one. The cross-correlation effect on long-range memory property among warehouses probably has less to do with product types,and the long-term memory of YZ warehouse is greater than others especially in total amount and wire rod product. Finally, we shuffle and surrogate data to explore the source of multifractal cross-correlation property in logistics system. Taking the total amount of warehouse-out quantity as example, we confirm that the fat-tail distribution of warehouse-out quantity sequences is the main factor for multifractal cross-correlation. Through comparing the performance of the multifractal detrended cross-correlation analysis (MF-DCCA), centered multifractal detrending moving average cross-correlation analysis (MF-X-DMA) algorithms, the forward and backward MF-X-DMA algorithms, we find that the forward and backward MF-X-DMA algorithms exhibit a better performance than the other ones.

  7. Spatial correlation of atmospheric wind at scales relevant for large scale wind turbines

    NASA Astrophysics Data System (ADS)

    Bardal, L. M.; Sætran, L. R.

    2016-09-01

    Wind measurements a short distance upstream of a wind turbine can provide input for a feedforward wind turbine controller. Since the turbulent wind field will be different at the point/plane of measurement and the rotor plane the degree of correlation between wind speed at two points in space both in the longitudinal and lateral direction should be evaluated. This study uses a 2D array of mast mounted anemometers to evaluate cross-correlation of longitudinal wind speed. The degree of correlation is found to increase with height and decrease with atmospheric stability. The correlation is furthermore considerably larger for longitudinal separation than for lateral separation. The integral length scale of turbulence is also considered.

  8. Hybrid Multiphoton Volumetric Functional Imaging of Large Scale Bioengineered Neuronal Networks

    PubMed Central

    Paluch, Shir; Dvorkin, Roman; Brosh, Inbar; Shoham, Shy

    2014-01-01

    Planar neural networks and interfaces serve as versatile in vitro models of central nervous system physiology, but adaptations of related methods to three dimensions (3D) have met with limited success. Here, we demonstrate for the first time volumetric functional imaging in a bio-engineered neural tissue growing in a transparent hydrogel with cortical cellular and synaptic densities, by introducing complementary new developments in nonlinear microscopy and neural tissue engineering. Our system uses a novel hybrid multiphoton microscope design combining a 3D scanning-line temporal-focusing subsystem and a conventional laser-scanning multiphoton microscope to provide functional and structural volumetric imaging capabilities: dense microscopic 3D sampling at tens of volumes/sec of structures with mm-scale dimensions containing a network of over 1000 developing cells with complex spontaneous activity patterns. These developments open new opportunities for large-scale neuronal interfacing and for applications of 3D engineered networks ranging from basic neuroscience to the screening of neuroactive substances. PMID:24898000

  9. Functional and large-scale testing of the ATLAS distributed analysis facilities with Ganga

    NASA Astrophysics Data System (ADS)

    Vanderster, D. C.; Elmsheuser, J.; Biglietti, M.; Galeazzi, F.; Serfon, C.; Slater, M.

    2010-04-01

    Effective distributed user analysis requires a system which meets the demands of running arbitrary user applications on sites with varied configurations and availabilities. The challenge of tracking such a system requires a tool to monitor not only the functional statuses of each grid site, but also to perform large-scale analysis challenges on the ATLAS grids. This work presents one such tool, the ATLAS GangaRobot, and the results of its use in tests and challenges. For functional testing, the GangaRobot performs daily tests of all sites; specifically, a set of exemplary applications are submitted to all sites and then monitored for success and failure conditions. These results are fed back into Ganga to improve job placements by avoiding currently problematic sites. For analysis challenges, a cloud is first prepared by replicating a number of desired DQ2 datasets across all the sites. Next, the GangaRobot is used to submit and manage a large number of jobs targeting these datasets. The high-loads resulting from multiple parallel instances of the GangaRobot exposes shortcomings in storage and network configurations. The results from a series of cloud-by-cloud analysis challenges starting in fall 2008 are presented.

  10. Large-scale functional models of visual cortex for remote sensing

    SciTech Connect

    Brumby, Steven P; Kenyon, Garrett; Rasmussen, Craig E; Swaminarayan, Sriram; Bettencourt, Luis; Landecker, Will

    2009-01-01

    Neuroscience has revealed many properties of neurons and of the functional organization of visual cortex that are believed to be essential to human vision, but are missing in standard artificial neural networks. Equally important may be the sheer scale of visual cortex requiring {approx}1 petaflop of computation. In a year, the retina delivers {approx}1 petapixel to the brain, leading to massively large opportunities for learning at many levels of the cortical system. We describe work at Los Alamos National Laboratory (LANL) to develop large-scale functional models of visual cortex on LANL's Roadrunner petaflop supercomputer. An initial run of a simple region VI code achieved 1.144 petaflops during trials at the IBM facility in Poughkeepsie, NY (June 2008). Here, we present criteria for assessing when a set of learned local representations is 'complete' along with general criteria for assessing computer vision models based on their projected scaling behavior. Finally, we extend one class of biologically-inspired learning models to problems of remote sensing imagery.

  11. Hybrid multiphoton volumetric functional imaging of large-scale bioengineered neuronal networks

    NASA Astrophysics Data System (ADS)

    Dana, Hod; Marom, Anat; Paluch, Shir; Dvorkin, Roman; Brosh, Inbar; Shoham, Shy

    2014-06-01

    Planar neural networks and interfaces serve as versatile in vitro models of central nervous system physiology, but adaptations of related methods to three dimensions (3D) have met with limited success. Here, we demonstrate for the first time volumetric functional imaging in a bioengineered neural tissue growing in a transparent hydrogel with cortical cellular and synaptic densities, by introducing complementary new developments in nonlinear microscopy and neural tissue engineering. Our system uses a novel hybrid multiphoton microscope design combining a 3D scanning-line temporal-focusing subsystem and a conventional laser-scanning multiphoton microscope to provide functional and structural volumetric imaging capabilities: dense microscopic 3D sampling at tens of volumes per second of structures with mm-scale dimensions containing a network of over 1,000 developing cells with complex spontaneous activity patterns. These developments open new opportunities for large-scale neuronal interfacing and for applications of 3D engineered networks ranging from basic neuroscience to the screening of neuroactive substances.

  12. Inferring cortical function in the mouse visual system through large-scale systems neuroscience.

    PubMed

    Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

    2016-07-05

    The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort.

  13. Inferring cortical function in the mouse visual system through large-scale systems neuroscience

    PubMed Central

    Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W.; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R. Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

    2016-01-01

    The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort. PMID:27382147

  14. Large-Scale Meta-Analysis of Human Medial Frontal Cortex Reveals Tripartite Functional Organization

    PubMed Central

    Chang, Luke J.; Banich, Marie T.; Wager, Tor D.; Yarkoni, Tal

    2016-01-01

    The functional organization of human medial frontal cortex (MFC) is a subject of intense study. Using fMRI, the MFC has been associated with diverse psychological processes, including motor function, cognitive control, affect, and social cognition. However, there have been few large-scale efforts to comprehensively map specific psychological functions to subregions of medial frontal anatomy. Here we applied a meta-analytic data-driven approach to nearly 10,000 fMRI studies to identify putatively separable regions of MFC and determine which psychological states preferentially recruit their activation. We identified regions at several spatial scales on the basis of meta-analytic coactivation, revealing three broad functional zones along a rostrocaudal axis composed of 2–4 smaller subregions each. Multivariate classification analyses aimed at identifying the psychological functions most strongly predictive of activity in each region revealed a tripartite division within MFC, with each zone displaying a relatively distinct functional signature. The posterior zone was associated preferentially with motor function, the middle zone with cognitive control, pain, and affect, and the anterior with reward, social processing, and episodic memory. Within each zone, the more fine-grained subregions showed distinct, but subtler, variations in psychological function. These results provide hypotheses about the functional organization of medial prefrontal cortex that can be tested explicitly in future studies. SIGNIFICANCE STATEMENT Activation of medial frontal cortex in fMRI studies is associated with a wide range of psychological states ranging from cognitive control to pain. However, this high rate of activation makes it challenging to determine how these various processes are topologically organized across medial frontal anatomy. We conducted a meta-analysis across nearly 10,000 studies to comprehensively map psychological states to discrete subregions in medial frontal cortex

  15. Large-scale atomistic density functional theory calculations of phosphorus-doped silicon quantum bits

    NASA Astrophysics Data System (ADS)

    Greenman, Loren; Whitley, Heather D.; Whaley, K. Birgitta

    2013-10-01

    We present density functional theory calculations of phosphorus dopants in bulk silicon and of several properties relating to their use as spin qubits for quantum computation. Rather than a mixed pseudopotential or a Heitler-London approach, we have used an explicit treatment for the phosphorus donor and examined the detailed electronic structure of the system as a function of the isotropic doping fraction, including lattice relaxation due to the presence of the impurity. Doping electron densities (ρdoped-ρbulk) and spin densities (ρ↑-ρ↓) are examined in order to study the properties of the dopant electron as a function of the isotropic doping fraction. Doping potentials (Vdoped-Vbulk) are also calculated for use in calculations of the scattering cross sections of the phosphorus dopants, which are important in the understanding of electrically detected magnetic resonance experiments. We find that the electron density around the dopant leads to nonspherical features in the doping potentials, such as trigonal lobes in the (001) plane at energy scales of +12 eV near the nucleus and of -700 meV extending away from the dopants. These features are generally neglected in effective mass theory and will affect the coupling between the donor electron and the phosphorus nucleus. Our density functional calculations reveal detail in the densities and potentials of the dopants which are not evident in calculations that do not include explicit treatment of the phosphorus donor atom and relaxation of the crystal lattice. These details can also be used to parametrize tight-binding models for simulation of large-scale devices.

  16. Perspective: Methods for large-scale density functional calculations on metallic systems

    NASA Astrophysics Data System (ADS)

    Aarons, Jolyon; Sarwar, Misbah; Thompsett, David; Skylaris, Chris-Kriton

    2016-12-01

    Current research challenges in areas such as energy and bioscience have created a strong need for Density Functional Theory (DFT) calculations on metallic nanostructures of hundreds to thousands of atoms to provide understanding at the atomic level in technologically important processes such as catalysis and magnetic materials. Linear-scaling DFT methods for calculations with thousands of atoms on insulators are now reaching a level of maturity. However such methods are not applicable to metals, where the continuum of states through the chemical potential and their partial occupancies provide significant hurdles which have yet to be fully overcome. Within this perspective we outline the theory of DFT calculations on metallic systems with a focus on methods for large-scale calculations, as required for the study of metallic nanoparticles. We present early approaches for electronic energy minimization in metallic systems as well as approaches which can impose partial state occupancies from a thermal distribution without access to the electronic Hamiltonian eigenvalues, such as the classes of Fermi operator expansions and integral expansions. We then focus on the significant progress which has been made in the last decade with developments which promise to better tackle the length-scale problem in metals. We discuss the challenges presented by each method, the likely future directions that could be followed and whether an accurate linear-scaling DFT method for metals is in sight.

  17. Correlating transcriptional networks to breast cancer survival: a large-scale coexpression analysis.

    PubMed

    Clarke, Colin; Madden, Stephen F; Doolan, Padraig; Aherne, Sinead T; Joyce, Helena; O'Driscoll, Lorraine; Gallagher, William M; Hennessy, Bryan T; Moriarty, Michael; Crown, John; Kennedy, Susan; Clynes, Martin

    2013-10-01

    Weighted gene coexpression network analysis (WGCNA) is a powerful 'guilt-by-association'-based method to extract coexpressed groups of genes from large heterogeneous messenger RNA expression data sets. We have utilized WGCNA to identify 11 coregulated gene clusters across 2342 breast cancer samples from 13 microarray-based gene expression studies. A number of these transcriptional modules were found to be correlated to clinicopathological variables (e.g. tumor grade), survival endpoints for breast cancer as a whole (disease-free survival, distant disease-free survival and overall survival) and also its molecular subtypes (luminal A, luminal B, HER2+ and basal-like). Examples of findings arising from this work include the identification of a cluster of proliferation-related genes that when upregulated correlated to increased tumor grade and were associated with poor survival in general. The prognostic potential of novel genes, for example, ubiquitin-conjugating enzyme E2S (UBE2S) within this group was confirmed in an independent data set. In addition, gene clusters were also associated with survival for breast cancer molecular subtypes including a cluster of genes that was found to correlate with prognosis exclusively for basal-like breast cancer. The upregulation of several single genes within this coexpression cluster, for example, the potassium channel, subfamily K, member 5 (KCNK5) was associated with poor outcome for the basal-like molecular subtype. We have developed an online database to allow user-friendly access to the coexpression patterns and the survival analysis outputs uncovered in this study (available at http://glados.ucd.ie/Coexpression/).

  18. Large-scale parallel surface functionalization of goblet-type whispering gallery mode microcavity arrays for biosensing applications.

    PubMed

    Bog, Uwe; Brinkmann, Falko; Kalt, Heinz; Koos, Christian; Mappes, Timo; Hirtz, Michael; Fuchs, Harald; Köber, Sebastian

    2014-10-15

    A novel surface functionalization technique is presented for large-scale selective molecule deposition onto whispering gallery mode microgoblet cavities. The parallel technique allows damage-free individual functionalization of the cavities, arranged on-chip in densely packaged arrays. As the stamp pad a glass slide is utilized, bearing phospholipids with different functional head groups. Coated microcavities are characterized and demonstrated as biosensors.

  19. Digital Image Correlation Techniques Applied to Large Scale Rocket Engine Testing

    NASA Technical Reports Server (NTRS)

    Gradl, Paul R.

    2016-01-01

    Rocket engine hot-fire ground testing is necessary to understand component performance, reliability and engine system interactions during development. The J-2X upper stage engine completed a series of developmental hot-fire tests that derived performance of the engine and components, validated analytical models and provided the necessary data to identify where design changes, process improvements and technology development were needed. The J-2X development engines were heavily instrumented to provide the data necessary to support these activities which enabled the team to investigate any anomalies experienced during the test program. This paper describes the development of an optical digital image correlation technique to augment the data provided by traditional strain gauges which are prone to debonding at elevated temperatures and limited to localized measurements. The feasibility of this optical measurement system was demonstrated during full scale hot-fire testing of J-2X, during which a digital image correlation system, incorporating a pair of high speed cameras to measure three-dimensional, real-time displacements and strains was installed and operated under the extreme environments present on the test stand. The camera and facility setup, pre-test calibrations, data collection, hot-fire test data collection and post-test analysis and results are presented in this paper.

  20. Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

    PubMed

    Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

    2016-12-01

    Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures.

  1. SU-E-T-531: Large--Scale DVH Quality Study: Correlated Aims Lead Relaxations

    SciTech Connect

    Nohadani, O; Roy, A; Das, I

    2015-06-15

    Purpose: Intensity modulated radiation therapy plans are designed to optimally target a tumor while sparing surrounding tissue. Desired dose distributions are iteratively approached via inverse planning. This leads to tradeoffs between clinical objectives for the planning target volume (PTV), organs at risk, and normal tissues. Dose volume histogram (DVHs) related aims are followed that are either institutional or internationally recommended. We analyze common goals and identify potential reasons that often lead to tradeoffs. Methods: 524 IMRT plans for various tumor sites were analyzed based on the main institutional DVH goal for PTV (D95) and the recommendations by ICRU-83 (D2, D50, and D98). Robust statistical tools are developed and applied to ensure that the results are immune to data uncertainties. The probability of violation was measured for each of the DVH goals based on the frequency of not meeting recommended doses. Conditional probabilities for satisfying and/or violating DVH aims were computed to test the hypothesized pair-wise relations between DVH aims. For example, for plans that satisfied D50, the probability of violating D98 was computed via P(D98 < 95% | 98% ≤ D50 ≤ 102%). The equality constraint D50 = 100% was relaxed to encompass the range [98,102]%. Results: A large majority of cases (88%) satisfied the institutional goal for PTV of D95 ≤ 95%. Similar consensus existed for D98. 51% of cases satisfied D2 ≥ 107%. However, only 18% of cases satisfied D50. The conditional probability showed correlations amongst the studied DVH goals. In fact, a negative correlation was revealed between D50 and D95 (and D98), suggesting that these competing goals cannot be satisfied concurrently. Conclusion: The majority of plans followed the institutional guidelines. The reason for their deviation from international recommendations seems to be that the latter goals are competing and cannot be satisfied concurrently in clinical practice.

  2. Risks of large-scale use of systemic insecticides to ecosystem functioning and services.

    PubMed

    Chagnon, Madeleine; Kreutzweiser, David; Mitchell, Edward A D; Morrissey, Christy A; Noome, Dominique A; Van der Sluijs, Jeroen P

    2015-01-01

    Large-scale use of the persistent and potent neonicotinoid and fipronil insecticides has raised concerns about risks to ecosystem functions provided by a wide range of species and environments affected by these insecticides. The concept of ecosystem services is widely used in decision making in the context of valuing the service potentials, benefits, and use values that well-functioning ecosystems provide to humans and the biosphere and, as an endpoint (value to be protected), in ecological risk assessment of chemicals. Neonicotinoid insecticides are frequently detected in soil and water and are also found in air, as dust particles during sowing of crops and aerosols during spraying. These environmental media provide essential resources to support biodiversity, but are known to be threatened by long-term or repeated contamination by neonicotinoids and fipronil. We review the state of knowledge regarding the potential impacts of these insecticides on ecosystem functioning and services provided by terrestrial and aquatic ecosystems including soil and freshwater functions, fisheries, biological pest control, and pollination services. Empirical studies examining the specific impacts of neonicotinoids and fipronil to ecosystem services have focused largely on the negative impacts to beneficial insect species (honeybees) and the impact on pollination service of food crops. However, here we document broader evidence of the effects on ecosystem functions regulating soil and water quality, pest control, pollination, ecosystem resilience, and community diversity. In particular, microbes, invertebrates, and fish play critical roles as decomposers, pollinators, consumers, and predators, which collectively maintain healthy communities and ecosystem integrity. Several examples in this review demonstrate evidence of the negative impacts of systemic insecticides on decomposition, nutrient cycling, soil respiration, and invertebrate populations valued by humans. Invertebrates

  3. Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

    PubMed

    Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

    2016-01-01

    Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities.

  4. Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

    PubMed

    Bassel, George W; Glaab, Enrico; Marquez, Julietta; Holdsworth, Michael J; Bacardit, Jaume

    2011-09-01

    The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed "coprediction," is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/.

  5. Correlated particle and magnetic field observations of a large-scale magnetic loop structure behind an interplanetary shock

    NASA Technical Reports Server (NTRS)

    Sanderson, T. R.; Marsden, R. G.; Reinhard, R.; Wenzel, K.-P.; Smith, E. J.

    1983-01-01

    From a survey of observations on ISEE-3, an example of correlated particle and magnetic field observations of a large-scale magnetic loop structure is presented. Bidirectional proton fluxes were observed for a period of 40 hours in the energy range 35-1600 keV approximately 12 hours after the passage of the interplanetary shock of December 11, 1980, and directly after the passage of a discontinuity. For each of the eight logarithmically spaced energy channels, a three-dimensional anisotropy analysis reveals streaming along both directions of the magnetic field. The magnetic field rotated slowly but steadily through approximately 180 deg during this same 40-hour period; this is consistent with the existence of a large-scale loop with extent greater than 0.5 AU. The observations suggest that the particles are being injected into the loop sunward of the spacecraft; they appear as bidirectional fluxes in the outermost regions of the loop arising from a combination of focusing and near scatter-free transport.

  6. Subspace accelerated inexact Newton method for large scale wave functions calculations in Density Functional Theory

    SciTech Connect

    Fattebert, J

    2008-07-29

    We describe an iterative algorithm to solve electronic structure problems in Density Functional Theory. The approach is presented as a Subspace Accelerated Inexact Newton (SAIN) solver for the non-linear Kohn-Sham equations. It is related to a class of iterative algorithms known as RMM-DIIS in the electronic structure community. The method is illustrated with examples of real applications using a finite difference discretization and multigrid preconditioning.

  7. Investigation of the large-scale functional brain networks modulated by acupuncture.

    PubMed

    Feng, Yuanyuan; Bai, Lijun; Ren, Yanshuang; Wang, Hu; Liu, Zhenyu; Zhang, Wensheng; Tian, Jie

    2011-09-01

    Previous neuroimaging studies have primarily focused on the neural activities involving the acute effects of acupuncture. Considering that acupuncture can induce long-lasting effects, several researchers have begun to pay attention to the sustained effects of acupuncture on the resting brain. Most of these researchers adopted functional connectivity analysis based on one or a few preselected brain regions and demonstrated various function-guided brain networks underlying the specific effect of acupuncture. Few have investigated how these brain networks interacted at the whole-brain level. In this study, we sought to investigate the functional correlations throughout the entire brain following acupuncture at acupoint ST36 (ACUP) in comparison with acupuncture at nearby nonacupoint (SHAM). We divided the whole brain into 90 regions and constructed functional brain network for each condition. Then we examined the network hubs and identified statistically significant differences in functional correlations between the two conditions. Following ACUP, but not SHAM, the limbic/paralimbic regions such as the amygdala, hippocampus and anterior cingulate gyrus emerged as network hubs. For direct comparisons, increased correlations for ACUP compared to SHAM were primarily related with the limbic/paralimbic and subcortical regions such as the insula, amygdala, anterior cingulate gyrus, and thalamus, whereas decreased correlations were mainly related with the sensory and frontal cortex. The heterogeneous modulation patterns between the two conditions may relate to the functional specific modulatory effects of acupuncture. The preliminary findings may help us to better understand the long-lasting effects of acupuncture on the entire resting brain, as well as the neurophysiological mechanisms underlying acupuncture.

  8. Microwave background anisotropies implied by large-scale galaxy correlations - The minimum of C(0) and cosmological parameters

    NASA Technical Reports Server (NTRS)

    Kashlinsky, A.

    1991-01-01

    Data from a recent APM survey are used to show that large-scale galaxy correlations found there imply the existence of measurable microwave background radiation (MBR) anisotropies on scales greater than several degrees. It is shown that sq rt C(0) is not less than 3.5 x 10 exp -5 if the APM data are used at Theta-0 = 20 deg, or sq rt C(0) is not less than 2.8 x 10 exp -5 if Theta-0 = 10 deg is used. These numbers are almost independent of the cosmological parameters Omega, Lambda, and the redshift of the last scattering surface. For finite-beamwidth experiments the minimal fluctuations depend on the cosmological parameters. The minimal anisotropies are smaller in a low-Omega universe.

  9. On the cognitive neurodynamics of listening effort: a phase clustering analysis of large-scale neural correlates.

    PubMed

    Strauss, Daniel J; Corona-Strauss, Farah I; Bernarding, Corinna; Reith, Wolfgang; Latzel, Matthias; Froehlich, Matthias

    2009-01-01

    An increased listening effort represents a major problem in humans with hearing impairment. Neurodiagnostic methods for an objective listening effort estimation could revolutionize auditory rehabilitation. However the cognitive neurodynamics of listening effort is not understood and research related its neural correlates is still in its infancy. In this paper we present a phase clustering analysis of large-scale listening effort correlates in auditory late responses (ALRs). For this we apply the complex wavelet transform as well as tight Gabor Frame (TGF) operators. We show (a) that phase clustering on the unit circle can separate ALR data from auditory paradigms which require a graduated effort for their solution; (b) the application of TGFs for an inverse artificial phase stabilization at the alpha/theta-border enlarges the endogenously driven listening effort correlates in the reconstructed time- domain waveforms. It is concluded that listening effort correlates can be extracted from ALR sequences using an instantaneous phase clustering analysis, at least by means of the applied experimental pure tone paradigm.

  10. Large-scale production of functional human lysozyme from marker-free transgenic cloned cows.

    PubMed

    Lu, Dan; Liu, Shen; Ding, Fangrong; Wang, Haiping; Li, Jing; Li, Ling; Dai, Yunping; Li, Ning

    2016-03-10

    Human lysozyme is an important natural non-specific immune protein that is highly expressed in breast milk and participates in the immune response of infants against bacterial and viral infections. Considering the medicinal value and market demand for human lysozyme, an animal model for large-scale production of recombinant human lysozyme (rhLZ) is needed. In this study, we generated transgenic cloned cows with the marker-free vector pBAC-hLF-hLZ, which was shown to efficiently express rhLZ in cow milk. Seven transgenic cloned cows, identified by polymerase chain reaction, Southern blot, and western blot analyses, produced rhLZ in milk at concentrations of up to 3149.19 ± 24.80 mg/L. The purified rhLZ had a similar molecular weight and enzymatic activity as wild-type human lysozyme possessed the same C-terminal and N-terminal amino acid sequences. The preliminary results from the milk yield and milk compositions from a naturally lactating transgenic cloned cow 0906 were also tested. These results provide a solid foundation for the large-scale production of rhLZ in the future.

  11. Large-scale functional brain networks in human non-rapid eye movement sleep: insights from combined electroencephalographic/functional magnetic resonance imaging studies.

    PubMed

    Spoormaker, Victor I; Czisch, Michael; Maquet, Pierre; Jäncke, Lutz

    2011-10-13

    This paper reviews the existing body of knowledge on the neural correlates of spontaneous oscillations, functional connectivity and brain plasticity in human non-rapid eye movement (NREM) sleep. The first section reviews the evidence that specific sleep events as slow waves and spindles are associated with transient increases in regional brain activity. The second section describes the changes in functional connectivity during NREM sleep, with a particular focus on changes within a low-frequency, large-scale functional brain network. The third section will discuss the possibility that spontaneous oscillations and differential functional connectivity are related to brain plasticity and systems consolidation, with a particular focus on motor skill acquisition. Implications for the mode of information processing per sleep stage and future experimental studies are discussed.

  12. Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

    PubMed Central

    Bauer, Corinna M.; Hirsch, Gabriella V.; Zajac, Lauren; Koo, Bang-Bon; Collignon, Olivier

    2017-01-01

    between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary, these findings provide complimentary evidence, as well as highlight potential contradictions, regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness. PMID:28328939

  13. Fast reproducible identification and large-scale databasing of individual functional cognitive networks

    PubMed Central

    Pinel, Philippe; Thirion, Bertrand; Meriaux, Sébastien; Jobert, Antoinette; Serres, Julien; Le Bihan, Denis; Poline, Jean-Baptiste; Dehaene, Stanislas

    2007-01-01

    Background Although cognitive processes such as reading and calculation are associated with reproducible cerebral networks, inter-individual variability is considerable. Understanding the origins of this variability will require the elaboration of large multimodal databases compiling behavioral, anatomical, genetic and functional neuroimaging data over hundreds of subjects. With this goal in mind, we designed a simple and fast acquisition procedure based on a 5-minute functional magnetic resonance imaging (fMRI) sequence that can be run as easily and as systematically as an anatomical scan, and is therefore used in every subject undergoing fMRI in our laboratory. This protocol captures the cerebral bases of auditory and visual perception, motor actions, reading, language comprehension and mental calculation at an individual level. Results 81 subjects were successfully scanned. Before describing inter-individual variability, we demonstrated in the present study the reliability of individual functional data obtained with this short protocol. Considering the anatomical variability, we then needed to correctly describe individual functional networks in a voxel-free space. We applied then non-voxel based methods that automatically extract main features of individual patterns of activation: group analyses performed on these individual data not only converge to those reported with a more conventional voxel-based random effect analysis, but also keep information concerning variance in location and degrees of activation across subjects. Conclusion This collection of individual fMRI data will help to describe the cerebral inter-subject variability of the correlates of some language, calculation and sensorimotor tasks. In association with demographic, anatomical, behavioral and genetic data, this protocol will serve as the cornerstone to establish a hybrid database of hundreds of subjects suitable to study the range and causes of variation in the cerebral bases of numerous

  14. A large-scale functional screen identifies Nova1 and Ncoa3 as regulators of neuronal miRNA function.

    PubMed

    Störchel, Peter H; Thümmler, Juliane; Siegel, Gabriele; Aksoy-Aksel, Ayla; Zampa, Federico; Sumer, Simon; Schratt, Gerhard

    2015-09-02

    MicroRNAs (miRNAs) are important regulators of neuronal development, network connectivity, and synaptic plasticity. While many neuronal miRNAs were previously shown to modulate neuronal morphogenesis, little is known regarding the regulation of miRNA function. In a large-scale functional screen, we identified two novel regulators of neuronal miRNA function, Nova1 and Ncoa3. Both proteins are expressed in the nucleus and the cytoplasm of developing hippocampal neurons. We found that Nova1 and Ncoa3 stimulate miRNA function by different mechanisms that converge on Argonaute (Ago) proteins, core components of the miRNA-induced silencing complex (miRISC). While Nova1 physically interacts with Ago proteins, Ncoa3 selectively promotes the expression of Ago2 at the transcriptional level. We further show that Ncoa3 regulates dendritic complexity and dendritic spine maturation of hippocampal neurons in a miRNA-dependent fashion. Importantly, both the loss of miRNA activity and increased dendrite complexity upon Ncoa3 knockdown were rescued by Ago2 overexpression. Together, we uncovered two novel factors that control neuronal miRISC function at the level of Ago proteins, with possible implications for the regulation of synapse development and plasticity.

  15. Large-scale probabilistic functional modes from resting state fMRI.

    PubMed

    Harrison, Samuel J; Woolrich, Mark W; Robinson, Emma C; Glasser, Matthew F; Beckmann, Christian F; Jenkinson, Mark; Smith, Stephen M

    2015-04-01

    It is well established that it is possible to observe spontaneous, highly structured, fluctuations in human brain activity from functional magnetic resonance imaging (fMRI) when the subject is 'at rest'. However, characterising this activity in an interpretable manner is still a very open problem. In this paper, we introduce a method for identifying modes of coherent activity from resting state fMRI (rfMRI) data. Our model characterises a mode as the outer product of a spatial map and a time course, constrained by the nature of both the between-subject variation and the effect of the haemodynamic response function. This is presented as a probabilistic generative model within a variational framework that allows Bayesian inference, even on voxelwise rfMRI data. Furthermore, using this approach it becomes possible to infer distinct extended modes that are correlated with each other in space and time, a property which we believe is neuroscientifically desirable. We assess the performance of our model on both simulated data and high quality rfMRI data from the Human Connectome Project, and contrast its properties with those of both spatial and temporal independent component analysis (ICA). We show that our method is able to stably infer sets of modes with complex spatio-temporal interactions and spatial differences between subjects.

  16. Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks.

    PubMed

    Qiu, Maolin; Scheinost, Dustin; Ramani, Ramachandran; Constable, R Todd

    2017-03-01

    Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing

  17. The Determination of the Large-Scale Circulation of the Pacific Ocean from Satellite Altimetry using Model Green's Functions

    NASA Technical Reports Server (NTRS)

    Stammer, Detlef; Wunsch, Carl

    1996-01-01

    A Green's function method for obtaining an estimate of the ocean circulation using both a general circulation model and altimetric data is demonstrated. The fundamental assumption is that the model is so accurate that the differences between the observations and the model-estimated fields obey a linear dynamics. In the present case, the calculations are demonstrated for model/data differences occurring on very a large scale, where the linearization hypothesis appears to be a good one. A semi-automatic linearization of the Bryan/Cox general circulation model is effected by calculating the model response to a series of isolated (in both space and time) geostrophically balanced vortices. These resulting impulse responses or 'Green's functions' then provide the kernels for a linear inverse problem. The method is first demonstrated with a set of 'twin experiments' and then with real data spanning the entire model domain and a year of TOPEX/POSEIDON observations. Our present focus is on the estimate of the time-mean and annual cycle of the model. Residuals of the inversion/assimilation are largest in the western tropical Pacific, and are believed to reflect primarily geoid error. Vertical resolution diminishes with depth with 1 year of data. The model mean is modified such that the subtropical gyre is weakened by about 1 cm/s and the center of the gyre shifted southward by about 10 deg. Corrections to the flow field at the annual cycle suggest that the dynamical response is weak except in the tropics, where the estimated seasonal cycle of the low-latitude current system is of the order of 2 cm/s. The underestimation of observed fluctuations can be related to the inversion on the coarse spatial grid, which does not permit full resolution of the tropical physics. The methodology is easily extended to higher resolution, to use of spatially correlated errors, and to other data types.

  18. A 3D sphere culture system containing functional polymers for large-scale human pluripotent stem cell production.

    PubMed

    Otsuji, Tomomi G; Bin, Jiang; Yoshimura, Azumi; Tomura, Misayo; Tateyama, Daiki; Minami, Itsunari; Yoshikawa, Yoshihiro; Aiba, Kazuhiro; Heuser, John E; Nishino, Taito; Hasegawa, Kouichi; Nakatsuji, Norio

    2014-05-06

    Utilizing human pluripotent stem cells (hPSCs) in cell-based therapy and drug discovery requires large-scale cell production. However, scaling up conventional adherent cultures presents challenges of maintaining a uniform high quality at low cost. In this regard, suspension cultures are a viable alternative, because they are scalable and do not require adhesion surfaces. 3D culture systems such as bioreactors can be exploited for large-scale production. However, the limitations of current suspension culture methods include spontaneous fusion between cell aggregates and suboptimal passaging methods by dissociation and reaggregation. 3D culture systems that dynamically stir carrier beads or cell aggregates should be refined to reduce shearing forces that damage hPSCs. Here, we report a simple 3D sphere culture system that incorporates mechanical passaging and functional polymers. This setup resolves major problems associated with suspension culture methods and dynamic stirring systems and may be optimal for applications involving large-scale hPSC production.

  19. Large-scale deformed QRPA calculations of the gamma-ray strength function based on a Gogny force

    NASA Astrophysics Data System (ADS)

    Martini, M.; Goriely, S.; Hilaire, S.; Péru, S.; Minato, F.

    2016-01-01

    The dipole excitations of nuclei play an important role in nuclear astrophysics processes in connection with the photoabsorption and the radiative neutron capture that take place in stellar environment. We present here the results of a large-scale axially-symmetric deformed QRPA calculation of the γ-ray strength function based on the finite-range Gogny force. The newly determined γ-ray strength is compared with experimental photoabsorption data for spherical as well as deformed nuclei. Predictions of γ-ray strength functions and Maxwellian-averaged neutron capture rates for Sn isotopes are also discussed.

  20. Efficient formalism for large-scale ab initio molecular dynamics based on time-dependent density functional theory.

    PubMed

    Alonso, J L; Andrade, X; Echenique, P; Falceto, F; Prada-Gracia, D; Rubio, A

    2008-08-29

    A new "on the fly" method to perform Born-Oppenheimer ab initio molecular dynamics (AIMD) simulations is presented. Inspired by Ehrenfest dynamics in time-dependent density functional theory, the electronic orbitals are evolved by a Schrödinger-like equation, where the orbital time derivative is multiplied by a parameter. This parameter controls the time scale of the fictitious electronic motion and speeds up the calculations with respect to standard Ehrenfest dynamics. In contrast with other methods, wave function orthogonality needs not be imposed as it is automatically preserved, which is of paramount relevance for large-scale AIMD simulations.

  1. Large-scale brain networks in affective and social neuroscience: towards an integrative functional architecture of the brain.

    PubMed

    Barrett, Lisa Feldman; Satpute, Ajay Bhaskar

    2013-06-01

    Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain.

  2. Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity

    PubMed Central

    Thompson, William Hedley; Fransson, Peter

    2016-01-01

    The brain is organized into large scale spatial networks that can be detected during periods of rest using fMRI. The brain is also a dynamic organ with activity that changes over time. We developed a method and investigated properties where the connections as a function of time are derived and quantified. The point based method (PBM) presented here derives covariance matrices after clustering individual time points based upon their global spatial pattern. This method achieved increased temporal sensitivity, together with temporal network theory, allowed us to study functional integration between resting-state networks. Our results show that functional integrations between two resting-state networks predominately occurs in bursts of activity. This is followed by varying intermittent periods of less connectivity. The described point-based method of dynamic resting-state functional connectivity allows for a detailed and expanded view on the temporal dynamics of resting-state connectivity that provides novel insights into how neuronal information processing is integrated in the human brain at the level of large-scale networks. PMID:27991540

  3. Development of large-scale functional networks from birth to adulthood: a guide to neuroimaging literature.

    PubMed

    Grayson, David S; Fair, Damien A

    2017-02-01

    The development of human cognition results from the emergence of coordinated brain activity betweeen distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI). We attempt to synthesize rs-fcMRI findings with other functional imaging techniques, with macro-scale structural connectivity, and with knowledge regarding the development of micro-scale structure. We highlight a number of outstanding conceptual and technical barriers that need to be addressed, as well as previous developmental findings that may need to be revisited. Finally, we discuss key areas ripe for future research in order to 1) better characterize normative developmental trajectories, 2) link these trajectories to biologic mechanistic events, as well as component behaviors and 3) better understand the clinical implications and pathophysiological basis of aberrant network development.

  4. Large-scale synthesis and functionalization of hexagonal boron nitride nanosheets

    NASA Astrophysics Data System (ADS)

    Bhimanapati, Ganesh R.; Kozuch, Daniel; Robinson, Joshua A.

    2014-09-01

    A simple and inexpensive method to functionalize hexagonal boron nitride (hBN) was achieved by using an acid mixture of phosphoric and sulphuric acid. This functionalization induced the exfoliation of the layered structure of hBN into monolayer to few-layer sheets where the sizes of the sheets were dependent on the parent hBN powder used. Exfoliated hBN was shown to be stable in solvents such as ethanol, acetone, deionized water and isopropyl alcohol, and this stability was linked to sulfur functionalization that was induced during the exfoliation process. Further evidence of the functionalization was observed using transmission electron spectroscopy (TEM) and X-ray photoelectron spectroscopy (XPS). By deconvoluting the high resolution peaks for B 1s, the bonding of boron to oxygen and sulfur was confirmed. The exfoliated hBN nanosheets were crystalline as confirmed from X-ray diffraction and they also exhibited an optically active defect related to sulfur functionalization at 320 nm (3.9 +/- 0.1 eV).A simple and inexpensive method to functionalize hexagonal boron nitride (hBN) was achieved by using an acid mixture of phosphoric and sulphuric acid. This functionalization induced the exfoliation of the layered structure of hBN into monolayer to few-layer sheets where the sizes of the sheets were dependent on the parent hBN powder used. Exfoliated hBN was shown to be stable in solvents such as ethanol, acetone, deionized water and isopropyl alcohol, and this stability was linked to sulfur functionalization that was induced during the exfoliation process. Further evidence of the functionalization was observed using transmission electron spectroscopy (TEM) and X-ray photoelectron spectroscopy (XPS). By deconvoluting the high resolution peaks for B 1s, the bonding of boron to oxygen and sulfur was confirmed. The exfoliated hBN nanosheets were crystalline as confirmed from X-ray diffraction and they also exhibited an optically active defect related to sulfur

  5. Pattern classification of large-scale functional brain networks: identification of informative neuroimaging markers for epilepsy.

    PubMed

    Zhang, Jie; Cheng, Wei; Wang, ZhengGe; Zhang, ZhiQiang; Lu, WenLian; Lu, GuangMing; Feng, Jianfeng

    2012-01-01

    The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology

  6. Large-scale synthesis and functionalization of hexagonal boron nitride nanosheets.

    PubMed

    Bhimanapati, Ganesh R; Kozuch, Daniel; Robinson, Joshua A

    2014-10-21

    A simple and inexpensive method to functionalize hexagonal boron nitride (hBN) was achieved by using an acid mixture of phosphoric and sulphuric acid. This functionalization induced the exfoliation of the layered structure of hBN into monolayer to few-layer sheets where the sizes of the sheets were dependent on the parent hBN powder used. Exfoliated hBN was shown to be stable in solvents such as ethanol, acetone, deionized water and isopropyl alcohol, and this stability was linked to sulfur functionalization that was induced during the exfoliation process. Further evidence of the functionalization was observed using transmission electron spectroscopy (TEM) and X-ray photoelectron spectroscopy (XPS). By deconvoluting the high resolution peaks for B 1s, the bonding of boron to oxygen and sulfur was confirmed. The exfoliated hBN nanosheets were crystalline as confirmed from X-ray diffraction and they also exhibited an optically active defect related to sulfur functionalization at 320 nm (3.9 ± 0.1 eV).

  7. Large-scale identification of human protein function using topological features of interaction network

    PubMed Central

    Li, Zhanchao; Liu, Zhiqing; Zhong, Wenqian; Huang, Menghua; Wu, Na; Xie, Yun; Dai, Zong; Zou, Xiaoyong

    2016-01-01

    The annotation of protein function is a vital step to elucidate the essence of life at a molecular level, and it is also meritorious in biomedical and pharmaceutical industry. Developments of sequencing technology result in constant expansion of the gap between the number of the known sequences and their functions. Therefore, it is indispensable to develop a computational method for the annotation of protein function. Herein, a novel method is proposed to identify protein function based on the weighted human protein-protein interaction network and graph theory. The network topology features with local and global information are presented to characterise proteins. The minimum redundancy maximum relevance algorithm is used to select 227 optimized feature subsets and support vector machine technique is utilized to build the prediction models. The performance of current method is assessed through 10-fold cross-validation test, and the range of accuracies is from 67.63% to 100%. Comparing with other annotation methods, the proposed way possesses a 50% improvement in the predictive accuracy. Generally, such network topology features provide insights into the relationship between protein functions and network architectures. The source code of Matlab is freely available on request from the authors. PMID:27849060

  8. Large-scale identification of human protein function using topological features of interaction network

    NASA Astrophysics Data System (ADS)

    Li, Zhanchao; Liu, Zhiqing; Zhong, Wenqian; Huang, Menghua; Wu, Na; Xie, Yun; Dai, Zong; Zou, Xiaoyong

    2016-11-01

    The annotation of protein function is a vital step to elucidate the essence of life at a molecular level, and it is also meritorious in biomedical and pharmaceutical industry. Developments of sequencing technology result in constant expansion of the gap between the number of the known sequences and their functions. Therefore, it is indispensable to develop a computational method for the annotation of protein function. Herein, a novel method is proposed to identify protein function based on the weighted human protein-protein interaction network and graph theory. The network topology features with local and global information are presented to characterise proteins. The minimum redundancy maximum relevance algorithm is used to select 227 optimized feature subsets and support vector machine technique is utilized to build the prediction models. The performance of current method is assessed through 10-fold cross-validation test, and the range of accuracies is from 67.63% to 100%. Comparing with other annotation methods, the proposed way possesses a 50% improvement in the predictive accuracy. Generally, such network topology features provide insights into the relationship between protein functions and network architectures. The source code of Matlab is freely available on request from the authors.

  9. Insights into Hox protein function from a large scale combinatorial analysis of protein domains.

    PubMed

    Merabet, Samir; Litim-Mecheri, Isma; Karlsson, Daniel; Dixit, Richa; Saadaoui, Mehdi; Monier, Bruno; Brun, Christine; Thor, Stefan; Vijayraghavan, K; Perrin, Laurent; Pradel, Jacques; Graba, Yacine

    2011-10-01

    Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA), we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences.

  10. Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks

    PubMed Central

    Sandhu, Kuljeet Singh; Li, Guoliang; Poh, Huay Mei; Quek, Yu Ling Kelly; Sia, Yee Yen; Peh, Su Qin; Mulawadi, Fabianus Hendriyan; Lim, Joanne; Sikic, Mile; Menghi, Francesca; Thalamuthu, Anbupalam; Sung, Wing Kin; Ruan, Xiaoan; Fullwood, Melissa Jane; Liu, Edison; Csermely, Peter; Ruan, Yijun

    2014-01-01

    SUMMARY Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions. PMID:23103170

  11. Long-term and large-scale perspectives on the relationship between biodiversity and ecosystem functioning

    USGS Publications Warehouse

    Symstad, A.J.; Chapin, F. S.; Wall, D.H.; Gross, K.L.; Huenneke, L.F.; Mittelbach, G.G.; Peters, Debra P. C.; Tilman, D.

    2003-01-01

    In a growing body of literature from a variety of ecosystems is strong evidence that various components of biodiversity have significant impacts on ecosystem functioning. However, much of this evidence comes from short-term, small-scale experiments in which communities are synthesized from relatively small species pools and conditions are highly controlled. Extrapolation of the results of such experiments to longer time scales and larger spatial scales - those of whole ecosystems - is difficult because the experiments do not incorporate natural processes such as recruitment limitation and colonization of new species. We show how long-term study of planned and accidental changes in species richness and composition suggests that the effects of biodiversity on ecosystem functioning will vary over time and space. More important, we also highlight areas of uncertainty that need to be addressed through coordinated cross-scale and cross-site research.

  12. Large scale brain functional networks support sentence comprehension: evidence from both explicit and implicit language tasks.

    PubMed

    Zhu, Zude; Fan, Yuanyuan; Feng, Gangyi; Huang, Ruiwang; Wang, Suiping

    2013-01-01

    Previous studies have indicated that sentences are comprehended via widespread brain regions in the fronto-temporo-parietal network in explicit language tasks (e.g., semantic congruency judgment tasks), and through restricted temporal or frontal regions in implicit language tasks (e.g., font size judgment tasks). This discrepancy has raised questions regarding a common network for sentence comprehension that acts regardless of task effect and whether different tasks modulate network properties. To this end, we constructed brain functional networks based on 27 subjects' fMRI data that was collected while performing explicit and implicit language tasks. We found that network properties and network hubs corresponding to the implicit language task were similar to those associated with the explicit language task. We also found common hubs in occipital, temporal and frontal regions in both tasks. Compared with the implicit language task, the explicit language task resulted in greater global efficiency and increased integrated betweenness centrality of the left inferior frontal gyrus, which is a key region related to sentence comprehension. These results suggest that brain functional networks support both explicit and implicit sentence comprehension; in addition, these two types of language tasks may modulate the properties of brain functional networks.

  13. Large-scale turnover of functional transcription factor bindingsites in Drosophila

    SciTech Connect

    Moses, Alan M.; Pollard, Daniel A.; Nix, David A.; Iyer, VenkyN.; Li, Xiao-Yong; Biggin, Mark D.; Eisen, Michael B.

    2006-07-14

    The gain and loss of functional transcription-factor bindingsites has been proposed as a major source of evolutionary change incis-regulatory DNA and gene expression. We have developed an evolutionarymodel to study binding site turnover that uses multiple sequencealignments to assess the evolutionary constraint on individual bindingsites, and to map gain and loss events along a phylogenetic tree. Weapply this model to study the evolutionary dynamics of binding sites ofthe Drosophila melanogaster transcription factor Zeste, using genome-widein vivo (ChIP-chip) binding data to identify functional Zeste bindingsites, and the genome sequences of D. melanogaster, D. simulans, D.erecta and D. yakuba to study their evolution. We estimate that more than5 percent of functional Zeste binding sites in D. melanogaster weregained along the D. melanogaster lineage or lost along one of the otherlineages. We find that Zeste bound regions have a reduced rate of bindingsite loss and an increased rate of binding site gain relative to flankingsequences. Finally, we show that binding site gains and losses areasymmetrically distributed with respect to D. melanogaster, consistentwith lineage-specific acquisition and loss of Zeste-responsive regulatoryelements.

  14. Identifying functional connectivity in large-scale neural ensemble recordings: a multiscale data mining approach.

    PubMed

    Eldawlatly, Seif; Jin, Rong; Oweiss, Karim G

    2009-02-01

    Identifying functional connectivity between neuronal elements is an essential first step toward understanding how the brain orchestrates information processing at the single-cell and population levels to carry out biological computations. This letter suggests a new approach to identify functional connectivity between neuronal elements from their simultaneously recorded spike trains. In particular, we identify clusters of neurons that exhibit functional interdependency over variable spatial and temporal patterns of interaction. We represent neurons as objects in a graph and connect them using arbitrarily defined similarity measures calculated across multiple timescales. We then use a probabilistic spectral clustering algorithm to cluster the neurons in the graph by solving a minimum graph cut optimization problem. Using point process theory to model population activity, we demonstrate the robustness of the approach in tracking a broad spectrum of neuronal interaction, from synchrony to rate co-modulation, by systematically varying the length of the firing history interval and the strength of the connecting synapses that govern the discharge pattern of each neuron. We also demonstrate how activity-dependent plasticity can be tracked and quantified in multiple network topologies built to mimic distinct behavioral contexts. We compare the performance to classical approaches to illustrate the substantial gain in performance.

  15. Large-scale functional analysis of the roles of phosphorylation in yeast metabolic pathways.

    PubMed

    Schulz, Juliane Caroline; Zampieri, Mattia; Wanka, Stefanie; von Mering, Christian; Sauer, Uwe

    2014-11-25

    Protein phosphorylation is a widespread posttranslational modification that regulates almost all cellular functions. To investigate the large number of phosphorylation events with unknown functions, we monitored the concentrations of several hundred intracellular metabolites in Saccharomyces cerevisiae yeast strains with deletions of 118 kinases or phosphatases. Whereas most deletion strains had no detectable difference in growth compared to wild-type yeast, two-thirds of deletion strains had alterations in metabolic profiles. For about half of the kinases and phosphatases encoded by the deleted genes, we inferred specific regulatory roles on the basis of knowledge about the affected metabolic pathways. We demonstrated that the phosphatase Ppq1 was required for metal homeostasis. Combining metabolomic data with published phosphoproteomic data in a stoichiometric model enabled us to predict functions for phosphorylation in the regulation of 47 enzymes. Overall, we provided insights and testable predictions covering greater than twice the number of known phosphorylated enzymes in yeast, suggesting extensive phosphorylation-dependent regulation of yeast metabolism.

  16. Tucker-tensor algorithm for large-scale Kohn-Sham density functional theory calculations

    NASA Astrophysics Data System (ADS)

    Motamarri, Phani; Gavini, Vikram; Blesgen, Thomas

    2016-03-01

    In this work, we propose a systematic way of computing a low-rank globally adapted localized Tucker-tensor basis for solving the Kohn-Sham density functional theory (DFT) problem. In every iteration of the self-consistent field procedure of the Kohn-Sham DFT problem, we construct an additive separable approximation of the Kohn-Sham Hamiltonian. The Tucker-tensor basis is chosen such as to span the tensor product of the one-dimensional eigenspaces corresponding to each of the spatially separable Hamiltonians, and the localized Tucker-tensor basis is constructed from localized representations of these one-dimensional eigenspaces. This Tucker-tensor basis forms a complete basis, and is naturally adapted to the Kohn-Sham Hamiltonian. Further, the locality of this basis in real-space allows us to exploit reduced-order scaling algorithms for the solution of the discrete Kohn-Sham eigenvalue problem. In particular, we use Chebyshev filtering to compute the eigenspace of the Kohn-Sham Hamiltonian, and evaluate nonorthogonal localized wave functions spanning the Chebyshev filtered space, all represented in the Tucker-tensor basis. We thereby compute the electron-density and other quantities of interest, using a Fermi-operator expansion of the Hamiltonian projected onto the subspace spanned by the nonorthogonal localized wave functions. Numerical results on benchmark examples involving pseudopotential calculations suggest an exponential convergence of the ground-state energy with the Tucker rank. Interestingly, the rank of the Tucker-tensor basis required to obtain chemical accuracy is found to be only weakly dependent on the system size, which results in close to linear-scaling complexity for Kohn-Sham DFT calculations for both insulating and metallic systems. A comparative study has revealed significant computational efficiencies afforded by the proposed Tucker-tensor approach in comparison to a plane-wave basis.

  17. Large-scale identification of human genes implicated in epidermal barrier function

    PubMed Central

    Toulza, Eve; Mattiuzzo, Nicolas R; Galliano, Marie-Florence; Jonca, Nathalie; Dossat, Carole; Jacob, Daniel; de Daruvar, Antoine; Wincker, Patrick; Serre, Guy; Guerrin, Marina

    2007-01-01

    Background During epidermal differentiation, keratinocytes progressing through the suprabasal layers undergo complex and tightly regulated biochemical modifications leading to cornification and desquamation. The last living cells, the granular keratinocytes (GKs), produce almost all of the proteins and lipids required for the protective barrier function before their programmed cell death gives rise to corneocytes. We present here the first analysis of the transcriptome of human GKs, purified from healthy epidermis by an original approach. Results Using the ORESTES method, 22,585 expressed sequence tags (ESTs) were produced that matched 3,387 genes. Despite normalization provided by this method (mean 4.6 ORESTES per gene), some highly transcribed genes, including that encoding dermokine, were overrepresented. About 330 expressed genes displayed less than 100 ESTs in UniGene clusters and are most likely to be specific for GKs and potentially involved in barrier function. This hypothesis was tested by comparing the relative expression of 73 genes in the basal and granular layers of epidermis by quantitative RT-PCR. Among these, 33 were identified as new, highly specific markers of GKs, including those encoding a protease, protease inhibitors and proteins involved in lipid metabolism and transport. We identified filaggrin 2 (also called ifapsoriasin), a poorly characterized member of the epidermal differentiation complex, as well as three new lipase genes clustered with paralogous genes on chromosome 10q23.31. A new gene of unknown function, C1orf81, is specifically disrupted in the human genome by a frameshift mutation. Conclusion These data increase the present knowledge of genes responsible for the formation of the skin barrier and suggest new candidates for genodermatoses of unknown origin. PMID:17562024

  18. Large-scale Generation of Patterned Bubble Arrays on Printed Bi-functional Boiling Surfaces

    PubMed Central

    Choi, Chang-Ho; David, Michele; Gao, Zhongwei; Chang, Alvin; Allen, Marshall; Wang, Hailei; Chang, Chih-hung

    2016-01-01

    Bubble nucleation control, growth and departure dynamics is important in understanding boiling phenomena and enhancing nucleate boiling heat transfer performance. We report a novel bi-functional heterogeneous surface structure that is capable of tuning bubble nucleation, growth and departure dynamics. For the fabrication of the surface, hydrophobic polymer dot arrays are first printed on a substrate, followed by hydrophilic ZnO nanostructure deposition via microreactor-assisted nanomaterial deposition (MAND) processing. Wettability contrast between the hydrophobic polymer dot arrays and aqueous ZnO solution allows for the fabrication of heterogeneous surfaces with distinct wettability regions. Heterogeneous surfaces with various configurations were fabricated and their bubble dynamics were examined at elevated heat flux, revealing various nucleate boiling phenomena. In particular, aligned and patterned bubbles with a tunable departure frequency and diameter were demonstrated in a boiling experiment for the first time. Taking advantage of our fabrication method, a 6 inch wafer size heterogeneous surface was prepared. Pool boiling experiments were also performed to demonstrate a heat flux enhancement up to 3X at the same surface superheat using bi-functional surfaces, compared to a bare stainless steel surface. PMID:27034255

  19. Large-scale Generation of Patterned Bubble Arrays on Printed Bi-functional Boiling Surfaces.

    PubMed

    Choi, Chang-Ho; David, Michele; Gao, Zhongwei; Chang, Alvin; Allen, Marshall; Wang, Hailei; Chang, Chih-hung

    2016-04-01

    Bubble nucleation control, growth and departure dynamics is important in understanding boiling phenomena and enhancing nucleate boiling heat transfer performance. We report a novel bi-functional heterogeneous surface structure that is capable of tuning bubble nucleation, growth and departure dynamics. For the fabrication of the surface, hydrophobic polymer dot arrays are first printed on a substrate, followed by hydrophilic ZnO nanostructure deposition via microreactor-assisted nanomaterial deposition (MAND) processing. Wettability contrast between the hydrophobic polymer dot arrays and aqueous ZnO solution allows for the fabrication of heterogeneous surfaces with distinct wettability regions. Heterogeneous surfaces with various configurations were fabricated and their bubble dynamics were examined at elevated heat flux, revealing various nucleate boiling phenomena. In particular, aligned and patterned bubbles with a tunable departure frequency and diameter were demonstrated in a boiling experiment for the first time. Taking advantage of our fabrication method, a 6 inch wafer size heterogeneous surface was prepared. Pool boiling experiments were also performed to demonstrate a heat flux enhancement up to 3X at the same surface superheat using bi-functional surfaces, compared to a bare stainless steel surface.

  20. Cost-Efficient and Multi-Functional Secure Aggregation in Large Scale Distributed Application

    PubMed Central

    Zhang, Ping; Li, Wenjun; Sun, Hua

    2016-01-01

    Secure aggregation is an essential component of modern distributed applications and data mining platforms. Aggregated statistical results are typically adopted in constructing a data cube for data analysis at multiple abstraction levels in data warehouse platforms. Generating different types of statistical results efficiently at the same time (or referred to as enabling multi-functional support) is a fundamental requirement in practice. However, most of the existing schemes support a very limited number of statistics. Securely obtaining typical statistical results simultaneously in the distribution system, without recovering the original data, is still an open problem. In this paper, we present SEDAR, which is a SEcure Data Aggregation scheme under the Range segmentation model. Range segmentation model is proposed to reduce the communication cost by capturing the data characteristics, and different range uses different aggregation strategy. For raw data in the dominant range, SEDAR encodes them into well defined vectors to provide value-preservation and order-preservation, and thus provides the basis for multi-functional aggregation. A homomorphic encryption scheme is used to achieve data privacy. We also present two enhanced versions. The first one is a Random based SEDAR (REDAR), and the second is a Compression based SEDAR (CEDAR). Both of them can significantly reduce communication cost with the trade-off lower security and lower accuracy, respectively. Experimental evaluations, based on six different scenes of real data, show that all of them have an excellent performance on cost and accuracy. PMID:27551747

  1. Attentional load modulates large-scale functional brain connectivity beyond the core attention networks.

    PubMed

    Alnæs, Dag; Kaufmann, Tobias; Richard, Geneviève; Duff, Eugene P; Sneve, Markus H; Endestad, Tor; Nordvik, Jan Egil; Andreassen, Ole A; Smith, Stephen M; Westlye, Lars T

    2015-04-01

    In line with the notion of a continuously active and dynamic brain, functional networks identified during rest correspond with those revealed by task-fMRI. Characterizing the dynamic cross-talk between these network nodes is key to understanding the successful implementation of effortful cognitive processing in healthy individuals and its breakdown in a variety of conditions involving aberrant brain biology and cognitive dysfunction. We employed advanced network modeling on fMRI data collected during a task involving sustained attentive tracking of objects at two load levels and during rest. Using multivariate techniques, we demonstrate that attentional load levels can be significantly discriminated, and from a resting-state condition, the accuracy approaches 100%, by means of estimates of between-node functional connectivity. Several network edges were modulated during task engagement: The dorsal attention network increased connectivity with a visual node, while decreasing connectivity with motor and sensory nodes. Also, we observed a decoupling between left and right hemisphere dorsal visual streams. These results support the notion of dynamic network reconfigurations based on attentional effort. No simple correspondence between node signal amplitude change and node connectivity modulations was found, thus network modeling provides novel information beyond what is revealed by conventional task-fMRI analysis. The current decoding of attentional states confirms that edge connectivity contains highly predictive information about the mental state of the individual, and the approach shows promise for the utilization in clinical contexts.

  2. The iBeetle large-scale RNAi screen reveals gene functions for insect development and physiology

    PubMed Central

    Schmitt-Engel, Christian; Schultheis, Dorothea; Schwirz, Jonas; Ströhlein, Nadi; Troelenberg, Nicole; Majumdar, Upalparna; Dao, Van Anh; Grossmann, Daniela; Richter, Tobias; Tech, Maike; Dönitz, Jürgen; Gerischer, Lizzy; Theis, Mirko; Schild, Inga; Trauner, Jochen; Koniszewski, Nikolaus D. B.; Küster, Elke; Kittelmann, Sebastian; Hu, Yonggang; Lehmann, Sabrina; Siemanowski, Janna; Ulrich, Julia; Panfilio, Kristen A.; Schröder, Reinhard; Morgenstern, Burkhard; Stanke, Mario; Buchhholz, Frank; Frasch, Manfred; Roth, Siegfried; Wimmer, Ernst A.; Schoppmeier, Michael; Klingler, Martin; Bucher, Gregor

    2015-01-01

    Genetic screens are powerful tools to identify the genes required for a given biological process. However, for technical reasons, comprehensive screens have been restricted to very few model organisms. Therefore, although deep sequencing is revealing the genes of ever more insect species, the functional studies predominantly focus on candidate genes previously identified in Drosophila, which is biasing research towards conserved gene functions. RNAi screens in other organisms promise to reduce this bias. Here we present the results of the iBeetle screen, a large-scale, unbiased RNAi screen in the red flour beetle, Tribolium castaneum, which identifies gene functions in embryonic and postembryonic development, physiology and cell biology. The utility of Tribolium as a screening platform is demonstrated by the identification of genes involved in insect epithelial adhesion. This work transcends the restrictions of the candidate gene approach and opens fields of research not accessible in Drosophila. PMID:26215380

  3. The iBeetle large-scale RNAi screen reveals gene functions for insect development and physiology.

    PubMed

    Schmitt-Engel, Christian; Schultheis, Dorothea; Schwirz, Jonas; Ströhlein, Nadi; Troelenberg, Nicole; Majumdar, Upalparna; Dao, Van Anh; Grossmann, Daniela; Richter, Tobias; Tech, Maike; Dönitz, Jürgen; Gerischer, Lizzy; Theis, Mirko; Schild, Inga; Trauner, Jochen; Koniszewski, Nikolaus D B; Küster, Elke; Kittelmann, Sebastian; Hu, Yonggang; Lehmann, Sabrina; Siemanowski, Janna; Ulrich, Julia; Panfilio, Kristen A; Schröder, Reinhard; Morgenstern, Burkhard; Stanke, Mario; Buchhholz, Frank; Frasch, Manfred; Roth, Siegfried; Wimmer, Ernst A; Schoppmeier, Michael; Klingler, Martin; Bucher, Gregor

    2015-07-28

    Genetic screens are powerful tools to identify the genes required for a given biological process. However, for technical reasons, comprehensive screens have been restricted to very few model organisms. Therefore, although deep sequencing is revealing the genes of ever more insect species, the functional studies predominantly focus on candidate genes previously identified in Drosophila, which is biasing research towards conserved gene functions. RNAi screens in other organisms promise to reduce this bias. Here we present the results of the iBeetle screen, a large-scale, unbiased RNAi screen in the red flour beetle, Tribolium castaneum, which identifies gene functions in embryonic and postembryonic development, physiology and cell biology. The utility of Tribolium as a screening platform is demonstrated by the identification of genes involved in insect epithelial adhesion. This work transcends the restrictions of the candidate gene approach and opens fields of research not accessible in Drosophila.

  4. Large-Scale and Comprehensive Immune Profiling and Functional Analysis of Normal Human Aging

    PubMed Central

    Whiting, Chan C.; Siebert, Janet; Newman, Aaron M.; Du, Hong-wu; Alizadeh, Ash A.; Goronzy, Jorg; Weyand, Cornelia M.; Krishnan, Eswar; Fathman, C. Garrison; Maecker, Holden T.

    2015-01-01

    While many age-associated immune changes have been reported, a comprehensive set of metrics of immune aging is lacking. Here we report data from 243 healthy adults aged 40–97, for whom we measured clinical and functional parameters, serum cytokines, cytokines and gene expression in stimulated and unstimulated PBMC, PBMC phenotypes, and cytokine-stimulated pSTAT signaling in whole blood. Although highly heterogeneous across individuals, many of these assays revealed trends by age, sex, and CMV status, to greater or lesser degrees. Age, then sex and CMV status, showed the greatest impact on the immune system, as measured by the percentage of assay readouts with significant differences. An elastic net regression model could optimally predict age with 14 analytes from different assays. This reinforces the importance of multivariate analysis for defining a healthy immune system. These data provide a reference for others measuring immune parameters in older people. PMID:26197454

  5. Large-scale density functional calculations of the surface properties of the Wigner crystal

    NASA Astrophysics Data System (ADS)

    Cortes-Huerto, R.; Ballone, P.

    2010-05-01

    The surface properties of the jellium model have been investigated by large supercell computations in the density functional theory-local spin-density (DFT-LSD) approach for planar slabs with up to 1000 electrons. A wide interval of densities has been explored, extending into the stability range of the Wigner crystal. Most computations have been carried out on nominally paramagnetic samples with an equal number of spin-up and spin-down electrons. The results show that within DFT-LSD spontaneous spin polarization and charge localization start nearly simultaneously at the surface for rs˜20 , then, with decreasing density, they progress toward the center of the slab. Electrons are fully localized and spin polarized at rs=30 . At this density the charge distribution is the superposition of disjoint charge blobs, each corresponding to one electron. The distribution of blobs displays both regularities and disorder, the first being represented by well-defined planes and simple in-plane geometries, and the latter by a variety of surface defects. The surface energy, surface dipole, electric polarisability, and magnetization pattern have been determined as a function of density. All these quantities display characteristic anomalies at the density of the localization transition. The analysis of the low-frequency electric conductivity shows that in the fluid paramagnetic regime the in-plane current preferentially flows in the central region of the slab and the two spin channels are equally conducting. In the charge localized, spin-polarized regime, conductivity is primarily a surface effect, and an apparent asymmetry is observed in the two spin currents.

  6. Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

    DOE PAGES

    Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...

    2016-02-02

    Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less

  7. Probability density function characterization for aggregated large-scale wind power based on Weibull mixtures

    SciTech Connect

    Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; Martin-Martinez, Sergio; Zhang, Jie; Hodge, Bri -Mathias; Molina-Garcia, Angel

    2016-02-02

    Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power data are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.

  8. Large Scale Functional Brain Networks Underlying Temporal Integration of Audio-Visual Speech Perception: An EEG Study.

    PubMed

    Kumar, G Vinodh; Halder, Tamesh; Jaiswal, Amit K; Mukherjee, Abhishek; Roy, Dipanjan; Banerjee, Arpan

    2016-01-01

    Observable lip movements of the speaker influence perception of auditory speech. A classical example of this influence is reported by listeners who perceive an illusory (cross-modal) speech sound (McGurk-effect) when presented with incongruent audio-visual (AV) speech stimuli. Recent neuroimaging studies of AV speech perception accentuate the role of frontal, parietal, and the integrative brain sites in the vicinity of the superior temporal sulcus (STS) for multisensory speech perception. However, if and how does the network across the whole brain participates during multisensory perception processing remains an open question. We posit that a large-scale functional connectivity among the neural population situated in distributed brain sites may provide valuable insights involved in processing and fusing of AV speech. Varying the psychophysical parameters in tandem with electroencephalogram (EEG) recordings, we exploited the trial-by-trial perceptual variability of incongruent audio-visual (AV) speech stimuli to identify the characteristics of the large-scale cortical network that facilitates multisensory perception during synchronous and asynchronous AV speech. We evaluated the spectral landscape of EEG signals during multisensory speech perception at varying AV lags. Functional connectivity dynamics for all sensor pairs was computed using the time-frequency global coherence, the vector sum of pairwise coherence changes over time. During synchronous AV speech, we observed enhanced global gamma-band coherence and decreased alpha and beta-band coherence underlying cross-modal (illusory) perception compared to unisensory perception around a temporal window of 300-600 ms following onset of stimuli. During asynchronous speech stimuli, a global broadband coherence was observed during cross-modal perception at earlier times along with pre-stimulus decreases of lower frequency power, e.g., alpha rhythms for positive AV lags and theta rhythms for negative AV lags. Thus, our

  9. Large Scale Functional Brain Networks Underlying Temporal Integration of Audio-Visual Speech Perception: An EEG Study

    PubMed Central

    Kumar, G. Vinodh; Halder, Tamesh; Jaiswal, Amit K.; Mukherjee, Abhishek; Roy, Dipanjan; Banerjee, Arpan

    2016-01-01

    Observable lip movements of the speaker influence perception of auditory speech. A classical example of this influence is reported by listeners who perceive an illusory (cross-modal) speech sound (McGurk-effect) when presented with incongruent audio-visual (AV) speech stimuli. Recent neuroimaging studies of AV speech perception accentuate the role of frontal, parietal, and the integrative brain sites in the vicinity of the superior temporal sulcus (STS) for multisensory speech perception. However, if and how does the network across the whole brain participates during multisensory perception processing remains an open question. We posit that a large-scale functional connectivity among the neural population situated in distributed brain sites may provide valuable insights involved in processing and fusing of AV speech. Varying the psychophysical parameters in tandem with electroencephalogram (EEG) recordings, we exploited the trial-by-trial perceptual variability of incongruent audio-visual (AV) speech stimuli to identify the characteristics of the large-scale cortical network that facilitates multisensory perception during synchronous and asynchronous AV speech. We evaluated the spectral landscape of EEG signals during multisensory speech perception at varying AV lags. Functional connectivity dynamics for all sensor pairs was computed using the time-frequency global coherence, the vector sum of pairwise coherence changes over time. During synchronous AV speech, we observed enhanced global gamma-band coherence and decreased alpha and beta-band coherence underlying cross-modal (illusory) perception compared to unisensory perception around a temporal window of 300–600 ms following onset of stimuli. During asynchronous speech stimuli, a global broadband coherence was observed during cross-modal perception at earlier times along with pre-stimulus decreases of lower frequency power, e.g., alpha rhythms for positive AV lags and theta rhythms for negative AV lags. Thus

  10. On the Annual Cycle, Variability, and Correlations of Oceanic Low-Topped Clouds With Large-Scale Circulation Using Aqua MODIS and ECMWF-Interim

    NASA Astrophysics Data System (ADS)

    Kubar, T. L.; Waliser, D. E.; Li, J.; Jiang, X.

    2011-12-01

    Understanding the extent to which low-topped clouds are fundamentally connected to the large-scale atmospheric circulation is of utmost importance in constraining and improving estimates of Earth climate sensitivity. Eight years of Aqua MODIS level-three cloud data with collocated ECMWF-Interim reanalysis data are used to investigate relationships between low-topped cloud cover (LOW CF) and large-scale dynamics and thermodynamics versus timescale. Over much of 25°S to 25°N, LOW CF is strongly anticorrelated with SST, with correlation coefficients increasing dramatically between one and 15 days, and then tending to saturate with only marginally more skill beyond. In five regions selected between 25°S and 25°N with monthly mean SSTs ranging from 291°K to 303°K, ΔLOW CF/ΔSST~ -0.07 K-1, with an r2=0.86, and a low cloud forcing estimate per degree SST change of 8.1 W m-2K-1. This provides insight into the sensitivity of TOA radiation to warming absent circulation changes in low-latitude low-topped cloud regimes. LOW CF is strongly positively correlated with ω500 at most locations, including some mid-latitude regions, with correlations increasing with timescale. Exceptions include regions where mean subsidence is pervasive. In equatorial, subtropical, and mid-latitude regions analyzed, LOW CF is small under ascending regimes and then increases strongly as a function of ω500 under subsidence. Where the fraction of variance explained by the annual LOW CF harmonic is high, maximum LOW CF tends to lead minimum SST by ~15-30 days. In these regions, low-topped clouds may have the effect of amplifying the SST annual cycle. Annual cycle maximum LOW CF tends to be almost in phase with maximum ω500, the latter of which represents the faster timescale of the free-troposphere. These nearly in-phase relationships are strongest where a strong annual cycle exists of ascent and descent, and argue for a strong sensitivity of LOW CF to circulation changes.

  11. Dysfunction of Large-Scale Brain Networks in Schizophrenia: A Meta-analysis of Resting-State Functional Connectivity.

    PubMed

    Dong, Debo; Wang, Yulin; Chang, Xuebin; Luo, Cheng; Yao, Dezhong

    2017-03-11

    Schizophrenia is a complex mental disorder with disorganized communication among large-scale brain networks, as demonstrated by impaired resting-state functional connectivity (rsFC). Individual rsFC studies, however, vary greatly in their methods and findings. We searched for consistent patterns of network dysfunction in schizophrenia by using a coordinate-based meta-analysis. Fifty-six seed-based voxel-wise rsFC datasets from 52 publications (2115 patients and 2297 healthy controls) were included in this meta-analysis. Then, coordinates of seed regions of interest (ROI) and between-group effects were extracted and coded. Seed ROIs were categorized into seed networks by their location within an a priori template. Multilevel kernel density analysis was used to identify brain networks in which schizophrenia was linked to hyper-connectivity or hypo-connectivity with each a priori network. Our results showed that schizophrenia was characterized by hypo-connectivity within the default network (DN, self-related thought), affective network (AN, emotion processing), ventral attention network (VAN, processing of salience), thalamus network (TN, gating information) and somatosensory network (SS, involved in sensory and auditory perception). Additionally, hypo-connectivity between the VAN and TN, VAN and DN, VAN and frontoparietal network (FN, external goal-directed regulation), FN and TN, and FN and DN were found in schizophrenia. Finally, the only instance of hyper-connectivity in schizophrenia was observed between the AN and VAN. Our meta-analysis motivates an empirical foundation for a disconnected large-scale brain networks model of schizophrenia in which the salience processing network (VAN) plays the core role, and its imbalanced communication with other functional networks may underlie the core difficulty of patients to differentiate self-representation (inner world) and environmental salience processing (outside world).

  12. The Joint Statistics of California Temperature and Precipitation as a Function of the Large-scale State of the Climate

    NASA Astrophysics Data System (ADS)

    OBrien, J. P.; O'Brien, T. A.

    2015-12-01

    Single climatic extremes have a strong and disproportionate effect on society and the natural environment. However, the joint occurrence of two or more concurrent extremes has the potential to negatively impact these areas of life in ways far greater than any single event could. California, USA, home to nearly 40 million people and the largest agricultural producer in the United States, is currently experiencing an extreme drought, which has persisted for several years. While drought is commonly thought of in terms of only precipitation deficits, above average temperatures co-occurring with precipitation deficits greatly exacerbate drought conditions. The 2014 calendar year in California was characterized both by extremely low precipitation and extremely high temperatures, which has significantly deepened the already extreme drought conditions leading to severe water shortages and wildfires. While many studies have shown the statistics of 2014 temperature and precipitation anomalies as outliers, none have demonstrated a connection with large-scale, long-term climate trends, which would provide useful relationships for predicting the future trajectory of California climate and water resources. We focus on understanding non-stationarity in the joint distribution of California temperature and precipitation anomalies in terms of large-scale, low-frequency trends in climate such as global mean temperature rise and oscillatory indices such as ENSO and the Pacific Decadal Oscillation among others. We consider temperature and precipitation data from the seven distinct climate divisions in California and employ a novel, high-fidelity kernel density estimation method to directly infer the multivariate distribution of temperature and precipitation anomalies conditioned on the large-scale state of the climate. We show that the joint distributions and associated statistics of temperature and precipitation are non-stationary and vary regionally in California. Further, we show

  13. Large Scale Parameter Estimation Problems in Frequency-Domain Elastodynamics Using an Error in Constitutive Equation Functional

    PubMed Central

    Banerjee, Biswanath; Walsh, Timothy F.; Aquino, Wilkins; Bonnet, Marc

    2012-01-01

    This paper presents the formulation and implementation of an Error in Constitutive Equations (ECE) method suitable for large-scale inverse identification of linear elastic material properties in the context of steady-state elastodynamics. In ECE-based methods, the inverse problem is postulated as an optimization problem in which the cost functional measures the discrepancy in the constitutive equations that connect kinematically admissible strains and dynamically admissible stresses. Furthermore, in a more recent modality of this methodology introduced by Feissel and Allix (2007), referred to as the Modified ECE (MECE), the measured data is incorporated into the formulation as a quadratic penalty term. We show that a simple and efficient continuation scheme for the penalty term, suggested by the theory of quadratic penalty methods, can significantly accelerate the convergence of the MECE algorithm. Furthermore, a (block) successive over-relaxation (SOR) technique is introduced, enabling the use of existing parallel finite element codes with minimal modification to solve the coupled system of equations that arises from the optimality conditions in MECE methods. Our numerical results demonstrate that the proposed methodology can successfully reconstruct the spatial distribution of elastic material parameters from partial and noisy measurements in as few as ten iterations in a 2D example and fifty in a 3D example. We show (through numerical experiments) that the proposed continuation scheme can improve the rate of convergence of MECE methods by at least an order of magnitude versus the alternative of using a fixed penalty parameter. Furthermore, the proposed block SOR strategy coupled with existing parallel solvers produces a computationally efficient MECE method that can be used for large scale materials identification problems, as demonstrated on a 3D example involving about 400,000 unknown moduli. Finally, our numerical results suggest that the proposed MECE

  14. RCSLenS: testing gravitational physics through the cross-correlation of weak lensing and large-scale structure

    NASA Astrophysics Data System (ADS)

    Blake, Chris; Joudaki, Shahab; Heymans, Catherine; Choi, Ami; Erben, Thomas; Harnois-Deraps, Joachim; Hildebrandt, Hendrik; Joachimi, Benjamin; Nakajima, Reiko; van Waerbeke, Ludovic; Viola, Massimo

    2016-03-01

    The unknown nature of `dark energy' motivates continued cosmological tests of large-scale gravitational physics. We present a new consistency check based on the relative amplitude of non-relativistic galaxy peculiar motions, measured via redshift-space distortion, and the relativistic deflection of light by those same galaxies traced by galaxy-galaxy lensing. We take advantage of the latest generation of deep, overlapping imaging and spectroscopic data sets, combining the Red Cluster Sequence Lensing Survey, the Canada-France-Hawaii Telescope Lensing Survey, the WiggleZ Dark Energy Survey and the Baryon Oscillation Spectroscopic Survey. We quantify the results using the `gravitational slip' statistic EG, which we estimate as 0.48 ± 0.10 at z = 0.32 and 0.30 ± 0.07 at z = 0.57, the latter constituting the highest redshift at which this quantity has been determined. These measurements are consistent with the predictions of General Relativity, for a perturbed Friedmann-Robertson-Walker metric in a Universe dominated by a cosmological constant, which are EG = 0.41 and 0.36 at these respective redshifts. The combination of redshift-space distortion and gravitational lensing data from current and future galaxy surveys will offer increasingly stringent tests of fundamental cosmology.

  15. The large-scale distribution of galaxies

    NASA Technical Reports Server (NTRS)

    Geller, Margaret J.

    1989-01-01

    The spatial distribution of galaxies in the universe is characterized on the basis of the six completed strips of the Harvard-Smithsonian Center for Astrophysics redshift-survey extension. The design of the survey is briefly reviewed, and the results are presented graphically. Vast low-density voids similar to the void in Bootes are found, almost completely surrounded by thin sheets of galaxies. Also discussed are the implications of the results for the survey sampling problem, the two-point correlation function of the galaxy distribution, the possibility of detecting large-scale coherent flows, theoretical models of large-scale structure, and the identification of groups and clusters of galaxies.

  16. The integration of large-scale neural network modeling and functional brain imaging in speech motor control

    PubMed Central

    Golfinopoulos, E.; Tourville, J.A.; Guenther, F.H.

    2009-01-01

    Speech production demands a number of integrated processing stages. The system must encode the speech motor programs that command movement trajectories of the articulators and monitor transient spatiotemporal variations in auditory and somatosensory feedback. Early models of this system proposed that independent neural regions perform specialized speech processes. As technology advanced, neuroimaging data revealed that the dynamic sensorimotor processes of speech require a distributed set of interacting neural regions. The DIVA (Directions into Velocities of Articulators) neurocomputational model elaborates on early theories, integrating existing data and contemporary ideologies, to provide a mechanistic account of acoustic, kinematic, and functional magnetic resonance imaging (fMRI) data on speech acquisition and production. This large-scale neural network model is composed of several interconnected components whose cell activities and synaptic weight strengths are governed by differential equations. Cells in the model are associated with neuroanatomical substrates and have been mapped to locations in Montreal Neurological Institute stereotactic space, providing a means to compare simulated and empirical fMRI data. The DIVA model also provides a computational and neurophysiological framework within which to interpret and organize research on speech acquisition and production in fluent and dysfluent child and adult speakers. The purpose of this review article is to demonstrate how the DIVA model is used to motivate and guide functional imaging studies. We describe how model predictions are evaluated using voxel-based, region-of-interest-based parametric analyses and inter-regional effective connectivity modeling of fMRI data. PMID:19837177

  17. Evaluation of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Large-Scale Network Analysis Using Network-Based Statistic.

    PubMed

    Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, B Douglas; Kalinosky, Benjamin; Budde, Matthew D; Schmit, Brian D; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar N

    2017-03-15

    Large-scale network analysis characterizes the brain as a complex network of nodes and edges to evaluate functional connectivity patterns. The utility of graph-based techniques has been demonstrated in an increasing number of resting-state functional MRI (rs-fMRI) studies in the normal and diseased brain. However, to our knowledge, graph theory has not been used to study the reorganization pattern of resting-state brain networks in patients with traumatic complete spinal cord injury (SCI). In the present analysis, we applied a graph-theoretical approach to explore changes to global brain network architecture as a result of SCI. Fifteen subjects with chronic (> 2 years) complete (American Spinal Injury Association [ASIA] A) cervical SCI and 15 neurologically intact controls were scanned using rs-fMRI. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI) or nodes. The average time series was extracted at each node, and correlation analysis was performed between every pair of nodes. A functional connectivity matrix for each subject was then generated. Subsequently, the matrices were averaged across groups, and network changes were evaluated between groups using the network-based statistic (NBS) method. Our results showed decreased connectivity in a subnetwork of the whole brain in SCI compared with control subjects. Upon further examination, increased connectivity was observed in a subnetwork of the sensorimotor cortex and cerebellum network in SCI. In conclusion, our findings emphasize the applicability of NBS to study functional connectivity architecture in diseased brain states. Further, we show reorganization of large-scale resting-state brain networks in traumatic SCI, with potential prognostic and therapeutic implications.

  18. Tuning the morphology of silver nanostructures photochemically coated on glass substrates: an effective approach to large-scale functional surfaces

    NASA Astrophysics Data System (ADS)

    Zaier, Mohamed; Vidal, Loic; Hajjar-Garreau, Samar; Bubendorff, Jean-Luc; Balan, Lavinia

    2017-03-01

    This paper reports on a simple and environmentally friendly photochemical process capable of generating nano-layers (8–22 nm) of silver nanostructures directly onto glass surfaces. This approach opens the way to large-scale functionalized surfaces with plasmonic properties through a single light-induced processing. Thus, Ag nanostructures top-coated were obtained through photo-reduction, at room temperature, of a photosensitive formulation containing a metal precursor, free from extra toxic stabilizers or reducing agents. The reactive formulation was confined between two glass slides and exposed to a continuous near-UV source. In this way, stable silver nano-layers can be generated directly on the substrate with a very good control of the morphology of as-synthesized nanostructures that allows tailoring the optical properties of the coated layers. The position and width of the corresponding surface plasmon resonance bands can be adjusted over a broad spectral window. By extension, this low-cost and easy-to-apply process can also be used to coat ultra thin layers of metal nanostructures on a variety of substrates. The possibility of controlling of nanostructures shape should achieve valuable developments in many fields, as diverse as plasmonics, surface enhanced Raman scattering, nano-electronic circuitry, or medical devices.

  19. Tuning the morphology of silver nanostructures photochemically coated on glass substrates: an effective approach to large-scale functional surfaces.

    PubMed

    Zaier, Mohamed; Vidal, Loic; Hajjar-Garreau, Samar; Bubendorff, Jean-Luc; Balan, Lavinia

    2017-03-10

    This paper reports on a simple and environmentally friendly photochemical process capable of generating nano-layers (8-22 nm) of silver nanostructures directly onto glass surfaces. This approach opens the way to large-scale functionalized surfaces with plasmonic properties through a single light-induced processing. Thus, Ag nanostructures top-coated were obtained through photo-reduction, at room temperature, of a photosensitive formulation containing a metal precursor, free from extra toxic stabilizers or reducing agents. The reactive formulation was confined between two glass slides and exposed to a continuous near-UV source. In this way, stable silver nano-layers can be generated directly on the substrate with a very good control of the morphology of as-synthesized nanostructures that allows tailoring the optical properties of the coated layers. The position and width of the corresponding surface plasmon resonance bands can be adjusted over a broad spectral window. By extension, this low-cost and easy-to-apply process can also be used to coat ultra thin layers of metal nanostructures on a variety of substrates. The possibility of controlling of nanostructures shape should achieve valuable developments in many fields, as diverse as plasmonics, surface enhanced Raman scattering, nano-electronic circuitry, or medical devices.

  20. Large-scale functional RNAi screen in C. elegans identifies genes that regulate the dysfunction of mutant polyglutamine neurons

    PubMed Central

    2012-01-01

    Background A central goal in Huntington's disease (HD) research is to identify and prioritize candidate targets for neuroprotective intervention, which requires genome-scale information on the modifiers of early-stage neuron injury in HD. Results Here, we performed a large-scale RNA interference screen in C. elegans strains that express N-terminal huntingtin (htt) in touch receptor neurons. These neurons control the response to light touch. Their function is strongly impaired by expanded polyglutamines (128Q) as shown by the nearly complete loss of touch response in adult animals, providing an in vivo model in which to manipulate the early phases of expanded-polyQ neurotoxicity. In total, 6034 genes were examined, revealing 662 gene inactivations that either reduce or aggravate defective touch response in 128Q animals. Several genes were previously implicated in HD or neurodegenerative disease, suggesting that this screen has effectively identified candidate targets for HD. Network-based analysis emphasized a subset of high-confidence modifier genes in pathways of interest in HD including metabolic, neurodevelopmental and pro-survival pathways. Finally, 49 modifiers of 128Q-neuron dysfunction that are dysregulated in the striatum of either R/2 or CHL2 HD mice, or both, were identified. Conclusions Collectively, these results highlight the relevance to HD pathogenesis, providing novel information on the potential therapeutic targets for neuroprotection in HD. PMID:22413862

  1. Discovery and functional identification of fecundity-related genes in the brown planthopper by large-scale RNA interference.

    PubMed

    Qiu, J; He, Y; Zhang, J; Kang, K; Li, T; Zhang, W

    2016-12-01

    Recently, transcriptome and proteome data have increasingly been used to identify potential novel genes related to insect phenotypes. However, there are few studies reporting the large-scale functional identification of such genes in insects. To identify novel genes related to fecundity in the brown planthopper (BPH), Nilaparvata lugens, 115 genes were selected from the transcriptomic and proteomic data previously obtained from high- and low-fecundity populations in our laboratory. The results of RNA interference (RNAi) feeding experiments showed that 91.21% of the genes were involved in the regulation of vitellogenin (Vg) expression and may influence BPH fecundity. After RNAi injection experiments, 12 annotated genes were confirmed as fecundity-related genes and three novel genes were identified in the BPH. Finally, C-terminal binding protein (CtBP) was shown to play an important role in BPH fecundity. Knockdown of CtBP not only led to lower survival, underdeveloped ovaries and fewer eggs laid but also resulted in a reduction in Vg protein expression. The novel gene resources gained from this study will be useful for constructing a Vg regulation network and may provide potential target genes for RNAi-based pest control.

  2. Large-scale deformed quasiparticle random-phase approximation calculations of the γ -ray strength function using the Gogny force

    NASA Astrophysics Data System (ADS)

    Martini, M.; Péru, S.; Hilaire, S.; Goriely, S.; Lechaftois, F.

    2016-07-01

    Valuable theoretical predictions of nuclear dipole excitations in the whole chart are of great interest for different nuclear applications, including in particular nuclear astrophysics. Here we present large-scale calculations of the E 1 γ -ray strength function obtained in the framework of the axially symmetric deformed quasiparticle random-phase approximation based on the finite-range Gogny force. This approach is applied to even-even nuclei, the strength function for odd nuclei being derived by interpolation. The convergence with respect to the adopted number of harmonic oscillator shells and the cutoff energy introduced in the 2-quasiparticle (2 -q p ) excitation space is analyzed. The calculations performed with two different Gogny interactions, namely D1S and D1M, are compared. A systematic energy shift of the E 1 strength is found for D1M relative to D1S, leading to a lower energy centroid and a smaller energy-weighted sum rule for D1M. When comparing with experimental photoabsorption data, the Gogny-QRPA predictions are found to overestimate the giant dipole energy by typically ˜2 MeV. Despite the microscopic nature of our self-consistent Hartree-Fock-Bogoliubov plus QRPA calculation, some phenomenological corrections need to be included to take into account the effects beyond the standard 2 -q p QRPA excitations and the coupling between the single-particle and low-lying collective phonon degrees of freedom. For this purpose, three prescriptions of folding procedure are considered and adjusted to reproduce experimental photoabsorption data at best. All of them are shown to lead to somewhat similar predictions of the E 1 strength, both at low energies and for exotic neutron-rich nuclei. Predictions of γ -ray strength functions and Maxwellian-averaged neutron capture rates for the whole Sn isotopic chain are also discussed and compared with previous theoretical calculations.

  3. Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics

    PubMed Central

    Mitchell, Joshua M.; Fan, Teresa W.-M.; Lane, Andrew N.; Moseley, Hunter N. B.

    2014-01-01

    Large-scale identification of metabolites is key to elucidating and modeling metabolism at the systems level. Advances in metabolomics technologies, particularly ultra-high resolution mass spectrometry (MS) enable comprehensive and rapid analysis of metabolites. However, a significant barrier to meaningful data interpretation is the identification of a wide range of metabolites including unknowns and the determination of their role(s) in various metabolic networks. Chemoselective (CS) probes to tag metabolite functional groups combined with high mass accuracy provide additional structural constraints for metabolite identification and quantification. We have developed a novel algorithm, Chemically Aware Substructure Search (CASS) that efficiently detects functional groups within existing metabolite databases, allowing for combined molecular formula and functional group (from CS tagging) queries to aid in metabolite identification without a priori knowledge. Analysis of the isomeric compounds in both Human Metabolome Database (HMDB) and KEGG Ligand demonstrated a high percentage of isomeric molecular formulae (43 and 28%, respectively), indicating the necessity for techniques such as CS-tagging. Furthermore, these two databases have only moderate overlap in molecular formulae. Thus, it is prudent to use multiple databases in metabolite assignment, since each major metabolite database represents different portions of metabolism within the biosphere. In silico analysis of various CS-tagging strategies under different conditions for adduct formation demonstrate that combined FT-MS derived molecular formulae and CS-tagging can uniquely identify up to 71% of KEGG and 37% of the combined KEGG/HMDB database vs. 41 and 17%, respectively without adduct formation. This difference between database isomer disambiguation highlights the strength of CS-tagging for non-lipid metabolite identification. However, unique identification of complex lipids still needs additional

  4. Development and in silico evaluation of large-scale metabolite identification methods using functional group detection for metabolomics.

    PubMed

    Mitchell, Joshua M; Fan, Teresa W-M; Lane, Andrew N; Moseley, Hunter N B

    2014-01-01

    Large-scale identification of metabolites is key to elucidating and modeling metabolism at the systems level. Advances in metabolomics technologies, particularly ultra-high resolution mass spectrometry (MS) enable comprehensive and rapid analysis of metabolites. However, a significant barrier to meaningful data interpretation is the identification of a wide range of metabolites including unknowns and the determination of their role(s) in various metabolic networks. Chemoselective (CS) probes to tag metabolite functional groups combined with high mass accuracy provide additional structural constraints for metabolite identification and quantification. We have developed a novel algorithm, Chemically Aware Substructure Search (CASS) that efficiently detects functional groups within existing metabolite databases, allowing for combined molecular formula and functional group (from CS tagging) queries to aid in metabolite identification without a priori knowledge. Analysis of the isomeric compounds in both Human Metabolome Database (HMDB) and KEGG Ligand demonstrated a high percentage of isomeric molecular formulae (43 and 28%, respectively), indicating the necessity for techniques such as CS-tagging. Furthermore, these two databases have only moderate overlap in molecular formulae. Thus, it is prudent to use multiple databases in metabolite assignment, since each major metabolite database represents different portions of metabolism within the biosphere. In silico analysis of various CS-tagging strategies under different conditions for adduct formation demonstrate that combined FT-MS derived molecular formulae and CS-tagging can uniquely identify up to 71% of KEGG and 37% of the combined KEGG/HMDB database vs. 41 and 17%, respectively without adduct formation. This difference between database isomer disambiguation highlights the strength of CS-tagging for non-lipid metabolite identification. However, unique identification of complex lipids still needs additional

  5. Large-scale all-electron density functional theory calculations using an enriched finite-element basis

    NASA Astrophysics Data System (ADS)

    Kanungo, Bikash; Gavini, Vikram

    2017-01-01

    We present a computationally efficient approach to perform large-scale all-electron density functional theory calculations by enriching the classical finite element basis with compactly supported atom-centered numerical basis functions that are constructed from the solution of the Kohn-Sham (KS) problem for single atoms. We term these numerical basis functions as enrichment functions, and the resultant basis as the enriched finite element basis. The compact support for the enrichment functions is obtained by using smooth cutoff functions, which enhances the conditioning and maintains the locality of the enriched finite element basis. The integrals involved in the evaluation of the discrete KS Hamiltonian and overlap matrix in the enriched finite element basis are computed using an adaptive quadrature grid that is constructed based on the characteristics of enrichment functions. Further, we propose an efficient scheme to invert the overlap matrix by using a blockwise matrix inversion in conjunction with special reduced-order quadrature rules, which is required to transform the discrete Kohn-Sham problem to a standard eigenvalue problem. Finally, we solve the resulting standard eigenvalue problem, in each self-consistent field iteration, by using a Chebyshev polynomial based filtering technique to compute the relevant eigenspectrum. We demonstrate the accuracy, efficiency, and parallel scalability of the proposed method on semiconducting and heavy-metallic systems of various sizes, with the largest system containing 8694 electrons. We obtain accuracies in the ground-state energies that are ˜1 mHa with reference ground-state energies employing classical finite element as well as Gaussian basis sets. Using the proposed formulation based on enriched finite element basis, for accuracies commensurate with chemical accuracy, we observe a staggering 50 -300 -fold reduction in the overall computational time when compared to classical finite element basis. Further, we find a

  6. Large Scale Cortical Functional Networks Associated with Slow-Wave and Spindle-Burst-Related Spontaneous Activity

    PubMed Central

    McVea, David A.; Murphy, Timothy H.; Mohajerani, Majid H.

    2016-01-01

    Cortical sensory systems are active with rich patterns of activity during sleep and under light anesthesia. Remarkably, this activity shares many characteristics with those present when the awake brain responds to sensory stimuli. We review two specific forms of such activity: slow-wave activity (SWA) in the adult brain and spindle bursts in developing brain. SWA is composed of 0.5–4 Hz resting potential fluctuations. Although these fluctuations synchronize wide regions of cortex, recent large-scale imaging has shown spatial details of their distribution that reflect underlying cortical structural projections and networks. These networks are regulated, as prior awake experiences alter both the spatial and temporal features of SWA in subsequent sleep. Activity patterns of the immature brain, however, are very different from those of the adult. SWA is absent, and the dominant pattern is spindle bursts, intermittent high frequency oscillations superimposed on slower depolarizations within sensory cortices. These bursts are driven by intrinsic brain activity, which act to generate peripheral inputs, for example via limb twitches. They are present within developing sensory cortex before they are mature enough to exhibit directed movements and respond to external stimuli. Like in the adult, these patterns resemble those evoked by sensory stimulation when awake. It is suggested that spindle-burst activity is generated purposefully by the developing nervous system as a proxy for true external stimuli. While the sleep-related functions of both slow-wave and spindle-burst activity may not be entirely clear, they reflect robust regulated phenomena which can engage select wide-spread cortical circuits. These circuits are similar to those activated during sensory processing and volitional events. We highlight these two patterns of brain activity because both are prominent and well-studied forms of spontaneous activity that will yield valuable insights into brain function in

  7. Local unitary transformation method toward practical electron correlation calculations with scalar relativistic effect in large-scale molecules.

    PubMed

    Seino, Junji; Nakai, Hiromi

    2013-07-21

    In order to perform practical electron correlation calculations, the local unitary transformation (LUT) scheme at the spin-free infinite-order Douglas-Kroll-Hess (IODKH) level [J. Seino and H. Nakai, J. Chem. Phys. 136, 244102 (2012); and ibid. 137, 144101 (2012)], which is based on the locality of relativistic effects, has been combined with the linear-scaling divide-and-conquer (DC)-based Hartree-Fock (HF) and electron correlation methods, such as the second-order Mo̸ller-Plesset (MP2) and the coupled cluster theories with single and double excitations (CCSD). Numerical applications in hydrogen halide molecules, (HX)n (X = F, Cl, Br, and I), coinage metal chain systems, Mn (M = Cu and Ag), and platinum-terminated polyynediyl chain, trans,trans-{(p-CH3C6H4)3P}2(C6H5)Pt(C≡C)4Pt(C6H5){(p-CH3C6H4)3P}2, clarified that the present methods, namely DC-HF, MP2, and CCSD with the LUT-IODKH Hamiltonian, reproduce the results obtained using conventional methods with small computational costs. The combination of both LUT and DC techniques could be the first approach that achieves overall quasi-linear-scaling with a small prefactor for relativistic electron correlation calculations.

  8. Local unitary transformation method toward practical electron correlation calculations with scalar relativistic effect in large-scale molecules

    SciTech Connect

    Seino, Junji; Nakai, Hiromi

    2013-07-21

    In order to perform practical electron correlation calculations, the local unitary transformation (LUT) scheme at the spin-free infinite-order Douglas–Kroll–Hess (IODKH) level [J. Seino and H. Nakai, J. Chem. Phys.136, 244102 (2012); J. Seino and H. Nakai, J. Chem. Phys.137, 144101 (2012)], which is based on the locality of relativistic effects, has been combined with the linear-scaling divide-and-conquer (DC)-based Hartree–Fock (HF) and electron correlation methods, such as the second-order Møller–Plesset (MP2) and the coupled cluster theories with single and double excitations (CCSD). Numerical applications in hydrogen halide molecules, (HX){sub n} (X = F, Cl, Br, and I), coinage metal chain systems, M{sub n} (M = Cu and Ag), and platinum-terminated polyynediyl chain, trans,trans-((p-CH{sub 3}C{sub 6}H{sub 4}){sub 3}P){sub 2}(C{sub 6}H{sub 5})Pt(C≡C){sub 4}Pt(C{sub 6}H{sub 5})((p-CH{sub 3}C{sub 6}H{sub 4}){sub 3}P){sub 2}, clarified that the present methods, namely DC-HF, MP2, and CCSD with the LUT-IODKH Hamiltonian, reproduce the results obtained using conventional methods with small computational costs. The combination of both LUT and DC techniques could be the first approach that achieves overall quasi-linear-scaling with a small prefactor for relativistic electron correlation calculations.

  9. Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets[C][W][OA

    PubMed Central

    Bassel, George W.; Glaab, Enrico; Marquez, Julietta; Holdsworth, Michael J.; Bacardit, Jaume

    2011-01-01

    The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed “coprediction,” is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/. PMID:21896882

  10. Large scale dynamic systems

    NASA Technical Reports Server (NTRS)

    Doolin, B. F.

    1975-01-01

    Classes of large scale dynamic systems were discussed in the context of modern control theory. Specific examples discussed were in the technical fields of aeronautics, water resources and electric power.

  11. Parallel Large-scale Semidefinite Programming for Strong Electron Correlation: Using Correlation and Entanglement in the Design of Efficient Energy-Transfer Mechanisms

    DTIC Science & Technology

    2014-09-24

    RETURN YOUR FORM TO THE ABOVE ADDRESS. University of Chicago 5801 South Ellis Avenue Chicago , IL 60637 -5418 1 ABSTRACT Final Report: Parallel Large-scale...supported 2012: Promotion of PI to Full Professor at The University of Chicago 2014: Quantrell Award to PI from The University of Chicago ...sponsored research. 9 Final Report 2014 David A. Mazziotti The University of Chicago Statement of the Problem Solved Challenges addressed by the

  12. On using large scale correlation of the Ly-α forest and redshifted 21-cm signal to probe HI distribution during the post reionization era

    SciTech Connect

    Sarkar, Tapomoy Guha; Datta, Kanan K. E-mail: kanan.physics@presiuniv.ac.in

    2015-08-01

    We investigate the possibility of detecting the 3D cross correlation power spectrum of the Ly-α forest and HI 21 cm signal from the post reionization epoch. (The cross-correlation signal is directly dependent on the dark matter power spectrum and is sensitive to the 21-cm brightness temperature and Ly-α forest biases. These bias parameters dictate the strength of anisotropy in redshift space.) We find that the cross-correlation power spectrum can be detected using 400 hrs observation with SKA-mid (phase 1) and a futuristic BOSS like experiment with a quasar (QSO) density of 30 deg{sup −2} at a peak SNR of 15 for a single field experiment at redshift z = 2.5. on large scales using the linear bias model. We also study the possibility of constraining various bias parameters using the cross power spectrum. We find that with the same experiment 1 σ (conditional errors) on the 21-cm linear redshift space distortion parameter β{sub T} and β{sub F} corresponding to the Ly-α  forest are ∼ 2.7 % and ∼ 1.4 % respectively for 01 independent pointings of the SKA-mid (phase 1). This prediction indicates a significant improvement over existing measurements. We claim that the detection of the 3D cross correlation power spectrum will not only ascertain the cosmological origin of the signal in presence of astrophysical foregrounds but will also provide stringent constraints on large scale HI biases. This provides an independent probe towards understanding cosmological structure formation.

  13. Large-Scale Curriculum Reform in Finland--Exploring the Interrelation between Implementation Strategy, the Function of the Reform, and Curriculum Coherence

    ERIC Educational Resources Information Center

    Pietarinen, Janne; Pyhältö, Kirsi; Soini, Tiina

    2017-01-01

    The study aims to gain a better understanding of the national large-scale curriculum process in terms of the used implementation strategies, the function of the reform, and the curriculum coherence perceived by the stakeholders accountable in constructing the national core curriculum in Finland. A large body of school reform literature has shown…

  14. Large-scale structural optimization

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.

    1983-01-01

    Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

  15. Morphological, physiological and anatomical traits of plant functional types in temperate grasslands along a large-scale aridity gradient in northeastern China

    PubMed Central

    Guo, Chengyuan; Ma, Linna; Yuan, Shan; Wang, Renzhong

    2017-01-01

    At the species level, plants can respond to climate changes by changing their leaf traits; however, there is scant information regarding the responses of morphological, physiological and anatomical traits of plant functional types (PFTs) to aridity. Herein, the leaf traits of five PFTs representing 17 plant species in temperate grasslands were examined along a large-scale aridity gradient in northeastern China. The results show that leaf thickness in shrubs, perennial grasses and forbs increased with heightened aridity. Trees increased soluble sugar content, but shrubs, perennials and annual grasses enhanced proline accumulation due to increasing aridity. Moreover, vessel diameter and stomatal index in shrubs and perennial grasses decreased with increasing aridity, but stomatal density and vascular diameter of five PFTs were not correlated with water availability. In conclusion, divergences in adaptive strategies to aridity among these PFTs in temperate grasslands were likely caused by differences in their utilization of water resources, which have different temporal and spatial distribution patterns. Leaf traits of shrubs and perennial grasses had the largest responses to variability of aridity through regulation of morphological, physiological and anatomical traits, which was followed by perennial forbs. Trees and annual grasses endured aridity only by adjusting leaf physiological processes. PMID:28106080

  16. Metaproteomics reveals major microbial players and their biodegradation functions in a large-scale aerobic composting plant.

    PubMed

    Liu, Dongming; Li, Mingxiao; Xi, Beidou; Zhao, Yue; Wei, Zimin; Song, Caihong; Zhu, Chaowei

    2015-11-01

    Composting is an appropriate management alternative for municipal solid waste; however, our knowledge about the microbial regulation of this process is still scare. We employed metaproteomics to elucidate the main biodegradation pathways in municipal solid waste composting system across the main phases in a large-scale composting plant. The investigation of microbial succession revealed that Bacillales, Actinobacteria and Saccharomyces increased significantly with respect to abundance in composting process. The key microbiologic population for cellulose degradation in different composting stages was different. Fungi were found to be the main producers of cellulase in earlier phase. However, the cellulolytic fungal communities were gradually replaced by a purely bacterial one in active phase, which did not support the concept that the thermophilic fungi are active through the thermophilic phase. The effective decomposition of cellulose required the synergy between bacteria and fungi in the curing phase.

  17. Metaproteomics reveals major microbial players and their biodegradation functions in a large-scale aerobic composting plant

    PubMed Central

    Liu, Dongming; Li, Mingxiao; Xi, Beidou; Zhao, Yue; Wei, Zimin; Song, Caihong; Zhu, Chaowei

    2015-01-01

    Composting is an appropriate management alternative for municipal solid waste; however, our knowledge about the microbial regulation of this process is still scare. We employed metaproteomics to elucidate the main biodegradation pathways in municipal solid waste composting system across the main phases in a large-scale composting plant. The investigation of microbial succession revealed that Bacillales, Actinobacteria and Saccharomyces increased significantly with respect to abundance in composting process. The key microbiologic population for cellulose degradation in different composting stages was different. Fungi were found to be the main producers of cellulase in earlier phase. However, the cellulolytic fungal communities were gradually replaced by a purely bacterial one in active phase, which did not support the concept that the thermophilic fungi are active through the thermophilic phase. The effective decomposition of cellulose required the synergy between bacteria and fungi in the curing phase. PMID:25989417

  18. Large-Scale Disasters

    NASA Astrophysics Data System (ADS)

    Gad-El-Hak, Mohamed

    "Extreme" events - including climatic events, such as hurricanes, tornadoes, and drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents a review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters.

  19. Large-scale brain functional modularity is reflected in slow electroencephalographic rhythms across the human non-rapid eye movement sleep cycle.

    PubMed

    Tagliazucchi, Enzo; von Wegner, Frederic; Morzelewski, Astrid; Brodbeck, Verena; Borisov, Sergey; Jahnke, Kolja; Laufs, Helmut

    2013-04-15

    Large-scale brain functional networks (measured with functional magnetic resonance imaging, fMRI) are organized into separated but interacting modules, an architecture supporting the integration of distinct dynamical processes. In this work we study how the aforementioned modular architecture changes with the progressive loss of vigilance occurring in the descent to deep sleep and we examine the relationship between the ensuing slow electroencephalographic rhythms and large-scale network modularity as measured with fMRI. Graph theoretical methods are used to analyze functional connectivity graphs obtained from fifty-five participants at wakefulness, light and deep sleep. Network modularity (a measure of functional segregation) was found to increase during deeper sleep stages but not in light sleep. By endowing functional networks with dynamical properties, we found a direct link between increased electroencephalographic (EEG) delta power (1-4 Hz) and a breakdown of inter-modular connectivity. Both EEG slowing and increased network modularity were found to quickly decrease during awakenings from deep sleep to wakefulness, in a highly coordinated fashion. Studying the modular structure itself by means of a permutation test, we revealed different module memberships when deep sleep was compared to wakefulness. Analysis of node roles in the modular structure revealed an increase in the number of locally well-connected nodes and a decrease in the number of globally well-connected hubs, which hinders interactions between separated functional modules. Our results reveal a well-defined sequence of changes in brain modular organization occurring during the descent to sleep and establish a close parallel between modularity alterations in large-scale functional networks (accessible through whole brain fMRI recordings) and the slowing of scalp oscillations (visible on EEG). The observed re-arrangement of connectivity might play an important role in the processes underlying loss

  20. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function.

    PubMed

    Soler Artigas, María; Loth, Daan W; Wain, Louise V; Gharib, Sina A; Obeidat, Ma'en; Tang, Wenbo; Zhai, Guangju; Zhao, Jing Hua; Smith, Albert Vernon; Huffman, Jennifer E; Albrecht, Eva; Jackson, Catherine M; Evans, David M; Cadby, Gemma; Fornage, Myriam; Manichaikul, Ani; Lopez, Lorna M; Johnson, Toby; Aldrich, Melinda C; Aspelund, Thor; Barroso, Inês; Campbell, Harry; Cassano, Patricia A; Couper, David J; Eiriksdottir, Gudny; Franceschini, Nora; Garcia, Melissa; Gieger, Christian; Gislason, Gauti Kjartan; Grkovic, Ivica; Hammond, Christopher J; Hancock, Dana B; Harris, Tamara B; Ramasamy, Adaikalavan; Heckbert, Susan R; Heliövaara, Markku; Homuth, Georg; Hysi, Pirro G; James, Alan L; Jankovic, Stipan; Joubert, Bonnie R; Karrasch, Stefan; Klopp, Norman; Koch, Beate; Kritchevsky, Stephen B; Launer, Lenore J; Liu, Yongmei; Loehr, Laura R; Lohman, Kurt; Loos, Ruth J F; Lumley, Thomas; Al Balushi, Khalid A; Ang, Wei Q; Barr, R Graham; Beilby, John; Blakey, John D; Boban, Mladen; Boraska, Vesna; Brisman, Jonas; Britton, John R; Brusselle, Guy G; Cooper, Cyrus; Curjuric, Ivan; Dahgam, Santosh; Deary, Ian J; Ebrahim, Shah; Eijgelsheim, Mark; Francks, Clyde; Gaysina, Darya; Granell, Raquel; Gu, Xiangjun; Hankinson, John L; Hardy, Rebecca; Harris, Sarah E; Henderson, John; Henry, Amanda; Hingorani, Aroon D; Hofman, Albert; Holt, Patrick G; Hui, Jennie; Hunter, Michael L; Imboden, Medea; Jameson, Karen A; Kerr, Shona M; Kolcic, Ivana; Kronenberg, Florian; Liu, Jason Z; Marchini, Jonathan; McKeever, Tricia; Morris, Andrew D; Olin, Anna-Carin; Porteous, David J; Postma, Dirkje S; Rich, Stephen S; Ring, Susan M; Rivadeneira, Fernando; Rochat, Thierry; Sayer, Avan Aihie; Sayers, Ian; Sly, Peter D; Smith, George Davey; Sood, Akshay; Starr, John M; Uitterlinden, André G; Vonk, Judith M; Wannamethee, S Goya; Whincup, Peter H; Wijmenga, Cisca; Williams, O Dale; Wong, Andrew; Mangino, Massimo; Marciante, Kristin D; McArdle, Wendy L; Meibohm, Bernd; Morrison, Alanna C; North, Kari E; Omenaas, Ernst; Palmer, Lyle J; Pietiläinen, Kirsi H; Pin, Isabelle; Pola Sbreve Ek, Ozren; Pouta, Anneli; Psaty, Bruce M; Hartikainen, Anna-Liisa; Rantanen, Taina; Ripatti, Samuli; Rotter, Jerome I; Rudan, Igor; Rudnicka, Alicja R; Schulz, Holger; Shin, So-Youn; Spector, Tim D; Surakka, Ida; Vitart, Veronique; Völzke, Henry; Wareham, Nicholas J; Warrington, Nicole M; Wichmann, H-Erich; Wild, Sarah H; Wilk, Jemma B; Wjst, Matthias; Wright, Alan F; Zgaga, Lina; Zemunik, Tatijana; Pennell, Craig E; Nyberg, Fredrik; Kuh, Diana; Holloway, John W; Boezen, H Marike; Lawlor, Debbie A; Morris, Richard W; Probst-Hensch, Nicole; Kaprio, Jaakko; Wilson, James F; Hayward, Caroline; Kähönen, Mika; Heinrich, Joachim; Musk, Arthur W; Jarvis, Deborah L; Gläser, Sven; Järvelin, Marjo-Riitta; Ch Stricker, Bruno H; Elliott, Paul; O'Connor, George T; Strachan, David P; London, Stephanie J; Hall, Ian P; Gudnason, Vilmundur; Tobin, Martin D

    2011-09-25

    Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 × 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.

  1. Genome-wide association and large scale follow-up identifies 16 new loci influencing lung function

    PubMed Central

    Artigas, María Soler; Loth, Daan W; Wain, Louise V; Gharib, Sina A; Obeidat, Ma’en; Tang, Wenbo; Zhai, Guangju; Zhao, Jing Hua; Smith, Albert Vernon; Huffman, Jennifer E; Albrecht, Eva; Jackson, Catherine M; Evans, David M; Cadby, Gemma; Fornage, Myriam; Manichaikul, Ani; Lopez, Lorna M; Johnson, Toby; Aldrich, Melinda C; Aspelund, Thor; Barroso, Inês; Campbell, Harry; Cassano, Patricia A; Couper, David J; Eiriksdottir, Gudny; Franceschini, Nora; Garcia, Melissa; Gieger, Christian; Gislason, Gauti Kjartan; Grkovic, Ivica; Hammond, Christopher J; Hancock, Dana B; Harris, Tamara B; Ramasamy, Adaikalavan; Heckbert, Susan R; Heliövaara, Markku; Homuth, Georg; Hysi, Pirro G; James, Alan L; Jankovic, Stipan; Joubert, Bonnie R; Karrasch, Stefan; Klopp, Norman; Koch, Beate; Kritchevsky, Stephen B; Launer, Lenore J; Liu, Yongmei; Loehr, Laura R; Lohman, Kurt; Loos, Ruth JF; Lumley, Thomas; Al Balushi, Khalid A; Ang, Wei Q; Barr, R Graham; Beilby, John; Blakey, John D; Boban, Mladen; Boraska, Vesna; Brisman, Jonas; Britton, John R; Brusselle, Guy G; Cooper, Cyrus; Curjuric, Ivan; Dahgam, Santosh; Deary, Ian J; Ebrahim, Shah; Eijgelsheim, Mark; Francks, Clyde; Gaysina, Darya; Granell, Raquel; Gu, Xiangjun; Hankinson, John L; Hardy, Rebecca; Harris, Sarah E; Henderson, John; Henry, Amanda; Hingorani, Aroon D; Hofman, Albert; Holt, Patrick G; Hui, Jennie; Hunter, Michael L; Imboden, Medea; Jameson, Karen A; Kerr, Shona M; Kolcic, Ivana; Kronenberg, Florian; Liu, Jason Z; Marchini, Jonathan; McKeever, Tricia; Morris, Andrew D; Olin, Anna-Carin; Porteous, David J; Postma, Dirkje S; Rich, Stephen S; Ring, Susan M; Rivadeneira, Fernando; Rochat, Thierry; Sayer, Avan Aihie; Sayers, Ian; Sly, Peter D; Smith, George Davey; Sood, Akshay; Starr, John M; Uitterlinden, André G; Vonk, Judith M; Wannamethee, S Goya; Whincup, Peter H; Wijmenga, Cisca; Williams, O Dale; Wong, Andrew; Mangino, Massimo; Marciante, Kristin D; McArdle, Wendy L; Meibohm, Bernd; Morrison, Alanna C; North, Kari E; Omenaas, Ernst; Palmer, Lyle J; Pietiläinen, Kirsi H; Pin, Isabelle; Polašek, Ozren; Pouta, Anneli; Psaty, Bruce M; Hartikainen, Anna-Liisa; Rantanen, Taina; Ripatti, Samuli; Rotter, Jerome I; Rudan, Igor; Rudnicka, Alicja R; Schulz, Holger; Shin, So-Youn; Spector, Tim D; Surakka, Ida; Vitart, Veronique; Völzke, Henry; Wareham, Nicholas J; Warrington, Nicole M; Wichmann, H-Erich; Wild, Sarah H; Wilk, Jemma B; Wjst, Matthias; Wright, Alan F; Zgaga, Lina; Zemunik, Tatijana; Pennell, Craig E; Nyberg, Fredrik; Kuh, Diana; Holloway, John W; Boezen, H Marike; Lawlor, Debbie A; Morris, Richard W; Probst-Hensch, Nicole; Kaprio, Jaakko; Wilson, James F; Hayward, Caroline; Kähönen, Mika; Heinrich, Joachim; Musk, Arthur W; Jarvis, Deborah L; Gläser, Sven; Järvelin, Marjo-Riitta; Stricker, Bruno H Ch; Elliott, Paul; O’Connor, George T; Strachan, David P; London, Stephanie J; Hall, Ian P; Gudnason, Vilmundur; Tobin, Martin D

    2011-01-01

    Pulmonary function measures reflect respiratory health and predict mortality, and are used in the diagnosis of chronic obstructive pulmonary disease (COPD). We tested genome-wide association with the forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) in 48,201 individuals of European ancestry, with follow-up of top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P<5×10−8) with pulmonary function, in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1, and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function. PMID:21946350

  2. Large-Scale Determination of Sequence, Structure, and Function Relationships in Cytosolic Glutathione Transferases across the Biosphere

    PubMed Central

    Mashiyama, Susan T.; Malabanan, M. Merced; Akiva, Eyal; Bhosle, Rahul; Branch, Megan C.; Hillerich, Brandan; Jagessar, Kevin; Kim, Jungwook; Patskovsky, Yury; Seidel, Ronald D.; Stead, Mark; Toro, Rafael; Vetting, Matthew W.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.

    2014-01-01

    The cytosolic glutathione transferase (cytGST) superfamily comprises more than 13,000 nonredundant sequences found throughout the biosphere. Their key roles in metabolism and defense against oxidative damage have led to thousands of studies over several decades. Despite this attention, little is known about the physiological reactions they catalyze and most of the substrates used to assay cytGSTs are synthetic compounds. A deeper understanding of relationships across the superfamily could provide new clues about their functions. To establish a foundation for expanded classification of cytGSTs, we generated similarity-based subgroupings for the entire superfamily. Using the resulting sequence similarity networks, we chose targets that broadly covered unknown functions and report here experimental results confirming GST-like activity for 82 of them, along with 37 new 3D structures determined for 27 targets. These new data, along with experimentally known GST reactions and structures reported in the literature, were painted onto the networks to generate a global view of their sequence-structure-function relationships. The results show how proteins of both known and unknown function relate to each other across the entire superfamily and reveal that the great majority of cytGSTs have not been experimentally characterized or annotated by canonical class. A mapping of taxonomic classes across the superfamily indicates that many taxa are represented in each subgroup and highlights challenges for classification of superfamily sequences into functionally relevant classes. Experimental determination of disulfide bond reductase activity in many diverse subgroups illustrate a theme common for many reaction types. Finally, sequence comparison between an enzyme that catalyzes a reductive dechlorination reaction relevant to bioremediation efforts with some of its closest homologs reveals differences among them likely to be associated with evolution of this unusual reaction

  3. Large-scale determination of sequence, structure, and function relationships in cytosolic glutathione transferases across the biosphere.

    PubMed

    Mashiyama, Susan T; Malabanan, M Merced; Akiva, Eyal; Bhosle, Rahul; Branch, Megan C; Hillerich, Brandan; Jagessar, Kevin; Kim, Jungwook; Patskovsky, Yury; Seidel, Ronald D; Stead, Mark; Toro, Rafael; Vetting, Matthew W; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C

    2014-04-01

    The cytosolic glutathione transferase (cytGST) superfamily comprises more than 13,000 nonredundant sequences found throughout the biosphere. Their key roles in metabolism and defense against oxidative damage have led to thousands of studies over several decades. Despite this attention, little is known about the physiological reactions they catalyze and most of the substrates used to assay cytGSTs are synthetic compounds. A deeper understanding of relationships across the superfamily could provide new clues about their functions. To establish a foundation for expanded classification of cytGSTs, we generated similarity-based subgroupings for the entire superfamily. Using the resulting sequence similarity networks, we chose targets that broadly covered unknown functions and report here experimental results confirming GST-like activity for 82 of them, along with 37 new 3D structures determined for 27 targets. These new data, along with experimentally known GST reactions and structures reported in the literature, were painted onto the networks to generate a global view of their sequence-structure-function relationships. The results show how proteins of both known and unknown function relate to each other across the entire superfamily and reveal that the great majority of cytGSTs have not been experimentally characterized or annotated by canonical class. A mapping of taxonomic classes across the superfamily indicates that many taxa are represented in each subgroup and highlights challenges for classification of superfamily sequences into functionally relevant classes. Experimental determination of disulfide bond reductase activity in many diverse subgroups illustrate a theme common for many reaction types. Finally, sequence comparison between an enzyme that catalyzes a reductive dechlorination reaction relevant to bioremediation efforts with some of its closest homologs reveals differences among them likely to be associated with evolution of this unusual reaction

  4. Large-scale variation in combined impacts of canopy loss and disturbance on community structure and ecosystem functioning.

    PubMed

    Crowe, Tasman P; Cusson, Mathieu; Bulleri, Fabio; Davoult, Dominique; Arenas, Francisco; Aspden, Rebecca; Benedetti-Cecchi, Lisandro; Bevilacqua, Stanislao; Davidson, Irvine; Defew, Emma; Fraschetti, Simonetta; Golléty, Claire; Griffin, John N; Herkül, Kristjan; Kotta, Jonne; Migné, Aline; Molis, Markus; Nicol, Sophie K; Noël, Laure M-L J; Pinto, Isabel Sousa; Valdivia, Nelson; Vaselli, Stefano; Jenkins, Stuart R

    2013-01-01

    Ecosystems are under pressure from multiple human disturbances whose impact may vary depending on environmental context. We experimentally evaluated variation in the separate and combined effects of the loss of a key functional group (canopy algae) and physical disturbance on rocky shore ecosystems at nine locations across Europe. Multivariate community structure was initially affected (during the first three to six months) at six locations but after 18 months, effects were apparent at only three. Loss of canopy caused increases in cover of non-canopy algae in the three locations in southern Europe and decreases in some northern locations. Measures of ecosystem functioning (community respiration, gross primary productivity, net primary productivity) were affected by loss of canopy at five of the six locations for which data were available. Short-term effects on community respiration were widespread, but effects were rare after 18 months. Functional changes corresponded with changes in community structure and/or species richness at most locations and times sampled, but no single aspect of biodiversity was an effective predictor of longer-term functional changes. Most ecosystems studied were able to compensate in functional terms for impacts caused by indiscriminate physical disturbance. The only consistent effect of disturbance was to increase cover of non-canopy species. Loss of canopy algae temporarily reduced community resistance to disturbance at only two locations and at two locations actually increased resistance. Resistance to disturbance-induced changes in gross primary productivity was reduced by loss of canopy algae at four locations. Location-specific variation in the effects of the same stressors argues for flexible frameworks for the management of marine environments. These results also highlight the need to analyse how species loss and other stressors combine and interact in different environmental contexts.

  5. A large-scale zebrafish gene knockout resource for the genome-wide study of gene function.

    PubMed

    Varshney, Gaurav K; Lu, Jing; Gildea, Derek E; Huang, Haigen; Pei, Wuhong; Yang, Zhongan; Huang, Sunny C; Schoenfeld, David; Pho, Nam H; Casero, David; Hirase, Takashi; Mosbrook-Davis, Deborah; Zhang, Suiyuan; Jao, Li-En; Zhang, Bo; Woods, Ian G; Zimmerman, Steven; Schier, Alexander F; Wolfsberg, Tyra G; Pellegrini, Matteo; Burgess, Shawn M; Lin, Shuo

    2013-04-01

    With the completion of the zebrafish genome sequencing project, it becomes possible to analyze the function of zebrafish genes in a systematic way. The first step in such an analysis is to inactivate each protein-coding gene by targeted or random mutation. Here we describe a streamlined pipeline using proviral insertions coupled with high-throughput sequencing and mapping technologies to widely mutagenize genes in the zebrafish genome. We also report the first 6144 mutagenized and archived F1's predicted to carry up to 3776 mutations in annotated genes. Using in vitro fertilization, we have rescued and characterized ~0.5% of the predicted mutations, showing mutation efficacy and a variety of phenotypes relevant to both developmental processes and human genetic diseases. Mutagenized fish lines are being made freely available to the public through the Zebrafish International Resource Center. These fish lines establish an important milestone for zebrafish genetics research and should greatly facilitate systematic functional studies of the vertebrate genome.

  6. Differential Item Functioning by Gender on a Large-Scale Science Performance Assessment: A Comparison across Grade Levels.

    ERIC Educational Resources Information Center

    Holweger, Nancy; Taylor, Grace

    The fifth-grade and eighth-grade science items on a state performance assessment were compared for differential item functioning (DIF) due to gender. The grade 5 sample consisted of 8,539 females and 8,029 males and the grade 8 sample consisted of 7,477 females and 7,891 males. A total of 30 fifth grade items and 26 eighth grade items were…

  7. SOS2 and ACP1 Loci Identified through Large-Scale Exome Chip Analysis Regulate Kidney Development and Function.

    PubMed

    Li, Man; Li, Yong; Weeks, Olivia; Mijatovic, Vladan; Teumer, Alexander; Huffman, Jennifer E; Tromp, Gerard; Fuchsberger, Christian; Gorski, Mathias; Lyytikäinen, Leo-Pekka; Nutile, Teresa; Sedaghat, Sanaz; Sorice, Rossella; Tin, Adrienne; Yang, Qiong; Ahluwalia, Tarunveer S; Arking, Dan E; Bihlmeyer, Nathan A; Böger, Carsten A; Carroll, Robert J; Chasman, Daniel I; Cornelis, Marilyn C; Dehghan, Abbas; Faul, Jessica D; Feitosa, Mary F; Gambaro, Giovanni; Gasparini, Paolo; Giulianini, Franco; Heid, Iris; Huang, Jinyan; Imboden, Medea; Jackson, Anne U; Jeff, Janina; Jhun, Min A; Katz, Ronit; Kifley, Annette; Kilpeläinen, Tuomas O; Kumar, Ashish; Laakso, Markku; Li-Gao, Ruifang; Lohman, Kurt; Lu, Yingchang; Mägi, Reedik; Malerba, Giovanni; Mihailov, Evelin; Mohlke, Karen L; Mook-Kanamori, Dennis O; Robino, Antonietta; Ruderfer, Douglas; Salvi, Erika; Schick, Ursula M; Schulz, Christina-Alexandra; Smith, Albert V; Smith, Jennifer A; Traglia, Michela; Yerges-Armstrong, Laura M; Zhao, Wei; Goodarzi, Mark O; Kraja, Aldi T; Liu, Chunyu; Wessel, Jennifer; Boerwinkle, Eric; Borecki, Ingrid B; Bork-Jensen, Jette; Bottinger, Erwin P; Braga, Daniele; Brandslund, Ivan; Brody, Jennifer A; Campbell, Archie; Carey, David J; Christensen, Cramer; Coresh, Josef; Crook, Errol; Curhan, Gary C; Cusi, Daniele; de Boer, Ian H; de Vries, Aiko P J; Denny, Joshua C; Devuyst, Olivier; Dreisbach, Albert W; Endlich, Karlhans; Esko, Tõnu; Franco, Oscar H; Fulop, Tibor; Gerhard, Glenn S; Glümer, Charlotte; Gottesman, Omri; Grarup, Niels; Gudnason, Vilmundur; Hansen, Torben; Harris, Tamara B; Hayward, Caroline; Hocking, Lynne; Hofman, Albert; Hu, Frank B; Husemoen, Lise Lotte N; Jackson, Rebecca D; Jørgensen, Torben; Jørgensen, Marit E; Kähönen, Mika; Kardia, Sharon L R; König, Wolfgang; Kooperberg, Charles; Kriebel, Jennifer; Launer, Lenore J; Lauritzen, Torsten; Lehtimäki, Terho; Levy, Daniel; Linksted, Pamela; Linneberg, Allan; Liu, Yongmei; Loos, Ruth J F; Lupo, Antonio; Meisinger, Christine; Melander, Olle; Metspalu, Andres; Mitchell, Paul; Nauck, Matthias; Nürnberg, Peter; Orho-Melander, Marju; Parsa, Afshin; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Porteous, David; Probst-Hensch, Nicole M; Psaty, Bruce M; Qi, Lu; Raitakari, Olli T; Reiner, Alex P; Rettig, Rainer; Ridker, Paul M; Rivadeneira, Fernando; Rossouw, Jacques E; Schmidt, Frank; Siscovick, David; Soranzo, Nicole; Strauch, Konstantin; Toniolo, Daniela; Turner, Stephen T; Uitterlinden, André G; Ulivi, Sheila; Velayutham, Dinesh; Völker, Uwe; Völzke, Henry; Waldenberger, Melanie; Wang, Jie Jin; Weir, David R; Witte, Daniel; Kuivaniemi, Helena; Fox, Caroline S; Franceschini, Nora; Goessling, Wolfram; Köttgen, Anna; Chu, Audrey Y

    2017-03-01

    Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (nStage1: 111,666; nStage2: 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (PPM1J, EDEM3, ACP1, SPEG, EYA4, CYP1A1, and ATXN2L; PStage1<3.7×10(-7)), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 (P=5.4×10(-8) by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2-knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

  8. Large-scale phenotypic analysis reveals identical contributions to cell functions of known and unknown yeast genes.

    PubMed

    Bianchi, M M; Ngo, S; Vandenbol, M; Sartori, G; Morlupi, A; Ricci, C; Stefani, S; Morlino, G B; Hilger, F; Carignani, G; Slonimski, P P; Frontali, L

    2001-11-01

    Sequencing of the yeast genome has shown that about one-third of the yeast ORFs code for unknown proteins. Many other have similarity to known genes, but still the cellular functions of the gene products are unknown. The aim of the B1 Consortium of the EUROFAN project was to perform a qualitative phenotypic analysis on yeast strains deleted for functionally orphan genes. To this end we set up a simple approach to detect growth defects of a relatively large number of strains in the presence of osmolytes, ethanol, high temperature, inhibitory compounds or drugs affecting protein biosynthesis, phosphorylation level or nucleic acids biosynthesis. We have now developed this procedure to a semi-quantitative level, we have included new inhibitors, such as hygromycin B, benomyl, metals and additional drugs interfering with synthesis of nucleic acids, and we have performed phenotypic analysis on the deleted strains of 564 genes poorly characterized in respect to their cellular functions. About 30% of the deleted strains showed at least one phenotype: many of them were pleiotropic. For many gene deletions, the linkage between the deletion marker and the observed phenotype(s) was studied by tetrad analysis and their co-segregation was demonstrated. Co-segregation was found in about two-thirds of the analysed strains showing phenotype(s).

  9. Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms

    PubMed Central

    2012-01-01

    Background Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods. Results Argot2 is a web-based function prediction tool able to annotate nucleic or protein sequences from small datasets up to entire genomes. It accepts as input a list of sequences in FASTA format, which are processed using BLAST and HMMER searches vs UniProKB and Pfam databases respectively; these sequences are then annotated with GO terms retrieved from the UniProtKB-GOA database and the terms are weighted using the e-values from BLAST and HMMER. The weighted GO terms are processed according to both their semantic similarity relations described by the Gene Ontology and their associated score. The algorithm is based on the original idea developed in a previous tool called Argot. The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. Conclusions The revised algorithm has been already employed and successfully tested during in-house genome projects of grape and apple, and has proven to have a high precision and recall in all our benchmark conditions. It has also been successfully compared with Blast2GO, one of the methods most commonly employed for sequence annotation. The server is freely accessible at http://www.medcomp.medicina.unipd.it/Argot2. PMID:22536960

  10. Large scale interaction analysis predicts that the Gerbera hybrida floral E function is provided both by general and specialized proteins

    PubMed Central

    2010-01-01

    Background The ornamental plant Gerbera hybrida bears complex inflorescences with morphologically distinct floral morphs that are specific to the sunflower family Asteraceae. We have previously characterized several MADS box genes that regulate floral development in Gerbera. To study further their behavior in higher order complex formation according to the quartet model, we performed yeast two- and three-hybrid analysis with fourteen Gerbera MADS domain proteins to analyze their protein-protein interaction potential. Results The exhaustive pairwise interaction analysis showed significant differences in the interaction capacity of different Gerbera MADS domain proteins compared to other model plants. Of particular interest in these assays was the behavior of SEP-like proteins, known as GRCDs in Gerbera. The previously described GRCD1 and GRCD2 proteins, which are specific regulators involved in stamen and carpel development, respectively, showed very limited pairwise interactions, whereas the related GRCD4 and GRCD5 factors displayed hub-like positions in the interaction map. We propose GRCD4 and GRCD5 to provide a redundant and general E function in Gerbera, comparable to the SEP proteins in Arabidopsis. Based on the pairwise interaction data, combinations of MADS domain proteins were further subjected to yeast three-hybrid assays. Gerbera B function proteins showed active behavior in ternary complexes. All Gerbera SEP-like proteins with the exception of GRCD1 were excellent partners for B function proteins, further implicating the unique role of GRCD1 as a whorl- and flower-type specific C function partner. Conclusions Gerbera MADS domain proteins exhibit both conserved and derived behavior in higher order protein complex formation. This protein-protein interaction data can be used to classify and compare Gerbera MADS domain proteins to those of Arabidopsis and Petunia. Combined with our reverse genetic studies of Gerbera, these results reinforce the roles of

  11. Large scale traffic simulations

    SciTech Connect

    Nagel, K.; Barrett, C.L. |; Rickert, M. |

    1997-04-01

    Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computational speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated {open_quotes}looping{close_quotes} between the microsimulation and the simulated planning of individual person`s behavior is necessary). As a rough number, a real-time simulation of an area such as Los Angeles (ca. 1 million travellers) will need a computational speed of much higher than 1 million {open_quotes}particle{close_quotes} (= vehicle) updates per second. This paper reviews how this problem is approached in different projects and how these approaches are dependent both on the specific questions and on the prospective user community. The approaches reach from highly parallel and vectorizable, single-bit implementations on parallel supercomputers for Statistical Physics questions, via more realistic implementations on coupled workstations, to more complicated driving dynamics implemented again on parallel supercomputers. 45 refs., 9 figs., 1 tab.

  12. Large scale tracking algorithms

    SciTech Connect

    Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett; Karelitz, David B.; Pitts, Todd Alan; Zollweg, Joshua David; Anderson, Dylan Z.; Nandy, Prabal; Whitlow, Gary L.; Bender, Daniel A.; Byrne, Raymond Harry

    2015-01-01

    Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

  13. A large-scale zebrafish gene knockout resource for the genome-wide study of gene function

    PubMed Central

    Varshney, Gaurav K.; Lu, Jing; Gildea, Derek E.; Huang, Haigen; Pei, Wuhong; Yang, Zhongan; Huang, Sunny C.; Schoenfeld, David; Pho, Nam H.; Casero, David; Hirase, Takashi; Mosbrook-Davis, Deborah; Zhang, Suiyuan; Jao, Li-En; Zhang, Bo; Woods, Ian G.; Zimmerman, Steven; Schier, Alexander F.; Wolfsberg, Tyra G.; Pellegrini, Matteo; Burgess, Shawn M.; Lin, Shuo

    2013-01-01

    With the completion of the zebrafish genome sequencing project, it becomes possible to analyze the function of zebrafish genes in a systematic way. The first step in such an analysis is to inactivate each protein-coding gene by targeted or random mutation. Here we describe a streamlined pipeline using proviral insertions coupled with high-throughput sequencing and mapping technologies to widely mutagenize genes in the zebrafish genome. We also report the first 6144 mutagenized and archived F1's predicted to carry up to 3776 mutations in annotated genes. Using in vitro fertilization, we have rescued and characterized ∼0.5% of the predicted mutations, showing mutation efficacy and a variety of phenotypes relevant to both developmental processes and human genetic diseases. Mutagenized fish lines are being made freely available to the public through the Zebrafish International Resource Center. These fish lines establish an important milestone for zebrafish genetics research and should greatly facilitate systematic functional studies of the vertebrate genome. PMID:23382537

  14. Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations.

    PubMed

    Kirk, Isa Kristina; Weinhold, Nils; Belling, Kirstine; Skakkebæk, Niels Erik; Jensen, Thomas Skøt; Leffers, Henrik; Juul, Anders; Brunak, Søren

    2017-03-22

    Gene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies, gene and protein level alterations have fatal consequences. We used genome-wide protein-protein interaction data to identify chromosome-specific patterns of protein interactions. We found that some chromosomes encode proteins that interact infrequently with each other, chromosome 21 in particular. We combined the protein interaction data with transcriptome data from human brain tissue to investigate how this pattern of global interactions may affect cellular function. We identified highly connected proteins that also had coordinated gene expression. These proteins were associated with important neurological functions affecting the characteristic phenotypes for Down syndrome and have previously been validated in mouse knockout experiments. Our approach is general and applicable to other gene-dosage changes, such as arm-level amplifications in cancer.

  15. Large-scale molecular genetic analysis in plant-pathogenic fungi: a decade of genome-wide functional analysis.

    PubMed

    Motaung, Thabiso E; Saitoh, Hiromasa; Tsilo, Toi J

    2016-10-12

    Plant-pathogenic fungi cause diseases to all major crop plants world-wide and threaten global food security. Underpinning fungal diseases are virulence genes facilitating plant host colonization that often marks pathogenesis and crop failures, as well as an increase in staple food prices. Fungal molecular genetics is therefore the cornerstone to the sustainable prevention of disease outbreaks. Pathogenicity studies using mutant collections provide immense function-based information regarding virulence genes of economically relevant fungi. These collections are rich in potential targets for existing and new biological control agents. They contribute to host resistance breeding against fungal pathogens and are instrumental in searching for novel resistance genes through the identification of fungal effectors. Therefore, functional analyses of mutant collections propel gene discovery and characterization, and may be incorporated into disease management strategies. In the light of these attributes, mutant collections enhance the development of practical solutions to confront modern agricultural constraints. Here, a critical review of mutant collections constructed by various laboratories during the past decade is provided. We used Magnaporthe oryzae and Fusarium graminearum studies to show how mutant screens contribute to bridge existing knowledge gaps in pathogenicity and fungal-host interactions.

  16. Large-Scale Prospective T Cell Function Assays in Shipped, Unfrozen Blood Samples: Experiences from the Multicenter TRIGR Trial

    PubMed Central

    Cheung, Roy K.; Becker, Dorothy J.; Girgis, Rose; Palmer, Jerry P.; Cuthbertson, David; Krischer, Jeffrey P.

    2014-01-01

    Broad consensus assigns T lymphocytes fundamental roles in inflammatory, infectious, and autoimmune diseases. However, clinical investigations have lacked fully characterized and validated procedures, equivalent to those of widely practiced biochemical tests with established clinical roles, for measuring core T cell functions. The Trial to Reduce Insulin-dependent diabetes mellitus in the Genetically at Risk (TRIGR) type 1 diabetes prevention trial used consecutive measurements of T cell proliferative responses in prospectively collected fresh heparinized blood samples shipped by courier within North America. In this article, we report on the quality control implications of this simple and pragmatic shipping practice and the interpretation of positive- and negative-control analytes in our assay. We used polyclonal and postvaccination responses in 4,919 samples to analyze the development of T cell immunocompetence. We have found that the vast majority of the samples were viable up to 3 days from the blood draw, yet meaningful responses were found in a proportion of those with longer travel times. Furthermore, the shipping time of uncooled samples significantly decreased both the viabilities of the samples and the unstimulated cell counts in the viable samples. Also, subject age was significantly associated with the number of unstimulated cells and T cell proliferation to positive activators. Finally, we observed a pattern of statistically significant increases in T cell responses to tetanus toxin around the timing of infant vaccinations. This assay platform and shipping protocol satisfy the criteria for robust and reproducible long-term measurements of human T cell function, comparable to those of established blood biochemical tests. We present a stable technology for prospective disease-relevant T cell analysis in immunological diseases, vaccination medicine, and measurement of herd immunity. PMID:24334687

  17. Large-scale prospective T cell function assays in shipped, unfrozen blood samples: experiences from the multicenter TRIGR trial.

    PubMed

    Hadley, David; Cheung, Roy K; Becker, Dorothy J; Girgis, Rose; Palmer, Jerry P; Cuthbertson, David; Krischer, Jeffrey P; Dosch, Hans-Michael

    2014-02-01

    Broad consensus assigns T lymphocytes fundamental roles in inflammatory, infectious, and autoimmune diseases. However, clinical investigations have lacked fully characterized and validated procedures, equivalent to those of widely practiced biochemical tests with established clinical roles, for measuring core T cell functions. The Trial to Reduce Insulin-dependent diabetes mellitus in the Genetically at Risk (TRIGR) type 1 diabetes prevention trial used consecutive measurements of T cell proliferative responses in prospectively collected fresh heparinized blood samples shipped by courier within North America. In this article, we report on the quality control implications of this simple and pragmatic shipping practice and the interpretation of positive- and negative-control analytes in our assay. We used polyclonal and postvaccination responses in 4,919 samples to analyze the development of T cell immunocompetence. We have found that the vast majority of the samples were viable up to 3 days from the blood draw, yet meaningful responses were found in a proportion of those with longer travel times. Furthermore, the shipping time of uncooled samples significantly decreased both the viabilities of the samples and the unstimulated cell counts in the viable samples. Also, subject age was significantly associated with the number of unstimulated cells and T cell proliferation to positive activators. Finally, we observed a pattern of statistically significant increases in T cell responses to tetanus toxin around the timing of infant vaccinations. This assay platform and shipping protocol satisfy the criteria for robust and reproducible long-term measurements of human T cell function, comparable to those of established blood biochemical tests. We present a stable technology for prospective disease-relevant T cell analysis in immunological diseases, vaccination medicine, and measurement of herd immunity.

  18. Identification of genes important for cutaneous function revealed by a large scale reverse genetic screen in the mouse.

    PubMed

    DiTommaso, Tia; Jones, Lynelle K; Cottle, Denny L; Gerdin, Anna-Karin; Vancollie, Valerie E; Watt, Fiona M; Ramirez-Solis, Ramiro; Bradley, Allan; Steel, Karen P; Sundberg, John P; White, Jacqueline K; Smyth, Ian M

    2014-10-01

    The skin is a highly regenerative organ which plays critical roles in protecting the body and sensing its environment. Consequently, morbidity and mortality associated with skin defects represent a significant health issue. To identify genes important in skin development and homeostasis, we have applied a high throughput, multi-parameter phenotype screen to the conditional targeted mutant mice generated by the Wellcome Trust Sanger Institute's Mouse Genetics Project (Sanger-MGP). A total of 562 different mouse lines were subjected to a variety of tests assessing cutaneous expression, macroscopic clinical disease, histological change, hair follicle cycling, and aberrant marker expression. Cutaneous lesions were associated with mutations in 23 different genes. Many of these were not previously associated with skin disease in the organ (Mysm1, Vangl1, Trpc4ap, Nom1, Sparc, Farp2, and Prkab1), while others were ascribed new cutaneous functions on the basis of the screening approach (Krt76, Lrig1, Myo5a, Nsun2, and Nf1). The integration of these skin specific screening protocols into the Sanger-MGP primary phenotyping pipelines marks the largest reported reverse genetic screen undertaken in any organ and defines approaches to maximise the productivity of future projects of this nature, while flagging genes for further characterisation.

  19. Lagrangian space consistency relation for large scale structure

    SciTech Connect

    Horn, Bart; Hui, Lam; Xiao, Xiao E-mail: lh399@columbia.edu

    2015-09-01

    Consistency relations, which relate the squeezed limit of an (N+1)-point correlation function to an N-point function, are non-perturbative symmetry statements that hold even if the associated high momentum modes are deep in the nonlinear regime and astrophysically complex. Recently, Kehagias and Riotto and Peloso and Pietroni discovered a consistency relation applicable to large scale structure. We show that this can be recast into a simple physical statement in Lagrangian space: that the squeezed correlation function (suitably normalized) vanishes. This holds regardless of whether the correlation observables are at the same time or not, and regardless of whether multiple-streaming is present. The simplicity of this statement suggests that an analytic understanding of large scale structure in the nonlinear regime may be particularly promising in Lagrangian space.

  20. The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

    NASA Astrophysics Data System (ADS)

    Protat, A.; Delanoë, J.; May, P. T.; Haynes, J.; Jakob, C.; O'Connor, E.; Pope, M.; Wheeler, M. C.

    2011-08-01

    The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by

  1. Large-scale cortical networks and cognition.

    PubMed

    Bressler, S L

    1995-03-01

    The well-known parcellation of the mammalian cerebral cortex into a large number of functionally distinct cytoarchitectonic areas presents a problem for understanding the complex cortical integrative functions that underlie cognition. How do cortical areas having unique individual functional properties cooperate to accomplish these complex operations? Do neurons distributed throughout the cerebral cortex act together in large-scale functional assemblages? This review examines the substantial body of evidence supporting the view that complex integrative functions are carried out by large-scale networks of cortical areas. Pathway tracing studies in non-human primates have revealed widely distributed networks of interconnected cortical areas, providing an anatomical substrate for large-scale parallel processing of information in the cerebral cortex. Functional coactivation of multiple cortical areas has been demonstrated by neurophysiological studies in non-human primates and several different cognitive functions have been shown to depend on multiple distributed areas by human neuropsychological studies. Electrophysiological studies on interareal synchronization have provided evidence that active neurons in different cortical areas may become not only coactive, but also functionally interdependent. The computational advantages of synchronization between cortical areas in large-scale networks have been elucidated by studies using artificial neural network models. Recent observations of time-varying multi-areal cortical synchronization suggest that the functional topology of a large-scale cortical network is dynamically reorganized during visuomotor behavior.

  2. Large-Scale Functional RNAi Screen in C. elegans Identifies TGF-β and Notch Signaling Pathways as Modifiers of CACNA1A

    PubMed Central

    Pereira, Maria da Conceição; Morais, Sara; Sequeiros, Jorge

    2016-01-01

    Variants in CACNA1A that encodes the pore-forming α1-subunit of human voltage-gated Cav2.1 (P/Q-type) Ca2+ channels cause several autosomal-dominant neurologic disorders, including familial hemiplegic migraine type 1, episodic ataxia type 2, and spinocerebellar ataxia type 6. To identify modifiers of incoordination in movement disorders, we performed a large-scale functional RNAi screen, using the Caenorhabditis elegans strain CB55, which carries a truncating mutation in the unc-2 gene, the worm ortholog for the human CACNA1A. The screen was carried out by the feeding method in 96-well liquid culture format, using the ORFeome v1.1 feeding library, and time-lapse imaging of worms in liquid culture was used to assess changes in thrashing behavior. We looked for genes that, when silenced, either ameliorated the slow and uncoordinated phenotype of unc-2, or interacted to produce a more severe phenotype. Of the 350 putative hits from the primary screen, 37 genes consistently showed reproducible results. At least 75% of these are specifically expressed in the C. elegans neurons. Functional network analysis and gene ontology revealed overrepresentation of genes involved in development, growth, locomotion, signal transduction, and vesicle-mediated transport. We have expanded the functional network of genes involved in neurodegeneration leading to cerebellar ataxia related to unc-2/CACNA1A, further confirming the involvement of the transforming growth factor β pathway and adding a novel signaling cascade, the Notch pathway. PMID:27005779

  3. Large-Scale Hybrid Density Functional Theory Calculations in the Condensed-Phase: Ab Initio Molecular Dynamics in the Isobaric-Isothermal Ensemble

    NASA Astrophysics Data System (ADS)

    Ko, Hsin-Yu; Santra, Biswajit; Distasio, Robert A., Jr.; Wu, Xifan; Car, Roberto

    Hybrid functionals are known to alleviate the self-interaction error in density functional theory (DFT) and provide a more accurate description of the electronic structure of molecules and materials. However, hybrid DFT in the condensed-phase has a prohibitively high associated computational cost which limits their applicability to large systems of interest. In this work, we present a general-purpose order(N) implementation of hybrid DFT in the condensed-phase using Maximally localized Wannier function; this implementation is optimized for massively parallel computing architectures. This algorithm is used to perform large-scale ab initio molecular dynamics simulations of liquid water, ice, and aqueous ionic solutions. We have performed simulations in the isothermal-isobaric ensemble to quantify the effects of exact exchange on the equilibrium density properties of water at different thermodynamic conditions. We find that the anomalous density difference between ice I h and liquid water at ambient conditions as well as the enthalpy differences between ice I h, II, and III phases at the experimental triple point (238 K and 20 Kbar) are significantly improved using hybrid DFT over previous estimates using the lower rungs of DFT This work has been supported by the Department of Energy under Grants No. DE-FG02-05ER46201 and DE-SC0008626.

  4. Very Large Scale Optimization

    NASA Technical Reports Server (NTRS)

    Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)

    2002-01-01

    The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.

  5. LSI/VLSI (Large Scale Integration/Very Large Scale Integration) ion implanted GaAs (Gallium Arsenide) IC processing. Appendix A: Feasibility analysis of Gallium-Arsenide mask programmable functions and logic arrays for high performance communications systems

    NASA Astrophysics Data System (ADS)

    Zucca, R. R.; Kirkpatrick, C. G.; Asbeck, P. M.; Eisen, F. H.; Lee, C. P.

    1984-01-01

    Circuits critical to the performance of advanced radio, radar and spread spectrum communications systems require advances in the state-of-the-art in semiconductor technology to meet the demands of advanced systems. As these systems increase in complexity, extensive digital circuitry is required in addition to the typical linear signal processing circuits. The power, size and weight of advanced systems also becomes unacceptable without continuous advances in semiconductor technology. Moreover an increasing trend is seen in the use of metal mask selectable functions, programmable logic arrays and gate arrays to implement system specific circuitry in an attempt to lower non-recurring costs, minimize risk and shorten development times. GaAs and other technologies with very high speed power-performance figures-of-merit are critical ingredients in systems implementations which satisfy these needs. To meet these advanced system requirements this project was initiated as a multi-phase/year program to develop a group of mask programmable gallium arsenide (GaAs) circuit elements applicable to high speed/performance communications systems.

  6. Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

    PubMed Central

    Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E.; Thomas, Paul D.

    2016-01-01

    We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This ‘GO Phylogenetic Annotation’ approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations. Database URL: http://amigo.geneontology.org/amigo PMID:28025345

  7. Large-scale insertional mutagenesis of Chlamydomonas supports phylogenomic functional prediction of photosynthetic genes and analysis of classical acetate-requiring mutants.

    PubMed

    Dent, Rachel M; Sharifi, Marina N; Malnoë, Alizée; Haglund, Cat; Calderon, Robert H; Wakao, Setsuko; Niyogi, Krishna K

    2015-04-01

    Chlamydomonas reinhardtii is a unicellular green alga that is a key model organism in the study of photosynthesis and oxidative stress. Here we describe the large-scale generation of a population of insertional mutants that have been screened for phenotypes related to photosynthesis and the isolation of 459 flanking sequence tags from 439 mutants. Recent phylogenomic analysis has identified a core set of genes, named GreenCut2, that are conserved in green algae and plants. Many of these genes are likely to be central to the process of photosynthesis, and they are over-represented by sixfold among the screened insertional mutants, with insertion events isolated in or adjacent to 68 of 597 GreenCut2 genes. This enrichment thus provides experimental support for functional assignments based on previous bioinformatic analysis. To illustrate one of the uses of the population, a candidate gene approach based on genome position of the flanking sequence of the insertional mutant CAL027_01_20 was used to identify the molecular basis of the classical C. reinhardtii mutation ac17. These mutations were shown to affect the gene PDH2, which encodes a subunit of the plastid pyruvate dehydrogenase complex. The mutants and associated flanking sequence data described here are publicly available to the research community, and they represent one of the largest phenotyped collections of algal insertional mutants to date.

  8. Large-Scale Sequence Comparison.

    PubMed

    Lal, Devi; Verma, Mansi

    2017-01-01

    There are millions of sequences deposited in genomic databases, and it is an important task to categorize them according to their structural and functional roles. Sequence comparison is a prerequisite for proper categorization of both DNA and protein sequences, and helps in assigning a putative or hypothetical structure and function to a given sequence. There are various methods available for comparing sequences, alignment being first and foremost for sequences with a small number of base pairs as well as for large-scale genome comparison. Various tools are available for performing pairwise large sequence comparison. The best known tools either perform global alignment or generate local alignments between the two sequences. In this chapter we first provide basic information regarding sequence comparison. This is followed by the description of the PAM and BLOSUM matrices that form the basis of sequence comparison. We also give a practical overview of currently available methods such as BLAST and FASTA, followed by a description and overview of tools available for genome comparison including LAGAN, MumMER, BLASTZ, and AVID.

  9. Large-scale PACS implementation.

    PubMed

    Carrino, J A; Unkel, P J; Miller, I D; Bowser, C L; Freckleton, M W; Johnson, T G

    1998-08-01

    The transition to filmless radiology is a much more formidable task than making the request for proposal to purchase a (Picture Archiving and Communications System) PACS. The Department of Defense and the Veterans Administration have been pioneers in the transformation of medical diagnostic imaging to the electronic environment. Many civilian sites are expected to implement large-scale PACS in the next five to ten years. This presentation will related the empirical insights gleaned at our institution from a large-scale PACS implementation. Our PACS integration was introduced into a fully operational department (not a new hospital) in which work flow had to continue with minimal impact. Impediments to user acceptance will be addressed. The critical components of this enormous task will be discussed. The topics covered during this session will include issues such as phased implementation, DICOM (digital imaging and communications in medicine) standard-based interaction of devices, hospital information system (HIS)/radiology information system (RIS) interface, user approval, networking, workstation deployment and backup procedures. The presentation will make specific suggestions regarding the implementation team, operating instructions, quality control (QC), training and education. The concept of identifying key functional areas is relevant to transitioning the facility to be entirely on line. Special attention must be paid to specific functional areas such as the operating rooms and trauma rooms where the clinical requirements may not match the PACS capabilities. The printing of films may be necessary for certain circumstances. The integration of teleradiology and remote clinics into a PACS is a salient topic with respect to the overall role of the radiologists providing rapid consultation. A Web-based server allows a clinician to review images and reports on a desk-top (personal) computer and thus reduce the number of dedicated PACS review workstations. This session

  10. Subquadratic-scaling subspace projection method for large-scale Kohn-Sham density functional theory calculations using spectral finite-element discretization

    NASA Astrophysics Data System (ADS)

    Motamarri, Phani; Gavini, Vikram

    2014-09-01

    We present a subspace projection technique to conduct large-scale Kohn-Sham density functional theory calculations using higher-order spectral finite-element discretization. The proposed method treats both metallic and insulating materials in a single framework and is applicable to both pseudopotential as well as all-electron calculations. The key ideas involved in the development of this method include: (i) employing a higher-order spectral finite-element basis that is amenable to mesh adaption; (ii) using a Chebyshev filter to construct a subspace, which is an approximation to the occupied eigenspace in a given self-consistent field iteration; (iii) using a localization procedure to construct a nonorthogonal localized basis spanning the Chebyshev filtered subspace; and (iv) using a Fermi-operator expansion in terms of the subspace-projected Hamiltonian represented in the nonorthogonal localized basis to compute relevant quantities like the density matrix, electron density, and band energy. We demonstrate the accuracy and efficiency of the proposed approach on benchmark systems involving pseudopotential calculations on aluminum nanoclusters up to 3430 atoms and on alkane chains up to 7052 atoms, as well as all-electron calculations on silicon nanoclusters up to 3920 electrons. The benchmark studies revealed that accuracies commensurate with chemical accuracy can be obtained with the proposed method, and a subquadratic-scaling with system size was observed for the range of materials systems studied. In particular, for the alkane chains—representing an insulating material—close to linear scaling is observed, whereas, for aluminum nanoclusters—representing a metallic material—the scaling is observed to be O (N1.46). For all-electron calculations on silicon nanoclusters, the scaling with the number of electrons is computed to be O (N1.75). In all the benchmark systems, significant computational savings have been realized with the proposed approach, with

  11. Genetic invalidation of Lp-PLA2 as a therapeutic target: Large-scale study of five functional Lp-PLA2-lowering alleles.

    PubMed

    Gregson, John M; Freitag, Daniel F; Surendran, Praveen; Stitziel, Nathan O; Chowdhury, Rajiv; Burgess, Stephen; Kaptoge, Stephen; Gao, Pei; Staley, James R; Willeit, Peter; Nielsen, Sune F; Caslake, Muriel; Trompet, Stella; Polfus, Linda M; Kuulasmaa, Kari; Kontto, Jukka; Perola, Markus; Blankenberg, Stefan; Veronesi, Giovanni; Gianfagna, Francesco; Männistö, Satu; Kimura, Akinori; Lin, Honghuang; Reilly, Dermot F; Gorski, Mathias; Mijatovic, Vladan; Munroe, Patricia B; Ehret, Georg B; Thompson, Alex; Uria-Nickelsen, Maria; Malarstig, Anders; Dehghan, Abbas; Vogt, Thomas F; Sasaoka, Taishi; Takeuchi, Fumihiko; Kato, Norihiro; Yamada, Yoshiji; Kee, Frank; Müller-Nurasyid, Martina; Ferrières, Jean; Arveiler, Dominique; Amouyel, Philippe; Salomaa, Veikko; Boerwinkle, Eric; Thompson, Simon G; Ford, Ian; Wouter Jukema, J; Sattar, Naveed; Packard, Chris J; Shafi Majumder, Abdulla Al; Alam, Dewan S; Deloukas, Panos; Schunkert, Heribert; Samani, Nilesh J; Kathiresan, Sekar; Nordestgaard, Børge G; Saleheen, Danish; Howson, Joanna Mm; Di Angelantonio, Emanuele; Butterworth, Adam S; Danesh, John

    2017-03-01

    Aims Darapladib, a potent inhibitor of lipoprotein-associated phospholipase A2 (Lp-PLA2), has not reduced risk of cardiovascular disease outcomes in recent randomized trials. We aimed to test whether Lp-PLA2 enzyme activity is causally relevant to coronary heart disease. Methods In 72,657 patients with coronary heart disease and 110,218 controls in 23 epidemiological studies, we genotyped five functional variants: four rare loss-of-function mutations (c.109+2T > C (rs142974898), Arg82His (rs144983904), Val279Phe (rs76863441), Gln287Ter (rs140020965)) and one common modest-impact variant (Val379Ala (rs1051931)) in PLA2G7, the gene encoding Lp-PLA2. We supplemented de-novo genotyping with information on a further 45,823 coronary heart disease patients and 88,680 controls in publicly available databases and other previous studies. We conducted a systematic review of randomized trials to compare effects of darapladib treatment on soluble Lp-PLA2 activity, conventional cardiovascular risk factors, and coronary heart disease risk with corresponding effects of Lp-PLA2-lowering alleles. Results Lp-PLA2 activity was decreased by 64% ( p = 2.4 × 10(-25)) with carriage of any of the four loss-of-function variants, by 45% ( p < 10(-300)) for every allele inherited at Val279Phe, and by 2.7% ( p = 1.9 × 10(-12)) for every allele inherited at Val379Ala. Darapladib 160 mg once-daily reduced Lp-PLA2 activity by 65% ( p < 10(-300)). Causal risk ratios for coronary heart disease per 65% lower Lp-PLA2 activity were: 0.95 (0.88-1.03) with Val279Phe; 0.92 (0.74-1.16) with carriage of any loss-of-function variant; 1.01 (0.68-1.51) with Val379Ala; and 0.95 (0.89-1.02) with darapladib treatment. Conclusions In a large-scale human genetic study, none of a series of Lp-PLA2-lowering alleles was related to coronary heart disease risk, suggesting that Lp-PLA2 is unlikely to be a causal risk factor.

  12. The Effects of Non-Universal Large Scales on Conditional Statistics in Turbulence

    NASA Astrophysics Data System (ADS)

    Blum, Daniel Brian

    We report measurements of conditional Eulerian and Lagrangian structure functions in order to assess the effects of nonuniversal properties of the large scales on the small scales in turbulence. We study a 1x1x1.5 m^3 flowbetween oscillating grids which produces Taylor Reynold's number of 285 while containing regions of nearly homogeneous and highly inhomogeneous turbulence. Large data sets of three-dimensional tracer particle velocities have been collected using stereoscopic high speed cameras with real-time image compression technology. Eulerian and Lagrangian structure functions are measured in both homogeneous and inhomogeneous regions of the flow. We condition the structure functions on the instantaneous large scale velocity or on the grid phase. At all scales, the structure functions depend strongly on the large scale velocity, but are independent of the grid phase. We see clear signatures of inhomogeneity near the oscillating grids, but even in the homogeneous region in the center we see a surprisingly strong dependence on the large scale velocity that remains at all scales. We also find strong signatures of large scale intermittency. Additionally, 7 other turbulent flows are compared using conditional structure functions to further the understanding of the effects of large scale properties of the flow. Previous work has shown that similar correlations extend to very high Reynolds numbers. Comprehensive measurements of these effects in a laboratory flow provide a powerful tool for assessing the effects of shear, inhomogeneity and intermittency of the large scales on the small scales in turbulence.

  13. A Large Scale Gene-Centric Association Study of Lung Function in Newly-Hired Female Cotton Textile Workers with Endotoxin Exposure

    PubMed Central

    Chu, Minjie; Mehta, Amar; Wei, Yongyue; Liu, Yao; Xun, Pengcheng; Bai, Jianling; Yu, Hao; Su, Li; Zhang, Hongxi; Hu, Zhibin; Shen, Hongbing; Chen, Feng; Christiani, David C.

    2013-01-01

    Background Occupational exposure to endotoxin is associated with decrements in pulmonary function, but how much variation in this association is explained by genetic variants is not well understood. Objective We aimed to identify single nucleotide polymorphisms (SNPs) that are associated with the rate of forced expiratory volume in one second (FEV1) decline by a large scale genetic association study in newly-hired healthy young female cotton textile workers. Methods DNA samples were genotyped using the Illumina Human CVD BeadChip. Change rate in FEV1 was modeled as a function of each SNP genotype in linear regression model with covariate adjustment. We controlled the type 1 error in study-wide level by permutation method. The false discovery rate (FDR) and the family-wise error rate (FWER) were set to be 0.10 and 0.15 respectively. Results Two SNPs were found to be significant (P<6.29×10−5), including rs1910047 (P = 3.07×10−5, FDR = 0.0778) and rs9469089 (P = 6.19×10−5, FDR = 0.0967), as well as other eight suggestive (P<5×10−4) associated SNPs. Gene-gene and gene-environment interactions were also observed, such as rs1910047 and rs1049970 (P = 0.0418, FDR = 0.0895); rs9469089 and age (P = 0.0161, FDR = 0.0264). Genetic risk score analysis showed that the more risk loci the subjects carried, the larger the rate of FEV1 decline occurred (Ptrend = 3.01×10−18). However, the association was different among age subgroups (P = 7.11×10−6) and endotoxin subgroups (P = 1.08×10−2). Functional network analysis illustrates potential biological connections of all interacted genes. Conclusions Genetic variants together with environmental factors interact to affect the rate of FEV1 decline in cotton textile workers. PMID:23527081

  14. Multiple soft limits of cosmological correlation functions

    SciTech Connect

    Joyce, Austin; Khoury, Justin; Simonović, Marko E-mail: jkhoury@sas.upenn.edu

    2015-01-01

    We derive novel identities satisfied by inflationary correlation functions in the limit where two external momenta are taken to be small. We derive these statements in two ways: using background-wave arguments and as Ward identities following from the fixed-time path integral. Interestingly, these identities allow us to constrain some of the O(q{sup 2}) components of the soft limit, in contrast to their single-soft analogues. We provide several nontrivial checks of our identities both in the context of resonant non-Gaussianities and in small sound speed models. Additionally, we extend the relation at lowest order in external momenta to arbitrarily many soft legs, and comment on the many-soft extension at higher orders in the soft momentum. Finally, we consider how higher soft limits lead to identities satisfied by correlation functions in large-scale structure.

  15. The galaxy distribution and the large-scale structure of the universe

    NASA Technical Reports Server (NTRS)

    Geller, M. J.; Kurtz, M. J.; De Lapparent, V.

    1986-01-01

    Data related to the large-scale galaxy distribution are discussed. The galaxy counts of Shane-Wirtanen (1967) are analyzed; the effects of residual systematic errors on the galaxy distribution measurements are considered. The analysis reveals that the Shane-Wirtanen data are not applicable to the study of large-scale structure. A model which is capable of measuring galaxy correlation functions on scales greater than about 10 Mpc is evaluated.

  16. Optimisation and Validation of the ARAMIS Digital Image Correlation System for Use in Large-scale High-strain-rate Events

    DTIC Science & Technology

    2013-08-01

    strain-rate synergistic blast and fragmentation event. The ARAMIS system uses 3D digital photogrammetry to track surface deformation of an object...high-speed photogrammetry . These issues included adequate lighting conditions, the use of mirrors, large stand-off distances, speckle pattern...Ackermann, F. (1984) Digital Image Correlation: Performance and Potential Application in Photogrammetry . The Photogrammetric Record 11 (64) pp 429-439 2

  17. Hexagonalization of correlation functions

    NASA Astrophysics Data System (ADS)

    Fleury, Thiago; Komatsu, Shota

    2017-01-01

    We propose a nonperturbative framework to study general correlation functions of single-trace operators in N = 4 supersymmetric Yang-Mills theory at large N . The basic strategy is to decompose them into fundamental building blocks called the hexagon form factors, which were introduced earlier to study structure constants using integrability. The decomposition is akin to a triangulation of a Riemann surface, and we thus call it hexagonalization. We propose a set of rules to glue the hexagons together based on symmetry, which naturally incorporate the dependence on the conformal and the R-symmetry cross ratios. Our method is conceptually different from the conventional operator product expansion and automatically takes into account multi-trace operators exchanged in OPE channels. To illustrate the idea in simple set-ups, we compute four-point functions of BPS operators of arbitrary lengths and correlation functions of one Konishi operator and three short BPS operators, all at one loop. In all cases, the results are in perfect agreement with the perturbative data. We also suggest that our method can be a useful tool to study conformal integrals, and show it explicitly for the case of ladder integrals.

  18. Large-scale nanophotonic phased array.

    PubMed

    Sun, Jie; Timurdogan, Erman; Yaacobi, Ami; Hosseini, Ehsan Shah; Watts, Michael R

    2013-01-10

    Electromagnetic phased arrays at radio frequencies are well known and have enabled applications ranging from communications to radar, broadcasting and astronomy. The ability to generate arbitrary radiation patterns with large-scale phased arrays has long been pursued. Although it is extremely expensive and cumbersome to deploy large-scale radiofrequency phased arrays, optical phased arrays have a unique advantage in that the much shorter optical wavelength holds promise for large-scale integration. However, the short optical wavelength also imposes stringent requirements on fabrication. As a consequence, although optical phased arrays have been studied with various platforms and recently with chip-scale nanophotonics, all of the demonstrations so far are restricted to one-dimensional or small-scale two-dimensional arrays. Here we report the demonstration of a large-scale two-dimensional nanophotonic phased array (NPA), in which 64 × 64 (4,096) optical nanoantennas are densely integrated on a silicon chip within a footprint of 576 μm × 576 μm with all of the nanoantennas precisely balanced in power and aligned in phase to generate a designed, sophisticated radiation pattern in the far field. We also show that active phase tunability can be realized in the proposed NPA by demonstrating dynamic beam steering and shaping with an 8 × 8 array. This work demonstrates that a robust design, together with state-of-the-art complementary metal-oxide-semiconductor technology, allows large-scale NPAs to be implemented on compact and inexpensive nanophotonic chips. In turn, this enables arbitrary radiation pattern generation using NPAs and therefore extends the functionalities of phased arrays beyond conventional beam focusing and steering, opening up possibilities for large-scale deployment in applications such as communication, laser detection and ranging, three-dimensional holography and biomedical sciences, to name just a few.

  19. Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

    NASA Technical Reports Server (NTRS)

    Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

    2016-01-01

    This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

  20. The CLASSgal code for relativistic cosmological large scale structure

    SciTech Connect

    Dio, Enea Di; Montanari, Francesco; Durrer, Ruth; Lesgourgues, Julien E-mail: Francesco.Montanari@unige.ch E-mail: Ruth.Durrer@unige.ch

    2013-11-01

    We present accurate and efficient computations of large scale structure observables, obtained with a modified version of the CLASS code which is made publicly available. This code includes all relativistic corrections and computes both the power spectrum C{sub ℓ}(z{sub 1},z{sub 2}) and the corresponding correlation function ξ(θ,z{sub 1},z{sub 2}) of the matter density and the galaxy number fluctuations in linear perturbation theory. For Gaussian initial perturbations, these quantities contain the full information encoded in the large scale matter distribution at the level of linear perturbation theory. We illustrate the usefulness of our code for cosmological parameter estimation through a few simple examples.

  1. Functional clustering and lineage markers: insights into cellular differentiation and gene function from large-scale microarray studies of purified primary cell populations.

    PubMed

    Hume, David A; Summers, Kim M; Raza, Sobia; Baillie, J Kenneth; Freeman, Thomas C

    2010-06-01

    Very large microarray datasets showing gene expression across multiple tissues and cell populations provide a window on the transcriptional networks that underpin the differences in functional activity between biological systems. Clusters of co-expressed genes provide lineage markers, candidate regulators of cell function and, by applying the principle of guilt by association, candidate functions for genes of currently unknown function. We have analysed a dataset comprising pure cell populations from hemopoietic and non-hemopoietic cell types (http://biogps.gnf.org). Using a novel network visualisation and clustering approach, we demonstrate that it is possible to identify very tight expression signatures associated specifically with embryonic stem cells, mesenchymal cells and hematopoietic lineages. Selected examples validate the prediction that gene function can be inferred by co-expression. One expression cluster was enriched in phagocytes, which, alongside endosome-lysosome constituents, contains genes that may make up a 'pathway' for phagocyte differentiation. Promoters of these genes are enriched for binding sites for the ETS/PU.1 and MITF families. Another cluster was associated with the production of a specific extracellular matrix, with high levels of gene expression shared by cells of mesenchymal origin (fibroblasts, adipocytes, osteoblasts and myoblasts). We discuss the limitations placed upon such data by the presence of alternative promoters with distinct tissue specificity within many protein-coding genes.

  2. Making Large-Scale Networks from fMRI Data

    PubMed Central

    Schmittmann, Verena D.; Jahfari, Sara; Borsboom, Denny; Savi, Alexander O.; Waldorp, Lourens J.

    2015-01-01

    Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series. PMID:26325185

  3. Regional and large-scale patterns in Amazon forest structure and function are mediated by variations in soil physical and chemical properties

    NASA Astrophysics Data System (ADS)

    A, Quesada, C.; Lloyd, J.

    2009-04-01

    Forest structure and dynamics have been noted to vary across the Amazon Basin in an east-west gradient in a pattern which coincides with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. To test this hypothesis and assess the importance of edaphic properties in affect forest structure and dynamics, soil and plant samples were collected in a total of 59 different forest plots across the Amazon Basin. Samples were analysed for exchangeable cations, C, N, pH with various P fractions also determined. Physical properties were also examined and an index of soil physical quality developed. Overall, forest structure and dynamics were found to be strongly and quantitatively related to edaphic conditions. Tree turnover rates emerged to be mostly influenced by soil physical properties whereas forest growth rates were mainly related to a measure of available soil phosphorus, although also dependent on rainfall amount and distribution. On the other hand, large scale variations in forest biomass could not be explained by any of the edaphic properties measured, nor by variation in climate. A new hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining forest disturbance levels, species composition and forest productivity on a Basin wide scale.

  4. Large-scale functional annotation and expanded implementations of the P{wHy} hybrid transposon in the Drosophila melanogaster genome.

    PubMed

    Myrick, Kyl V; Huet, François; Mohr, Stephanie E; Alvarez-García, Inés; Lu, Jeffrey T; Smith, Mark A; Crosby, Madeline A; Gelbart, William M

    2009-07-01

    Whole genome sequencing of the model organisms has created increased demand for efficient tools to facilitate the genome annotation efforts. Accordingly, we report the further implementations and analyses stemming from our publicly available P{wHy} library for Drosophila melanogaster. A two-step regime-large scale transposon mutagenesis followed by hobo-induced nested deletions-allows mutation saturation and provides significant enhancements to existing genomic coverage. We previously showed that, for a given starting insert, deletion saturation is readily obtained over a 60-kb interval; here, we perform a breakdown analysis of efficiency to identify rate-limiting steps in the process. Transrecombination, the hobo-induced recombination between two P{wHy} half molecules, was shown to further expand the P{wHy} mutational range, pointing to a potent, iterative process of transrecombination-reconstitution-transrecombination for alternating between very large and very fine-grained deletions in a self-contained manner. A number of strains also showed partial or complete repression of P{wHy} markers, depending on chromosome location, whereby asymmetric marker silencing allowed continuous phenotypic detection, indicating that P{wHy}-based saturational mutagenesis should be useful for the study of heterochromatin/positional effects.

  5. Large-scale instabilities of helical flows

    NASA Astrophysics Data System (ADS)

    Cameron, Alexandre; Alexakis, Alexandros; Brachet, Marc-Étienne

    2016-10-01

    Large-scale hydrodynamic instabilities of periodic helical flows of a given wave number K are investigated using three-dimensional Floquet numerical computations. In the Floquet formalism the unstable field is expanded in modes of different spacial periodicity. This allows us (i) to clearly distinguish large from small scale instabilities and (ii) to study modes of wave number q of arbitrarily large-scale separation q ≪K . Different flows are examined including flows that exhibit small-scale turbulence. The growth rate σ of the most unstable mode is measured as a function of the scale separation q /K ≪1 and the Reynolds number Re. It is shown that the growth rate follows the scaling σ ∝q if an AKA effect [Frisch et al., Physica D: Nonlinear Phenomena 28, 382 (1987), 10.1016/0167-2789(87)90026-1] is present or a negative eddy viscosity scaling σ ∝q2 in its absence. This holds both for the Re≪1 regime where previously derived asymptotic results are verified but also for Re=O (1 ) that is beyond their range of validity. Furthermore, for values of Re above a critical value ReSc beyond which small-scale instabilities are present, the growth rate becomes independent of q and the energy of the perturbation at large scales decreases with scale separation. The nonlinear behavior of these large-scale instabilities is also examined in the nonlinear regime where the largest scales of the system are found to be the most dominant energetically. These results are interpreted by low-order models.

  6. Large-scale planar lightwave circuits

    NASA Astrophysics Data System (ADS)

    Bidnyk, Serge; Zhang, Hua; Pearson, Matt; Balakrishnan, Ashok

    2011-01-01

    By leveraging advanced wafer processing and flip-chip bonding techniques, we have succeeded in hybrid integrating a myriad of active optical components, including photodetectors and laser diodes, with our planar lightwave circuit (PLC) platform. We have combined hybrid integration of active components with monolithic integration of other critical functions, such as diffraction gratings, on-chip mirrors, mode-converters, and thermo-optic elements. Further process development has led to the integration of polarization controlling functionality. Most recently, all these technological advancements have been combined to create large-scale planar lightwave circuits that comprise hundreds of optical elements integrated on chips less than a square inch in size.

  7. Effective theory of squeezed correlation functions

    SciTech Connect

    Mirbabayi, Mehrdad; Simonović, Marko E-mail: markos@ias.edu

    2016-03-01

    Various inflationary scenarios can often be distinguished from one another by looking at the squeezed limit behavior of correlation functions. Therefore, it is useful to have a framework designed to study this limit in a more systematic and efficient way. We propose using an expansion in terms of weakly coupled super-horizon degrees of freedom, which is argued to generically exist in a near de Sitter space-time. The modes have a simple factorized form which leads to factorization of the squeezed-limit correlation functions with power-law behavior in k{sub long}/k{sub short}. This approach reproduces the known results in single-, quasi-single-, and multi-field inflationary models. However, it is applicable even if, unlike the above examples, the additional degrees of freedom are not weakly coupled at sub-horizon scales. Stronger results are derived in two-field (or sufficiently symmetric multi-field) inflationary models. We discuss the observability of the non-Gaussian 3-point function in the large-scale structure surveys, and argue that the squeezed limit behavior has a higher detectability chance than equilateral behavior when it scales as (k{sub long}/k{sub short}){sup Δ} with Δ < 1—where local non-Gaussianity corresponds to Δ = 0.

  8. Large Scale Magnetostrictive Valve Actuator

    NASA Technical Reports Server (NTRS)

    Richard, James A.; Holleman, Elizabeth; Eddleman, David

    2008-01-01

    Marshall Space Flight Center's Valves, Actuators and Ducts Design and Development Branch developed a large scale magnetostrictive valve actuator. The potential advantages of this technology are faster, more efficient valve actuators that consume less power and provide precise position control and deliver higher flow rates than conventional solenoid valves. Magnetostrictive materials change dimensions when a magnetic field is applied; this property is referred to as magnetostriction. Magnetostriction is caused by the alignment of the magnetic domains in the material s crystalline structure and the applied magnetic field lines. Typically, the material changes shape by elongating in the axial direction and constricting in the radial direction, resulting in no net change in volume. All hardware and testing is complete. This paper will discuss: the potential applications of the technology; overview of the as built actuator design; discuss problems that were uncovered during the development testing; review test data and evaluate weaknesses of the design; and discuss areas for improvement for future work. This actuator holds promises of a low power, high load, proportionally controlled actuator for valves requiring 440 to 1500 newtons load.

  9. Large scale cluster computing workshop

    SciTech Connect

    Dane Skow; Alan Silverman

    2002-12-23

    Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community.

  10. Statistics of density maxima and the large-scale matter distribution

    NASA Technical Reports Server (NTRS)

    Kaiser, N.

    1986-01-01

    High peaks in Gaussian noise display enhanced clustering. The enhancement takes two forms: on large scales one obtains a linear amplification of the correlation function which is independent of scale. On smaller scales, but larger than the mass scale of the peaks themselves, a nonlinear (exponential) enhancement of the number density of high peaks in overdense regions arises. The large-scale correlations of Abell's rich clusters can be understood as a manifestation of this phenomenon. If the formation of bright galaxies favors the high overdensity peaks then the number of galaxies (per unit mass) in clusters and groups may be considerably enhanced. Consequences of these ideas for the density parameter and the large-scale matter distribution are discussed.

  11. The correlation function for density perturbations in an expanding universe. IV - The evolution of the correlation function. [galaxy distribution

    NASA Technical Reports Server (NTRS)

    Mcclelland, J.; Silk, J.

    1979-01-01

    The evolution of the two-point correlation function for the large-scale distribution of galaxies in an expanding universe is studied on the assumption that the perturbation densities lie in a Gaussian distribution centered on any given mass scale. The perturbations are evolved according to the Friedmann equation, and the correlation function for the resulting distribution of perturbations at the present epoch is calculated. It is found that: (1) the computed correlation function gives a satisfactory fit to the observed function in cosmological models with a density parameter (Omega) of approximately unity, provided that a certain free parameter is suitably adjusted; (2) the power-law slope in the nonlinear regime reflects the initial fluctuation spectrum, provided that the density profile of individual perturbations declines more rapidly than the -2.4 power of distance; and (3) both positive and negative contributions to the correlation function are predicted for cosmological models with Omega less than unity.

  12. Differential Item and Person Functioning in Large-Scale Writing Assessments within the Context of the SAT®. Research Report 2013-6

    ERIC Educational Resources Information Center

    Engelhard, George, Jr.; Wind, Stefanie A.; Kobrin, Jennifer L.; Chajewski, Michael

    2013-01-01

    The purpose of this study is to illustrate the use of explanatory models based on Rasch measurement theory to detect systematic relationships between student and item characteristics and achievement differences using differential item functioning (DIF), differential group functioning (DGF), and differential person functioning (DPF) techniques. The…

  13. Dynamic functional network connectivity using distance correlation

    NASA Astrophysics Data System (ADS)

    Rudas, Jorge; Guaje, Javier; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-01-01

    Investigations about the intrinsic brain organization in resting-state are critical for the understanding of healthy, pathological and pharmacological cerebral states. Recent studies on fMRI suggest that resting state activity is organized on large scale networks of coordinated activity, in the so called, Resting State Networks (RSNs). The assessment of the interactions among these functional networks plays an important role for the understanding of different brain pathologies. Current methods to quantify these interactions commonly assume that the underlying coordination mechanisms are stationary and linear through the whole recording of the resting state phenomena. Nevertheless, recent evidence suggests that rather than stationary, these mechanisms may exhibit a rich set of time-varying repertoires. In addition, these approaches do not consider possible non-linear relationships maybe linked to feed-back communication mechanisms between RSNs. In this work, we introduce a novel approach for dynamical functional network connectivity for functional magnetic resonance imaging (fMRI) resting activity, which accounts for non-linear dynamic relationships between RSNs. The proposed method is based on a windowed distance correlations computed on resting state time-courses extracted at single subject level. We showed that this strategy is complementary to the current approaches for dynamic functional connectivity and will help to enhance the discrimination capacity of patients with disorder of consciousness.

  14. Large-Scale Information Systems

    SciTech Connect

    D. M. Nicol; H. R. Ammerlahn; M. E. Goldsby; M. M. Johnson; D. E. Rhodes; A. S. Yoshimura

    2000-12-01

    Large enterprises are ever more dependent on their Large-Scale Information Systems (LSLS), computer systems that are distinguished architecturally by distributed components--data sources, networks, computing engines, simulations, human-in-the-loop control and remote access stations. These systems provide such capabilities as workflow, data fusion and distributed database access. The Nuclear Weapons Complex (NWC) contains many examples of LSIS components, a fact that motivates this research. However, most LSIS in use grew up from collections of separate subsystems that were not designed to be components of an integrated system. For this reason, they are often difficult to analyze and control. The problem is made more difficult by the size of a typical system, its diversity of information sources, and the institutional complexities associated with its geographic distribution across the enterprise. Moreover, there is no integrated approach for analyzing or managing such systems. Indeed, integrated development of LSIS is an active area of academic research. This work developed such an approach by simulating the various components of the LSIS and allowing the simulated components to interact with real LSIS subsystems. This research demonstrated two benefits. First, applying it to a particular LSIS provided a thorough understanding of the interfaces between the system's components. Second, it demonstrated how more rapid and detailed answers could be obtained to questions significant to the enterprise by interacting with the relevant LSIS subsystems through simulated components designed with those questions in mind. In a final, added phase of the project, investigations were made on extending this research to wireless communication networks in support of telemetry applications.

  15. Scaled density functional theory correlation functionals.

    PubMed

    Ghouri, Mohammed M; Singh, Saurabh; Ramachandran, B

    2007-10-18

    We show that a simple one-parameter scaling of the dynamical correlation energy estimated by the density functional theory (DFT) correlation functionals helps increase the overall accuracy for several local and nonlocal functionals. The approach taken here has been described as the "scaled dynamical correlation" (SDC) method [Ramachandran, J. Phys. Chem. A 2006, 110, 396], and its justification is the same as that of the scaled external correlation (SEC) method of Brown and Truhlar. We examine five local and five nonlocal (hybrid) DFT functionals, the latter group including three functionals developed specifically for kinetics by the Truhlar group. The optimum scale factors are obtained by use of a set of 98 data values consisting of molecules, ions, and transition states. The optimum scale factors, found with a linear regression relationship, are found to differ from unity with a high degree of correlation in nearly every case, indicating that the deviation of calculated results from the experimental values are systematic and proportional to the dynamic correlation energy. As a consequence, the SDC scaling of dynamical correlation decreases the mean errors (signed and unsigned) by significant amounts in an overwhelming majority of cases. These results indicate that there are gains to be realized from further parametrization of several popular exchange-correlation functionals.

  16. Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network

    PubMed Central

    Liao, Qi; Liu, Changning; Yuan, Xiongying; Kang, Shuli; Miao, Ruoyu; Xiao, Hui; Zhao, Guoguang; Luo, Haitao; Bu, Dechao; Zhao, Haitao; Skogerbø, Geir; Wu, Zhongdao; Zhao, Yi

    2011-01-01

    Although accumulating evidence has provided insight into the various functions of long-non-coding RNAs (lncRNAs), the exact functions of the majority of such transcripts are still unknown. Here, we report the first computational annotation of lncRNA functions based on public microarray expression profiles. A coding–non-coding gene co-expression (CNC) network was constructed from re-annotated Affymetrix Mouse Genome Array data. Probable functions for altogether 340 lncRNAs were predicted based on topological or other network characteristics, such as module sharing, association with network hubs and combinations of co-expression and genomic adjacency. The functions annotated to the lncRNAs mainly involve organ or tissue development (e.g. neuron, eye and muscle development), cellular transport (e.g. neuronal transport and sodium ion, acid or lipid transport) or metabolic processes (e.g. involving macromolecules, phosphocreatine and tyrosine). PMID:21247874

  17. Scientific Accomplishments for ARL Brain Structure-Function Couplings Research on Large-Scale Brain Networks from FY11-FY13 (DSI Final Report)

    DTIC Science & Technology

    2014-03-01

    changes in blood flow as a proxy measure of brain activity and electroencephalography (EEG) data that records electrical activity on the scalp that...neuroimaging technologies: Magnetic resonance imaging (MRI) and Electroencephalography (EEG). The first can provide both structural and functional brain data...Michigan, Ann Arbor, and the University of California, San Diego. Electroencephalography (EEG) records the synchronous electrical activity of

  18. Large scale study of tooth enamel

    SciTech Connect

    Bodart, F.; Deconninck, G.; Martin, M.Th.

    1981-04-01

    Human tooth enamel contains traces of foreign elements. The presence of these elements is related to the history and the environment of the human body and can be considered as the signature of perturbations which occur during the growth of a tooth. A map of the distribution of these traces on a large scale sample of the population will constitute a reference for further investigations of environmental effects. One hundred eighty samples of teeth were first analysed using PIXE, backscattering and nuclear reaction techniques. The results were analysed using statistical methods. Correlations between O, F, Na, P, Ca, Mn, Fe, Cu, Zn, Pb and Sr were observed and cluster analysis was in progress. The techniques described in the present work have been developed in order to establish a method for the exploration of very large samples of the Belgian population.

  19. Redshift distortions of galaxy correlation functions

    NASA Astrophysics Data System (ADS)

    Fry, J. N.; Gaztanaga, Enrique

    1994-04-01

    To examine how peculiar velocities can affect the two-, three-, and four-point redshift correlation functions, we evaluate volume-average correlations for configurations that emphasize and minimize redshift distortions for four different volume-limited samples from each of the CfA, SSRS, and IRAS redshift catalogs. We present the results as the correlation length r0 and power index gamma of the two-point correlations, bar-xi0 = (r0/r)gamma, and as the hierarchical amplitudes of the three- and four-point functions, S3 = bar-xi3/bar-xi22 and S4 = bar-xi4/bar-xi32. We find a characteristic distortion for bar-xi2, the slope gamma is flatter and the correlation length is larger in redshift space than in real space; that is, redshift distortions 'move' correlations from small to large scales. At the largest scales (up to 12 Mpc), the extra power in the redshift distribution is compatible with Omega4/7/b approximately equal to 1. We estimate Omega4/7/b to be 0.53 +/- 0.15, 1.10 +/- 0.16, and 0.84 +/- 0.45 for the CfA, SSRS, and IRAS catalogs. Higher order correlations bar-xi3 and bar-xi4 suffer similar redshift distortions but in such a way that, within the accuracy of our analysis, the normalized amplitudes S3 and S4 are insensitive to this effect. The hierarchical amplitudes S3 and S4 are constant as a function of scale between 1 and 12 Mpc and have similar values in all samples and catalogs, S3 approximately equal to 2 and S4 approximately equal to 6, despite the fact that bar-xi2, bar-xi3, and bar-xi4 differ from one sample to another by large factors (up to a factor of 4 in bar-xi2, 8 for bar-xi3, and 12 for bar-xi4). The agreement between the independent estimations of S3 and S4 is remarkable given the different criteria in the selection of galaxies and also the difference in the resulting range of densities, luminosities, and locations between samples.

  20. Redshift distortions of galaxy correlation functions

    NASA Astrophysics Data System (ADS)

    Fry, J. N.; Gaztanaga, E.

    1993-05-01

    To examine how peculiar velocities can affect the 2-, 3-, and 4-point correlation functions, we evaluate volume-average correlations for configurations that emphasize and minimize distortions for four different volume-limited samples from each of the CfA, SSRS, and IRAS redshift catalogs. We present the results as the correlation length r0 and power index gamma of the 2-point correlation, bar-xi2 = (r0/r)gamma), and as the hierarchical amplitudes of the 3- and 4-point functions, S3 = bar-xi3/bar-xi22 and S4 = bar-xi/bar-xi)23. We find a characteristic distortion for bar-xi2: The slope gamma is flatter and the correlation length is larger in redshift space than in real space; that is, redshift distortions 'move' correlations from small to large scales. At the largest scales, extra power in the redshift distribution is compatible with Omega4/7/b approx. 1; we find 0.53 plus/minus 0.15, 1.10 plus/minus 0.16 and 0.84 plus/minus 0.45 for the CfA, SSRS and IRAS catalogs. Higher order correlations bar-xi3 and bar-xi4 suffer similar redshift distortions, but in such a way that, within the accuracy of our analysis, the normalized amplitudes S3 and S4 are insensitive to this effect. The hierarchical amplitudes S3 and S4 are constant as a function of scale between 1-12 h-1 Mpc and have similar values in all samples and catalogues, S3 approx. 2 and S4 approx. 6, despite the fact that bar-xi2, bar-xi3, and bar-xi4 differ from one sample to another by large factors. The agreement between the independent estimations of S3 and S4 is remarkable given the different criteria in the selection of galaxies and also the difference in the resulting range of densities, luminosities and locations between samples.

  1. Multitree Algorithms for Large-Scale Astrostatistics

    NASA Astrophysics Data System (ADS)

    March, William B.; Ozakin, Arkadas; Lee, Dongryeol; Riegel, Ryan; Gray, Alexander G.

    2012-03-01

    this number every week, resulting in billions of objects. At such scales, even linear-time analysis operations present challenges, particularly since statistical analyses are inherently interactive processes, requiring that computations complete within some reasonable human attention span. The quadratic (or worse) runtimes of straightforward implementations become quickly unbearable. Examples of applications. These analysis subroutines occur ubiquitously in astrostatistical work. We list just a few examples. The need to cross-match objects across different catalogs has led to various algorithms, which at some point perform an AllNN computation. 2-point and higher-order spatial correlations for the basis of spatial statistics, and are utilized in astronomy to compare the spatial structures of two datasets, such as an observed sample and a theoretical sample, for example, forming the basis for two-sample hypothesis testing. Friends-of-friends clustering is often used to identify halos in data from astrophysical simulations. Minimum spanning tree properties have also been proposed as statistics of large-scale structure. Comparison of the distributions of different kinds of objects requires accurate density estimation, for which KDE is the overall statistical method of choice. The prediction of redshifts from optical data requires accurate regression, for which kernel regression is a powerful method. The identification of objects of various types in astronomy, such as stars versus galaxies, requires accurate classification, for which KDA is a powerful method. Overview. In this chapter, we will briefly sketch the main ideas behind recent fast algorithms which achieve, for example, linear runtimes for pairwise-distance problems, or similarly dramatic reductions in computational growth. In some cases, the runtime orders for these algorithms are mathematically provable statements, while in others we have only conjectures backed by experimental observations for the time being

  2. Large-Scale Quantum-Mechanical Molecular Dynamics Simulations Using Density-Functional Tight-Binding Combined with the Fragment Molecular Orbital Method.

    PubMed

    Nishimoto, Yoshio; Nakata, Hiroya; Fedorov, Dmitri G; Irle, Stephan

    2015-12-17

    The fully analytic gradient is developed for density-functional tight-binding (DFTB) combined with the fragment molecular orbital (FMO) method (FMO-DFTB). The response terms arising from the coupling of the electronic state to the embedding potential are derived, and the gradient accuracy is demonstrated on water clusters and a polypeptide. The radial distribution functions (RDFs) obtained with FMO-DFTB are found to be similar to those from conventional DFTB, while the computational cost is greatly reduced; for 256 water molecules one molecular dynamics (MD) step takes 73.26 and 0.68 s with full DFTB and FMO-DFTB, respectively, showing a speed-up factor of 108. FMO-DFTB/MD is applied to 100 ps MD simulations of liquid hydrogen halides and is found to reproduce experimental RDFs reasonably well.

  3. Large-scale assembly of colloidal particles

    NASA Astrophysics Data System (ADS)

    Yang, Hongta

    This study reports a simple, roll-to-roll compatible coating technology for producing three-dimensional highly ordered colloidal crystal-polymer composites, colloidal crystals, and macroporous polymer membranes. A vertically beveled doctor blade is utilized to shear align silica microsphere-monomer suspensions to form large-area composites in a single step. The polymer matrix and the silica microspheres can be selectively removed to create colloidal crystals and self-standing macroporous polymer membranes. The thickness of the shear-aligned crystal is correlated with the viscosity of the colloidal suspension and the coating speed, and the correlations can be qualitatively explained by adapting the mechanisms developed for conventional doctor blade coating. Five important research topics related to the application of large-scale three-dimensional highly ordered macroporous films by doctor blade coating are covered in this study. The first topic describes the invention in large area and low cost color reflective displays. This invention is inspired by the heat pipe technology. The self-standing macroporous polymer films exhibit brilliant colors which originate from the Bragg diffractive of visible light form the three-dimensional highly ordered air cavities. The colors can be easily changed by tuning the size of the air cavities to cover the whole visible spectrum. When the air cavities are filled with a solvent which has the same refractive index as that of the polymer, the macroporous polymer films become completely transparent due to the index matching. When the solvent trapped in the cavities is evaporated by in-situ heating, the sample color changes back to brilliant color. This process is highly reversible and reproducible for thousands of cycles. The second topic reports the achievement of rapid and reversible vapor detection by using 3-D macroporous photonic crystals. Capillary condensation of a condensable vapor in the interconnected macropores leads to the

  4. Correlation dynamics of Green functions

    NASA Astrophysics Data System (ADS)

    Shun-Jin, Wang; Wei, Zuo; Wolfgang, Cassing

    1994-06-01

    We generalize the methods used in the theory of correlation dynamics and establish a set of equations of motion for many-body correlation Green functions in the nonrelativistic case. These nonlinear and coupled equations of motion describe the dynamical evolution of correlation Green functions of different order and transparently show how many-body correlations are generated by the different interaction terms in a genuine nonperturbative framework. The nonperturbative results of the conventional Green function theory are included in the present formalism as two limiting cases (the so-called ladder-diagram summation and ring-diagram summation) as well as the familiar correlation dynamics of density matrices in the equal-time limit. We present explicit expressions for three- and four-body correlation functions that can be used to dynamically restore the trace relations for spin-symmetric Fermi systems and study numerically the relative importance of two-, three- and four-body correlations for nuclear configurations close to the ground state.

  5. Cultural norm fulfillment, interpersonal belonging, or getting ahead? A large-scale cross-cultural test of three perspectives on the function of self-esteem.

    PubMed

    Gebauer, Jochen E; Sedikides, Constantine; Wagner, Jenny; Bleidorn, Wiebke; Rentfrow, Peter J; Potter, Jeff; Gosling, Samuel D

    2015-09-01

    What is the function of self-esteem? We classified relevant theoretical work into 3 perspectives. The cultural norm-fulfillment perspective regards self-esteem a result of adherence to cultural norms. The interpersonal-belonging perspective regards self-esteem as a sociometer of interpersonal belonging. The getting-ahead perspective regards self-esteem as a sociometer of getting ahead in the social world, while regarding low anxiety/neuroticism as a sociometer of getting along with others. The 3 perspectives make contrasting predictions on the relation between the Big Five personality traits and self-esteem across cultures. We tested these predictions in a self-report study (2,718,838 participants from 106 countries) and an informant-report study (837,655 informants from 64 countries). We obtained some evidence for cultural norm fulfillment, but the effect size was small. Hence, this perspective does not satisfactorily account for self-esteem's function. We found a strong relation between Extraversion and higher self-esteem, but no such relation between Agreeableness and self-esteem. These 2 traits are pillars of interpersonal belonging. Hence, the results do not fit the interpersonal-belonging perspective either. However, the results closely fit the getting-ahead perspective. The relation between Extraversion and higher self-esteem is consistent with this perspective, because Extraversion is the Big Five driver for getting ahead in the social world. The relation between Agreeableness and lower neuroticism is also consistent with this perspective, because Agreeableness is the Big Five driver for getting along with others.

  6. Large Scale Organization of a Near Wall Turbulent Boundary Layer

    NASA Astrophysics Data System (ADS)

    Stanislas, Michel; Dekou Tiomajou, Raoul Florent; Foucaut, Jean Marc

    2016-11-01

    This study lies in the context of large scale coherent structures investigation in a near wall turbulent boundary layer. An experimental database at high Reynolds numbers (Re θ = 9830 and Re θ = 19660) was obtained in the LML wind tunnel with stereo-PIV at 4 Hz and hot wire anemometry at 30 kHz. A Linear Stochastic Estimation procedure, is used to reconstruct a 3 component field resolved in space and time. Algorithms were developed to extract coherent structures from the reconstructed field. A sample of 3D view of the structures is depicted in Figure 1. Uniform momentum regions are characterized with their mean hydraulic diameter in the YZ plane, their life time and their contribution to Reynolds stresses. The vortical motions are characterized by their position, radius, circulation and vorticity in addition to their life time and their number computed at a fixed position from the wall. The spatial organization of the structures was investigated through a correlation of their respective indicative functions in the spanwise direction. The simplified large scale model that arise is compared to the ones available in the literature. Streamwise low (green) and high (yellow) uniform momentum regions with positive (red) and negative (blue) vortical motions. This work was supported by Campus International pour la Sécurité et l'Intermodalité des Transports.

  7. The correlation function of galaxy ellipticities produced by gravitational lensing

    NASA Technical Reports Server (NTRS)

    Miralda-Escude, Jordi

    1991-01-01

    The correlation of galaxy ellipticities produced by gravitational lensing is calculated as a function of the power spectrum of density fluctuations in the universe by generalizing an analytical method developed by Gunn (1967). The method is applied to a model where identical objects with spherically symmetric density profiles are randomly laid down in space, and to the cold dark matter model. The possibility of detecting this correlation is discussed. Although an ellipticity correlation can also be caused by an intrinsic alignment of the axes of galaxies belonging to a cluster or a supercluster, a method is suggested by which one type of correlation can be distinguished from another. The advantage of this ellipticity correlation is that it is one of the few astronomical observations that can directly probe large-scale mass fluctuations in the universe.

  8. Large Scale Quantum Simulations of Nuclear Pasta

    NASA Astrophysics Data System (ADS)

    Fattoyev, Farrukh J.; Horowitz, Charles J.; Schuetrumpf, Bastian

    2016-03-01

    Complex and exotic nuclear geometries collectively referred to as ``nuclear pasta'' are expected to naturally exist in the crust of neutron stars and in supernovae matter. Using a set of self-consistent microscopic nuclear energy density functionals we present the first results of large scale quantum simulations of pasta phases at baryon densities 0 . 03 < ρ < 0 . 10 fm-3, proton fractions 0 . 05

  9. Large-scale sequential quadratic programming algorithms

    SciTech Connect

    Eldersveld, S.K.

    1992-09-01

    The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

  10. Large-scale characterization of the murine cardiac proteome.

    PubMed

    Cosme, Jake; Emili, Andrew; Gramolini, Anthony O

    2013-01-01

    Cardiomyopathies are diseases of the heart that result in impaired cardiac muscle function. This dysfunction can progress to an inability to supply blood to the body. Cardiovascular diseases play a large role in overall global morbidity. Investigating the protein changes in the heart during disease can uncover pathophysiological mechanisms and potential therapeutic targets. Establishing a global protein expression "footprint" can facilitate more targeted studies of diseases of the heart.In the technical review presented here, we present methods to elucidate the heart's proteome through subfractionation of the cellular compartments to reduce sample complexity and improve detection of lower abundant proteins during multidimensional protein identification technology analysis. Analysis of the cytosolic, microsomal, and mitochondrial subproteomes separately in order to characterize the murine cardiac proteome is advantageous by simplifying complex cardiac protein mixtures. In combination with bioinformatic analysis and genome correlation, large-scale protein changes can be identified at the cellular compartment level in this animal model.

  11. Galaxy clustering and the origin of large-scale flows

    NASA Technical Reports Server (NTRS)

    Juszkiewicz, R.; Yahil, A.

    1989-01-01

    Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

  12. Voids in the Large-Scale Structure

    NASA Astrophysics Data System (ADS)

    El-Ad, Hagai; Piran, Tsvi

    1997-12-01

    Voids are the most prominent feature of the large-scale structure of the universe. Still, their incorporation into quantitative analysis of it has been relatively recent, owing essentially to the lack of an objective tool to identify the voids and to quantify them. To overcome this, we present here the VOID FINDER algorithm, a novel tool for objectively quantifying voids in the galaxy distribution. The algorithm first classifies galaxies as either wall galaxies or field galaxies. Then, it identifies voids in the wall-galaxy distribution. Voids are defined as continuous volumes that do not contain any wall galaxies. The voids must be thicker than an adjustable limit, which is refined in successive iterations. In this way, we identify the same regions that would be recognized as voids by the eye. Small breaches in the walls are ignored, avoiding artificial connections between neighboring voids. We test the algorithm using Voronoi tesselations. By appropriate scaling of the parameters with the selection function, we apply it to two redshift surveys, the dense SSRS2 and the full-sky IRAS 1.2 Jy. Both surveys show similar properties: ~50% of the volume is filled by voids. The voids have a scale of at least 40 h-1 Mpc and an average -0.9 underdensity. Faint galaxies do not fill the voids, but they do populate them more than bright ones. These results suggest that both optically and IRAS-selected galaxies delineate the same large-scale structure. Comparison with the recovered mass distribution further suggests that the observed voids in the galaxy distribution correspond well to underdense regions in the mass distribution. This confirms the gravitational origin of the voids.

  13. The Shane-Wirtanen counts. [in galaxy correlation function

    NASA Technical Reports Server (NTRS)

    Geller, M. J.; Kurtz, M. J.; De Lapparent, V.

    1984-01-01

    It is shown that the 2.5 degree-break in the galaxy correlation function derived from the Shane-Wirtanen star counts is indistinguishable from an artifact introduced by residual systematic variations in the effective magnitude limit from plate to plate. In order to avoid the introduction of a break, the maximum error from plate to plate must be no more than about 0.05 mag. Other large scale features in the data which are also affected by the systematic variations are discussed.

  14. Large scale digital atlases in neuroscience

    NASA Astrophysics Data System (ADS)

    Hawrylycz, M.; Feng, D.; Lau, C.; Kuan, C.; Miller, J.; Dang, C.; Ng, L.

    2014-03-01

    Imaging in neuroscience has revolutionized our current understanding of brain structure, architecture and increasingly its function. Many characteristics of morphology, cell type, and neuronal circuitry have been elucidated through methods of neuroimaging. Combining this data in a meaningful, standardized, and accessible manner is the scope and goal of the digital brain atlas. Digital brain atlases are used today in neuroscience to characterize the spatial organization of neuronal structures, for planning and guidance during neurosurgery, and as a reference for interpreting other data modalities such as gene expression and connectivity data. The field of digital atlases is extensive and in addition to atlases of the human includes high quality brain atlases of the mouse, rat, rhesus macaque, and other model organisms. Using techniques based on histology, structural and functional magnetic resonance imaging as well as gene expression data, modern digital atlases use probabilistic and multimodal techniques, as well as sophisticated visualization software to form an integrated product. Toward this goal, brain atlases form a common coordinate framework for summarizing, accessing, and organizing this knowledge and will undoubtedly remain a key technology in neuroscience in the future. Since the development of its flagship project of a genome wide image-based atlas of the mouse brain, the Allen Institute for Brain Science has used imaging as a primary data modality for many of its large scale atlas projects. We present an overview of Allen Institute digital atlases in neuroscience, with a focus on the challenges and opportunities for image processing and computation.

  15. Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path

    PubMed Central

    Cheng, Bastian; Messé, Arnaud; Thomalla, Götz; Gerloff, Christian; König, Peter

    2016-01-01

    In this study, we investigate if phase-locking of fast oscillatory activity relies on the anatomical skeleton and if simple computational models informed by structural connectivity can help further to explain missing links in the structure-function relationship. We use diffusion tensor imaging data and alpha band-limited EEG signal recorded in a group of healthy individuals. Our results show that about 23.4% of the variance in empirical networks of resting-state functional connectivity is explained by the underlying white matter architecture. Simulating functional connectivity using a simple computational model based on the structural connectivity can increase the match to 45.4%. In a second step, we use our modeling framework to explore several technical alternatives along the modeling path. First, we find that an augmentation of homotopic connections in the structural connectivity matrix improves the link to functional connectivity while a correction for fiber distance slightly decreases the performance of the model. Second, a more complex computational model based on Kuramoto oscillators leads to a slight improvement of the model fit. Third, we show that the comparison of modeled and empirical functional connectivity at source level is much more specific for the underlying structural connectivity. However, different source reconstruction algorithms gave comparable results. Of note, as the fourth finding, the model fit was much better if zero-phase lag components were preserved in the empirical functional connectome, indicating a considerable amount of functionally relevant synchrony taking place with near zero or zero-phase lag. The combination of the best performing alternatives at each stage in the pipeline results in a model that explains 54.4% of the variance in the empirical EEG functional connectivity. Our study shows that large-scale brain circuits of fast neural network synchrony strongly rely upon the structural connectome and simple computational

  16. Large Scale Metal Additive Techniques Review

    SciTech Connect

    Nycz, Andrzej; Adediran, Adeola I; Noakes, Mark W; Love, Lonnie J

    2016-01-01

    In recent years additive manufacturing made long strides toward becoming a main stream production technology. Particularly strong progress has been made in large-scale polymer deposition. However, large scale metal additive has not yet reached parity with large scale polymer. This paper is a review study of the metal additive techniques in the context of building large structures. Current commercial devices are capable of printing metal parts on the order of several cubic feet compared to hundreds of cubic feet for the polymer side. In order to follow the polymer progress path several factors are considered: potential to scale, economy, environment friendliness, material properties, feedstock availability, robustness of the process, quality and accuracy, potential for defects, and post processing as well as potential applications. This paper focuses on current state of art of large scale metal additive technology with a focus on expanding the geometric limits.

  17. Large-scale regions of antimatter

    SciTech Connect

    Grobov, A. V. Rubin, S. G.

    2015-07-15

    Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.

  18. A relativistic signature in large-scale structure

    NASA Astrophysics Data System (ADS)

    Bartolo, Nicola; Bertacca, Daniele; Bruni, Marco; Koyama, Kazuya; Maartens, Roy; Matarrese, Sabino; Sasaki, Misao; Verde, Licia; Wands, David

    2016-09-01

    In General Relativity, the constraint equation relating metric and density perturbations is inherently nonlinear, leading to an effective non-Gaussianity in the dark matter density field on large scales-even if the primordial metric perturbation is Gaussian. Intrinsic non-Gaussianity in the large-scale dark matter overdensity in GR is real and physical. However, the variance smoothed on a local physical scale is not correlated with the large-scale curvature perturbation, so that there is no relativistic signature in the galaxy bias when using the simplest model of bias. It is an open question whether the observable mass proxies such as luminosity or weak lensing correspond directly to the physical mass in the simple halo bias model. If not, there may be observables that encode this relativistic signature.

  19. Identification of seven genes essential for male fertility through a genome-wide association study of non-obstructive azoospermia and RNA interference-mediated large-scale functional screening in Drosophila.

    PubMed

    Yu, Jun; Wu, Hao; Wen, Yang; Liu, Yujuan; Zhou, Tao; Ni, Bixian; Lin, Yuan; Dong, Jing; Zhou, Zuomin; Hu, Zhibin; Guo, Xuejiang; Sha, Jiahao; Tong, Chao

    2015-03-01

    Non-obstructive azoospermia (NOA) is a complex and severe condition whose etiology remains largely unknown. In a genome-wide association study (GWAS) of NOA in Chinese men, few loci reached genome-wide significance, although this might be a result of genetic heterogeneity. Single nucleotide polymorphisms (SNPs) without genome-wide significance may also indicate genes that are essential for fertility, and multiple stage validation can lead to false-negative results. To perform large-scale functional screening of the genes surrounding these SNPs, we used in vivo RNA interference (RNAi) in Drosophila, which has a short maturation cycle and is suitable for high-throughput analysis. The analysis found that 7 (31.8%) of the 22 analyzed orthologous Drosophila genes were essential for male fertility. These genes corresponded to nine loci. Of these genes, leukocyte-antigen-related-like (Lar) is primarily required in germ cells to sustain spermatogenesis, whereas CG12404, doublesex-Mab-related 11E (dmrt11E), CG6769, estrogen-related receptor (ERR) and sulfateless (sfl) function in somatic cells. Interestingly, ERR and sfl are also required for testis morphogenesis. Our study thus demonstrates that SNPs without genome-wide significance in GWAS may also provide clues to disease-related genes and therefore warrant functional analysis.

  20. Omega from the anisotropy of the redshift correlation function

    NASA Technical Reports Server (NTRS)

    Hamilton, A. J. S.

    1993-01-01

    Peculiar velocities distort the correlation function of galaxies observed in redshift space. In the large scale, linear regime, the distortion takes a characteristic quadrupole plus hexadecapole form, with the amplitude of the distortion depending on the cosmological density parameter omega. Preliminary measurements are reported here of the harmonics of the correlation function in the CfA, SSRS, and IRAS 2 Jansky redshift surveys. The observed behavior of the harmonics agrees qualitatively with the predictions of linear theory on large scales in every survey. However, real anisotropy in the galaxy distribution induces large fluctuations in samples which do not yet probe a sufficiently fair volume of the Universe. In the CfA 14.5 sample in particular, the Great Wall induces a large negative quadrupole, which taken at face value implies an unrealistically large omega 20. The IRAS 2 Jy survey, which covers a substantially larger volume than the optical surveys and is less affected by fingers-of-god, yields a more reliable and believable value, omega = 0.5 sup +.5 sub -.25.

  1. Basic biotechnologies essential for the Japanese chemical industry in the 1990's and beyond. Bioreactors, large-scale mammalian cell culture, recombinant DNAs, functional protein systems, and bio-electronic devices

    SciTech Connect

    Fujimura, R.K.

    1992-01-01

    The purpose of the program is to induce private company laboratories to do research considered essential for the development of new technologies. One group of projects initially funded under the program was in the field of biotechnology. More specifically, the biotechnology projects were aimed at developing technologies for the chemical industry for the decade of the 1990's. Various projects dealt with bioreactors, large-scale cell culture, and recombinant DNA. These initial biotechnology projects have now been completed. The report reviews their accomplishments and assesses their possible impact on the Japanese chemical industry. A new project on functional protein complexes was added in 1989. Progress on the nine-year project is also reviewed. Finally, an assessment is provided of the biotechnology components of an unrelated group of projects being administered by the Research and Development Association for Future Electron Devices. The relevant components in the program involve bio-electronic devices and functional protein complexes. The objectives are to mimic biological systems for use in microsensors, information transmission and processing, artificial tissues and organs, robotics, and artificial intelligence.

  2. Characterization of maximally random jammed sphere packings: Voronoi correlation functions.

    PubMed

    Klatt, Michael A; Torquato, Salvatore

    2014-11-01

    We characterize the structure of maximally random jammed (MRJ) sphere packings by computing the Minkowski functionals (volume, surface area, and integrated mean curvature) of their associated Voronoi cells. The probability distribution functions of these functionals of Voronoi cells in MRJ sphere packings are qualitatively similar to those of an equilibrium hard-sphere liquid and partly even to the uncorrelated Poisson point process, implying that such local statistics are relatively structurally insensitive. This is not surprising because the Minkowski functionals of a single Voronoi cell incorporate only local information and are insensitive to global structural information. To improve upon this, we introduce descriptors that incorporate nonlocal information via the correlation functions of the Minkowski functionals of two cells at a given distance as well as certain cell-cell probability density functions. We evaluate these higher-order functions for our MRJ packings as well as equilibrium hard spheres and the Poisson point process. It is shown that these Minkowski correlation and density functions contain visibly more information than the corresponding standard pair-correlation functions. We find strong anticorrelations in the Voronoi volumes for the hyperuniform MRJ packings, consistent with previous findings for other pair correlations [A. Donev et al., Phys. Rev. Lett. 95, 090604 (2005)PRLTAO0031-900710.1103/PhysRevLett.95.090604], indicating that large-scale volume fluctuations are suppressed by accompanying large Voronoi cells with small cells, and vice versa. In contrast to the aforementioned local Voronoi statistics, the correlation functions of the Voronoi cells qualitatively distinguish the structure of MRJ sphere packings (prototypical glasses) from that of not only the Poisson point process but also the correlated equilibrium hard-sphere liquids. Moreover, while we did not find any perfect icosahedra (the locally densest possible structure in which a

  3. A novel computational approach towards the certification of large-scale boson sampling

    NASA Astrophysics Data System (ADS)

    Huh, Joonsuk

    Recent proposals of boson sampling and the corresponding experiments exhibit the possible disproof of extended Church-Turning Thesis. Furthermore, the application of boson sampling to molecular computation has been suggested theoretically. Till now, however, only small-scale experiments with a few photons have been successfully performed. The boson sampling experiments of 20-30 photons are expected to reveal the computational superiority of the quantum device. A novel theoretical proposal for the large-scale boson sampling using microwave photons is highly promising due to the deterministic photon sources and the scalability. Therefore, the certification protocol of large-scale boson sampling experiments should be presented to complete the exciting story. We propose, in this presentation, a computational protocol towards the certification of large-scale boson sampling. The correlations of paired photon modes and the time-dependent characteristic functional with its Fourier component can show the fingerprint of large-scale boson sampling. This work was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(NRF-2015R1A6A3A04059773), the ICT R&D program of MSIP/IITP [2015-019, Fundamental Research Toward Secure Quantum Communication] and Mueunjae Institute for Chemistry (MIC) postdoctoral fellowship.

  4. The IR-resummed Effective Field Theory of Large Scale Structures

    SciTech Connect

    Senatore, Leonardo; Zaldarriaga, Matias E-mail: matiasz@ias.edu

    2015-02-01

    We present a new method to resum the effect of large scale motions in the Effective Field Theory of Large Scale Structures. Because the linear power spectrum in ΛCDM is not scale free the effects of the large scale flows are enhanced. Although previous EFT calculations of the equal-time density power spectrum at one and two loops showed a remarkable agreement with numerical results, they also showed a 2% residual which appeared related to the BAO oscillations. We show that this was indeed the case, explain the physical origin and show how a Lagrangian based calculation removes this differences. We propose a simple method to upgrade existing Eulerian calculations to effectively make them Lagrangian and compare the new results with existing fits to numerical simulations. Our new two-loop results agrees with numerical results up to k∼ 0.6 h Mpc{sup −1} to within 1% with no oscillatory residuals. We also compute power spectra involving momentum which is significantly more affected by the large scale flows. We show how keeping track of these velocities significantly enhances the UV reach of the momentum power spectrum in addition to removing the BAO related residuals. We compute predictions for the real space correlation function around the BAO scale and investigate its sensitivity to the EFT parameters and the details of the resummation technique.

  5. A large-scale perspective on stress-induced alterations in resting-state networks

    NASA Astrophysics Data System (ADS)

    Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

    2016-02-01

    Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

  6. The Evolution of Baryons in Cosmic Large Scale Structure

    NASA Astrophysics Data System (ADS)

    Snedden, Ali; Arielle Phillips, Lara; Mathews, Grant James; Coughlin, Jared; Suh, In-Saeng; Bhattacharya, Aparna

    2015-01-01

    The environments of galaxies play a critical role in their formation and evolution. We study these environments using cosmological simulations with star formation and supernova feedback included. From these simulations, we parse the large scale structure into clusters, filaments and voids using a segmentation algorithm adapted from medical imaging. We trace the star formation history, gas phase and metal evolution of the baryons in the intergalactic medium as function of structure. We find that our algorithm reproduces the baryon fraction in the intracluster medium and that the majority of star formation occurs in cold, dense filaments. We present the consequences this large scale environment has for galactic halos and galaxy evolution.

  7. Survey on large scale system control methods

    NASA Technical Reports Server (NTRS)

    Mercadal, Mathieu

    1987-01-01

    The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

  8. Newton Methods for Large Scale Problems in Machine Learning

    ERIC Educational Resources Information Center

    Hansen, Samantha Leigh

    2014-01-01

    The focus of this thesis is on practical ways of designing optimization algorithms for minimizing large-scale nonlinear functions with applications in machine learning. Chapter 1 introduces the overarching ideas in the thesis. Chapters 2 and 3 are geared towards supervised machine learning applications that involve minimizing a sum of loss…

  9. Extracting Useful Semantic Information from Large Scale Corpora of Text

    ERIC Educational Resources Information Center

    Mendoza, Ray Padilla, Jr.

    2012-01-01

    Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…

  10. REIONIZATION ON LARGE SCALES. I. A PARAMETRIC MODEL CONSTRUCTED FROM RADIATION-HYDRODYNAMIC SIMULATIONS

    SciTech Connect

    Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.

    2013-10-20

    We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048{sup 3} dark matter particles, 2048{sup 3} gas cells, and 17 billion adaptive rays in a L = 100 Mpc h {sup –1} box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h {sup –1}). This correlation can be statistically represented by a scale-dependent linear bias. We construct a parametric function for the bias, which is then used to filter any large-scale density field to derive the corresponding spatially varying reionization redshift field. The parametric model has three free parameters that can be reduced to one free parameter when we fit the two bias parameters to simulation results. We can differentiate degenerate combinations of the bias parameters by combining results for the global ionization histories and correlation length between ionized regions. Unlike previous semi-analytic models, the evolution of the reionization redshift field in our model is directly compared cell by cell against simulations and performs well in all tests. Our model maps the high-resolution, intermediate-volume radiation-hydrodynamic simulations onto lower-resolution, larger-volume N-body simulations (∼> 2 Gpc h {sup –1}) in order to make mock observations and theoretical predictions.

  11. Functional Multiple-Set Canonical Correlation Analysis

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

    2012-01-01

    We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

  12. Management of large-scale technology

    NASA Technical Reports Server (NTRS)

    Levine, A.

    1985-01-01

    Two major themes are addressed in this assessment of the management of large-scale NASA programs: (1) how a high technology agency was a decade marked by a rapid expansion of funds and manpower in the first half and almost as rapid contraction in the second; and (2) how NASA combined central planning and control with decentralized project execution.

  13. Evaluating Large-Scale Interactive Radio Programmes

    ERIC Educational Resources Information Center

    Potter, Charles; Naidoo, Gordon

    2009-01-01

    This article focuses on the challenges involved in conducting evaluations of interactive radio programmes in South Africa with large numbers of schools, teachers, and learners. It focuses on the role such large-scale evaluation has played during the South African radio learning programme's development stage, as well as during its subsequent…

  14. The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

    NASA Technical Reports Server (NTRS)

    Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

    1990-01-01

    The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

  15. Multiscaling and nonextensivity of large-scale structures in the Universe

    NASA Astrophysics Data System (ADS)

    Ramos, F. M.; Wuensche, C. A.; Ribeiro, A. L. B.; Rosa, R. R.

    2002-08-01

    There has been a trend in the past decade to describe the large-scale structures in the Universe as a (multi)fractal set. However, one of the main objections raised by the opponents of this approach deals with the transition to homogeneity. Moreover, they claim there is not enough sampling space to determine a scaling index which characterizes a (multi)fractal set. In this work we propose an alternative solution to this problem, using the generalized thermostatistics formalism. We show that applying the idea of nonextensivity, intrinsic to this approach, it is possible to derive an expression for the correlation function, describing the scaling properties of large-scale structures in the Universe and the transition to homogeneity, which is in good agreement with observational data.

  16. Bias in the effective field theory of large scale structures

    SciTech Connect

    Senatore, Leonardo

    2015-11-05

    We study how to describe collapsed objects, such as galaxies, in the context of the Effective Field Theory of Large Scale Structures. The overdensity of galaxies at a given location and time is determined by the initial tidal tensor, velocity gradients and spatial derivatives of the regions of dark matter that, during the evolution of the universe, ended up at that given location. Similarly to what was recently done for dark matter, we show how this Lagrangian space description can be recovered by upgrading simpler Eulerian calculations. We describe the Eulerian theory. We show that it is perturbatively local in space, but non-local in time, and we explain the observational consequences of this fact. We give an argument for why to a certain degree of accuracy the theory can be considered as quasi time-local and explain what the operator structure is in this case. Furthermore, we describe renormalization of the bias coefficients so that, after this and after upgrading the Eulerian calculation to a Lagrangian one, the perturbative series for galaxies correlation functions results in a manifestly convergent expansion in powers of k/kNL and k/kM, where k is the wavenumber of interest, kNL is the wavenumber associated to the non-linear scale, and kM is the comoving wavenumber enclosing the mass of a galaxy.

  17. Bias in the effective field theory of large scale structures

    DOE PAGES

    Senatore, Leonardo

    2015-11-05

    We study how to describe collapsed objects, such as galaxies, in the context of the Effective Field Theory of Large Scale Structures. The overdensity of galaxies at a given location and time is determined by the initial tidal tensor, velocity gradients and spatial derivatives of the regions of dark matter that, during the evolution of the universe, ended up at that given location. Similarly to what was recently done for dark matter, we show how this Lagrangian space description can be recovered by upgrading simpler Eulerian calculations. We describe the Eulerian theory. We show that it is perturbatively local inmore » space, but non-local in time, and we explain the observational consequences of this fact. We give an argument for why to a certain degree of accuracy the theory can be considered as quasi time-local and explain what the operator structure is in this case. Furthermore, we describe renormalization of the bias coefficients so that, after this and after upgrading the Eulerian calculation to a Lagrangian one, the perturbative series for galaxies correlation functions results in a manifestly convergent expansion in powers of k/kNL and k/kM, where k is the wavenumber of interest, kNL is the wavenumber associated to the non-linear scale, and kM is the comoving wavenumber enclosing the mass of a galaxy.« less

  18. Methods for Ranking and Selection in Large-Scale Inference

    NASA Astrophysics Data System (ADS)

    Henderson, Nicholas C.

    This thesis addresses two distinct problems: one related to ranking and selection for large-scale inference and another related to latent class modeling of longitudinal count data. The first part of the thesis focuses on the problem of identifying leading measurement units from a large collection with a focus on settings with differing levels of estimation precision across measurement units. The main approach presented is a Bayesian ranking procedure that populates the list of top units in a way that maximizes the expected overlap between the true and reported top lists for all list sizes. This procedure relates unit-specific posterior upper tail probabilities with their empirical distribution to yield a ranking variable. It discounts high-variance units less than other common methods and thus achieves improved operating characteristics in the models considered. In the second part of the thesis, we introduce and describe a finite mixture model for longitudinal count data where, conditional on the class label, the subject-specific observations are assumed to arise from a discrete autoregressive process. This approach offers notable computational advantages over related methods due to the within-class closed form of the likelihood function and, as we describe, has a within-class correlation structure which improves model identifiability. We also outline computational strategies for estimating model parameters, and we describe a novel measure of the underlying separation between latent classes and discuss its relation to posterior classification.

  19. Bias in the effective field theory of large scale structures

    SciTech Connect

    Senatore, Leonardo

    2015-11-01

    We study how to describe collapsed objects, such as galaxies, in the context of the Effective Field Theory of Large Scale Structures. The overdensity of galaxies at a given location and time is determined by the initial tidal tensor, velocity gradients and spatial derivatives of the regions of dark matter that, during the evolution of the universe, ended up at that given location. Similarly to what was recently done for dark matter, we show how this Lagrangian space description can be recovered by upgrading simpler Eulerian calculations. We describe the Eulerian theory. We show that it is perturbatively local in space, but non-local in time, and we explain the observational consequences of this fact. We give an argument for why to a certain degree of accuracy the theory can be considered as quasi time-local and explain what the operator structure is in this case. We describe renormalization of the bias coefficients so that, after this and after upgrading the Eulerian calculation to a Lagrangian one, the perturbative series for galaxies correlation functions results in a manifestly convergent expansion in powers of k/k{sub NL} and k/k{sub M}, where k is the wavenumber of interest, k{sub NL} is the wavenumber associated to the non-linear scale, and k{sub M} is the comoving wavenumber enclosing the mass of a galaxy.

  20. Uplink channel estimation error for large scale MIMO system

    NASA Astrophysics Data System (ADS)

    Albdran, Saleh; Alshammari, Ahmad; Matin, Mohammad

    2016-09-01

    The high demand on the wireless networks and the need for higher data rates are the motivation to develop new technologies. Recently, the idea of using large-scale MIMO systems has grabbed great attention from the researchers due to its high spectral and energy efficiency. In this paper, we analyze the UL channel estimation error using large number of antennas in the base station where the UL channel is based on predefined pilot signal. By making a comparison between the identified UL pilot signal and the received UL signal we can get the realization of the channel. We choose to deal with one cell scenario where the effect of inter-cell interference is eliminated for the sake of studying simple approach. While the number of antennas is very large in the base station side, we choose to have one antennal in the user terminal side. We choose to have two models to generate the channel covariance matrix includes one-ring model and exponential correlation model. Figures of channel estimation error are generated where the performance of the mean square error MSE per antenna is presented as a function signal to noise ratio SNR. The simulation results show that the higher the SNR the better the performance. Furthermore, the affect of the pilot length on the channel estimation error is studied where two different covariance models are used to see the impact of the two cases. In the two cases, the increase of the pilot length has improved the estimation accuracy.

  1. Dominant modes of variability in large-scale Birkeland currents

    NASA Astrophysics Data System (ADS)

    Cousins, E. D. P.; Matsuo, Tomoko; Richmond, A. D.; Anderson, B. J.

    2015-08-01

    Properties of variability in large-scale Birkeland currents are investigated through empirical orthogonal function (EOF) analysis of 1 week of data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). Mean distributions and dominant modes of variability are identified for both the Northern and Southern Hemispheres. Differences in the results from the two hemispheres are observed, which are attributed to seasonal differences in conductivity (the study period occurred near solstice). A universal mean and set of dominant modes of variability are obtained through combining the hemispheric results, and it is found that the mean and first three modes of variability (EOFs) account for 38% of the total observed squared magnetic perturbations (δB2) from both hemispheres. The mean distribution represents a standard Region 1/Region 2 (R1/R2) morphology of currents and EOF 1 captures the strengthening/weakening of the average distribution and is well correlated with the north-south component of the interplanetary magnetic field (IMF). EOF 2 captures a mixture of effects including the expansion/contraction and rotation of the (R1/R2) currents; this mode correlates only weakly with possible external driving parameters. EOF 3 captures changes in the morphology of the currents in the dayside cusp region and is well correlated with the dawn-dusk component of the IMF. The higher-order EOFs capture more complex, smaller-scale variations in the Birkeland currents and appear generally uncorrelated with external driving parameters. The results of the EOF analysis described here are used for describing error covariance in a data assimilation procedure utilizing AMPERE data, as described in a companion paper.

  2. Loops in inflationary correlation functions

    NASA Astrophysics Data System (ADS)

    Tanaka, Takahiro; Urakawa, Yuko

    2013-12-01

    We review the recent progress regarding the loop corrections to the correlation functions in the inflationary universe. A naive perturbation theory predicts that the loop corrections generated during inflation suffer from various infrared (IR) pathologies. Introducing an IR cutoff by hand is neither satisfactory nor enough to fix the problem of a secular growth, which may ruin the predictive power of inflation models if the inflation lasts sufficiently long. We discuss the origin of the IR divergences and explore the regularity conditions of the loop corrections for the adiabatic perturbation, the iso-curvature perturbation, and the tensor perturbation, in turn. These three kinds of perturbations have qualitative differences, but in discussing the IR regularity there is a feature common to all cases, which is the importance of the proper identification of observable quantities. Genuinely, observable quantities should respect the gauge invariance from the view point of a local observer. Interestingly, we find that the requirement of the IR regularity restricts the allowed quantum states.

  3. Large-scale Advanced Propfan (LAP) program

    NASA Technical Reports Server (NTRS)

    Sagerser, D. A.; Ludemann, S. G.

    1985-01-01

    The propfan is an advanced propeller concept which maintains the high efficiencies traditionally associated with conventional propellers at the higher aircraft cruise speeds associated with jet transports. The large-scale advanced propfan (LAP) program extends the research done on 2 ft diameter propfan models to a 9 ft diameter article. The program includes design, fabrication, and testing of both an eight bladed, 9 ft diameter propfan, designated SR-7L, and a 2 ft diameter aeroelastically scaled model, SR-7A. The LAP program is complemented by the propfan test assessment (PTA) program, which takes the large-scale propfan and mates it with a gas generator and gearbox to form a propfan propulsion system and then flight tests this system on the wing of a Gulfstream 2 testbed aircraft.

  4. Condition Monitoring of Large-Scale Facilities

    NASA Technical Reports Server (NTRS)

    Hall, David L.

    1999-01-01

    This document provides a summary of the research conducted for the NASA Ames Research Center under grant NAG2-1182 (Condition-Based Monitoring of Large-Scale Facilities). The information includes copies of view graphs presented at NASA Ames in the final Workshop (held during December of 1998), as well as a copy of a technical report provided to the COTR (Dr. Anne Patterson-Hine) subsequent to the workshop. The material describes the experimental design, collection of data, and analysis results associated with monitoring the health of large-scale facilities. In addition to this material, a copy of the Pennsylvania State University Applied Research Laboratory data fusion visual programming tool kit was also provided to NASA Ames researchers.

  5. Large-Scale Aerosol Modeling and Analysis

    DTIC Science & Technology

    2008-09-30

    aerosol species up to six days in advance anywhere on the globe. NAAPS and COAMPS are particularly useful for forecasts of dust storms in areas...impact cloud processes globally. With increasing dust storms due to climate change and land use changes in desert regions, the impact of the...bacteria in large-scale dust storms is expected to significantly impact warm ice cloud formation, human health, and ecosystems globally. In Niemi et al

  6. Economically viable large-scale hydrogen liquefaction

    NASA Astrophysics Data System (ADS)

    Cardella, U.; Decker, L.; Klein, H.

    2017-02-01

    The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

  7. Large-Scale Visual Data Analysis

    NASA Astrophysics Data System (ADS)

    Johnson, Chris

    2014-04-01

    Modern high performance computers have speeds measured in petaflops and handle data set sizes measured in terabytes and petabytes. Although these machines offer enormous potential for solving very large-scale realistic computational problems, their effectiveness will hinge upon the ability of human experts to interact with their simulation results and extract useful information. One of the greatest scientific challenges of the 21st century is to effectively understand and make use of the vast amount of information being produced. Visual data analysis will be among our most most important tools in helping to understand such large-scale information. Our research at the Scientific Computing and Imaging (SCI) Institute at the University of Utah has focused on innovative, scalable techniques for large-scale 3D visual data analysis. In this talk, I will present state- of-the-art visualization techniques, including scalable visualization algorithms and software, cluster-based visualization methods and innovate visualization techniques applied to problems in computational science, engineering, and medicine. I will conclude with an outline for a future high performance visualization research challenges and opportunities.

  8. Large-scale neuromorphic computing systems

    NASA Astrophysics Data System (ADS)

    Furber, Steve

    2016-10-01

    Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.

  9. Testing gravity using large-scale redshift-space distortions

    NASA Astrophysics Data System (ADS)

    Raccanelli, Alvise; Bertacca, Daniele; Pietrobon, Davide; Schmidt, Fabian; Samushia, Lado; Bartolo, Nicola; Doré, Olivier; Matarrese, Sabino; Percival, Will J.

    2013-11-01

    We use luminous red galaxies from the Sloan Digital Sky Survey (SDSS) II to test the cosmological structure growth in two alternatives to the standard Λ cold dark matter (ΛCDM)+general relativity (GR) cosmological model. We compare observed three-dimensional clustering in SDSS Data Release 7 (DR7) with theoretical predictions for the standard vanilla ΛCDM+GR model, unified dark matter (UDM) cosmologies and the normal branch Dvali-Gabadadze-Porrati (nDGP). In computing the expected correlations in UDM cosmologies, we derive a parametrized formula for the growth factor in these models. For our analysis we apply the methodology tested in Raccanelli et al. and use the measurements of Samushia et al. that account for survey geometry, non-linear and wide-angle effects and the distribution of pair orientation. We show that the estimate of the growth rate is potentially degenerate with wide-angle effects, meaning that extremely accurate measurements of the growth rate on large scales will need to take such effects into account. We use measurements of the zeroth and second-order moments of the correlation function from SDSS DR7 data and the Large Suite of Dark Matter Simulations (LasDamas), and perform a likelihood analysis to constrain the parameters of the models. Using information on the clustering up to rmax = 120 h-1 Mpc, and after marginalizing over the bias, we find, for UDM models, a speed of sound c∞ ≤ 6.1e-4, and, for the nDGP model, a cross-over scale rc ≥ 340 Mpc, at 95 per cent confidence level.

  10. The Effective Field Theory of Large Scale Structures at two loops

    SciTech Connect

    Carrasco, John Joseph M.; Foreman, Simon; Green, Daniel; Senatore, Leonardo E-mail: sfore@stanford.edu E-mail: senatore@stanford.edu

    2014-07-01

    Large scale structure surveys promise to be the next leading probe of cosmological information. It is therefore crucial to reliably predict their observables. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a manifestly convergent perturbation theory for the weakly non-linear regime of dark matter, where correlation functions are computed in an expansion of the wavenumber k of a mode over the wavenumber associated with the non-linear scale k{sub NL}. Since most of the information is contained at high wavenumbers, it is necessary to compute higher order corrections to correlation functions. After the one-loop correction to the matter power spectrum, we estimate that the next leading one is the two-loop contribution, which we compute here. At this order in k/k{sub NL}, there is only one counterterm in the EFTofLSS that must be included, though this term contributes both at tree-level and in several one-loop diagrams. We also discuss correlation functions involving the velocity and momentum fields. We find that the EFTofLSS prediction at two loops matches to percent accuracy the non-linear matter power spectrum at redshift zero up to k∼ 0.6 h Mpc{sup −1}, requiring just one unknown coefficient that needs to be fit to observations. Given that Standard Perturbation Theory stops converging at redshift zero at k∼ 0.1 h Mpc{sup −1}, our results demonstrate the possibility of accessing a factor of order 200 more dark matter quasi-linear modes than naively expected. If the remaining observational challenges to accessing these modes can be addressed with similar success, our results show that there is tremendous potential for large scale structure surveys to explore the primordial universe.

  11. The new discussion of a neutrino mass and issues in the formation of large-scale structure

    NASA Technical Reports Server (NTRS)

    Melott, Adrian L.

    1991-01-01

    It is argued that the discrepancy between the large-scale structure predicted by cosmological models with neutrino mass (hot dark matter) do not differ drastically from the observed structure. Evidence from the correlation amplitude, nonlinearity and the onset of galaxy formation, large-scale streaming velocities, and the topology of large-scale structure is considered. Hot dark matter models seem to be as accurate predictors of the large-scale structure as are cold dark matter models.

  12. New probes of Cosmic Microwave Background large-scale anomalies

    NASA Astrophysics Data System (ADS)

    Aiola, Simone

    Fifty years of Cosmic Microwave Background (CMB) data played a crucial role in constraining the parameters of the LambdaCDM model, where Dark Energy, Dark Matter, and Inflation are the three most important pillars not yet understood. Inflation prescribes an isotropic universe on large scales, and it generates spatially-correlated density fluctuations over the whole Hubble volume. CMB temperature fluctuations on scales bigger than a degree in the sky, affected by modes on super-horizon scale at the time of recombination, are a clean snapshot of the universe after inflation. In addition, the accelerated expansion of the universe, driven by Dark Energy, leaves a hardly detectable imprint in the large-scale temperature sky at late times. Such fundamental predictions have been tested with current CMB data and found to be in tension with what we expect from our simple LambdaCDM model. Is this tension just a random fluke or a fundamental issue with the present model? In this thesis, we present a new framework to probe the lack of large-scale correlations in the temperature sky using CMB polarization data. Our analysis shows that if a suppression in the CMB polarization correlations is detected, it will provide compelling evidence for new physics on super-horizon scale. To further analyze the statistical properties of the CMB temperature sky, we constrain the degree of statistical anisotropy of the CMB in the context of the observed large-scale dipole power asymmetry. We find evidence for a scale-dependent dipolar modulation at 2.5sigma. To isolate late-time signals from the primordial ones, we test the anomalously high Integrated Sachs-Wolfe effect signal generated by superstructures in the universe. We find that the detected signal is in tension with the expectations from LambdaCDM at the 2.5sigma level, which is somewhat smaller than what has been previously argued. To conclude, we describe the current status of CMB observations on small scales, highlighting the

  13. Experimental Simulations of Large-Scale Collisions

    NASA Technical Reports Server (NTRS)

    Housen, Kevin R.

    2002-01-01

    This report summarizes research on the effects of target porosity on the mechanics of impact cratering. Impact experiments conducted on a centrifuge provide direct simulations of large-scale cratering on porous asteroids. The experiments show that large craters in porous materials form mostly by compaction, with essentially no deposition of material into the ejecta blanket that is a signature of cratering in less-porous materials. The ratio of ejecta mass to crater mass is shown to decrease with increasing crater size or target porosity. These results are consistent with the observation that large closely-packed craters on asteroid Mathilde appear to have formed without degradation to earlier craters.

  14. Large-Scale PV Integration Study

    SciTech Connect

    Lu, Shuai; Etingov, Pavel V.; Diao, Ruisheng; Ma, Jian; Samaan, Nader A.; Makarov, Yuri V.; Guo, Xinxin; Hafen, Ryan P.; Jin, Chunlian; Kirkham, Harold; Shlatz, Eugene; Frantzis, Lisa; McClive, Timothy; Karlson, Gregory; Acharya, Dhruv; Ellis, Abraham; Stein, Joshua; Hansen, Clifford; Chadliev, Vladimir; Smart, Michael; Salgo, Richard; Sorensen, Rahn; Allen, Barbara; Idelchik, Boris

    2011-07-29

    This research effort evaluates the impact of large-scale photovoltaic (PV) and distributed generation (DG) output on NV Energy’s electric grid system in southern Nevada. It analyzes the ability of NV Energy’s generation to accommodate increasing amounts of utility-scale PV and DG, and the resulting cost of integrating variable renewable resources. The study was jointly funded by the United States Department of Energy and NV Energy, and conducted by a project team comprised of industry experts and research scientists from Navigant Consulting Inc., Sandia National Laboratories, Pacific Northwest National Laboratory and NV Energy.

  15. What is a large-scale dynamo?

    NASA Astrophysics Data System (ADS)

    Nigro, G.; Pongkitiwanichakul, P.; Cattaneo, F.; Tobias, S. M.

    2017-01-01

    We consider kinematic dynamo action in a sheared helical flow at moderate to high values of the magnetic Reynolds number (Rm). We find exponentially growing solutions which, for large enough shear, take the form of a coherent part embedded in incoherent fluctuations. We argue that at large Rm large-scale dynamo action should be identified by the presence of structures coherent in time, rather than those at large spatial scales. We further argue that although the growth rate is determined by small-scale processes, the period of the coherent structures is set by mean-field considerations.

  16. Neutrinos and large-scale structure

    SciTech Connect

    Eisenstein, Daniel J.

    2015-07-15

    I review the use of cosmological large-scale structure to measure properties of neutrinos and other relic populations of light relativistic particles. With experiments to measure the anisotropies of the cosmic microwave anisotropies and the clustering of matter at low redshift, we now have securely measured a relativistic background with density appropriate to the cosmic neutrino background. Our limits on the mass of the neutrino continue to shrink. Experiments coming in the next decade will greatly improve the available precision on searches for the energy density of novel relativistic backgrounds and the mass of neutrinos.

  17. Colloquium: Large scale simulations on GPU clusters

    NASA Astrophysics Data System (ADS)

    Bernaschi, Massimo; Bisson, Mauro; Fatica, Massimiliano

    2015-06-01

    Graphics processing units (GPU) are currently used as a cost-effective platform for computer simulations and big-data processing. Large scale applications require that multiple GPUs work together but the efficiency obtained with cluster of GPUs is, at times, sub-optimal because the GPU features are not exploited at their best. We describe how it is possible to achieve an excellent efficiency for applications in statistical mechanics, particle dynamics and networks analysis by using suitable memory access patterns and mechanisms like CUDA streams, profiling tools, etc. Similar concepts and techniques may be applied also to other problems like the solution of Partial Differential Equations.

  18. Large scale phononic metamaterials for seismic isolation

    SciTech Connect

    Aravantinos-Zafiris, N.; Sigalas, M. M.

    2015-08-14

    In this work, we numerically examine structures that could be characterized as large scale phononic metamaterials. These novel structures could have band gaps in the frequency spectrum of seismic waves when their dimensions are chosen appropriately, thus raising the belief that they could be serious candidates for seismic isolation structures. Different and easy to fabricate structures were examined made from construction materials such as concrete and steel. The well-known finite difference time domain method is used in our calculations in order to calculate the band structures of the proposed metamaterials.

  19. Large-scale Heterogeneous Network Data Analysis

    DTIC Science & Technology

    2012-07-31

    Data for Multi-Player Influence Maximization on Social Networks.” KDD 2012 (Demo).  Po-Tzu Chang , Yen-Chieh Huang, Cheng-Lun Yang, Shou-De Lin, Pu...Jen Cheng. “Learning-Based Time-Sensitive Re-Ranking for Web Search.” SIGIR 2012 (poster)  Hung -Che Lai, Cheng-Te Li, Yi-Chen Lo, and Shou-De Lin...Exploiting and Evaluating MapReduce for Large-Scale Graph Mining.” ASONAM 2012 (Full, 16% acceptance ratio).  Hsun-Ping Hsieh , Cheng-Te Li, and Shou

  20. Channel capacity of next generation large scale MIMO systems

    NASA Astrophysics Data System (ADS)

    Alshammari, A.; Albdran, S.; Matin, M.

    2016-09-01

    Information rate that can be transferred over a given bandwidth is limited by the information theory. Capacity depends on many factors such as the signal to noise ratio (SNR), channel state information (CSI) and the spatial correlation in the propagation environment. It is very important to increase spectral efficiency in order to meet the growing demand for wireless services. Thus, Multiple input multiple output (MIMO) technology has been developed and applied in most of the wireless standards and it has been very successful in increasing capacity and reliability. As the demand is still increasing, attention now is shifting towards large scale multiple input multiple output (MIMO) which has a potential of bringing orders of magnitude of improvement in spectral and energy efficiency. It has been shown that users channels decorrelate after increasing the number of antennas. As a result, inter-user interference can be avoided since energy can be focused on precise directions. This paper investigates the limits of channel capacity for large scale MIMO. We study the relation between spectral efficiency and the number of antenna N. We use time division duplex (TDD) system in order to obtain CSI using training sequence in the uplink. The same CSI is used for the downlink because the channel is reciprocal. Spectral efficiency is measured for channel model that account for small scale fading while ignoring the effect of large scale fading. It is shown the spectral efficiency can be improved significantly when compared to single antenna systems in ideal circumstances.

  1. Alteration of Large-Scale Chromatin Structure by Estrogen Receptor

    PubMed Central

    Nye, Anne C.; Rajendran, Ramji R.; Stenoien, David L.; Mancini, Michael A.; Katzenellenbogen, Benita S.; Belmont, Andrew S.

    2002-01-01

    The estrogen receptor (ER), a member of the nuclear hormone receptor superfamily important in human physiology and disease, recruits coactivators which modify local chromatin structure. Here we describe effects of ER on large-scale chromatin structure as visualized in live cells. We targeted ER to gene-amplified chromosome arms containing large numbers of lac operator sites either directly, through a lac repressor-ER fusion protein (lac rep-ER), or indirectly, by fusing lac repressor with the ER interaction domain of the coactivator steroid receptor coactivator 1. Significant decondensation of large-scale chromatin structure, comparable to that produced by the ∼150-fold-stronger viral protein 16 (VP16) transcriptional activator, was produced by ER in the absence of estradiol using both approaches. Addition of estradiol induced a partial reversal of this unfolding by green fluorescent protein-lac rep-ER but not by wild-type ER recruited by a lac repressor-SRC570-780 fusion protein. The chromatin decondensation activity did not require transcriptional activation by ER nor did it require ligand-induced coactivator interactions, and unfolding did not correlate with histone hyperacetylation. Ligand-induced coactivator interactions with helix 12 of ER were necessary for the partial refolding of chromatin in response to estradiol using the lac rep-ER tethering system. This work demonstrates that when tethered or recruited to DNA, ER possesses a novel large-scale chromatin unfolding activity. PMID:11971975

  2. Large-scale flow generation by inhomogeneous helicity.

    PubMed

    Yokoi, N; Brandenburg, A

    2016-03-01

    The effect of kinetic helicity (velocity-vorticity correlation) on turbulent momentum transport is investigated. The turbulent kinetic helicity (pseudoscalar) enters the Reynolds stress (mirror-symmetric tensor) expression in the form of a helicity gradient as the coupling coefficient for the mean vorticity and/or the angular velocity (axial vector), which suggests the possibility of mean-flow generation in the presence of inhomogeneous helicity. This inhomogeneous helicity effect, which was previously confirmed at the level of a turbulence- or closure-model simulation, is examined with the aid of direct numerical simulations of rotating turbulence with nonuniform helicity sustained by an external forcing. The numerical simulations show that the spatial distribution of the Reynolds stress is in agreement with the helicity-related term coupled with the angular velocity, and that a large-scale flow is generated in the direction of angular velocity. Such a large-scale flow is not induced in the case of homogeneous turbulent helicity. This result confirms the validity of the inhomogeneous helicity effect in large-scale flow generation and suggests that a vortex dynamo is possible even in incompressible turbulence where there is no baroclinicity effect.

  3. Large-scale Intelligent Transporation Systems simulation

    SciTech Connect

    Ewing, T.; Canfield, T.; Hannebutte, U.; Levine, D.; Tentner, A.

    1995-06-01

    A prototype computer system has been developed which defines a high-level architecture for a large-scale, comprehensive, scalable simulation of an Intelligent Transportation System (ITS) capable of running on massively parallel computers and distributed (networked) computer systems. The prototype includes the modelling of instrumented ``smart`` vehicles with in-vehicle navigation units capable of optimal route planning and Traffic Management Centers (TMC). The TMC has probe vehicle tracking capabilities (display position and attributes of instrumented vehicles), and can provide 2-way interaction with traffic to provide advisories and link times. Both the in-vehicle navigation module and the TMC feature detailed graphical user interfaces to support human-factors studies. The prototype has been developed on a distributed system of networked UNIX computers but is designed to run on ANL`s IBM SP-X parallel computer system for large scale problems. A novel feature of our design is that vehicles will be represented by autonomus computer processes, each with a behavior model which performs independent route selection and reacts to external traffic events much like real vehicles. With this approach, one will be able to take advantage of emerging massively parallel processor (MPP) systems.

  4. Local gravity and large-scale structure

    NASA Technical Reports Server (NTRS)

    Juszkiewicz, Roman; Vittorio, Nicola; Wyse, Rosemary F. G.

    1990-01-01

    The magnitude and direction of the observed dipole anisotropy of the galaxy distribution can in principle constrain the amount of large-scale power present in the spectrum of primordial density fluctuations. This paper confronts the data, provided by a recent redshift survey of galaxies detected by the IRAS satellite, with the predictions of two cosmological models with very different levels of large-scale power: the biased Cold Dark Matter dominated model (CDM) and a baryon-dominated model (BDM) with isocurvature initial conditions. Model predictions are investigated for the Local Group peculiar velocity, v(R), induced by mass inhomogeneities distributed out to a given radius, R, for R less than about 10,000 km/s. Several convergence measures for v(R) are developed, which can become powerful cosmological tests when deep enough samples become available. For the present data sets, the CDM and BDM predictions are indistinguishable at the 2 sigma level and both are consistent with observations. A promising discriminant between cosmological models is the misalignment angle between v(R) and the apex of the dipole anisotropy of the microwave background.

  5. Large-scale Globally Propagating Coronal Waves.

    PubMed

    Warmuth, Alexander

    Large-scale, globally propagating wave-like disturbances have been observed in the solar chromosphere and by inference in the corona since the 1960s. However, detailed analysis of these phenomena has only been conducted since the late 1990s. This was prompted by the availability of high-cadence coronal imaging data from numerous spaced-based instruments, which routinely show spectacular globally propagating bright fronts. Coronal waves, as these perturbations are usually referred to, have now been observed in a wide range of spectral channels, yielding a wealth of information. Many findings have supported the "classical" interpretation of the disturbances: fast-mode MHD waves or shocks that are propagating in the solar corona. However, observations that seemed inconsistent with this picture have stimulated the development of alternative models in which "pseudo waves" are generated by magnetic reconfiguration in the framework of an expanding coronal mass ejection. This has resulted in a vigorous debate on the physical nature of these disturbances. This review focuses on demonstrating how the numerous observational findings of the last one and a half decades can be used to constrain our models of large-scale coronal waves, and how a coherent physical understanding of these disturbances is finally emerging.

  6. The Large Scale Synthesis of Aligned Plate Nanostructures

    NASA Astrophysics Data System (ADS)

    Zhou, Yang; Nash, Philip; Liu, Tian; Zhao, Naiqin; Zhu, Shengli

    2016-07-01

    We propose a novel technique for the large-scale synthesis of aligned-plate nanostructures that are self-assembled and self-supporting. The synthesis technique involves developing nanoscale two-phase microstructures through discontinuous precipitation followed by selective etching to remove one of the phases. The method may be applied to any alloy system in which the discontinuous precipitation transformation goes to completion. The resulting structure may have many applications in catalysis, filtering and thermal management depending on the phase selection and added functionality through chemical reaction with the retained phase. The synthesis technique is demonstrated using the discontinuous precipitation of a γ‧ phase, (Ni, Co)3Al, followed by selective dissolution of the γ matrix phase. The production of the nanostructure requires heat treatments on the order of minutes and can be performed on a large scale making this synthesis technique of great economic potential.

  7. Large-scale linear nonparallel support vector machine solver.

    PubMed

    Tian, Yingjie; Ping, Yuan

    2014-02-01

    Twin support vector machines (TWSVMs), as the representative nonparallel hyperplane classifiers, have shown the effectiveness over standard SVMs from some aspects. However, they still have some serious defects restricting their further study and real applications: (1) They have to compute and store the inverse matrices before training, it is intractable for many applications where data appear with a huge number of instances as well as features; (2) TWSVMs lost the sparseness by using a quadratic loss function making the proximal hyperplane close enough to the class itself. This paper proposes a Sparse Linear Nonparallel Support Vector Machine, termed as L1-NPSVM, to deal with large-scale data based on an efficient solver-dual coordinate descent (DCD) method. Both theoretical analysis and experiments indicate that our method is not only suitable for large scale problems, but also performs as good as TWSVMs and SVMs.

  8. The Large Scale Synthesis of Aligned Plate Nanostructures

    PubMed Central

    Zhou, Yang; Nash, Philip; Liu, Tian; Zhao, Naiqin; Zhu, Shengli

    2016-01-01

    We propose a novel technique for the large-scale synthesis of aligned-plate nanostructures that are self-assembled and self-supporting. The synthesis technique involves developing nanoscale two-phase microstructures through discontinuous precipitation followed by selective etching to remove one of the phases. The method may be applied to any alloy system in which the discontinuous precipitation transformation goes to completion. The resulting structure may have many applications in catalysis, filtering and thermal management depending on the phase selection and added functionality through chemical reaction with the retained phase. The synthesis technique is demonstrated using the discontinuous precipitation of a γ′ phase, (Ni, Co)3Al, followed by selective dissolution of the γ matrix phase. The production of the nanostructure requires heat treatments on the order of minutes and can be performed on a large scale making this synthesis technique of great economic potential. PMID:27439672

  9. In the fast lane: large-scale bacterial genome engineering.

    PubMed

    Fehér, Tamás; Burland, Valerie; Pósfai, György

    2012-07-31

    The last few years have witnessed rapid progress in bacterial genome engineering. The long-established, standard ways of DNA synthesis, modification, transfer into living cells, and incorporation into genomes have given way to more effective, large-scale, robust genome modification protocols. Expansion of these engineering capabilities is due to several factors. Key advances include: (i) progress in oligonucleotide synthesis and in vitro and in vivo assembly methods, (ii) optimization of recombineering techniques, (iii) introduction of parallel, large-scale, combinatorial, and automated genome modification procedures, and (iv) rapid identification of the modifications by barcode-based analysis and sequencing. Combination of the brute force of these techniques with sophisticated bioinformatic design and modeling opens up new avenues for the analysis of gene functions and cellular network interactions, but also in engineering more effective producer strains. This review presents a summary of recent technological advances in bacterial genome engineering.

  10. A new technique for the detection of large scale landslides in glacio-lacustrine deposits using image correlation based upon aerial imagery: A case study from the French Alps

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

    Landslide monitoring has benefited from recent advances in the use of image correlation of high resolution optical imagery. However, this approach has typically involved satellite imagery that may not be available for all landslides depending on their time of movement and location. This study has investigated the application of image correlation techniques applied to a sequence of aerial imagery to an active landslide in the French Alps. We apply an indirect landslide monitoring technique (COSI-Corr) based upon the cross-correlation between aerial photographs, to obtain horizontal displacement rates. Results for the 2001-2003 time interval are presented, providing a spatial model of landslide activity and motion across the landslide, which is consistent with previous studies. The study has identified areas of new landslide activity in addition to known areas and through image decorrelation has identified and mapped two new lateral landslides within the main landslide complex. This new approach for landslide monitoring is likely to be of wide applicability to other areas characterised by complex ground displacements.

  11. Functional CAR models for large spatially correlated functional datasets.

    PubMed

    Zhang, Lin; Baladandayuthapani, Veerabhadran; Zhu, Hongxiao; Baggerly, Keith A; Majewski, Tadeusz; Czerniak, Bogdan A; Morris, Jeffrey S

    2016-01-01

    We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on functions defined on higher dimensional domains such as images. Through simulation studies, we demonstrate that accounting for the spatial correlation in our modeling leads to improved functional regression performance. Applied to a high-throughput spatially correlated copy number dataset, the model identifies genetic markers not identified by comparable methods that ignore spatial correlations.

  12. Large-scale genotoxicity assessments in the marine environment.

    PubMed Central

    Hose, J E

    1994-01-01

    There are a number of techniques for detecting genotoxicity in the marine environment, and many are applicable to large-scale field assessments. Certain tests can be used to evaluate responses in target organisms in situ while others utilize surrogate organisms exposed to field samples in short-term laboratory bioassays. Genotoxicity endpoints appear distinct from traditional toxicity endpoints, but some have chemical or ecotoxicologic correlates. One versatile end point, the frequency of anaphase aberrations, has been used in several large marine assessments to evaluate genotoxicity in the New York Bight, in sediment from San Francisco Bay, and following the Exxon Valdez oil spill. PMID:7713029

  13. Large-scale genotoxicity assessments in the marine environment

    SciTech Connect

    Hose, J.E.

    1994-12-01

    There are a number of techniques for detecting genotoxicity in the marine environment, and many are applicable to large-scale field assessments. Certain tests can be used to evaluate responses in target organisms in situ while others utilize surrogate organisms exposed to field samples in short-term laboratory bioassays. Genotoxicity endpoints appear distinct from traditional toxicity endpoints, but some have chemical or ecotoxicologic correlates. One versatile end point, the frequency of anaphase aberrations, has been used in several large marine assessments to evaluate genotoxicity in the New York Bight, in sediment from San Francisco Bay, and following the Exxon Valdez oil spill. 31 refs., 2 tabs.

  14. Engineering management of large scale systems

    NASA Technical Reports Server (NTRS)

    Sanders, Serita; Gill, Tepper L.; Paul, Arthur S.

    1989-01-01

    The organization of high technology and engineering problem solving, has given rise to an emerging concept. Reasoning principles for integrating traditional engineering problem solving with system theory, management sciences, behavioral decision theory, and planning and design approaches can be incorporated into a methodological approach to solving problems with a long range perspective. Long range planning has a great potential to improve productivity by using a systematic and organized approach. Thus, efficiency and cost effectiveness are the driving forces in promoting the organization of engineering problems. Aspects of systems engineering that provide an understanding of management of large scale systems are broadly covered here. Due to the focus and application of research, other significant factors (e.g., human behavior, decision making, etc.) are not emphasized but are considered.

  15. Large-scale parametric survival analysis.

    PubMed

    Mittal, Sushil; Madigan, David; Cheng, Jerry Q; Burd, Randall S

    2013-10-15

    Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only a small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power have led to considerable interest in analyzing very-high-dimensional data where the number of predictor variables and the number of observations range between 10(4) and 10(6). In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of the cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models.

  16. Primer design for large scale sequencing.

    PubMed

    Haas, S; Vingron, M; Poustka, A; Wiemann, S

    1998-06-15

    We have developed PRIDE, a primer design program that automatically designs primers in single contigs or whole sequencing projects to extend the already known sequence and to double strand single-stranded regions. The program is fully integrated into the Staden package (GAP4) and accessible with a graphical user interface. PRIDE uses a fuzzy logic-based system to calculate primer qualities. The computational performance of PRIDE is enhanced by using suffix trees to store the huge amount of data being produced. A test set of 110 sequencing primers and 11 PCR primer pairs has been designed on genomic templates, cDNAs and sequences containing repetitive elements to analyze PRIDE's success rate. The high performance of PRIDE, combined with its minimal requirement of user interaction and its fast algorithm, make this program useful for the large scale design of primers, especially in large sequencing projects.

  17. Large scale preparation of pure phycobiliproteins.

    PubMed

    Padgett, M P; Krogmann, D W

    1987-01-01

    This paper describes simple procedures for the purification of large amounts of phycocyanin and allophycocyanin from the cyanobacterium Microcystis aeruginosa. A homogeneous natural bloom of this organism provided hundreds of kilograms of cells. Large samples of cells were broken by freezing and thawing. Repeated extraction of the broken cells with distilled water released phycocyanin first, then allophycocyanin, and provides supporting evidence for the current models of phycobilisome structure. The very low ionic strength of the aqueous extracts allowed allophycocyanin release in a particulate form so that this protein could be easily concentrated by centrifugation. Other proteins in the extract were enriched and concentrated by large scale membrane filtration. The biliproteins were purified to homogeneity by chromatography on DEAE cellulose. Purity was established by HPLC and by N-terminal amino acid sequence analysis. The proteins were examined for stability at various pHs and exposures to visible light.

  18. Large-Scale Organization of Glycosylation Networks

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Lee, Dong-Yup; Jeong, Hawoong

    2009-03-01

    Glycosylation is a highly complex process to produce a diverse repertoire of cellular glycans that are frequently attached to proteins and lipids. Glycans participate in fundamental biological processes including molecular trafficking and clearance, cell proliferation and apoptosis, developmental biology, immune response, and pathogenesis. N-linked glycans found on proteins are formed by sequential attachments of monosaccharides with the help of a relatively small number of enzymes. Many of these enzymes can accept multiple N-linked glycans as substrates, thus generating a large number of glycan intermediates and their intermingled pathways. Motivated by the quantitative methods developed in complex network research, we investigate the large-scale organization of such N-glycosylation pathways in a mammalian cell. The uncovered results give the experimentally-testable predictions for glycosylation process, and can be applied to the engineering of therapeutic glycoproteins.

  19. Efficient, large scale separation of coal macerals

    SciTech Connect

    Dyrkacz, G.R.; Bloomquist, C.A.A.

    1988-01-01

    The authors believe that the separation of macerals by continuous flow centrifugation offers a simple technique for the large scale separation of macerals. With relatively little cost (/approximately/ $10K), it provides an opportunity for obtaining quite pure maceral fractions. Although they have not completely worked out all the nuances of this separation system, they believe that the problems they have indicated can be minimized to pose only minor inconvenience. It cannot be said that this system completely bypasses the disagreeable tedium or time involved in separating macerals, nor will it by itself overcome the mental inertia required to make maceral separation an accepted necessary fact in fundamental coal science. However, they find their particular brand of continuous flow centrifugation is considerably faster than sink/float separation, can provide a good quality product with even one separation cycle, and permits the handling of more material than a conventional sink/float centrifuge separation.

  20. Large scale cryogenic fluid systems testing

    NASA Technical Reports Server (NTRS)

    1992-01-01

    NASA Lewis Research Center's Cryogenic Fluid Systems Branch (CFSB) within the Space Propulsion Technology Division (SPTD) has the ultimate goal of enabling the long term storage and in-space fueling/resupply operations for spacecraft and reusable vehicles in support of space exploration. Using analytical modeling, ground based testing, and on-orbit experimentation, the CFSB is studying three primary categories of fluid technology: storage, supply, and transfer. The CFSB is also investigating fluid handling, advanced instrumentation, and tank structures and materials. Ground based testing of large-scale systems is done using liquid hydrogen as a test fluid at the Cryogenic Propellant Tank Facility (K-site) at Lewis' Plum Brook Station in Sandusky, Ohio. A general overview of tests involving liquid transfer, thermal control, pressure control, and pressurization is given.

  1. Large-scale optimization of neuron arbors

    NASA Astrophysics Data System (ADS)

    Cherniak, Christopher; Changizi, Mark; Won Kang, Du

    1999-05-01

    At the global as well as local scales, some of the geometry of types of neuron arbors-both dendrites and axons-appears to be self-organizing: Their morphogenesis behaves like flowing water, that is, fluid dynamically; waterflow in branching networks in turn acts like a tree composed of cords under tension, that is, vector mechanically. Branch diameters and angles and junction sites conform significantly to this model. The result is that such neuron tree samples globally minimize their total volume-rather than, for example, surface area or branch length. In addition, the arbors perform well at generating the cheapest topology interconnecting their terminals: their large-scale layouts are among the best of all such possible connecting patterns, approaching 5% of optimum. This model also applies comparably to arterial and river networks.

  2. Grid sensitivity capability for large scale structures

    NASA Technical Reports Server (NTRS)

    Nagendra, Gopal K.; Wallerstein, David V.

    1989-01-01

    The considerations and the resultant approach used to implement design sensitivity capability for grids into a large scale, general purpose finite element system (MSC/NASTRAN) are presented. The design variables are grid perturbations with a rather general linking capability. Moreover, shape and sizing variables may be linked together. The design is general enough to facilitate geometric modeling techniques for generating design variable linking schemes in an easy and straightforward manner. Test cases have been run and validated by comparison with the overall finite difference method. The linking of a design sensitivity capability for shape variables in MSC/NASTRAN with an optimizer would give designers a powerful, automated tool to carry out practical optimization design of real life, complicated structures.

  3. Primer design for large scale sequencing.

    PubMed Central

    Haas, S; Vingron, M; Poustka, A; Wiemann, S

    1998-01-01

    We have developed PRIDE, a primer design program that automatically designs primers in single contigs or whole sequencing projects to extend the already known sequence and to double strand single-stranded regions. The program is fully integrated into the Staden package (GAP4) and accessible with a graphical user interface. PRIDE uses a fuzzy logic-based system to calculate primer qualities. The computational performance of PRIDE is enhanced by using suffix trees to store the huge amount of data being produced. A test set of 110 sequencing primers and 11 PCR primer pairs has been designed on genomic templates, cDNAs and sequences containing repetitive elements to analyze PRIDE's success rate. The high performance of PRIDE, combined with its minimal requirement of user interaction and its fast algorithm, make this program useful for the large scale design of primers, especially in large sequencing projects. PMID:9611248

  4. Modeling the Internet's large-scale topology

    PubMed Central

    Yook, Soon-Hyung; Jeong, Hawoong; Barabási, Albert-László

    2002-01-01

    Network generators that capture the Internet's large-scale topology are crucial for the development of efficient routing protocols and modeling Internet traffic. Our ability to design realistic generators is limited by the incomplete understanding of the fundamental driving forces that affect the Internet's evolution. By combining several independent databases capturing the time evolution, topology, and physical layout of the Internet, we identify the universal mechanisms that shape the Internet's router and autonomous system level topology. We find that the physical layout of nodes form a fractal set, determined by population density patterns around the globe. The placement of links is driven by competition between preferential attachment and linear distance dependence, a marked departure from the currently used exponential laws. The universal parameters that we extract significantly restrict the class of potentially correct Internet models and indicate that the networks created by all available topology generators are fundamentally different from the current Internet. PMID:12368484

  5. Time-sliced perturbation theory for large scale structure I: general formalism

    NASA Astrophysics Data System (ADS)

    Blas, Diego; Garny, Mathias; Ivanov, Mikhail M.; Sibiryakov, Sergey

    2016-07-01

    We present a new analytic approach to describe large scale structure formation in the mildly non-linear regime. The central object of the method is the time-dependent probability distribution function generating correlators of the cosmological observables at a given moment of time. Expanding the distribution function around the Gaussian weight we formulate a perturbative technique to calculate non-linear corrections to cosmological correlators, similar to the diagrammatic expansion in a three-dimensional Euclidean quantum field theory, with time playing the role of an external parameter. For the physically relevant case of cold dark matter in an Einstein-de Sitter universe, the time evolution of the distribution function can be found exactly and is encapsulated by a time-dependent coupling constant controlling the perturbative expansion. We show that all building blocks of the expansion are free from spurious infrared enhanced contributions that plague the standard cosmological perturbation theory. This paves the way towards the systematic resummation of infrared effects in large scale structure formation. We also argue that the approach proposed here provides a natural framework to account for the influence of short-scale dynamics on larger scales along the lines of effective field theory.

  6. Reliability assessment for components of large scale photovoltaic systems

    NASA Astrophysics Data System (ADS)

    Ahadi, Amir; Ghadimi, Noradin; Mirabbasi, Davar

    2014-10-01

    Photovoltaic (PV) systems have significantly shifted from independent power generation systems to a large-scale grid-connected generation systems in recent years. The power output of PV systems is affected by the reliability of various components in the system. This study proposes an analytical approach to evaluate the reliability of large-scale, grid-connected PV systems. The fault tree method with an exponential probability distribution function is used to analyze the components of large-scale PV systems. The system is considered in the various sequential and parallel fault combinations in order to find all realistic ways in which the top or undesired events can occur. Additionally, it can identify areas that the planned maintenance should focus on. By monitoring the critical components of a PV system, it is possible not only to improve the reliability of the system, but also to optimize the maintenance costs. The latter is achieved by informing the operators about the system component's status. This approach can be used to ensure secure operation of the system by its flexibility in monitoring system applications. The implementation demonstrates that the proposed method is effective and efficient and can conveniently incorporate more system maintenance plans and diagnostic strategies.

  7. Learning Short Binary Codes for Large-scale Image Retrieval.

    PubMed

    Liu, Li; Yu, Mengyang; Shao, Ling

    2017-03-01

    Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.

  8. Assessing salivary cortisol in large-scale, epidemiological research.

    PubMed

    Adam, Emma K; Kumari, Meena

    2009-11-01

    Salivary cortisol measures are increasingly being incorporated into large-scale, population-based, or epidemiological research, in which participants are selected to be representative of particular communities or populations of interest, and sample sizes are in the order of hundreds to tens of thousands of participants. These approaches to studying salivary cortisol provide important advantages but pose a set of challenges. The representative nature of sampling, and large samples sizes associated with population-based research offer high generalizability and power, and the ability to examine cortisol functioning in relation to: (a) a wide range of social environments; (b) a diverse array individuals and groups; and (c) a broad set of pre-disease and disease outcomes. The greater importance of high response rates (to maintain generalizability) and higher costs associated with this type of large-scale research, however, requires special adaptations of existing ambulatory cortisol protocols. These include: using the most efficient sample collection protocol possible that still adequately address the specific cortisol-related questions at hand, and ensuring the highest possible response and compliance rates among those individuals invited to participate. Examples of choices made, response rates obtained, and examples of results obtained from existing epidemiological cortisol studies are offered, as are suggestions for the modeling and interpretation of salivary cortisol data obtained in large-scale epidemiological research.

  9. Large-scale biodiversity patterns in freshwater phytoplankton.

    PubMed

    Stomp, Maayke; Huisman, Jef; Mittelbach, Gary G; Litchman, Elena; Klausmeier, Christopher A

    2011-11-01

    Our planet shows striking gradients in the species richness of plants and animals, from high biodiversity in the tropics to low biodiversity in polar and high-mountain regions. Recently, similar patterns have been described for some groups of microorganisms, but the large-scale biogeographical distribution of freshwater phytoplankton diversity is still largely unknown. We examined the species diversity of freshwater phytoplankton sampled from 540 lakes and reservoirs distributed across the continental United States and found strong latitudinal, longitudinal, and altitudinal gradients in phytoplankton biodiversity, demonstrating that microorganisms can show substantial geographic variation in biodiversity. Detailed analysis using structural equation models indicated that these large-scale biodiversity gradients in freshwater phytoplankton diversity were mainly driven by local environmental factors, although there were residual direct effects of latitude, longitude, and altitude as well. Specifically, we found that phytoplankton species richness was an increasing saturating function of lake chlorophyll a concentration, increased with lake surface area and possibly increased with water temperature, resembling effects of productivity, habitat area, and temperature on diversity patterns commonly observed for macroorganisms. In turn, these local environmental factors varied along latitudinal, longitudinal, and altitudinal gradients. These results imply that changes in land use or climate that affect these local environmental factors are likely to have major impacts on large-scale biodiversity patterns of freshwater phytoplankton.

  10. A model of plasma heating by large-scale flow

    NASA Astrophysics Data System (ADS)

    Pongkitiwanichakul, P.; Cattaneo, F.; Boldyrev, S.; Mason, J.; Perez, J. C.

    2015-12-01

    In this work, we study the process of energy dissipation triggered by a slow large-scale motion of a magnetized conducting fluid. Our consideration is motivated by the problem of heating the solar corona, which is believed to be governed by fast reconnection events set off by the slow motion of magnetic field lines anchored in the photospheric plasma. To elucidate the physics governing the disruption of the imposed laminar motion and the energy transfer to small scales, we propose a simplified model where the large-scale motion of magnetic field lines is prescribed not at the footpoints but rather imposed volumetrically. As a result, the problem can be treated numerically with an efficient, highly accurate spectral method, allowing us to use a resolution and statistical ensemble exceeding those of the previous work. We find that, even though the large-scale deformations are slow, they eventually lead to reconnection events that drive a turbulent state at smaller scales. The small-scale turbulence displays many of the universal features of field-guided magnetohydrodynamic turbulence like a well-developed inertial range spectrum. Based on these observations, we construct a phenomenological model that gives the scalings of the amplitude of the fluctuations and the energy-dissipation rate as functions of the input parameters. We find good agreement between the numerical results and the predictions of the model.

  11. Supporting large-scale computational science

    SciTech Connect

    Musick, R

    1998-10-01

    A study has been carried out to determine the feasibility of using commercial database management systems (DBMSs) to support large-scale computational science. Conventional wisdom in the past has been that DBMSs are too slow for such data. Several events over the past few years have muddied the clarity of this mindset: 1. 2. 3. 4. Several commercial DBMS systems have demonstrated storage and ad-hoc quer access to Terabyte data sets. Several large-scale science teams, such as EOSDIS [NAS91], high energy physics [MM97] and human genome [Kin93] have adopted (or make frequent use of) commercial DBMS systems as the central part of their data management scheme. Several major DBMS vendors have introduced their first object-relational products (ORDBMSs), which have the potential to support large, array-oriented data. In some cases, performance is a moot issue. This is true in particular if the performance of legacy applications is not reduced while new, albeit slow, capabilities are added to the system. The basic assessment is still that DBMSs do not scale to large computational data. However, many of the reasons have changed, and there is an expiration date attached to that prognosis. This document expands on this conclusion, identifies the advantages and disadvantages of various commercial approaches, and describes the studies carried out in exploring this area. The document is meant to be brief, technical and informative, rather than a motivational pitch. The conclusions within are very likely to become outdated within the next 5-7 years, as market forces will have a significant impact on the state of the art in scientific data management over the next decade.

  12. Improving Recent Large-Scale Pulsar Surveys

    NASA Astrophysics Data System (ADS)

    Cardoso, Rogerio Fernando; Ransom, S.

    2011-01-01

    Pulsars are unique in that they act as celestial laboratories for precise tests of gravity and other extreme physics (Kramer 2004). There are approximately 2000 known pulsars today, which is less than ten percent of pulsars in the Milky Way according to theoretical models (Lorimer 2004). Out of these 2000 known pulsars, approximately ten percent are known millisecond pulsars, objects used for their period stability for detailed physics tests and searches for gravitational radiation (Lorimer 2008). As the field and instrumentation progress, pulsar astronomers attempt to overcome observational biases and detect new pulsars, consequently discovering new millisecond pulsars. We attempt to improve large scale pulsar surveys by examining three recent pulsar surveys. The first, the Green Bank Telescope 350MHz Drift Scan, a low frequency isotropic survey of the northern sky, has yielded a large number of candidates that were visually inspected and identified, resulting in over 34.000 thousands candidates viewed, dozens of detections of known pulsars, and the discovery of a new low-flux pulsar, PSRJ1911+22. The second, the PALFA survey, is a high frequency survey of the galactic plane with the Arecibo telescope. We created a processing pipeline for the PALFA survey at the National Radio Astronomy Observatory in Charlottesville- VA, in addition to making needed modifications upon advice from the PALFA consortium. The third survey examined is a new GBT 820MHz survey devoted to find new millisecond pulsars by observing the target-rich environment of unidentified sources in the FERMI LAT catalogue. By approaching these three pulsar surveys at different stages, we seek to improve the success rates of large scale surveys, and hence the possibility for ground-breaking work in both basic physics and astrophysics.

  13. Supporting large-scale computational science

    SciTech Connect

    Musick, R., LLNL

    1998-02-19

    Business needs have driven the development of commercial database systems since their inception. As a result, there has been a strong focus on supporting many users, minimizing the potential corruption or loss of data, and maximizing performance metrics like transactions per second, or TPC-C and TPC-D results. It turns out that these optimizations have little to do with the needs of the scientific community, and in particular have little impact on improving the management and use of large-scale high-dimensional data. At the same time, there is an unanswered need in the scientific community for many of the benefits offered by a robust DBMS. For example, tying an ad-hoc query language such as SQL together with a visualization toolkit would be a powerful enhancement to current capabilities. Unfortunately, there has been little emphasis or discussion in the VLDB community on this mismatch over the last decade. The goal of the paper is to identify the specific issues that need to be resolved before large-scale scientific applications can make use of DBMS products. This topic is addressed in the context of an evaluation of commercial DBMS technology applied to the exploration of data generated by the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). The paper describes the data being generated for ASCI as well as current capabilities for interacting with and exploring this data. The attraction of applying standard DBMS technology to this domain is discussed, as well as the technical and business issues that currently make this an infeasible solution.

  14. Introducing Large-Scale Innovation in Schools

    NASA Astrophysics Data System (ADS)

    Sotiriou, Sofoklis; Riviou, Katherina; Cherouvis, Stephanos; Chelioti, Eleni; Bogner, Franz X.

    2016-08-01

    Education reform initiatives tend to promise higher effectiveness in classrooms especially when emphasis is given to e-learning and digital resources. Practical changes in classroom realities or school organization, however, are lacking. A major European initiative entitled Open Discovery Space (ODS) examined the challenge of modernizing school education via a large-scale implementation of an open-scale methodology in using technology-supported innovation. The present paper describes this innovation scheme which involved schools and teachers all over Europe, embedded technology-enhanced learning into wider school environments and provided training to teachers. Our implementation scheme consisted of three phases: (1) stimulating interest, (2) incorporating the innovation into school settings and (3) accelerating the implementation of the innovation. The scheme's impact was monitored for a school year using five indicators: leadership and vision building, ICT in the curriculum, development of ICT culture, professional development support, and school resources and infrastructure. Based on about 400 schools, our study produced four results: (1) The growth in digital maturity was substantial, even for previously high scoring schools. This was even more important for indicators such as vision and leadership" and "professional development." (2) The evolution of networking is presented graphically, showing the gradual growth of connections achieved. (3) These communities became core nodes, involving numerous teachers in sharing educational content and experiences: One out of three registered users (36 %) has shared his/her educational resources in at least one community. (4) Satisfaction scores ranged from 76 % (offer of useful support through teacher academies) to 87 % (good environment to exchange best practices). Initiatives such as ODS add substantial value to schools on a large scale.

  15. The Phoenix series large scale LNG pool fire experiments.

    SciTech Connect

    Simpson, Richard B.; Jensen, Richard Pearson; Demosthenous, Byron; Luketa, Anay Josephine; Ricks, Allen Joseph; Hightower, Marion Michael; Blanchat, Thomas K.; Helmick, Paul H.; Tieszen, Sheldon Robert; Deola, Regina Anne; Mercier, Jeffrey Alan; Suo-Anttila, Jill Marie; Miller, Timothy J.

    2010-12-01

    The increasing demand for natural gas could increase the number and frequency of Liquefied Natural Gas (LNG) tanker deliveries to ports across the United States. Because of the increasing number of shipments and the number of possible new facilities, concerns about the potential safety of the public and property from an accidental, and even more importantly intentional spills, have increased. While improvements have been made over the past decade in assessing hazards from LNG spills, the existing experimental data is much smaller in size and scale than many postulated large accidental and intentional spills. Since the physics and hazards from a fire change with fire size, there are concerns about the adequacy of current hazard prediction techniques for large LNG spills and fires. To address these concerns, Congress funded the Department of Energy (DOE) in 2008 to conduct a series of laboratory and large-scale LNG pool fire experiments at Sandia National Laboratories (Sandia) in Albuquerque, New Mexico. This report presents the test data and results of both sets of fire experiments. A series of five reduced-scale (gas burner) tests (yielding 27 sets of data) were conducted in 2007 and 2008 at Sandia's Thermal Test Complex (TTC) to assess flame height to fire diameter ratios as a function of nondimensional heat release rates for extrapolation to large-scale LNG fires. The large-scale LNG pool fire experiments were conducted in a 120 m diameter pond specially designed and constructed in Sandia's Area III large-scale test complex. Two fire tests of LNG spills of 21 and 81 m in diameter were conducted in 2009 to improve the understanding of flame height, smoke production, and burn rate and therefore the physics and hazards of large LNG spills and fires.

  16. Large-Scale Fusion of Gray Matter and Resting-State Functional MRI Reveals Common and Distinct Biological Markers across the Psychosis Spectrum in the B-SNIP Cohort

    PubMed Central

    Wang, Zheng; Meda, Shashwath A.; Keshavan, Matcheri S.; Tamminga, Carol A.; Sweeney, John A.; Clementz, Brett A.; Schretlen, David J.; Calhoun, Vince D.; Lui, Su; Pearlson, Godfrey D.

    2015-01-01

    To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses [schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar I disorder with psychosis (BP)] and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives, and 242 healthy controls (1). All subjects underwent structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) scanning. Joint-independent component analysis (jICA) was used to fuse sMRI gray matter and rs-fMRI amplitude of low-frequency fluctuations data to identify the relationship between the two modalities. jICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal–striatal–thalamic–cerebellar network and structural abnormalities in the default mode network was found to be common across psychotic diagnoses and correlated with cognitive function, social function, and schizo-bipolar scale scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality). Using a multivariate-fused approach involving two widely used imaging markers, we demonstrate both shared and distinct biological traits across the psychosis spectrum. Furthermore, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes. PMID:26732139

  17. CIPRO 2.5: Ciona intestinalis protein database, a unique integrated repository of large-scale omics data, bioinformatic analyses and curated annotation, with user rating and reviewing functionality.

    PubMed

    Endo, Toshinori; Ueno, Keisuke; Yonezawa, Kouki; Mineta, Katsuhiko; Hotta, Kohji; Satou, Yutaka; Yamada, Lixy; Ogasawara, Michio; Takahashi, Hiroki; Nakajima, Ayako; Nakachi, Mia; Nomura, Mamoru; Yaguchi, Junko; Sasakura, Yasunori; Yamasaki, Chisato; Sera, Miho; Yoshizawa, Akiyasu C; Imanishi, Tadashi; Taniguchi, Hisaaki; Inaba, Kazuo

    2011-01-01

    The Ciona intestinalis protein database (CIPRO) is an integrated protein database for the tunicate species C. intestinalis. The database is unique in two respects: first, because of its phylogenetic position, Ciona is suitable model for understanding vertebrate evolution; and second, the database includes original large-scale transcriptomic and proteomic data. Ciona intestinalis has also been a favorite of developmental biologists. Therefore, large amounts of data exist on its development and morphology, along with a recent genome sequence and gene expression data. The CIPRO database is aimed at collecting those published data as well as providing unique information from unpublished experimental data, such as 3D expression profiling, 2D-PAGE and mass spectrometry-based large-scale analyses at various developmental stages, curated annotation data and various bioinformatic data, to facilitate research in diverse areas, including developmental, comparative and evolutionary biology. For medical and evolutionary research, homologs in humans and major model organisms are intentionally included. The current database is based on a recently developed KH model containing 36,034 unique sequences, but for higher usability it covers 89,683 all known and predicted proteins from all gene models for this species. Of these sequences, more than 10,000 proteins have been manually annotated. Furthermore, to establish a community-supported protein database, these annotations are open to evaluation by users through the CIPRO website. CIPRO 2.5 is freely accessible at http://cipro.ibio.jp/2.5.

  18. Statistical analysis of large-scale neuronal recording data

    PubMed Central

    Reed, Jamie L.; Kaas, Jon H.

    2010-01-01

    Relating stimulus properties to the response properties of individual neurons and neuronal networks is a major goal of sensory research. Many investigators implant electrode arrays in multiple brain areas and record from chronically implanted electrodes over time to answer a variety of questions. Technical challenges related to analyzing large-scale neuronal recording data are not trivial. Several analysis methods traditionally used by neurophysiologists do not account for dependencies in the data that are inherent in multi-electrode recordings. In addition, when neurophysiological data are not best modeled by the normal distribution and when the variables of interest may not be linearly related, extensions of the linear modeling techniques are recommended. A variety of methods exist to analyze correlated data, even when data are not normally distributed and the relationships are nonlinear. Here we review expansions of the Generalized Linear Model designed to address these data properties. Such methods are used in other research fields, and the application to large-scale neuronal recording data will enable investigators to determine the variable properties that convincingly contribute to the variances in the observed neuronal measures. Standard measures of neuron properties such as response magnitudes can be analyzed using these methods, and measures of neuronal network activity such as spike timing correlations can be analyzed as well. We have done just that in recordings from 100-electrode arrays implanted in the primary somatosensory cortex of owl monkeys. Here we illustrate how one example method, Generalized Estimating Equations analysis, is a useful method to apply to large-scale neuronal recordings. PMID:20472395

  19. Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics

    PubMed Central

    Tagliazucchi, Enzo; Chialvo, Dante R.; Siniatchkin, Michael; Amico, Enrico; Brichant, Jean-Francois; Bonhomme, Vincent; Noirhomme, Quentin; Laufs, Helmut; Laureys, Steven

    2016-01-01

    Loss of cortical integration and changes in the dynamics of electrophysiological brain signals characterize the transition from wakefulness towards unconsciousness. In this study, we arrive at a basic model explaining these observations based on the theory of phase transitions in complex systems. We studied the link between spatial and temporal correlations of large-scale brain activity recorded with functional magnetic resonance imaging during wakefulness, propofol-induced sedation and loss of consciousness and during the subsequent recovery. We observed that during unconsciousness activity in frontothalamic regions exhibited a reduction of long-range temporal correlations and a departure of functional connectivity from anatomical constraints. A model of a system exhibiting a phase transition reproduced our findings, as well as the diminished sensitivity of the cortex to external perturbations during unconsciousness. This framework unifies different observations about brain activity during unconsciousness and predicts that the principles we identified are universal and independent from its causes. PMID:26819336

  20. Pfaffian Correlation Functions of Planar Dimer Covers

    NASA Astrophysics Data System (ADS)

    Aizenman, Michael; Valcázar, Manuel Laínz; Warzel, Simone

    2017-01-01

    The Pfaffian structure of the boundary monomer correlation functions in the dimer-covering planar graph models is rederived through a combinatorial/topological argument. These functions are then extended into a larger family of order-disorder correlation functions which are shown to exhibit Pfaffian structure throughout the bulk. Key tools involve combinatorial switching symmetries which are identified through the loop-gas representation of the double dimer model, and topological implications of planarity.

  1. On the velocity in the Effective Field Theory of Large Scale Structures

    SciTech Connect

    Mercolli, Lorenzo; Pajer, Enrico E-mail: enrico.pajer@gmail.com

    2014-03-01

    We compute the renormalized two-point functions of density, divergence and vorticity of the velocity in the Effective Field Theory of Large Scale Structures. Because of momentum and mass conservation, the corrections from short scales to the large-scale power spectra of density, divergence and vorticity must start at order k{sup 4}. For the vorticity this constitutes one of the two leading terms. Exact (approximated) self-similarity of an Einstein-de Sitter (ΛCDM) background fixes the time dependence so that the vorticity power spectrum at leading order is determined by the symmetries of the problem and the power spectrum around the non-linear scale. We show that to cancel all divergences in the velocity correlators one needs new counterterms. These fix the definition of velocity and do not represent new properties of the system. For an Einstein-de Sitter universe, we show that all three renormalized cross- and auto-correlation functions have the same structure but different numerical coefficients, which we compute. We elucidate the differences between using momentum and velocity.

  2. Multi-thread parallel algorithm for reconstructing 3D large-scale porous structures

    NASA Astrophysics Data System (ADS)

    Ju, Yang; Huang, Yaohui; Zheng, Jiangtao; Qian, Xu; Xie, Heping; Zhao, Xi

    2017-04-01

    Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure.

  3. Large-scale wind turbine structures

    NASA Technical Reports Server (NTRS)

    Spera, David A.

    1988-01-01

    The purpose of this presentation is to show how structural technology was applied in the design of modern wind turbines, which were recently brought to an advanced stage of development as sources of renewable power. Wind turbine structures present many difficult problems because they are relatively slender and flexible; subject to vibration and aeroelastic instabilities; acted upon by loads which are often nondeterministic; operated continuously with little maintenance in all weather; and dominated by life-cycle cost considerations. Progress in horizontal-axis wind turbines (HAWT) development was paced by progress in the understanding of structural loads, modeling of structural dynamic response, and designing of innovative structural response. During the past 15 years a series of large HAWTs was developed. This has culminated in the recent completion of the world's largest operating wind turbine, the 3.2 MW Mod-5B power plane installed on the island of Oahu, Hawaii. Some of the applications of structures technology to wind turbine will be illustrated by referring to the Mod-5B design. First, a video overview will be presented to provide familiarization with the Mod-5B project and the important components of the wind turbine system. Next, the structural requirements for large-scale wind turbines will be discussed, emphasizing the difficult fatigue-life requirements. Finally, the procedures used to design the structure will be presented, including the use of the fracture mechanics approach for determining allowable fatigue stresses.

  4. Large-scale tides in general relativity

    NASA Astrophysics Data System (ADS)

    Ip, Hiu Yan; Schmidt, Fabian

    2017-02-01

    Density perturbations in cosmology, i.e. spherically symmetric adiabatic perturbations of a Friedmann-Lemaȋtre-Robertson-Walker (FLRW) spacetime, are locally exactly equivalent to a different FLRW solution, as long as their wavelength is much larger than the sound horizon of all fluid components. This fact is known as the "separate universe" paradigm. However, no such relation is known for anisotropic adiabatic perturbations, which correspond to an FLRW spacetime with large-scale tidal fields. Here, we provide a closed, fully relativistic set of evolutionary equations for the nonlinear evolution of such modes, based on the conformal Fermi (CFC) frame. We show explicitly that the tidal effects are encoded by the Weyl tensor, and are hence entirely different from an anisotropic Bianchi I spacetime, where the anisotropy is sourced by the Ricci tensor. In order to close the system, certain higher derivative terms have to be dropped. We show that this approximation is equivalent to the local tidal approximation of Hui and Bertschinger [1]. We also show that this very simple set of equations matches the exact evolution of the density field at second order, but fails at third and higher order. This provides a useful, easy-to-use framework for computing the fully relativistic growth of structure at second order.

  5. Large-scale autostereoscopic outdoor display

    NASA Astrophysics Data System (ADS)

    Reitterer, Jörg; Fidler, Franz; Saint Julien-Wallsee, Ferdinand; Schmid, Gerhard; Gartner, Wolfgang; Leeb, Walter; Schmid, Ulrich

    2013-03-01

    State-of-the-art autostereoscopic displays are often limited in size, effective brightness, number of 3D viewing zones, and maximum 3D viewing distances, all of which are mandatory requirements for large-scale outdoor displays. Conventional autostereoscopic indoor concepts like lenticular lenses or parallax barriers cannot simply be adapted for these screens due to the inherent loss of effective resolution and brightness, which would reduce both image quality and sunlight readability. We have developed a modular autostereoscopic multi-view laser display concept with sunlight readable effective brightness, theoretically up to several thousand 3D viewing zones, and maximum 3D viewing distances of up to 60 meters. For proof-of-concept purposes a prototype display with two pixels was realized. Due to various manufacturing tolerances each individual pixel has slightly different optical properties, and hence the 3D image quality of the display has to be calculated stochastically. In this paper we present the corresponding stochastic model, we evaluate the simulation and measurement results of the prototype display, and we calculate the achievable autostereoscopic image quality to be expected for our concept.

  6. Food appropriation through large scale land acquisitions

    NASA Astrophysics Data System (ADS)

    Rulli, Maria Cristina; D'Odorico, Paolo

    2014-05-01

    The increasing demand for agricultural products and the uncertainty of international food markets has recently drawn the attention of governments and agribusiness firms toward investments in productive agricultural land, mostly in the developing world. The targeted countries are typically located in regions that have remained only marginally utilized because of lack of modern technology. It is expected that in the long run large scale land acquisitions (LSLAs) for commercial farming will bring the technology required to close the existing crops yield gaps. While the extent of the acquired land and the associated appropriation of freshwater resources have been investigated in detail, the amount of food this land can produce and the number of people it could feed still need to be quantified. Here we use a unique dataset of land deals to provide a global quantitative assessment of the rates of crop and food appropriation potentially associated with LSLAs. We show how up to 300-550 million people could be fed by crops grown in the acquired land, should these investments in agriculture improve crop production and close the yield gap. In contrast, about 190-370 million people could be supported by this land without closing of the yield gap. These numbers raise some concern because the food produced in the acquired land is typically exported to other regions, while the target countries exhibit high levels of malnourishment. Conversely, if used for domestic consumption, the crops harvested in the acquired land could ensure food security to the local populations.

  7. Large scale mechanical metamaterials as seismic shields

    NASA Astrophysics Data System (ADS)

    Miniaci, Marco; Krushynska, Anastasiia; Bosia, Federico; Pugno, Nicola M.

    2016-08-01

    Earthquakes represent one of the most catastrophic natural events affecting mankind. At present, a universally accepted risk mitigation strategy for seismic events remains to be proposed. Most approaches are based on vibration isolation of structures rather than on the remote shielding of incoming waves. In this work, we propose a novel approach to the problem and discuss the feasibility of a passive isolation strategy for seismic waves based on large-scale mechanical metamaterials, including for the first time numerical analysis of both surface and guided waves, soil dissipation effects, and adopting a full 3D simulations. The study focuses on realistic structures that can be effective in frequency ranges of interest for seismic waves, and optimal design criteria are provided, exploring different metamaterial configurations, combining phononic crystals and locally resonant structures and different ranges of mechanical properties. Dispersion analysis and full-scale 3D transient wave transmission simulations are carried out on finite size systems to assess the seismic wave amplitude attenuation in realistic conditions. Results reveal that both surface and bulk seismic waves can be considerably attenuated, making this strategy viable for the protection of civil structures against seismic risk. The proposed remote shielding approach could open up new perspectives in the field of seismology and in related areas of low-frequency vibration damping or blast protection.

  8. Large-scale carbon fiber tests

    NASA Technical Reports Server (NTRS)

    Pride, R. A.

    1980-01-01

    A realistic release of carbon fibers was established by burning a minimum of 45 kg of carbon fiber composite aircraft structural components in each of five large scale, outdoor aviation jet fuel fire tests. This release was quantified by several independent assessments with various instruments developed specifically for these tests. The most likely values for the mass of single carbon fibers released ranged from 0.2 percent of the initial mass of carbon fiber for the source tests (zero wind velocity) to a maximum of 0.6 percent of the initial carbon fiber mass for dissemination tests (5 to 6 m/s wind velocity). Mean fiber lengths for fibers greater than 1 mm in length ranged from 2.5 to 3.5 mm. Mean diameters ranged from 3.6 to 5.3 micrometers which was indicative of significant oxidation. Footprints of downwind dissemination of the fire released fibers were measured to 19.1 km from the fire.

  9. Large-Scale Measurement of Absolute Protein Glycosylation Stoichiometry.

    PubMed

    Sun, Shisheng; Zhang, Hui

    2015-07-07

    Protein glycosylation is one of the most important protein modifications. Glycosylation site occupancy alteration has been implicated in human diseases and cancers. However, current glycoproteomic methods focus on the identification and quantification of glycosylated peptides and glycosylation sites but not glycosylation occupancy or glycoform stoichiometry. Here we describe a method for large-scale determination of the absolute glycosylation stoichiometry using three independent relative ratios. Using this method, we determined 117 absolute N-glycosylation occupancies in OVCAR-3 cells. Finally, we investigated the possible functions and the determinants for partial glycosylation.

  10. Clusters as cornerstones of large-scale structure.

    NASA Astrophysics Data System (ADS)

    Gottlöber, S.; Retzlaff, J.; Turchaninov, V.

    1997-04-01

    Galaxy clusters are one of the best tracers of large-scale structure in the Universe on scales well above 100 Mpc. The authors investigate here the clustering properties of a redshift sample of Abell/ACO clusters and compare the observational sample with mock samples constructed from N-body simulations on the basis of four different cosmological models. The authors discuss the power spectrum, the Minkowski functionals and the void statistics of these samples and conclude, that the SCDM and TCDM models are ruled out whereas the ACDM and BSI models are in agreement with the observational data.

  11. Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks

    PubMed Central

    Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

    2015-01-01

    Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators’ careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system

  12. Chaotic dynamics of large-scale structures in a turbulent wake

    NASA Astrophysics Data System (ADS)

    Varon, Eliott; Eulalie, Yoann; Edwige, Stephie; Gilotte, Philippe; Aider, Jean-Luc

    2017-03-01

    The dynamics of a three-dimensional (3D) bimodal turbulent wake downstream of a square-back Ahmed body are experimentally studied in a wind tunnel through high-frequency wall-pressure probes mapping the rear of the model and a horizontal two-dimensional (2D) velocity field. The barycenters of the pressure distribution over the rear part of the model and the intensity recirculation are found highly correlated. Both described the most energetic large-scale structures dynamics, confirming the relation between the large-scale recirculation bubble and its wall-pressure footprint. Focusing on the pressure, its barycenter trajectory has a stochastic behavior but its low-frequency dynamics exhibit the same characteristics as a weak strange chaotic attractor system, with two well-defined attractors. The low-frequency dynamics associated to the large-scale structures are then analyzed. The largest Lyapunov exponent is first estimated, leading to a low positive value characteristic of strange attractors and weak chaotic systems. Afterwards, analyzing the autocorrelation function of the timeseries, we compute the correlation dimension, larger than two. The signal is finally transformed and analyzed as a telegraph signal, showing that its dynamics correspond to a quasirandom telegraph signal. This is the first demonstration that the low-frequency dynamics of a turbulent 3D wake are not a purely stochastic process but rather a weak chaotic process exhibiting strange attractors. From the flow control point of view, it also opens the path to more simple closed-loop flow-control strategies aiming at the stabilization of the wake and the control of the dynamics of the wake barycenter.

  13. Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

    PubMed

    Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

    2015-01-01

    Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system

  14. The Large-scale Structure of the Universe: Probes of Cosmology and Structure Formation

    NASA Astrophysics Data System (ADS)

    Noh, Yookyung

    The usefulness of large-scale structure as a probe of cosmology and structure formation is increasing as large deep surveys in multi-wavelength bands are becoming possible. The observational analysis of large-scale structure guided by large volume numerical simulations are beginning to offer us complementary information and crosschecks of cosmological parameters estimated from the anisotropies in Cosmic Microwave Background (CMB) radiation. Understanding structure formation and evolution and even galaxy formation history is also being aided by observations of different redshift snapshots of the Universe, using various tracers of large-scale structure. This dissertation work covers aspects of large-scale structure from the baryon acoustic oscillation scale, to that of large scale filaments and galaxy clusters. First, I discuss a large- scale structure use for high precision cosmology. I investigate the reconstruction of Baryon Acoustic Oscillation (BAO) peak within the context of Lagrangian perturbation theory, testing its validity in a large suite of cosmological volume N-body simulations. Then I consider galaxy clusters and the large scale filaments surrounding them in a high resolution N-body simulation. I investigate the geometrical properties of galaxy cluster neighborhoods, focusing on the filaments connected to clusters. Using mock observations of galaxy clusters, I explore the correlations of scatter in galaxy cluster mass estimates from multi-wavelength observations and different measurement techniques. I also examine the sources of the correlated scatter by considering the intrinsic and environmental properties of clusters.

  15. Sensitivity technologies for large scale simulation.

    SciTech Connect

    Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias; Wilcox, Lucas C.; Hill, Judith C.; Ghattas, Omar; Berggren, Martin Olof; Akcelik, Volkan; Ober, Curtis Curry; van Bloemen Waanders, Bart Gustaaf; Keiter, Eric Richard

    2005-01-01

    Sensitivity analysis is critically important to numerous analysis algorithms, including large scale optimization, uncertainty quantification,reduced order modeling, and error estimation. Our research focused on developing tools, algorithms and standard interfaces to facilitate the implementation of sensitivity type analysis into existing code and equally important, the work was focused on ways to increase the visibility of sensitivity analysis. We attempt to accomplish the first objective through the development of hybrid automatic differentiation tools, standard linear algebra interfaces for numerical algorithms, time domain decomposition algorithms and two level Newton methods. We attempt to accomplish the second goal by presenting the results of several case studies in which direct sensitivities and adjoint methods have been effectively applied, in addition to an investigation of h-p adaptivity using adjoint based a posteriori error estimation. A mathematical overview is provided of direct sensitivities and adjoint methods for both steady state and transient simulations. Two case studies are presented to demonstrate the utility of these methods. A direct sensitivity method is implemented to solve a source inversion problem for steady state internal flows subject to convection diffusion. Real time performance is achieved using novel decomposition into offline and online calculations. Adjoint methods are used to reconstruct initial conditions of a contamination event in an external flow. We demonstrate an adjoint based transient solution. In addition, we investigated time domain decomposition algorithms in an attempt to improve the efficiency of transient simulations. Because derivative calculations are at the root of sensitivity calculations, we have developed hybrid automatic differentiation methods and implemented this approach for shape optimization for gas dynamics using the Euler equations. The hybrid automatic differentiation method was applied to a first

  16. Brief Mental Training Reorganizes Large-Scale Brain Networks

    PubMed Central

    Tang, Yi-Yuan; Tang, Yan; Tang, Rongxiang; Lewis-Peacock, Jarrod A.

    2017-01-01

    Emerging evidences have shown that one form of mental training—mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training—integrative body–mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing. PMID:28293180

  17. Brief Mental Training Reorganizes Large-Scale Brain Networks.

    PubMed

    Tang, Yi-Yuan; Tang, Yan; Tang, Rongxiang; Lewis-Peacock, Jarrod A

    2017-01-01

    Emerging evidences have shown that one form of mental training-mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training-integrative body-mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing.

  18. On the measurability of quantum correlation functions

    NASA Astrophysics Data System (ADS)

    de Lima Bernardo, Bertúlio; Azevedo, Sérgio; Rosas, Alexandre

    2015-05-01

    The concept of correlation function is widely used in classical statistical mechanics to characterize how two or more variables depend on each other. In quantum mechanics, on the other hand, there are observables that cannot be measured at the same time; the so-called incompatible observables. This prospect imposes a limitation on the definition of a quantum analog for the correlation function in terms of a sequence of measurements. Here, based on the notion of sequential weak measurements, we circumvent this limitation by introducing a framework to measure general quantum correlation functions, in principle, independently of the state of the system and the operators involved. To illustrate, we propose an experimental configuration to obtain explicitly the quantum correlation function between two Pauli operators, in which the input state is an arbitrary mixed qubit state encoded on the polarization of photons.

  19. On the measurability of quantum correlation functions

    SciTech Connect

    Lima Bernardo, Bertúlio de Azevedo, Sérgio; Rosas, Alexandre

    2015-05-15

    The concept of correlation function is widely used in classical statistical mechanics to characterize how two or more variables depend on each other. In quantum mechanics, on the other hand, there are observables that cannot be measured at the same time; the so-called incompatible observables. This prospect imposes a limitation on the definition of a quantum analog for the correlation function in terms of a sequence of measurements. Here, based on the notion of sequential weak measurements, we circumvent this limitation by introducing a framework to measure general quantum correlation functions, in principle, independently of the state of the system and the operators involved. To illustrate, we propose an experimental configuration to obtain explicitly the quantum correlation function between two Pauli operators, in which the input state is an arbitrary mixed qubit state encoded on the polarization of photons.

  20. Large Scale Flame Spread Environmental Characterization Testing

    NASA Technical Reports Server (NTRS)

    Clayman, Lauren K.; Olson, Sandra L.; Gokoghi, Suleyman A.; Brooker, John E.; Ferkul, Paul V.; Kacher, Henry F.

    2013-01-01

    Under the Advanced Exploration Systems (AES) Spacecraft Fire Safety Demonstration Project (SFSDP), as a risk mitigation activity in support of the development of a large-scale fire demonstration experiment in microgravity, flame-spread tests were conducted in normal gravity on thin, cellulose-based fuels in a sealed chamber. The primary objective of the tests was to measure pressure rise in a chamber as sample material, burning direction (upward/downward), total heat release, heat release rate, and heat loss mechanisms were varied between tests. A Design of Experiments (DOE) method was imposed to produce an array of tests from a fixed set of constraints and a coupled response model was developed. Supplementary tests were run without experimental design to additionally vary select parameters such as initial chamber pressure. The starting chamber pressure for each test was set below atmospheric to prevent chamber overpressure. Bottom ignition, or upward propagating burns, produced rapid acceleratory turbulent flame spread. Pressure rise in the chamber increases as the amount of fuel burned increases mainly because of the larger amount of heat generation and, to a much smaller extent, due to the increase in gaseous number of moles. Top ignition, or downward propagating burns, produced a steady flame spread with a very small flat flame across the burning edge. Steady-state pressure is achieved during downward flame spread as the pressure rises and plateaus. This indicates that the heat generation by the flame matches the heat loss to surroundings during the longer, slower downward burns. One heat loss mechanism included mounting a heat exchanger directly above the burning sample in the path of the plume to act as a heat sink and more efficiently dissipate the heat due to the combustion event. This proved an effective means for chamber overpressure mitigation for those tests producing the most total heat release and thusly was determined to be a feasible mitigation

  1. Spatial Correlation Function of the Chandra Selected Active Galactic Nuclei

    NASA Technical Reports Server (NTRS)

    Yang, Y.; Mushotzky, R. F.; Barger, A. J.; Cowie, L. L.

    2006-01-01

    two groups. We have also found that the correlation between X-ray luminosity and clustering amplitude is weak, which, however, is fully consistent with the expectation using the simplest relations between X-ray luminosity, black hole mass, and dark halo mass. We study the evolution of the AGN clustering by dividing the samples into 4 redshift bins over 0.1 Mpc< z <3.0 Mpc. We find a very mild evolution in the clustering amplitude, which show the same evolution trend found in optically selected quasars in the 2dF survey. We estimate the evolution of the bias, and find that the bias increases rapidly with redshift (b(z = 0.45) = 0.95 +/- 0.15 and b(z = 2.07) = 3.03 +/- 0.83): The typical mass of the dark matter halo derived from the bias estimates show little change with redshift. The average halo mass is found to be log (M(sub halo)/M(sun))approximates 12.1. Subject headings: cosmology: observations - large-scale structure of the universe - x-rays: diffuse background - galaxies: nuclei

  2. The correlation function for density perturbations in an expanding universe. III The three-point and predictions of the four-point and higher order correlation functions

    NASA Technical Reports Server (NTRS)

    Mcclelland, J.; Silk, J.

    1978-01-01

    Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.

  3. Synchronization of coupled large-scale Boolean networks

    NASA Astrophysics Data System (ADS)

    Li, Fangfei

    2014-03-01

    This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

  4. Synchronization of coupled large-scale Boolean networks

    SciTech Connect

    Li, Fangfei

    2014-03-15

    This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

  5. Large-Scale Structures of Planetary Systems

    NASA Astrophysics Data System (ADS)

    Murray-Clay, Ruth; Rogers, Leslie A.

    2015-12-01

    A class of solar system analogs has yet to be identified among the large crop of planetary systems now observed. However, since most observed worlds are more easily detectable than direct analogs of the Sun's planets, the frequency of systems with structures similar to our own remains unknown. Identifying the range of possible planetary system architectures is complicated by the large number of physical processes that affect the formation and dynamical evolution of planets. I will present two ways of organizing planetary system structures. First, I will suggest that relatively few physical parameters are likely to differentiate the qualitative architectures of different systems. Solid mass in a protoplanetary disk is perhaps the most obvious possible controlling parameter, and I will give predictions for correlations between planetary system properties that we would expect to be present if this is the case. In particular, I will suggest that the solar system's structure is representative of low-metallicity systems that nevertheless host giant planets. Second, the disk structures produced as young stars are fed by their host clouds may play a crucial role. Using the observed distribution of RV giant planets as a function of stellar mass, I will demonstrate that invoking ice lines to determine where gas giants can form requires fine tuning. I will suggest that instead, disk structures built during early accretion have lasting impacts on giant planet distributions, and disk clean-up differentially affects the orbital distributions of giant and lower-mass planets. These two organizational hypotheses have different implications for the solar system's context, and I will suggest observational tests that may allow them to be validated or falsified.

  6. Very large-scale motions in a turbulent pipe flow

    NASA Astrophysics Data System (ADS)

    Lee, Jae Hwa; Jang, Seong Jae; Sung, Hyung Jin

    2011-11-01

    Direct numerical simulation of a turbulent pipe flow with ReD=35000 was performed to investigate the spatially coherent structures associated with very large-scale motions. The corresponding friction Reynolds number, based on pipe radius R, is R+=934, and the computational domain length is 30 R. The computed mean flow statistics agree well with previous DNS data at ReD=44000 and 24000. Inspection of the instantaneous fields and two-point correlation of the streamwise velocity fluctuations showed that the very long meandering motions exceeding 25R exist in logarithmic and wake regions, and the streamwise length scale is almost linearly increased up to y/R ~0.3, while the structures in the turbulent boundary layer only reach up to the edge of the log-layer. Time-resolved instantaneous fields revealed that the hairpin packet-like structures grow with continuous stretching along the streamwise direction and create the very large-scale structures with meandering in the spanwise direction, consistent with the previous conceptual model of Kim & Adrian (1999). This work was supported by the Creative Research Initiatives of NRF/MEST of Korea (No. 2011-0000423).

  7. The Impact of Large Scale Environments on Cluster Entropy Profiles

    NASA Astrophysics Data System (ADS)

    Trierweiler, Isabella; Su, Yuanyuan

    2017-01-01

    We perform a systematic analysis of 21 clusters imaged by the Suzaku satellite to determine the relation between the richness of cluster environments and entropy at large radii. Entropy profiles for clusters are expected to follow a power-law, but Suzaku observations show that the entropy profiles of many clusters are significantly flattened beyond 0.3 Rvir. While the entropy at the outskirts of clusters is thought to be highly dependent on the large scale cluster environment, the exact nature of the environment/entropy relation is unclear. Using the Sloan Digital Sky Survey and 6dF Galaxy Survey, we study the 20 Mpc large scale environment for all clusters in our sample. We find no strong relation between the entropy deviations at the virial radius and the total luminosity of the cluster surroundings, indicating that accretion and mergers have a more complex and indirect influence on the properties of the gas at large radii. We see a possible anti-correlation between virial temperature and richness of the cluster environment and find that density excess appears to play a larger role in the entropy flattening than temperature, suggesting that clumps of gas can lower entropy.

  8. Systematic renormalization of the effective theory of Large Scale Structure

    SciTech Connect

    Abolhasani, Ali Akbar; Mirbabayi, Mehrdad; Pajer, Enrico

    2016-05-31

    A perturbative description of Large Scale Structure is a cornerstone of our understanding of the observed distribution of matter in the universe. Renormalization is an essential and defining step to make this description physical and predictive. Here we introduce a systematic renormalization procedure, which neatly associates counterterms to the UV-sensitive diagrams order by order, as it is commonly done in quantum field theory. As a concrete example, we renormalize the one-loop power spectrum and bispectrum of both density and velocity. In addition, we present a series of results that are valid to all orders in perturbation theory. First, we show that while systematic renormalization requires temporally non-local counterterms, in practice one can use an equivalent basis made of local operators. We give an explicit prescription to generate all counterterms allowed by the symmetries. Second, we present a formal proof of the well-known general argument that the contribution of short distance perturbations to large scale density contrast δ and momentum density π(k) scale as k{sup 2} and k, respectively. Third, we demonstrate that the common practice of introducing counterterms only in the Euler equation when one is interested in correlators of δ is indeed valid to all orders.

  9. Generalized hydrodynamic correlations and fractional memory functions

    NASA Astrophysics Data System (ADS)

    Rodríguez, Rosalio F.; Fujioka, Jorge

    2015-12-01

    A fractional generalized hydrodynamic (GH) model of the longitudinal velocity fluctuations correlation, and its associated memory function, for a complex fluid is analyzed. The adiabatic elimination of fast variables introduces memory effects in the transport equations, and the dynamic of the fluctuations is described by a generalized Langevin equation with long-range noise correlations. These features motivate the introduction of Caputo time fractional derivatives and allows us to calculate analytic expressions for the fractional longitudinal velocity correlation function and its associated memory function. Our analysis eliminates a spurious constant term in the non-fractional memory function found in the non-fractional description. It also produces a significantly slower power-law decay of the memory function in the GH regime that reduces to the well-known exponential decay in the non-fractional Navier-Stokes limit.

  10. Multitime correlation functions in nonclassical stochastic processes

    NASA Astrophysics Data System (ADS)

    Krumm, F.; Sperling, J.; Vogel, W.

    2016-06-01

    A general method is introduced for verifying multitime quantum correlations through the characteristic function of the time-dependent P functional that generalizes the Glauber-Sudarshan P function. Quantum correlation criteria are derived which identify quantum effects for an arbitrary number of points in time. The Magnus expansion is used to visualize the impact of the required time ordering, which becomes crucial in situations when the interaction problem is explicitly time dependent. We show that the latter affects the multi-time-characteristic function and, therefore, the temporal evolution of the nonclassicality. As an example, we apply our technique to an optical parametric process with a frequency mismatch. The resulting two-time-characteristic function yields full insight into the two-time quantum correlation properties of such a system.

  11. Radar backscattering from a sea having an anisotropic large-scale surface, part 2

    NASA Technical Reports Server (NTRS)

    Wentz, F. J.

    1977-01-01

    A two scale scattering model was derived that combines specular reflections from sea waves and Bragg scattering in a manner consistent with energy conservation. The effect of the tilting of the small scale roughness by the large scale roughness was included, which accounted for the reduction of reflected power. The special case of backscattering for which the transmitted polarization equaled the received polarization was considered. An anisotropic large scale surface was used to specify the probability density function of the large scale surface normal. In order to isolate the azimuthal variation of the normalized radar cross section produced by the anisotropic probability density function, an isotropical small scale spectrum was assumed.

  12. Consistency relations for large-scale structures with primordial non-Gaussianities

    NASA Astrophysics Data System (ADS)

    Valageas, Patrick; Taruya, Atsushi; Nishimichi, Takahiro

    2017-01-01

    We investigate how the consistency relations of large-scale structures are modified when the initial density field is not Gaussian. We consider both scenarios where the primordial density field can be written as a nonlinear functional of a Gaussian field and more general scenarios where the probability distribution of the primordial density field can be expanded around the Gaussian distribution, up to all orders over δL 0. Working at linear order over the non-Gaussianity parameters fNL(n ) or Sn, we find that the consistency relations for the matter density fields are modified as they include additional contributions that involve all-order mixed linear-nonlinear correlations ⟨∏δL∏δ ⟩. We derive the conditions needed to recover the simple Gaussian form of the consistency relations. This corresponds to scenarios that become Gaussian in the squeezed limit. Our results also apply to biased tracers and velocity or momentum cross-correlations.

  13. Emergence of large-scale vorticity during diffusion in a random potential under an alternating bias.

    PubMed

    Makeev, Maxim A; Derényi, Imre; Barabási, Albert-László

    2005-02-01

    Conventional wisdom indicates that the presence of an alternating driving force will not change the long-term behavior of a Brownian particle moving in a random potential. Although this is true in one dimension, here we offer direct evidence that the inevitable local symmetry breaking present in a two-dimensional random potential leads to the emergence of a local ratchet effect that generates large-scale vorticity patterns consisting of steady-state net diffusive currents. For small fields the spatial correlation function of the current follows a logarithmic distance dependence, while for large external fields both the vorticity and the correlations gradually disappear. We uncover the scaling laws characterizing this unique pattern formation process, and discuss their potential relevance to real systems.

  14. Large-Scale Spacecraft Fire Safety Tests

    NASA Technical Reports Server (NTRS)

    Urban, David; Ruff, Gary A.; Ferkul, Paul V.; Olson, Sandra; Fernandez-Pello, A. Carlos; T'ien, James S.; Torero, Jose L.; Cowlard, Adam J.; Rouvreau, Sebastien; Minster, Olivier; Toth, Balazs; Legros, Guillaume; Eigenbrod, Christian; Smirnov, Nickolay; Fujita, Osamu; Jomaas, Grunde

    2014-01-01

    An international collaborative program is underway to address open issues in spacecraft fire safety. Because of limited access to long-term low-gravity conditions and the small volume generally allotted for these experiments, there have been relatively few experiments that directly study spacecraft fire safety under low-gravity conditions. Furthermore, none of these experiments have studied sample sizes and environment conditions typical of those expected in a spacecraft fire. The major constraint has been the size of the sample, with prior experiments limited to samples of the order of 10 cm in length and width or smaller. This lack of experimental data forces spacecraft designers to base their designs and safety precautions on 1-g understanding of flame spread, fire detection, and suppression. However, low-gravity combustion research has demonstrated substantial differences in flame behavior in low-gravity. This, combined with the differences caused by the confined spacecraft environment, necessitates practical scale spacecraft fire safety research to mitigate risks for future space missions. To address this issue, a large-scale spacecraft fire experiment is under development by NASA and an international team of investigators. This poster presents the objectives, status, and concept of this collaborative international project (Saffire). The project plan is to conduct fire safety experiments on three sequential flights of an unmanned ISS re-supply spacecraft (the Orbital Cygnus vehicle) after they have completed their delivery of cargo to the ISS and have begun their return journeys to earth. On two flights (Saffire-1 and Saffire-3), the experiment will consist of a flame spread test involving a meter-scale sample ignited in the pressurized volume of the spacecraft and allowed to burn to completion while measurements are made. On one of the flights (Saffire-2), 9 smaller (5 x 30 cm) samples will be tested to evaluate NASAs material flammability screening tests

  15. From correlation functions to event shapes

    NASA Astrophysics Data System (ADS)

    Belitsky, A. V.; Hohenegger, S.; Korchemsky, G. P.; Sokatchev, E.; Zhiboedov, A.

    2014-07-01

    We present a new approach to computing event shape distributions or, more precisely, charge flow correlations in a generic conformal field theory (CFT). These infrared finite observables are familiar from collider physics studies and describe the angular distribution of global charges in outgoing radiation created from the vacuum by some source. The charge flow correlations can be expressed in terms of Wightman correlation functions in a certain limit. We explain how to compute these quantities starting from their Euclidean analogues by means of a nontrivial analytic continuation which, in the framework of CFT, can be performed elegantly in Mellin space. The relation between the charge flow correlations and Euclidean correlation functions can be reformulated directly in configuration space, bypassing the Mellin representation, as a certain Lorentzian double discontinuity of the correlation function integrated along the cuts. We illustrate the general formalism in N=4 SYM, making use of the well-known results on the four-point correlation function of half-BPS scalar operators. We compute the double scalar flow correlation in N=4 SYM, at weak and strong coupling and show that it agrees with known results obtained by different techniques. One of the remarkable features of the N=4 theory is that the scalar and energy flow correlations are proportional to each other. Imposing natural physical conditions on the energy flow correlations (finiteness, positivity and regularity), we formulate additional constraints on the four-point correlation functions in N=4 SYM that should be valid at any coupling and away from the planar limit. presence of intrinsic infrared (IR) divergences; integration over the phase space of the final state and subsequent intricate IR cancellations; necessity for summation over all final states. Let us comment on each of these points. They are very well understood in the context of perturbation theory no IR divergences are present in the correlation

  16. Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy.

    PubMed

    de Campos, Brunno Machado; Coan, Ana Carolina; Lin Yasuda, Clarissa; Casseb, Raphael Fernandes; Cendes, Fernando

    2016-09-01

    Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  17. Pair correlation function integrals: Computation and use

    NASA Astrophysics Data System (ADS)

    Wedberg, Rasmus; O'Connell, John P.; Peters, Günther H.; Abildskov, Jens

    2011-08-01

    We describe a method for extending radial distribution functions obtained from molecular simulations of pure and mixed molecular fluids to arbitrary distances. The method allows total correlation function integrals to be reliably calculated from simulations of relatively small systems. The long-distance behavior of radial distribution functions is determined by requiring that the corresponding direct correlation functions follow certain approximations at long distances. We have briefly described the method and tested its performance in previous communications [R. Wedberg, J. P. O'Connell, G. H. Peters, and J. Abildskov, Mol. Simul. 36, 1243 (2010);, 10.1080/08927020903536366 Fluid Phase Equilib. 302, 32 (2011)], 10.1016/j.fluid.2010.10.004, but describe here its theoretical basis more thoroughly and derive long-distance approximations for the direct correlation functions. We describe the numerical implementation of the method in detail, and report numerical tests complementing previous results. Pure molecular fluids are here studied in the isothermal-isobaric ensemble with isothermal compressibilities evaluated from the total correlation function integrals and compared with values derived from volume fluctuations. For systems where the radial distribution function has structure beyond the sampling limit imposed by the system size, the integration is more reliable, and usually more accurate, than simple integral truncation.

  18. Population generation for large-scale simulation

    NASA Astrophysics Data System (ADS)

    Hannon, Andrew C.; King, Gary; Morrison, Clayton; Galstyan, Aram; Cohen, Paul

    2005-05-01

    Computer simulation is used to research phenomena ranging from the structure of the space-time continuum to population genetics and future combat.1-3 Multi-agent simulations in particular are now commonplace in many fields.4, 5 By modeling populations whose complex behavior emerges from individual interactions, these simulations help to answer questions about effects where closed form solutions are difficult to solve or impossible to derive.6 To be useful, simulations must accurately model the relevant aspects of the underlying domain. In multi-agent simulation, this means that the modeling must include both the agents and their relationships. Typically, each agent can be modeled as a set of attributes drawn from various distributions (e.g., height, morale, intelligence and so forth). Though these can interact - for example, agent height is related to agent weight - they are usually independent. Modeling relations between agents, on the other hand, adds a new layer of complexity, and tools from graph theory and social network analysis are finding increasing application.7, 8 Recognizing the role and proper use of these techniques, however, remains the subject of ongoing research. We recently encountered these complexities while building large scale social simulations.9-11 One of these, the Hats Simulator, is designed to be a lightweight proxy for intelligence analysis problems. Hats models a "society in a box" consisting of many simple agents, called hats. Hats gets its name from the classic spaghetti western, in which the heroes and villains are known by the color of the hats they wear. The Hats society also has its heroes and villains, but the challenge is to identify which color hat they should be wearing based on how they behave. There are three types of hats: benign hats, known terrorists, and covert terrorists. Covert terrorists look just like benign hats but act like terrorists. Population structure can make covert hat identification significantly more

  19. Large scale ocean circulation from the GRACE GGM01 Geoid

    NASA Astrophysics Data System (ADS)

    Tapley, B. D.; Chambers, D. P.; Bettadpur, S.; Ries, J. C.

    2003-11-01

    The GRACE Gravity Model 01 (GGM01), computed from 111 days of GRACE K-band ranging (KBR) data, is differenced from a global mean sea surface (MSS) computed from a decade of satellite altimetry to determine a mean dynamic ocean topography (DOT). As a test of the GGM01 gravity model, large-scale zonal and meridional surface geostrophic currents are computed from the topography and are compared with those derived from a mean hydrographic surface. Reduction in residual RMS between the two by 30-60% (and increased correlation) indicates that the GGM01 geoid represents a dramatic improvement over older geoid models, which were developed from multiple satellite tracking data, altimetry, and surface gravity measurements. For the first time, all major current systems are clearly observed in the DOT from space-based measurements.

  20. Statistics of Caustics in Large-Scale Structure Formation

    NASA Astrophysics Data System (ADS)

    Feldbrugge, Job L.; Hidding, Johan; van de Weygaert, Rien

    2016-10-01

    The cosmic web is a complex spatial pattern of walls, filaments, cluster nodes and underdense void regions. It emerged through gravitational amplification from the Gaussian primordial density field. Here we infer analytical expressions for the spatial statistics of caustics in the evolving large-scale mass distribution. In our analysis, following the quasi-linear Zel'dovich formalism and confined to the 1D and 2D situation, we compute number density and correlation properties of caustics in cosmic density fields that evolve from Gaussian primordial conditions. The analysis can be straightforwardly extended to the 3D situation. We moreover, are currently extending the approach to the non-linear regime of structure formation by including higher order Lagrangian approximations and Lagrangian effective field theory.

  1. Probing large-scale structure with radio observations

    NASA Astrophysics Data System (ADS)

    Brown, Shea D.

    This thesis focuses on detecting magnetized relativistic plasma in the intergalactic medium (IGM) of filamentary large-scale structure (LSS) by observing synchrotron emission emitted by structure formation shocks. Little is known about the IGM beyond the largest clusters of galaxies, and synchrotron emission holds enormous promise as a means of probing magnetic fields and relativistic particle populations in these low density regions. I'll first report on observations taken at the Very Large Array and the Westerbork Synthesis Radio Telescope of the diffuse radio source 0809+39. I use these observations to demonstrate that 0809+39 is likely the first "radio relic" discovered that is not associated with a rich |"X-ray emitting cluster of galaxies. I then demonstrate that an unconventional reprocessing of the NVSS polarization survey can reveal structures on scales from 15' to hundreds of degrees, far larger than the nominal shortest-baseline scale. This yields hundreds of new diffuse sources as well as the identification of a new nearby galactic loop . These observations also highlight the major obstacle that diffuse galactic foreground emission poses for any search for large-scale, low surface- brightness extragalactic emission. I therefore explore the cross-correlation of diffuse radio emission with optical tracers of LSS as a means of statistically detecting the presence of magnetic fields in the low-density regions of the cosmic web. This initial study with the Bonn 1.4 GHz radio survey yields an upper limit of 0.2 mG for large-scale filament magnetic fields. Finally, I report on new Green Bank Telescope and Westerbork Synthesis Radio Telescope observations of the famous Coma cluster of galaxies. Major findings include an extension to the Coma cluster radio relic source 1253+275 which makes its total extent ~2 Mpc, as well as a sharp edge, or "front", on the Western side of the radio halo which shows a strong correlation with merger activity associated with an

  2. Resonant plankton patchiness induced by large-scale turbulent flow

    NASA Astrophysics Data System (ADS)

    McKiver, William J.; Neufeld, Zoltán

    2011-01-01

    Here we study how large-scale variability of oceanic plankton is affected by mesoscale turbulence in a spatially heterogeneous environment. We consider a phytoplankton-zooplankton (PZ) ecosystem model, with different types of zooplankton grazing functions, coupled to a turbulent flow described by the two-dimensional Navier-Stokes equations, representing large-scale horizontal transport in the ocean. We characterize the system using a dimensionless parameter, γ=TB/TF, which is the ratio of the ecosystem biological time scale TB and the flow time scale TF. Through numerical simulations, we examine how the PZ system depends on the time-scale ratio γ and find that the variance of both species changes significantly, with maximum phytoplankton variability at intermediate mixing rates. Through an analysis of the linearized population dynamics, we find an analytical solution based on the forced harmonic oscillator, which explains the behavior of the ecosystem, where there is resonance between the advection and the ecosystem predator-prey dynamics when the forcing time scales match the ecosystem time scales. We also examine the dependence of the power spectra on γ and find that the resonance behavior leads to different spectral slopes for phytoplankton and zooplankton, in agreement with observations.

  3. Resonant plankton patchiness induced by large-scale turbulent flow.

    PubMed

    McKiver, William J; Neufeld, Zoltán

    2011-01-01

    Here we study how large-scale variability of oceanic plankton is affected by mesoscale turbulence in a spatially heterogeneous environment. We consider a phytoplankton-zooplankton (PZ) ecosystem model, with different types of zooplankton grazing functions, coupled to a turbulent flow described by the two-dimensional Navier-Stokes equations, representing large-scale horizontal transport in the ocean. We characterize the system using a dimensionless parameter, γ=T(B)/T(F), which is the ratio of the ecosystem biological time scale T(B) and the flow time scale T(F). Through numerical simulations, we examine how the PZ system depends on the time-scale ratio γ and find that the variance of both species changes significantly, with maximum phytoplankton variability at intermediate mixing rates. Through an analysis of the linearized population dynamics, we find an analytical solution based on the forced harmonic oscillator, which explains the behavior of the ecosystem, where there is resonance between the advection and the ecosystem predator-prey dynamics when the forcing time scales match the ecosystem time scales. We also examine the dependence of the power spectra on γ and find that the resonance behavior leads to different spectral slopes for phytoplankton and zooplankton, in agreement with observations.

  4. The effect of large scale inhomogeneities on the luminosity distance

    NASA Astrophysics Data System (ADS)

    Brouzakis, Nikolaos; Tetradis, Nikolaos; Tzavara, Eleftheria

    2007-02-01

    We study the form of the luminosity distance as a function of redshift in the presence of large scale inhomogeneities, with sizes of order 10 Mpc or larger. We approximate the Universe through the Swiss-cheese model, with each spherical region described by the Lemaitre Tolman Bondi metric. We study the propagation of light beams in this background, assuming that the locations of the source and the observer are random. We derive the optical equations for the evolution of the beam area and shear. Through their integration we determine the configurations that can lead to an increase of the luminosity distance relative to the homogeneous cosmology. We find that this can be achieved if the Universe is composed of spherical void-like regions, with matter concentrated near their surface. For inhomogeneities consistent with the observed large scale structure, the relative increase of the luminosity distance is of the order of a few per cent at redshifts near 1, and falls short of explaining the substantial increase required by the supernova data. On the other hand, the effect we describe is important for the correct determination of the energy content of the Universe from observations.

  5. Halo detection via large-scale Bayesian inference

    NASA Astrophysics Data System (ADS)

    Merson, Alexander I.; Jasche, Jens; Abdalla, Filipe B.; Lahav, Ofer; Wandelt, Benjamin; Jones, D. Heath; Colless, Matthew

    2016-08-01

    We present a proof-of-concept of a novel and fully Bayesian methodology designed to detect haloes of different masses in cosmological observations subject to noise and systematic uncertainties. Our methodology combines the previously published Bayesian large-scale structure inference algorithm, HAmiltonian Density Estimation and Sampling algorithm (HADES), and a Bayesian chain rule (the Blackwell-Rao estimator), which we use to connect the inferred density field to the properties of dark matter haloes. To demonstrate the capability of our approach, we construct a realistic galaxy mock catalogue emulating the wide-area 6-degree Field Galaxy Survey, which has a median redshift of approximately 0.05. Application of HADES to the catalogue provides us with accurately inferred three-dimensional density fields and corresponding quantification of uncertainties inherent to any cosmological observation. We then use a cosmological simulation to relate the amplitude of the density field to the probability of detecting a halo with mass above a specified threshold. With this information, we can sum over the HADES density field realisations to construct maps of detection probabilities and demonstrate the validity of this approach within our mock scenario. We find that the probability of successful detection of haloes in the mock catalogue increases as a function of the signal to noise of the local galaxy observations. Our proposed methodology can easily be extended to account for more complex scientific questions and is a promising novel tool to analyse the cosmic large-scale structure in observations.

  6. Pre-slow-roll initial conditions: Large scale power suppression and infrared aspects during inflation

    NASA Astrophysics Data System (ADS)

    Lello, Louis; Boyanovsky, Daniel; Holman, Richard

    2014-03-01

    If the large-scale anomalies in the temperature power spectrum of the cosmic microwave background are of primordial origin, they may herald modifications to the slow-roll inflationary paradigm on the largest scales. We study the possibility that the origin of the large-scale power suppression is a modification of initial conditions during slow roll as a result of a pre-slow-roll phase during which the inflaton evolves rapidly. This stage is manifest in a potential in the equations for the Gaussian fluctuations during slow roll and modifies the power spectra of scalar perturbations via an initial condition transfer function T(k). We provide a general analytical study of its large- and small-scale properties and analyze the impact of these initial conditions on the infrared aspects of typical test scalar fields. The infrared behavior of massless minimally coupled test scalar field theories leads to the dynamical generation of mass and anomalous dimensions, both depending nonanalytically on T(0). During inflation, all quanta decay into many quanta even of the same field because of the lack of kinematic thresholds. The decay leads to a quantum entangled state of subhorizon and superhorizon quanta with correlations across the horizon. We find the modifications of the decay width and the entanglement entropy from the initial conditions. In all cases, initial conditions from a "fast-roll" stage that lead to a suppression in the scalar power spectrum at large scales also result in a suppression of the dynamically generated masses, anomalous dimensions and decay widths.

  7. A marked correlation function for constraining modified gravity models

    NASA Astrophysics Data System (ADS)

    White, Martin

    2016-11-01

    Future large scale structure surveys will provide increasingly tight constraints on our cosmological model. These surveys will report results on the distance scale and growth rate of perturbations through measurements of Baryon Acoustic Oscillations and Redshift-Space Distortions. It is interesting to ask: what further analyses should become routine, so as to test as-yet-unknown models of cosmic acceleration? Models which aim to explain the accelerated expansion rate of the Universe by modifications to General Relativity often invoke screening mechanisms which can imprint a non-standard density dependence on their predictions. This suggests density-dependent clustering as a `generic' constraint. This paper argues that a density-marked correlation function provides a density-dependent statistic which is easy to compute and report and requires minimal additional infrastructure beyond what is routinely available to such survey analyses. We give one realization of this idea and study it using low order perturbation theory. We encourage groups developing modified gravity theories to see whether such statistics provide discriminatory power for their models.

  8. Triplet correlation functions in liquid water

    NASA Astrophysics Data System (ADS)

    Dhabal, Debdas; Singh, Murari; Wikfeldt, Kjartan Thor; Chakravarty, Charusita

    2014-11-01

    Triplet correlations have been shown to play a crucial role in the transformation of simple liquids to anomalous tetrahedral fluids [M. Singh, D. Dhabal, A. H. Nguyen, V. Molinero, and C. Chakravarty, Phys. Rev. Lett. 112, 147801 (2014)]. Here we examine triplet correlation functions for water, arguably the most important tetrahedral liquid, under ambient conditions, using configurational ensembles derived from molecular dynamics (MD) simulations and reverse Monte Carlo (RMC) datasets fitted to experimental scattering data. Four different RMC data sets with widely varying hydrogen-bond topologies fitted to neutron and x-ray scattering data are considered [K. T. Wikfeldt, M. Leetmaa, M. P. Ljungberg, A. Nilsson, and L. G. M. Pettersson, J. Phys. Chem. B 113, 6246 (2009)]. Molecular dynamics simulations are performed for two rigid-body effective pair potentials (SPC/E and TIP4P/2005) and the monatomic water (mW) model. Triplet correlation functions are compared with other structural measures for tetrahedrality, such as the O-O-O angular distribution function and the local tetrahedral order distributions. In contrast to the pair correlation functions, which are identical for all the RMC ensembles, the O-O-O triplet correlation function can discriminate between ensembles with different degrees of tetrahedral network formation with the maximally symmetric, tetrahedral SYM dataset displaying distinct signatures of tetrahedrality similar to those obtained from atomistic simulations of the SPC/E model. Triplet correlations from the RMC datasets conform closely to the Kirkwood superposition approximation, while those from MD simulations show deviations within the first two neighbour shells. The possibilities for experimental estimation of triplet correlations of water and other tetrahedral liquids are discussed.

  9. Triplet correlation functions in liquid water

    SciTech Connect

    Dhabal, Debdas; Chakravarty, Charusita; Singh, Murari; Wikfeldt, Kjartan Thor

    2014-11-07

    Triplet correlations have been shown to play a crucial role in the transformation of simple liquids to anomalous tetrahedral fluids [M. Singh, D. Dhabal, A. H. Nguyen, V. Molinero, and C. Chakravarty, Phys. Rev. Lett. 112, 147801 (2014)]. Here we examine triplet correlation functions for water, arguably the most important tetrahedral liquid, under ambient conditions, using configurational ensembles derived from molecular dynamics (MD) simulations and reverse Monte Carlo (RMC) datasets fitted to experimental scattering data. Four different RMC data sets with widely varying hydrogen-bond topologies fitted to neutron and x-ray scattering data are considered [K. T. Wikfeldt, M. Leetmaa, M. P. Ljungberg, A. Nilsson, and L. G. M. Pettersson, J. Phys. Chem. B 113, 6246 (2009)]. Molecular dynamics simulations are performed for two rigid-body effective pair potentials (SPC/E and TIP4P/2005) and the monatomic water (mW) model. Triplet correlation functions are compared with other structural measures for tetrahedrality, such as the O–O–O angular distribution function and the local tetrahedral order distributions. In contrast to the pair correlation functions, which are identical for all the RMC ensembles, the O–O–O triplet correlation function can discriminate between ensembles with different degrees of tetrahedral network formation with the maximally symmetric, tetrahedral SYM dataset displaying distinct signatures of tetrahedrality similar to those obtained from atomistic simulations of the SPC/E model. Triplet correlations from the RMC datasets conform closely to the Kirkwood superposition approximation, while those from MD simulations show deviations within the first two neighbour shells. The possibilities for experimental estimation of triplet correlations of water and other tetrahedral liquids are discussed.

  10. Correlation functions of Coulomb branch operators

    NASA Astrophysics Data System (ADS)

    Gerchkovitz, Efrat; Gomis, Jaume; Ishtiaque, Nafiz; Karasik, Avner; Komargodski, Zohar; Pufu, Silviu S.

    2017-01-01

    We consider the correlation functions of Coulomb branch operators in four-dimensional N = 2 Superconformal Field Theories (SCFTs) involving exactly one antichiral operator. These extremal correlators are the "minimal" non-holomorphic local observables in the theory. We show that they can be expressed in terms of certain determinants of derivatives of the four-sphere partition function of an appropriate deformation of the SCFT. This relation between the extremal correlators and the deformed four-sphere partition function is non-trivial due to the presence of conformal anomalies, which lead to operator mixing on the sphere. Evaluating the deformed four-sphere partition function using supersymmetric localization, we compute the extremal correlators explicitly in many interesting examples. Additionally, the representation of the extremal correlators mentioned above leads to a system of integrable differential equations. We compare our exact results with previous perturbative computations and with the four-dimensional tt ∗ equations. We also use our results to study some of the asymptotic properties of the perturbative series expansions we obtain in N = 2 SQCD.

  11. Fast large scale structure perturbation theory using one-dimensional fast Fourier transforms

    NASA Astrophysics Data System (ADS)

    Schmittfull, Marcel; Vlah, Zvonimir; McDonald, Patrick

    2016-05-01

    The usual fluid equations describing the large-scale evolution of mass density in the universe can be written as local in the density, velocity divergence, and velocity potential fields. As a result, the perturbative expansion in small density fluctuations, usually written in terms of convolutions in Fourier space, can be written as a series of products of these fields evaluated at the same location in configuration space. Based on this, we establish a new method to numerically evaluate the 1-loop power spectrum (i.e., Fourier transform of the 2-point correlation function) with one-dimensional fast Fourier transforms. This is exact and a few orders of magnitude faster than previously used numerical approaches. Numerical results of the new method are in excellent agreement with the standard quadrature integration method. This fast model evaluation can in principle be extended to higher loop order where existing codes become painfully slow. Our approach follows by writing higher order corrections to the 2-point correlation function as, e.g., the correlation between two second-order fields or the correlation between a linear and a third-order field. These are then decomposed into products of correlations of linear fields and derivatives of linear fields. The method can also be viewed as evaluating three-dimensional Fourier space convolutions using products in configuration space, which may also be useful in other contexts where similar integrals appear.

  12. Semiclassical approximations to quantum time correlation functions

    NASA Astrophysics Data System (ADS)

    Egorov, S. A.; Skinner, J. L.

    1998-09-01

    Over the last 40 years several ad hoc semiclassical approaches have been developed in order to obtain approximate quantum time correlation functions, using as input only the corresponding classical time correlation functions. The accuracy of these approaches has been tested for several exactly solvable gas-phase models. In this paper we test the accuracy of these approaches by comparing to an exactly solvable many-body condensed-phase model. We show that in the frequency domain the Egelstaff approach is the most accurate, especially at high frequencies, while in the time domain one of the other approaches is more accurate.

  13. SMJ's analysis of Ising model correlation functions

    NASA Astrophysics Data System (ADS)

    Kadanoff, Leo P.; Kohmoto, Mahito

    1980-05-01

    In a series of recent publications Sato, Miwa, and Jimbo (SMJ) have shown how to derive multispin correlation functions of the two-dimensional Ising model in the continuum, or scaling, limit by analyzing the behavior of the solutions to the two-dimensional version of the Dirac equation. The major purpose of the present work is to describe SMJ's analysis more discursively and in terms closer to that used in previous studies of the Ising model. In addition, new and more compact expressions for their basic equations are derived. A single new answer is obtained: the form of the three-spin correlation function at criticality.

  14. Impact performance of large scale electromagnetic launchers

    SciTech Connect

    Fahrenthold, E.P. . Dept. of Mechanical Engineering)

    1991-01-01

    This paper reports on the development of high performance electromagnetic launchers and associated pulsed power supplies which has led to the aerodynamic and structural design of new projectile types. The impact performance of monolithic railgun projectiles between one and four kilograms in mass has been estimated using Lagrangian hydrocode simulations at velocities up to three kilometers per second. The simulation predictions are within expected bounds, based on existing correlations of experimental measurements on cylindrical projectiles of equivalent mass.

  15. Bias to CMB lensing measurements from the bispectrum of large-scale structure

    NASA Astrophysics Data System (ADS)

    Böhm, Vanessa; Schmittfull, Marcel; Sherwin, Blake D.

    2016-08-01

    The rapidly improving precision of measurements of gravitational lensing of the cosmic microwave background (CMB) also requires a corresponding increase in the precision of theoretical modeling. A commonly made approximation is to model the CMB deflection angle or lensing potential as a Gaussian random field. In this paper, however, we analytically quantify the influence of the non-Gaussianity of large-scale structure (LSS) lenses, arising from nonlinear structure formation, on CMB lensing measurements. In particular, evaluating the impact of the nonzero bispectrum of large-scale structure on the relevant CMB four-point correlation functions, we find that there is a bias to estimates of the CMB lensing power spectrum. For temperature-based lensing reconstruction with CMB stage III and stage IV experiments, we find that this lensing power spectrum bias is negative and is of order 1% of the signal. This corresponds to a shift of multiple standard deviations for these upcoming experiments. We caution, however, that our numerical calculation only evaluates two of the largest bias terms and, thus, only provides an approximate estimate of the full bias. We conclude that further investigation into lensing biases from nonlinear structure formation is required and that these biases should be accounted for in future lensing analyses.

  16. Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity

    PubMed Central

    Wang, Lubin; Zhai, Tianye; Zou, Feng; Ye, Enmao; Jin, Xiao; Li, Wuju; Qi, Jianlin; Yang, Zheng

    2015-01-01

    Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI). Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM) task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN) and default mode network (DMN). Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation. PMID:26218521

  17. Large-scale structure in a texture-seeded cold dark matter cosmogony

    NASA Technical Reports Server (NTRS)

    Park, Changbom; Spergel, David N.; Turok, Nail

    1991-01-01

    This paper studies the formation of large-scale structure by global texture in a flat universe dominated by cold dark matter. A code for evolution of the texture fields was combined with an N-body code for evolving the dark matter. The results indicate some promising aspects: with only one free parameter, the observed galaxy-galaxy correlation function is reproduced, clusters of galaxies are found to be significantly clustered on a scale of 20-50/h Mpc, and coherent structures of over 50/h Mpc in the galaxy distribution were found. The large-scale streaming motions observed are in good agreement with the observations: the average magnitude of the velocity field smoothed over 30/h Mpc is 430 km/sec. Global texture produces a cosmic Mach number that is compatible with observation. Also, significant evolution of clusters at low redshift was seen. Possible problems for the theory include too high velocity dispersions in clusters, and voids which are not as empty as those observed.

  18. Test Problems for Large-Scale Multiobjective and Many-Objective Optimization.

    PubMed

    Cheng, Ran; Jin, Yaochu; Olhofer, Markus; Sendhoff, Bernhard

    2016-08-26

    The interests in multiobjective and many-objective optimization have been rapidly increasing in the evolutionary computation community. However, most studies on multiobjective and many-objective optimization are limited to small-scale problems, despite the fact that many real-world multiobjective and many-objective optimization problems may involve a large number of decision variables. As has been evident in the history of evolutionary optimization, the development of evolutionary algorithms (EAs) for solving a particular type of optimization problems has undergone a co-evolution with the development of test problems. To promote the research on large-scale multiobjective and many-objective optimization, we propose a set of generic test problems based on design principles widely used in the literature of multiobjective and many-objective optimization. In order for the test problems to be able to reflect challenges in real-world applications, we consider mixed separability between decision variables and nonuniform correlation between decision variables and objective functions. To assess the proposed test problems, six representative evolutionary multiobjective and many-objective EAs are tested on the proposed test problems. Our empirical results indicate that although the compared algorithms exhibit slightly different capabilities in dealing with the challenges in the test problems, none of them are able to efficiently solve these optimization problems, calling for the need for developing new EAs dedicated to large-scale multiobjective and many-objective optimization.

  19. Radially dependent large-scale dynamos in global cylindrical shear flows and the local cartesian limit

    NASA Astrophysics Data System (ADS)

    Ebrahimi, F.; Blackman, E. G.

    2016-06-01

    For cylindrical differentially rotating plasmas, we study large-scale magnetic field generation from finite amplitude non-axisymmetric perturbations by comparing numerical simulations with quasi-linear analytic theory. When initiated with a vertical magnetic field of either zero or finite net flux, our global cylindrical simulations exhibit the magnetorotational instability (MRI) and large-scale dynamo growth of radially alternating mean fields, averaged over height and azimuth. This dynamo growth is explained by our analytic calculations of a non-axisymmetric fluctuation-induced electromotive force that is sustained by azimuthal shear of the fluctuating fields. The standard `Ω effect' (shear of the mean field by differential rotation) is unimportant. For the MRI case, we express the large-scale dynamo field as a function of differential rotation. The resulting radially alternating large-scale fields may have implications for angular momentum transport in discs and corona. To connect with previous work on large-scale dynamos with local linear shear and identify the minimum conditions needed for large-scale field growth, we also solve our equations in local Cartesian coordinates. We find that large-scale dynamo growth in a linear shear flow without rotation can be sustained by shear plus non-axisymmetric fluctuations - even if not helical, a seemingly previously unidentified distinction. The linear shear flow dynamo emerges as a more restricted version of our more general new global cylindrical calculations.

  20. Group entropies, correlation laws, and zeta functions

    NASA Astrophysics Data System (ADS)

    Tempesta, Piergiulio

    2011-08-01

    The notion of group entropy is proposed. It enables the unification and generaliztion of many different definitions of entropy known in the literature, such as those of Boltzmann-Gibbs, Tsallis, Abe, and Kaniadakis. Other entropic functionals are introduced, related to nontrivial correlation laws characterizing universality classes of systems out of equilibrium when the dynamics is weakly chaotic. The associated thermostatistics are discussed. The mathematical structure underlying our construction is that of formal group theory, which provides the general structure of the correlations among particles and dictates the associated entropic functionals. As an example of application, the role of group entropies in information theory is illustrated and generalizations of the Kullback-Leibler divergence are proposed. A new connection between statistical mechanics and zeta functions is established. In particular, Tsallis entropy is related to the classical Riemann zeta function.

  1. Large-scale dimension densities for heart rate variability analysis

    NASA Astrophysics Data System (ADS)

    Raab, Corinna; Wessel, Niels; Schirdewan, Alexander; Kurths, Jürgen

    2006-04-01

    In this work, we reanalyze the heart rate variability (HRV) data from the 2002 Computers in Cardiology (CiC) Challenge using the concept of large-scale dimension densities and additionally apply this technique to data of healthy persons and of patients with cardiac diseases. The large-scale dimension density (LASDID) is estimated from the time series using a normalized Grassberger-Procaccia algorithm, which leads to a suitable correction of systematic errors produced by boundary effects in the rather large scales of a system. This way, it is possible to analyze rather short, nonstationary, and unfiltered data, such as HRV. Moreover, this method allows us to analyze short parts of the data and to look for differences between day and night. The circadian changes in the dimension density enable us to distinguish almost completely between real data and computer-generated data from the CiC 2002 challenge using only one parameter. In the second part we analyzed the data of 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects (EH), as well as 18 young and healthy persons (YH). With our method we are able to separate completely the AF (ρlsμ=0.97±0.02) group from the others and, especially during daytime, the CHF patients show significant differences from the young and elderly healthy volunteers (CHF, 0.65±0.13 ; EH, 0.54±0.05 ; YH, 0.57±0.05 ; p<0.05 for both comparisons). Moreover, for the CHF patients we find no circadian changes in ρlsμ (day, 0.65±0.13 ; night, 0.66±0.12 ; n.s.) in contrast to healthy controls (day, 0.54±0.05 ; night, 0.61±0.05 ; p=0.002 ). Correlation analysis showed no statistical significant relation between standard HRV and circadian LASDID, demonstrating a possibly independent application of our method for clinical risk stratification.

  2. Correlation Functions Aid Analyses Of Spectra

    NASA Technical Reports Server (NTRS)

    Beer, Reinhard; Norton, Robert H., Jr.

    1989-01-01

    New uses found for correlation functions in analyses of spectra. In approach combining elements of both pattern-recognition and traditional spectral-analysis techniques, spectral lines identified in data appear useless at first glance because they are dominated by noise. New approach particularly useful in measurement of concentrations of rare species of molecules in atmosphere.

  3. Pass-transistor very large scale integration

    NASA Technical Reports Server (NTRS)

    Maki, Gary K. (Inventor); Bhatia, Prakash R. (Inventor)

    2004-01-01

    Logic elements are provided that permit reductions in layout size and avoidance of hazards. Such logic elements may be included in libraries of logic cells. A logical function to be implemented by the logic element is decomposed about logical variables to identify factors corresponding to combinations of the logical variables and their complements. A pass transistor network is provided for implementing the pass network function in accordance with this decomposition. The pass transistor network includes ordered arrangements of pass transistors that correspond to the combinations of variables and complements resulting from the logical decomposition. The logic elements may act as selection circuits and be integrated with memory and buffer elements.

  4. Large-scale systems: Complexity, stability, reliability

    NASA Technical Reports Server (NTRS)

    Siljak, D. D.

    1975-01-01

    After showing that a complex dynamic system with a competitive structure has highly reliable stability, a class of noncompetitive dynamic systems for which competitive models can be constructed is defined. It is shown that such a construction is possible in the context of the hierarchic stability analysis. The scheme is based on the comparison principle and vector Liapunov functions.

  5. Sample-Starved Large Scale Network Analysis

    DTIC Science & Technology

    2016-05-05

    advisory functions 1. A. Hero serves on the National Academy of Sciences Committee on Applied and Theoretical Statistics ( CATS ), 2012-. Advises the...National Academies on the use of statistics in science, engineering and technology. CATS organizes workshops for government agencies (currently

  6. Engineering large-scale agent-based systems with consensus

    NASA Technical Reports Server (NTRS)

    Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.

    1994-01-01

    The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.

  7. Towards Online Multiresolution Community Detection in Large-Scale Networks

    PubMed Central

    Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

    2011-01-01

    The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

  8. Optical modulation of aqueous metamaterial properties at large scale.

    PubMed

    Yang, Sui; Wang, Yuan; Ni, Xingjie; Zhang, Xiang

    2015-11-02

    Dynamical control of metamaterials by adjusting their shape and structures has been developed to achieve desired optical functionalities and to enable modulation and selection of spectra responses. However it is still challenging to realize such a manipulation at large scale. Recently, it has been shown that the desired high (or low) symmetry metamaterials structure in solution can be self-assembled under external light stimuli. Using the this approach, we systematically investiagted the optical controlling process and report here a dynamical manipulation of magnetic properties of metamaterials. Under external laser excitations, we demonstrated that selected magnetic properties of metamaterials can be tuned with the freedom of chosen wavelength ranges. The magnetic dipole selectivity and tunability were further quantified by in situ spectral measurement.

  9. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    DOE PAGES

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less

  10. Large scale rigidity-based flexibility analysis of biomolecules

    PubMed Central

    Streinu, Ileana

    2016-01-01

    KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

  11. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    SciTech Connect

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinate with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.

  12. Nonclassicality criteria: Quasiprobability distributions and correlation functions

    NASA Astrophysics Data System (ADS)

    Alexanian, Moorad

    2016-10-01

    We use the exact calculation of the quantum mechanical, temporal characteristic function χ (η ) and the degree of second-order coherence g(2 )(τ ) for a single-mode, degenerate parametric amplifier for a system in the Gaussian state, viz., a displaced-squeezed thermal state, to study the different criteria for nonclassicality. In particular, we contrast criteria that involve only one-time functions of the dynamical system, for instance, the quasiprobability distribution P (β ) of the Glauber-Sudarshan coherent or P representation of the density of state and the Mandel QM(τ ) parameter, versus the criteria associated with the two-time correlation function g(2 )(τ ) .

  13. The trispectrum in the Effective Field Theory of Large Scale Structure

    NASA Astrophysics Data System (ADS)

    Bertolini, Daniele; Schutz, Katelin; Solon, Mikhail P.; Zurek, Kathryn M.

    2016-06-01

    We compute the connected four point correlation function (the trispectrum in Fourier space) of cosmological density perturbations at one-loop order in Standard Perturbation Theory (SPT) and the Effective Field Theory of Large Scale Structure (EFT of LSS). This paper is a companion to our earlier work on the non-Gaussian covariance of the matter power spectrum, which corresponds to a particular wavenumber configuration of the trispectrum. In the present calculation, we highlight and clarify some of the subtle aspects of the EFT framework that arise at third order in perturbation theory for general wavenumber configurations of the trispectrum. We consistently incorporate vorticity and non-locality in time into the EFT counterterms and lay out a complete basis of building blocks for the stress tensor. We show predictions for the one-loop SPT trispectrum and the EFT contributions, focusing on configurations which have particular relevance for using LSS to constrain primordial non-Gaussianity.

  14. Dark matter, long-range forces, and large-scale structure

    NASA Technical Reports Server (NTRS)

    Gradwohl, Ben-Ami; Frieman, Joshua A.

    1992-01-01

    If the dark matter in galaxies and clusters is nonbaryonic, it can interact with additional long-range fields that are invisible to experimental tests of the equivalence principle. We discuss the astrophysical and cosmological implications of a long-range force coupled only to the dark matter and find rather tight constraints on its strength. If the force is repulsive (attractive), the masses of galaxy groups and clusters (and the mean density of the universe inferred from them) have been systematically underestimated (overestimated). We explore the consequent effects on the two-point correlation function, large-scale velocity flows, and microwave background anisotropies, for models with initial scale-invariant adiabatic perturbations and cold dark matter.

  15. A case study of large-scale structure in a 'hot' model universe

    NASA Technical Reports Server (NTRS)

    Centrella, Joan M.; Gallagher, John S., III; Melott, Adrian L.; Bushouse, Howard A.

    1988-01-01

    Large-scale structure is studied in an Omega(0) = 1 model universe filled with 'hot' dark matter. A particle mesh computer code is used to calculate the development of gravitational instabilities in 64-cubed mass clouds on a 64-cubed three-dimensional grid over an expansion factor of about 1000. The present epoch is identified by matching the slope of the model particle-particle two-point correlation function with that obtained from observations of galaxies, and the model then corresponds to a cubical sample of the universe of about 105/h Mpc on a side. Properties of the simulated universe are investigated by casting the model quantities into observer's coordinates and comparing the results with observations of the spatial and velocity distributions of luminous matter. It is concluded based on simple arguments that current limits on the time of galaxy formation do not rule out 'hot' dark matter.

  16. Large-scale quantum mechanical simulations of high-Z metals

    SciTech Connect

    Yang, L H; Hood, R; Pask, J; Klepeis, J

    2007-01-03

    High-Z metals constitute a particular challenge for large-scale ab initio calculations, as they require high resolution due to the presence of strongly localized states and require many eigenstates to be computed due to the large number of electrons and need to accurately resolve the Fermi surface. Here, we report recent findings on high-Z materials, using an efficient massively parallel planewave implementation on some of the largest computational architectures currently available. We discuss the particular architectures employed and methodological advances required to harness them effectively. We present a pair-correlation function for U, calculated using quantum molecular dynamics, and discuss relaxations of Pu atoms in the vicinity of defects in aged and alloyed Pu. We find that the self-irradiation associated with aging has a negligible effect on the compressibility of Pu relative to other factors such as alloying.

  17. Large-scale imaging in small brains

    PubMed Central

    Ahrens, Misha B.; Engert, Florian

    2016-01-01

    The dense connectivity in the brain and arrangements of cells into circuits means that one neuron’s activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates. PMID:25636154

  18. Large-Scale Sequential Quadratic Programming Algorithms

    DTIC Science & Technology

    1992-09-01

    KKT conditions for the QP subproblem shows that Pk(gk) = pk(VL). To see why, note that the KKT necessary and sufficient conditions ...number of active functional constraints at x*). Let Z* be a basis for the null space of A* (so that A*Z* = 0). The KKT necessary conditions for (x*, A... optimal (i.e. when the working set has identified the active set). Let g* FkP* +9k and omit the subscript k. Consider the first-order KKT conditions for

  19. Inflationary tensor fossils in large-scale structure

    SciTech Connect

    Dimastrogiovanni, Emanuela; Fasiello, Matteo; Jeong, Donghui; Kamionkowski, Marc E-mail: mrf65@case.edu E-mail: kamion@jhu.edu

    2014-12-01

    Inflation models make specific predictions for a tensor-scalar-scalar three-point correlation, or bispectrum, between one gravitational-wave (tensor) mode and two density-perturbation (scalar) modes. This tensor-scalar-scalar correlation leads to a local power quadrupole, an apparent departure from statistical isotropy in our Universe, as well as characteristic four-point correlations in the current mass distribution in the Universe. So far, the predictions for these observables have been worked out only for single-clock models in which certain consistency conditions between the tensor-scalar-scalar correlation and tensor and scalar power spectra are satisfied. Here we review the requirements on inflation models for these consistency conditions to be satisfied. We then consider several examples of inflation models, such as non-attractor and solid-inflation models, in which these conditions are put to the test. In solid inflation the simplest consistency conditions are already violated whilst in the non-attractor model we find that, contrary to the standard scenario, the tensor-scalar-scalar correlator probes directly relevant model-dependent information. We work out the predictions for observables in these models. For non-attractor inflation we find an apparent local quadrupolar departure from statistical isotropy in large-scale structure but that this power quadrupole decreases very rapidly at smaller scales. The consistency of the CMB quadrupole with statistical isotropy then constrains the distance scale that corresponds to the transition from the non-attractor to attractor phase of inflation to be larger than the currently observable horizon. Solid inflation predicts clustering fossils signatures in the current galaxy distribution that may be large enough to be detectable with forthcoming, and possibly even current, galaxy surveys.

  20. Correlates of functional capacity among centenarians.

    PubMed

    Martin, Peter; MacDonald, Maurice; Margrett, Jennifer; Siegler, Ilene; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Markesbery, W R; Woodard, J L; Johnson, M A; Tenover, J S; Rodgers, W L; Hausman, D B; Rott, C; Davey, A; Arnold, J

    2013-04-01

    This study investigated correlates of functional capacity among participants of the Georgia Centenarian Study. Six domains (demographics and health, positive and negative affect, personality, social and economic support, life events and coping, distal influences) were related to functional capacity for 234 centenarians and near centenarians (i.e., 98 years and older). Data were provided by proxy informants. Domain-specific multiple regression analyses suggested that younger centenarians, those living in the community and rated to be in better health were more likely to have higher functional capacity scores. Higher scores in positive affect, conscientiousness, social provisions, religious coping, and engaged lifestyle were also associated with higher levels of functional capacity. The results suggest that functional capacity levels continue to be associated with age after 100 years of life and that positive affect levels and past lifestyle activities as reported by proxies are salient factors of adaptation in very late life.

  1. Large-Scale Spray Releases: Additional Aerosol Test Results

    SciTech Connect

    Daniel, Richard C.; Gauglitz, Phillip A.; Burns, Carolyn A.; Fountain, Matthew S.; Shimskey, Rick W.; Billing, Justin M.; Bontha, Jagannadha R.; Kurath, Dean E.; Jenks, Jeromy WJ; MacFarlan, Paul J.; Mahoney, Lenna A.

    2013-08-01

    One of the events postulated in the hazard analysis for the Waste Treatment and Immobilization Plant (WTP) and other U.S. Department of Energy (DOE) nuclear facilities is a breach in process piping that produces aerosols with droplet sizes in the respirable range. The current approach for predicting the size and concentration of aerosols produced in a spray leak event involves extrapolating from correlations reported in the literature. These correlations are based on results obtained from small engineered spray nozzles using pure liquids that behave as a Newtonian fluid. The narrow ranges of physical properties on which the correlations are based do not cover the wide range of slurries and viscous materials that will be processed in the WTP and in processing facilities across the DOE complex. To expand the data set upon which the WTP accident and safety analyses were based, an aerosol spray leak testing program was conducted by Pacific Northwest National Laboratory (PNNL). PNNL’s test program addressed two key technical areas to improve the WTP methodology (Larson and Allen 2010). The first technical area was to quantify the role of slurry particles in small breaches where slurry particles may plug the hole and prevent high-pressure sprays. The results from an effort to address this first technical area can be found in Mahoney et al. (2012a). The second technical area was to determine aerosol droplet size distribution and total droplet volume from prototypic breaches and fluids, including sprays from larger breaches and sprays of slurries for which literature data are mostly absent. To address the second technical area, the testing program collected aerosol generation data at two scales, commonly referred to as small-scale and large-scale testing. The small-scale testing and resultant data are described in Mahoney et al. (2012b), and the large-scale testing and resultant data are presented in Schonewill et al. (2012). In tests at both scales, simulants were used

  2. New results on large-scale structures

    NASA Astrophysics Data System (ADS)

    Kalinkov, M.; Stavrev, K.; Kuneva, I.

    A new version of the magnetic-tape catalog of Abell clusters of galaxies is used to obtain redshift estimators and to generate two samples of clusters. A procedure for searching for superclusters of galaxies is applied and the results are given in tabular and graphic form. For a limited homogeneous sample (distance 60 - 275 Mpc, galactic latitude B > 35°), 12 multiplets, having member clusters with known redshifts, are found. It is shown that the spatial covariance function for rich clusters has the form ξ = (r0/r)γ with r0 = 22.4±1.8 Mpc and γ = 1.90±0.25 for 3 Mpc ⪉ r ⪉ 80 Mpc.

  3. Large scale propagation intermittency in the atmosphere

    NASA Astrophysics Data System (ADS)

    Mehrabi, Ali

    2000-11-01

    Long-term (several minutes to hours) amplitude variations observed in outdoor sound propagation experiments at Disneyland, California, in February 1998 are explained in terms of a time varying index of refraction. The experimentally propagated acoustic signals were received and recorded at several locations ranging from 300 meters to 2,800 meters. Meteorological data was taken as a function of altitude simultaneously with the received signal levels. There were many barriers along the path of acoustic propagation that affected the received signal levels, especially at short ranges. In a downward refraction situation, there could be a random change of amplitude in the predicted signals. A computer model based on the Fast Field Program (FFP) was used to compute the signal loss at the different receiving locations and to verify that the variations in the received signal levels can be predicted numerically. The calculations agree with experimental data with the same trend variations in average amplitude.

  4. Information Tailoring Enhancements for Large-Scale Social Data

    DTIC Science & Technology

    2016-06-15

    Intelligent Automation Incorporated Information Tailoring Enhancements for Large-Scale...Automation Incorporated Progress Report No. 3 Information Tailoring Enhancements for Large-Scale Social Data Submitted in accordance with...also gathers information about entities from all news articles and displays it on over one million entity pages [5][6], and the information is made

  5. Large Scale Deformation Monitoring and Atmospheric Removal in Mexico City

    NASA Astrophysics Data System (ADS)

    McCardle, Adrian; McCardel, Jim; Ramos, Fernanda Ledo G.

    2010-03-01

    Large scale, accurate measurement of non-linear ground movement is required for monitoring applications pertaining to groundwater extraction, oil and gas production, and carbon capture and storage. Mexico City experiences severe subsidence as high as 35 centimeters per year due to continued exploitation of groundwater. Such extreme ground deformation has caused damage to infrastructure and many areas of the city are now subjected to periodic flooding. Furthermore, subsidence rates change seasonally creating a non-linear deformation signature manifesting over an area larger than 30 x 30 kilometers. The geographical location and climate of Mexico City, coupled with aforementioned subsidence characteristics create unique challenges for repeat-pass InSAR processing: Firstly, Mexico City is a tropical highland and experiences an oceanic climate that leads to significant temporal de-correlation. Secondly, the large magnitude subsidence leads to phase aliasing over coherent targets, particularly for interferograms with large temporal separation. Lastly, the expansive deformation is spatially correlated on scales similar to the long-range atmosphere, complicating the separation of the two signals. This paper discusses the results from the application of traditional DInSAR techniques combined with Multi-temporal InSAR Network Analysis processing algorithms to accurately identify and measure displacement, specifically in light of the challenges peculiar to Mexico City. Multi-temporal InSAR Network Analysis techniques are used to identify non-linear displacement and remove atmospheric noise from 38 ENVISAT images that were acquired over Mexico City from 2002 to 2007.

  6. In situ vitrification large-scale operational acceptance test analysis

    SciTech Connect

    Buelt, J.L.; Carter, J.G.

    1986-05-01

    A thermal treatment process is currently under study to provide possible enhancement of in-place stabilization of transuranic and chemically contaminated soil sites. The process is known as in situ vitrification (ISV). In situ vitrification is a remedial action process that destroys solid and liquid organic contaminants and incorporates radionuclides into a glass-like material that renders contaminants substantially less mobile and less likely to impact the environment. A large-scale operational acceptance test (LSOAT) was recently completed in which more than 180 t of vitrified soil were produced in each of three adjacent settings. The LSOAT demonstrated that the process conforms to the functional design criteria necessary for the large-scale radioactive test (LSRT) to be conducted following verification of the performance capabilities of the process. The energy requirements and vitrified block size, shape, and mass are sufficiently equivalent to those predicted by the ISV mathematical model to confirm its usefulness as a predictive tool. The LSOAT demonstrated an electrode replacement technique, which can be used if an electrode fails, and techniques have been identified to minimize air oxidation, thereby extending electrode life. A statistical analysis was employed during the LSOAT to identify graphite collars and an insulative surface as successful cold cap subsidence techniques. The LSOAT also showed that even under worst-case conditions, the off-gas system exceeds the flow requirements necessary to maintain a negative pressure on the hood covering the area being vitrified. The retention of simulated radionuclides and chemicals in the soil and off-gas system exceeds requirements so that projected emissions are one to two orders of magnitude below the maximum permissible concentrations of contaminants at the stack.

  7. Simulating the large-scale structure of HI intensity maps

    SciTech Connect

    Seehars, Sebastian; Paranjape, Aseem; Witzemann, Amadeus; Refregier, Alexandre; Amara, Adam; Akeret, Joel E-mail: aseem@iucaa.in E-mail: alexandre.refregier@phys.ethz.ch E-mail: joel.akeret@phys.ethz.ch

    2016-03-01

    Intensity mapping of neutral hydrogen (HI) is a promising observational probe of cosmology and large-scale structure. We present wide field simulations of HI intensity maps based on N-body simulations of a 2.6 Gpc / h box with 2048{sup 3} particles (particle mass 1.6 × 10{sup 11} M{sub ⊙} / h). Using a conditional mass function to populate the simulated dark matter density field with halos below the mass resolution of the simulation (10{sup 8} M{sub ⊙} / h < M{sub halo} < 10{sup 13} M{sub ⊙} / h), we assign HI to those halos according to a phenomenological halo to HI mass relation. The simulations span a redshift range of 0.35 ∼< z ∼< 0.9 in redshift bins of width Δ z ≈ 0.05 and cover a quarter of the sky at an angular resolution of about 7'. We use the simulated intensity maps to study the impact of non-linear effects and redshift space distortions on the angular clustering of HI. Focusing on the autocorrelations of the maps, we apply and compare several estimators for the angular power spectrum and its covariance. We verify that these estimators agree with analytic predictions on large scales and study the validity of approximations based on Gaussian random fields, particularly in the context of the covariance. We discuss how our results and the simulated maps can be useful for planning and interpreting future HI intensity mapping surveys.

  8. Large-scale GW software development

    NASA Astrophysics Data System (ADS)

    Kim, Minjung; Mandal, Subhasish; Mikida, Eric; Jindal, Prateek; Bohm, Eric; Jain, Nikhil; Kale, Laxmikant; Martyna, Glenn; Ismail-Beigi, Sohrab

    Electronic excitations are important in understanding and designing many functional materials. In terms of ab initio methods, the GW and Bethe-Saltpeter Equation (GW-BSE) beyond DFT methods have proved successful in describing excited states in many materials. However, the heavy computational loads and large memory requirements have hindered their routine applicability by the materials physics community. We summarize some of our collaborative efforts to develop a new software framework designed for GW calculations on massively parallel supercomputers. Our GW code is interfaced with the plane-wave pseudopotential ab initio molecular dynamics software ``OpenAtom'' which is based on the Charm++ parallel library. The computation of the electronic polarizability is one of the most expensive parts of any GW calculation. We describe our strategy that uses a real-space representation to avoid the large number of fast Fourier transforms (FFTs) common to most GW methods. We also describe an eigendecomposition of the plasmon modes from the resulting dielectric matrix that enhances efficiency. This work is supported by NSF through Grant ACI-1339804.

  9. Territorial Polymers and Large Scale Genome Organization

    NASA Astrophysics Data System (ADS)

    Grosberg, Alexander

    2012-02-01

    Chromatin fiber in interphase nucleus represents effectively a very long polymer packed in a restricted volume. Although polymer models of chromatin organization were considered, most of them disregard the fact that DNA has to stay not too entangled in order to function properly. One polymer model with no entanglements is the melt of unknotted unconcatenated rings. Extensive simulations indicate that rings in the melt at large length (monomer numbers) N approach the compact state, with gyration radius scaling as N^1/3, suggesting every ring being compact and segregated from the surrounding rings. The segregation is consistent with the known phenomenon of chromosome territories. Surface exponent β (describing the number of contacts between neighboring rings scaling as N^β) appears only slightly below unity, β 0.95. This suggests that the loop factor (probability to meet for two monomers linear distance s apart) should decay as s^-γ, where γ= 2 - β is slightly above one. The later result is consistent with HiC data on real human interphase chromosomes, and does not contradict to the older FISH data. The dynamics of rings in the melt indicates that the motion of one ring remains subdiffusive on the time scale well above the stress relaxation time.

  10. Testing LSST Dither Strategies for Large-scale Structure Systematics

    NASA Astrophysics Data System (ADS)

    Awan, Humna; Gawiser, Eric J.; Kurczynski, Peter

    2017-01-01

    The Large Synoptic Survey Telescope (LSST) will start a ten-year survey of the southern sky in 2022. Since the telescope observing strategy can lead to artifacts in the observed data, we undertake an investigation of implementing large telescope-pointing offsets (called dithers) as a means to minimize the induced artifacts. We implement various types of dithers, varying in both implementation timescale and the dither geometry, and examine their effects on the r-band coadded depth after the 10-year survey. Then we propagate the depth fluctuations to galaxy counts fluctuations, which are a systematic for large-scale structure studies. We show that the observing strategies induce window function uncertainties which set a constraint on the level of information we can extract from an optimized survey to precisely measure Baryonic Acoustic Oscillations at high redshifts. We find that the best dither strategies lead to window function uncertainties well below the minimum statistical uncertainty after the 10 years of survey, hence not requiring any systematics correction methods. While the systematics level is considerably higher after the first year of the survey, dithering can play a critical role in reducing it. We also explore different cadences, and demonstrate that the best dither strategies minimize the window function uncertainties for various cadences.

  11. Measuring Omega and the real correlation function from the redshift correlation function

    NASA Technical Reports Server (NTRS)

    Hamilton, A. J. S.

    1992-01-01

    Peculiar velocities distort the correlation function of galaxies in redshift space. In the linear regime, the distortion has a characteristic quadrupole plus hexadecapole form. The amplitude of the distortion depends on the cosmological density parameter Omega. Practical formulas are derived here which can be applied to redshift galaxy catalogs to measure Omega in the linear regime. The formulas also yield the real underlying correlation function in the linear regime, corrected for peculiar velocities.

  12. Distribution probability of large-scale landslides in central Nepal

    NASA Astrophysics Data System (ADS)

    Timilsina, Manita; Bhandary, Netra P.; Dahal, Ranjan Kumar; Yatabe, Ryuichi

    2014-12-01

    Large-scale landslides in the Himalaya are defined as huge, deep-seated landslide masses that occurred in the geological past. They are widely distributed in the Nepal Himalaya. The steep topography and high local relief provide high potential for such failures, whereas the dynamic geology and adverse climatic conditions play a key role in the occurrence and reactivation of such landslides. The major geoscientific problems related with such large-scale landslides are 1) difficulties in their identification and delineation, 2) sources of small-scale failures, and 3) reactivation. Only a few scientific publications have been published concerning large-scale landslides in Nepal. In this context, the identification and quantification of large-scale landslides and their potential distribution are crucial. Therefore, this study explores the distribution of large-scale landslides in the Lesser Himalaya. It provides simple guidelines to identify large-scale landslides based on their typical characteristics and using a 3D schematic diagram. Based on the spatial distribution of landslides, geomorphological/geological parameters and logistic regression, an equation of large-scale landslide distribution is also derived. The equation is validated by applying it to another area. For the new area, the area under the receiver operating curve of the landslide distribution probability in the new area is 0.699, and a distribution probability value could explain > 65% of existing landslides. Therefore, the regression equation can be applied to areas of the Lesser Himalaya of central Nepal with similar geological and geomorphological conditions.

  13. Unified Green's Function Retrieval by Cross Correlation

    SciTech Connect

    Wapenaar, Kees; Slob, Evert; Snieder, Roel

    2006-12-08

    It has been shown by many authors that the cross correlation of two recordings of a diffuse wave field at different receivers yields the Green's function between these receivers. Recently the theory has been extended for situations where time-reversal invariance does not hold (e.g., in attenuating media) and where source-receiver reciprocity breaks down (in moving fluids). Here we present a unified theory for Green's function retrieval that captures all these situations and, because of the unified form, readily extends to more complex situations, such as electrokinetic Green's function retrieval in poroelastic or piezoelectric media. The unified theory has a wide range of applications in ''remote sensing without a source.''.

  14. A coarse grained perturbation theory for the Large Scale Structure, with cosmology and time independence in the UV

    SciTech Connect

    Manzotti, Alessandro; Peloso, Marco; Pietroni, Massimo; Viel, Matteo; Villaescusa-Navarro, Francisco E-mail: peloso@physics.umn.edu E-mail: viel@oats.inaf.it

    2014-09-01

    Standard cosmological perturbation theory (SPT) for the Large Scale Structure (LSS) of the Universe fails at small scales (UV) due to strong nonlinearities and to multistreaming effects. In ref. [1] a new framework was proposed in which the large scales (IR) are treated perturbatively while the information on the UV, mainly small scale velocity dispersion, is obtained by nonlinear methods like N-body simulations. Here we develop this approach, showing that it is possible to reproduce the fully nonlinear power spectrum (PS) by combining a simple (and fast) 1-loop computation for the IR scales and the measurement of a single, dominant, correlator from N-body simulations for the UV ones. We measure this correlator for a suite of seven different cosmologies, and we show that its inclusion in our perturbation scheme reproduces the fully non-linear PS with percent level accuracy, for wave numbers up to k∼ 0.4 h Mpc{sup -1} down to 0z=. We then show that, once this correlator has been measured in a given cosmology, there is no need to run a new simulation for a different cosmology in the suite. Indeed, by rescaling this correlator by a proper function computable in SPT, the reconstruction procedure works also for the other cosmologies and for all redshifts, with comparable accuracy. Finally, we clarify the relation of this approach to the Effective Field Theory methods recently proposed in the LSS context.

  15. Decoupling local mechanics from large-scale structure in modular metamaterials.

    PubMed

    Yang, Nan; Silverberg, Jesse L

    2017-04-04

    A defining feature of mechanical metamaterials is that their properties are determined by the organization of internal structure instead of the raw fabrication materials. This shift of attention to engineering internal degrees of freedom has coaxed relatively simple materials into exhibiting a wide range of remarkable mechanical properties. For practical applications to be realized, however, this nascent understanding of metamaterial design must be translated into a capacity for engineering large-scale structures with prescribed mechanical functionality. Thus, the challenge is to systematically map desired functionality of large-scale structures backward into a design scheme while using finite parameter domains. Such "inverse design" is often complicated by the deep coupling between large-scale structure and local mechanical function, which limits the available design space. Here, we introduce a design strategy for constructing 1D, 2D, and 3D mechanical metamaterials inspired by modular origami and kirigami. Our approach is to assemble a number of modules into a voxelized large-scale structure, where the module's design has a greater number of mechanical design parameters than the number of constraints imposed by bulk assembly. This inequality allows each voxel in the bulk structure to be uniquely assigned mechanical properties independent from its ability to connect and deform with its neighbors. In studying specific examples of large-scale metamaterial structures we show that a decoupling of global structure from local mechanical function allows for a variety of mechanically and topologically complex designs.

  16. New angles on energy correlation functions

    NASA Astrophysics Data System (ADS)

    Moult, Ian; Necib, Lina; Thaler, Jesse

    2016-12-01

    Jet substructure observables, designed to identify specific features within jets, play an essential role at the Large Hadron Collider (LHC), both for searching for signals beyond the Standard Model and for testing QCD in extreme phase space regions. In this paper, we systematically study the structure of infrared and collinear safe substructure observables, defining a generalization of the energy correlation functions to probe n-particle correlations within a jet. These generalized correlators provide a flexible basis for constructing new substructure observables optimized for specific purposes. Focusing on three major targets of the jet substructure community — boosted top tagging, boosted W/Z/H tagging, and quark/gluon discrimination — we use power-counting techniques to identify three new series of powerful discriminants: M i , N i , and U i . The M i series is designed for use on groomed jets, providing a novel example of observables with improved discrimination power after the removal of soft radiation. The N i series behave parametrically like the N -subjettiness ratio observables, but are defined without respect to subjet axes, exhibiting improved behavior in the unresolved limit. Finally, the U i series improves quark/gluon discrimination by using higher-point correlators to simultaneously probe multiple emissions within a jet. Taken together, these observables broaden the scope for jet substructure studies at the LHC.

  17. The small-world organization of large-scale brain systems and relationships with subcortical structures.

    PubMed

    Koziol, Leonard F; Barker, Lauren A; Joyce, Arthur W; Hrin, Skip

    2014-01-01

    Brain structure and function is characterized by large-scale brain systems. However, each system has its own "small-world" organization, with sub-regions, or "hubs," that have varying degrees of specialization for certain cognitive and behavioral processes. This article describes this small-world organization, and the concepts of functional specialization and functional integration are defined and explained through practical examples. We also describe the development of large-scale brain systems and this small-world organization as a sensitive, protracted process, vulnerable to a variety of influences that generate neurodevelopmental disorders.

  18. Analyzing the cosmic variance limit of remote dipole measurements of the cosmic microwave background using the large-scale kinetic Sunyaev Zel'dovich effect

    NASA Astrophysics Data System (ADS)

    Terrana, Alexandra; Harris, Mary-Jean; Johnson, Matthew C.

    2017-02-01

    Due to cosmic variance we cannot learn any more about large-scale inhomogeneities from the primary cosmic microwave background (CMB) alone. More information on large scales is essential for resolving large angular scale anomalies in the CMB. Here we consider cross correlating the large-scale kinetic Sunyaev Zel'dovich (kSZ) effect and probes of large-scale structure, a technique known as kSZ tomography. The statistically anisotropic component of the cross correlation encodes the CMB dipole as seen by free electrons throughout the observable Universe, providing information about long wavelength inhomogeneities. We compute the large angular scale power asymmetry, constructing the appropriate transfer functions, and estimate the cosmic variance limited signal to noise for a variety of redshift bin configurations. The signal to noise is significant over a large range of power multipoles and numbers of bins. We present a simple mode counting argument indicating that kSZ tomography can be used to estimate more modes than the primary CMB on comparable scales. A basic forecast indicates that a first detection could be made with next-generation CMB experiments and galaxy surveys. This paper motivates a more systematic investigation of how close to the cosmic variance limit it will be possible to get with future observations.

  19. Large-scale Chromosomal Movements During Interphase Progression in Drosophila

    PubMed Central

    Csink, Amy K.; Henikoff, Steven

    1998-01-01

    We examined the effect of cell cycle progression on various levels of chromosome organization in Drosophila. Using bromodeoxyuridine incorporation and DNA quantitation in combination with fluorescence in situ hybridization, we detected gross chromosomal movements in diploid interphase nuclei of larvae. At the onset of S-phase, an increased separation was seen between proximal and distal positions of a long chromsome arm. Progression through S-phase disrupted heterochromatic associations that have been correlated with gene silencing. Additionally, we have found that large-scale G1 nuclear architecture is continually dynamic. Nuclei display a Rabl configuration for only ∼2 h after mitosis, and with further progression of G1-phase can establish heterochromatic interactions between distal and proximal parts of the chromosome arm. We also find evidence that somatic pairing of homologous chromosomes is disrupted during S-phase more rapidly for a euchromatic than for a heterochromatic region. Such interphase chromosome movements suggest a possible mechanism that links gene regulation via nuclear positioning to the cell cycle: delayed maturation of heterochromatin during G1-phase delays establishment of a silent chromatin state. PMID:9763417

  20. Adaptive Texture Synthesis for Large Scale City Modeling

    NASA Astrophysics Data System (ADS)

    Despine, G.; Colleu, T.

    2015-02-01

    Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

  1. Ectopically tethered CP190 induces large-scale chromatin decondensation

    NASA Astrophysics Data System (ADS)

    Ahanger, Sajad H.; Günther, Katharina; Weth, Oliver; Bartkuhn, Marek; Bhonde, Ramesh R.; Shouche, Yogesh S.; Renkawitz, Rainer

    2014-01-01

    Insulator mediated alteration in higher-order chromatin and/or nucleosome organization is an important aspect of epigenetic gene regulation. Recent studies have suggested a key role for CP190 in such processes. In this study, we analysed the effects of ectopically tethered insulator factors on chromatin structure and found that CP190 induces large-scale decondensation when targeted to a condensed lacO array in mammalian and Drosophila cells. In contrast, dCTCF alone, is unable to cause such a decondensation, however, when CP190 is present, dCTCF recruits it to the lacO array and mediates chromatin unfolding. The CP190 induced opening of chromatin may not be correlated with transcriptional activation, as binding of CP190 does not enhance luciferase activity in reporter assays. We propose that CP190 may mediate histone modification and chromatin remodelling activity to induce an open chromatin state by its direct recruitment or targeting by a DNA binding factor such as dCTCF.

  2. Simulation of fatigue crack growth under large scale yielding conditions

    NASA Astrophysics Data System (ADS)

    Schweizer, Christoph; Seifert, Thomas; Riedel, Hermann

    2010-07-01

    A simple mechanism based model for fatigue crack growth assumes a linear correlation between the cyclic crack-tip opening displacement (ΔCTOD) and the crack growth increment (da/dN). The objective of this work is to compare analytical estimates of ΔCTOD with results of numerical calculations under large scale yielding conditions and to verify the physical basis of the model by comparing the predicted and the measured evolution of the crack length in a 10%-chromium-steel. The material is described by a rate independent cyclic plasticity model with power-law hardening and Masing behavior. During the tension-going part of the cycle, nodes at the crack-tip are released such that the crack growth increment corresponds approximately to the crack-tip opening. The finite element analysis performed in ABAQUS is continued for so many cycles until a stabilized value of ΔCTOD is reached. The analytical model contains an interpolation formula for the J-integral, which is generalized to account for cyclic loading and crack closure. Both simulated and estimated ΔCTOD are reasonably consistent. The predicted crack length evolution is found to be in good agreement with the behavior of microcracks observed in a 10%-chromium steel.

  3. Calculation of large scale relative permeabilities from stochastic properties of the permeability field and fluid properties

    SciTech Connect

    Lenormand, R.; Thiele, M.R.

    1997-08-01

    The paper describes the method and presents preliminary results for the calculation of homogenized relative permeabilities using stochastic properties of the permeability field. In heterogeneous media, the spreading of an injected fluid is mainly sue to the permeability heterogeneity and viscosity fingering. At large scale, when the heterogeneous medium is replaced by a homogeneous one, we need to introduce a homogenized (or pseudo) relative permeability to obtain the same spreading. Generally, is derived by using fine-grid numerical simulations (Kyte and Berry). However, this operation is time consuming and cannot be performed for all the meshes of the reservoir. We propose an alternate method which uses the information given by the stochastic properties of the field without any numerical simulation. The method is based on recent developments on homogenized transport equations (the {open_quotes}MHD{close_quotes} equation, Lenormand SPE 30797). The MHD equation accounts for the three basic mechanisms of spreading of the injected fluid: (1) Dispersive spreading due to small scale randomness, characterized by a macrodispersion coefficient D. (2) Convective spreading due to large scale heterogeneities (layers) characterized by a heterogeneity factor H. (3) Viscous fingering characterized by an apparent viscosity ration M. In the paper, we first derive the parameters D and H as functions of variance and correlation length of the permeability field. The results are shown to be in good agreement with fine-grid simulations. The are then derived a function of D, H and M. The main result is that this approach lead to a time dependent . Finally, the calculated are compared to the values derived by history matching using fine-grid numerical simulations.

  4. Large-scale analysis of microRNA evolution

    PubMed Central

    2012-01-01

    Background In animals, microRNAs (miRNA) are important genetic regulators. Animal miRNAs appear to have expanded in conjunction with an escalation in complexity during early bilaterian evolution. Their small size and high-degree of similarity makes them challenging for phylogenetic approaches. Furthermore, genomic locations encoding miRNAs are not clearly defined in many species. A number of studies have looked at the evolution of individual miRNA families. However, we currently lack resources for large-scale analysis of miRNA evolution. Results We addressed some of these issues in order to analyse the evolution of miRNAs. We perform syntenic and phylogenetic analysis for miRNAs from 80 animal species. We present synteny maps, phylogenies and functional data for miRNAs across these species. These data represent the basis of our analyses and also act as a resource for the community. Conclusions We use these data to explore the distribution of miRNAs across phylogenetic space, characterise their birth and death, and examine functional relationships between miRNAs and other genes. These data confirm a number of previously reported findings on a larger scale and also offer novel insights into the evolution of the miRNA repertoire in animals, and it’s genomic organization. PMID:22672736

  5. Van Hove correlation functions for identical fermions

    NASA Astrophysics Data System (ADS)

    Macke, Wilhelm; Miesenböck, Helga M.; Hingerl, Kurt; Bachlechner, Martina E.

    1989-02-01

    For a quantum system of identical fermions a partition of the density-density correlation function in its ``self'' and ``distinct'' part is presented. These quantities show different properties than their classical counterparts, e.g., they violate the ``detailed balance'' and are not necessarily real. Nevertheless it can be expected that they will provide a good tool for a better description of the self-motion in many-particle systems and are therefore investigated in second-order perturbation theory of the interparticle potential.

  6. Nuclear correlation functions in lattice QCD

    SciTech Connect

    Detmold, William; Orginos, Konstantinos

    2013-06-01

    We consider the problem of calculating the large number of Wick contractions necessary to compute states with the quantum numbers of many baryons in lattice QCD. We consider a constructive approach and a determinant-based approach and show that these methods allow the required contractions to be performed for certain choices of interpolating operators. Examples of correlation functions computed using these techniques are shown for the quantum numbers of the light nuclei, $^4$He, $^8$Be, $^{12}$C, $^{16}$O and $^{28}$Si.

  7. On soft limits of inflationary correlation functions

    NASA Astrophysics Data System (ADS)

    Assassi, Valentin; Baumann, Daniel; Green, Daniel

    2012-11-01

    Soft limits of inflationary correlation functions are both observationally relevant and theoretically robust. Various theorems can be proven about them that are insensitive to detailed model-building assumptions. In this paper, we re-derive several of these theorems in a universal way. Our method makes manifest why soft limits are such an interesting probe of the spectrum of additional light fields during inflation. We illustrate these abstract results with a detailed case study of the soft limits of quasi-single-field inflation.

  8. Pair correlation function for spin glasses

    NASA Astrophysics Data System (ADS)

    Fernández, Julio F.; Alonso, Juan J.

    2012-10-01

    We extract a pair correlation function (PCF) from probability distributions of the spin-overlap parameter q. The distributions come from Monte Carlo simulations. A measure, w, of the thermal fluctuations of magnetic patterns follows from the PCFs. We also obtain rms deviations (over different system samples) δp away from average probabilities for q. For the linear system sizes L that we have studied, w and δp are independent of L in the Edwards-Anderson model but scale as 1/L and L, respectively, in the Sherrington-Kirkpatrick model.

  9. MESON CORRELATION FUNCTIONS AT HIGH TEMPERATURES.

    SciTech Connect

    WISSEL, S.; DATTA, S.; KARSCH, F.; LAERMANN, E.; SHCHEREDIN, S.

    2005-07-25

    We present preliminary results for the correlation- and spectral functions of different meson channels on the lattice. The main focus lies on gaining control over cut-off as well as on the finite-volume effects. Extrapolations of screening masses above the deconfining temperature are guided by the result of the free (T = {infinity}) case on the lattice and in the continuum. We study the quenched non-perturbatively improved Wilson-clover fermion as well as the hypercube fermion action which might show less cut-off effects.

  10. Learning networks for sustainable, large-scale improvement.

    PubMed

    McCannon, C Joseph; Perla, Rocco J

    2009-05-01

    Large-scale improvement efforts known as improvement networks offer structured opportunities for exchange of information and insights into the adaptation of clinical protocols to a variety of settings.

  11. Modified gravity and large scale flows, a review

    NASA Astrophysics Data System (ADS)

    Mould, Jeremy

    2017-02-01

    Large scale flows have been a challenging feature of cosmography ever since galaxy scaling relations came on the scene 40 years ago. The next generation of surveys will offer a serious test of the standard cosmology.

  12. Needs, opportunities, and options for large scale systems research

    SciTech Connect

    Thompson, G.L.

    1984-10-01

    The Office of Energy Research was recently asked to perform a study of Large Scale Systems in order to facilitate the development of a true large systems theory. It was decided to ask experts in the fields of electrical engineering, chemical engineering and manufacturing/operations research for their ideas concerning large scale systems research. The author was asked to distribute a questionnaire among these experts to find out their opinions concerning recent accomplishments and future research directions in large scale systems research. He was also requested to convene a conference which included three experts in each area as panel members to discuss the general area of large scale systems research. The conference was held on March 26--27, 1984 in Pittsburgh with nine panel members, and 15 other attendees. The present report is a summary of the ideas presented and the recommendations proposed by the attendees.

  13. Matrix elements from moments of correlation functions

    SciTech Connect

    Chang, Chia Cheng; Bouchard, Chris; Orginos, Konstantinos; Richards, David G.

    2016-10-01

    Momentum-space derivatives of matrix elements can be related to their coordinate-space moments through the Fourier transform. We derive these expressions as a function of momentum transfer Q2 for asymptotic in/out states consisting of a single hadron. We calculate corrections to the finite volume moments by studying the spatial dependence of the lattice correlation functions. This method permits the computation of not only the values of matrix elements at momenta accessible on the lattice, but also the momentum-space derivatives, providing {\\it a priori} information about the Q2 dependence of form factors. As a specific application we use the method, at a single lattice spacing and with unphysically heavy quarks, to directly obtain the slope of the isovector form factor at various Q2, whence the isovector charge radius. The method has potential application in the calculation of any hadronic matrix element with momentum transfer, including those relevant to hadronic weak decays.

  14. Bayesian hierarchical model for large-scale covariance matrix estimation.

    PubMed

    Zhu, Dongxiao; Hero, Alfred O

    2007-12-01

    Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.

  15. A study of MLFMA for large-scale scattering problems

    NASA Astrophysics Data System (ADS)

    Hastriter, Michael Larkin

    This research is centered in computational electromagnetics with a focus on solving large-scale problems accurately in a timely fashion using first principle physics. Error control of the translation operator in 3-D is shown. A parallel implementation of the multilevel fast multipole algorithm (MLFMA) was studied as far as parallel efficiency and scaling. The large-scale scattering program (LSSP), based on the ScaleME library, was used to solve ultra-large-scale problems including a 200lambda sphere with 20 million unknowns. As these large-scale problems were solved, techniques were developed to accurately estimate the memory requirements. Careful memory management is needed in order to solve these massive problems. The study of MLFMA in large-scale problems revealed significant errors that stemmed from inconsistencies in constants used by different parts of the algorithm. These were fixed to produce the most accurate data possible for large-scale surface scattering problems. Data was calculated on a missile-like target using both high frequency methods and MLFMA. This data was compared and analyzed to determine possible strategies to increase data acquisition speed and accuracy through multiple computation method hybridization.

  16. Probing for Dark Energy Perturbations using the CMB and Large Scale Structure?

    NASA Astrophysics Data System (ADS)

    Bean, Rachel; Doré, Olivier

    2004-12-01

    We review the implications of having a non-trivial matter component in the universe and the potential for detecting such a component through the matter power spectrum and ISW effect. We adopt a phenomenological approach and consider the mysterious dark energy to be a cosmic fluid. It is thus fully characterized, up to linear order, by its equation of state and its speed of sound. Whereas the equation of state has been widely studied in the literature, less interest has been devoted to the speed of sound. Its observational consequences come predominantly from very large scale modes of dark matter perturbations (k < 0.01hMpc-1). Since these modes have hardly been probed so far by large scale galaxy surveys, we investigate whether joint constraints that can be placed on those two quantities using the recent CMB fluctuations measurements by WMAP as well as the recently measured CMB large scale structure cross-correlation.

  17. Large scale baroclinic instability of the mean oceanic circulation: a local approach

    NASA Astrophysics Data System (ADS)

    Hochet, Antoine; Huck, Thierry; de Verdière, Alain Colin

    2016-04-01

    Large scale baroclinic instability is investigated as a potential source of Rossby waves and large scale variability in the ocean. This baroclinic instability is first reviewed in a two and a half layer model. As already noticed by several authors, the instability arises in westward surface mean flow when the phase velocities of the two vertical modes are made equal by mean flow influence. This large scale instability is stronger at low latitudes and thus is likely to happen in the westward return flow of the subtropical gyres. Further investigations with a continuous stratification quasi-geostrophic model show that the instability is stronger where the mean flow projects negatively on the second baroclinic mode (imposing positive vertical modes at the surface). The linear stability calculation is then performed on ARGO derived mean flow along with mean stratification data. The results show that the unstable regions are situated at low latitudes in every oceanic basin, in Western boundary currents and in some part of the Antarctic Circumpolar Current. The location of these unstable regions is well correlated with the region of negative projection of the mean flow on the second baroclinic mode. Given that the unstable mode growth times are generally smaller than six months at low latitudes, these unstable modes are likely to be observable in satellite altimetry. Therefore, results of the present article suggest that the large scale instability is indeed a source of large scale variability at low latitudes.

  18. Large scale stochastic spatio-temporal modelling with PCRaster

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.

    2013-04-01

    software from the eScience Technology Platform (eSTeP), developed at the Netherlands eScience Center. This will allow us to scale up to hundreds of machines, with thousands of compute cores. A key requirement is not to change the user experience of the software. PCRaster operations and the use of the Python framework classes should work in a similar manner on machines ranging from a laptop to a supercomputer. This enables a seamless transfer of models from small machines, where model development is done, to large machines used for large-scale model runs. Domain specialists from a large range of disciplines, including hydrology, ecology, sedimentology, and land use change studies, currently use the PCRaster Python software within research projects. Applications include global scale hydrological modelling and error propagation in large-scale land use change models. The software runs on MS Windows, Linux operating systems, and OS X.

  19. Ferroelectric opening switches for large-scale pulsed power drivers.

    SciTech Connect

    Brennecka, Geoffrey L.; Rudys, Joseph Matthew; Reed, Kim Warren; Pena, Gary Edward; Tuttle, Bruce Andrew; Glover, Steven Frank

    2009-11-01

    Fast electrical energy storage or Voltage-Driven Technology (VDT) has dominated fast, high-voltage pulsed power systems for the past six decades. Fast magnetic energy storage or Current-Driven Technology (CDT) is characterized by 10,000 X higher energy density than VDT and has a great number of other substantial advantages, but it has all but been neglected for all of these decades. The uniform explanation for neglect of CDT technology is invariably that the industry has never been able to make an effective opening switch, which is essential for the use of CDT. Most approaches to opening switches have involved plasma of one sort or another. On a large scale, gaseous plasmas have been used as a conductor to bridge the switch electrodes that provides an opening function when the current wave front propagates through to the output end of the plasma and fully magnetizes the plasma - this is called a Plasma Opening Switch (POS). Opening can be triggered in a POS using a magnetic field to push the plasma out of the A-K gap - this is called a Magnetically Controlled Plasma Opening Switch (MCPOS). On a small scale, depletion of electron plasmas in semiconductor devices is used to affect opening switch behavior, but these devices are relatively low voltage and low current compared to the hundreds of kilo-volts and tens of kilo-amperes of interest to pulsed power. This work is an investigation into an entirely new approach to opening switch technology that utilizes new materials in new ways. The new materials are Ferroelectrics and using them as an opening switch is a stark contrast to their traditional applications in optics and transducer applications. Emphasis is on use of high performance ferroelectrics with the objective of developing an opening switch that would be suitable for large scale pulsed power applications. Over the course of exploring this new ground, we have discovered new behaviors and properties of these materials that were here to fore unknown. Some of

  20. Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval.

    PubMed

    Xu, Xing; Shen, Fumin; Yang, Yang; Shen, Heng Tao; Li, Xuelong

    2017-05-01

    Hashing based methods have attracted considerable attention for efficient cross-modal retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to learn compact binary codes that construct the underlying correlations between heterogeneous features from different modalities. A majority of recent approaches aim at learning hash functions to preserve the pairwise similarities defined by given class labels. However, these methods fail to explicitly explore the discriminative property of class labels during hash function learning. In addition, they usually discard the discrete constraints imposed on the to-be-learned binary codes, and compromise to solve a relaxed problem with quantization to obtain the approximate binary solution. Therefore, the binary codes generated by these methods are suboptimal and less discriminative to different classes. To overcome these drawbacks, we propose a novel cross-modal hashing method, termed discrete cross-modal hashing (DCH), which directly learns discriminative binary codes while retaining the discrete constraints. Specifically, DCH learns modality-specific hash functions for generating unified binary codes, and these binary codes are viewed as representative features for discriminative classification with class labels. An effective discrete optimization algorithm is developed for DCH to jointly learn the modality-specific hash function and the unified binary codes. Extensive experiments on three benchmark data sets highlight the superiority of DCH under various cross-modal scenarios and show its state-of-the-art performance.

  1. Constraints on the dark energy dipole from large-scale structures

    NASA Astrophysics Data System (ADS)

    Hurier, G.

    2016-11-01

    The high-significance measurement of large-scale structure signals enables testing the isotropy of the Universe. The measurement of cosmological parameters through the large-scale distribution of matter is now a mature domain. This approach is mainly limited by our knowledge of astrophysical processes that are used to observe the large-scale structure. However, when we assume that these astrophysical processes are the same across the Universe, then it is possible to tightly constrain the isotropy of cosmological parameters across the sky. Particularly the X-SZ cross-correlation has been shown to be a probe of the large scale structures that has a high signal-to-noise ratio and low bias. For this analysis, we used a localized measurement of the X-SZ cross-correlation as a test of the cosmological parameter isotropy. Using the scatter of the X-SZ cross-correlation across the sky, we derive cosmological constraints σ8(Ωm/ 0.28)0.34 = 0.78 ± 0.02 and tight isotropy constraints on the dark energy dipole ΔΩΛ < 0.07 at 95% confidence level.

  2. Large-Scale Spray Releases: Initial Aerosol Test Results

    SciTech Connect

    Schonewill, Philip P.; Gauglitz, Phillip A.; Bontha, Jagannadha R.; Daniel, Richard C.; Kurath, Dean E.; Adkins, Harold E.; Billing, Justin M.; Burns, Carolyn A.; Davis, James M.; Enderlin, Carl W.; Fischer, Christopher M.; Jenks, Jeromy WJ; Lukins, Craig D.; MacFarlan, Paul J.; Shutthanandan, Janani I.; Smith, Dennese M.

    2012-12-01

    One of the events postulated in the hazard analysis at the Waste Treatment and Immobilization Plant (WTP) and other U.S. Department of Energy (DOE) nuclear facilities is a breach in process piping that produces aerosols with droplet sizes in the respirable range. The current approach for predicting the size and concentration of aerosols produced in a spray leak involves extrapolating from correlations reported in the literature. These correlations are based on results obtained from small engineered spray nozzles using pure liquids with Newtonian fluid behavior. The narrow ranges of physical properties on which the correlations are based do not cover the wide range of slurries and viscous materials that will be processed in the WTP and across processing facilities in the DOE complex. Two key technical areas were identified where testing results were needed to improve the technical basis by reducing the uncertainty due to extrapolating existing literature results. The first technical need was to quantify the role of slurry particles in small breaches where the slurry particles may plug and result in substantially reduced, or even negligible, respirable fraction formed by high-pressure sprays. The second technical need was to determine the aerosol droplet size distribution and volume from prototypic breaches and fluids, specifically including sprays from larger breaches with slurries where data from the literature are scarce. To address these technical areas, small- and large-scale test stands were constructed and operated with simulants to determine aerosol release fractions and generation rates from a range of breach sizes and geometries. The properties of the simulants represented the range of properties expected in the WTP process streams and included water, sodium salt solutions, slurries containing boehmite or gibbsite, and a hazardous chemical simulant. The effect of anti-foam agents was assessed with most of the simulants. Orifices included round holes and

  3. Intensive agriculture erodes β-diversity at large scales.

    PubMed

    Karp, Daniel S; Rominger, Andrew J; Zook, Jim; Ranganathan, Jai; Ehrlich, Paul R; Daily, Gretchen C

    2012-09-01

    Biodiversity is declining from unprecedented land conversions that replace diverse, low-intensity agriculture with vast expanses under homogeneous, intensive production. Despite documented losses of species richness, consequences for β-diversity, changes in community composition between sites, are largely unknown, especially in the tropics. Using a 10-year data set on Costa Rican birds, we find that low-intensity agriculture sustained β-diversity across large scales on a par with forest. In high-intensity agriculture, low local (α) diversity inflated β-diversity as a statistical artefact. Therefore, at small spatial scales, intensive agriculture appeared to retain β-diversity. Unlike in forest or low-intensity systems, however, high-intensity agriculture also homogenised vegetation structure over large distances, thereby decoupling the fundamental ecological pattern of bird communities changing with geographical distance. This ~40% decline in species turnover indicates a significant decline in β-diversity at large spatial scales. These findings point the way towards multi-functional agricultural systems that maintain agricultural productivity while simultaneously conserving biodiversity.

  4. Assessing large-scale wildlife responses to human infrastructure development

    PubMed Central

    Torres, Aurora; Jaeger, Jochen A. G.; Alonso, Juan Carlos

    2016-01-01

    Habitat loss and deterioration represent the main threats to wildlife species, and are closely linked to the expansion of roads and human settlements. Unfortunately, large-scale effects of these structures remain generally overlooked. Here, we analyzed the European transportation infrastructure network and found that 50% of the continent is within 1.5 km of transportation infrastructure. We present a method for assessing the impacts from infrastructure on wildlife, based on functional response curves describing density reductions in birds and mammals (e.g., road-effect zones), and apply it to Spain as a case study. The imprint of infrastructure extends over most of the country (55.5% in the case of birds and 97.9% for mammals), with moderate declines predicted for birds (22.6% of individuals) and severe declines predicted for mammals (46.6%). Despite certain limitations, we suggest the approach proposed is widely applicable to the evaluation of effects of planned infrastructure developments under multiple scenarios, and propose an internationally coordinated strategy to update and improve it in the future. PMID:27402749

  5. High-throughput solution processing of large-scale graphene.

    PubMed

    Tung, Vincent C; Allen, Matthew J; Yang, Yang; Kaner, Richard B

    2009-01-01

    The electronic properties of graphene, such as high charge carrier concentrations and mobilities, make it a promising candidate for next-generation nanoelectronic devices. In particular, electrons and holes can undergo ballistic transport on the sub-micrometre scale in graphene and do not suffer from the scale limitations of current MOSFET technologies. However, it is still difficult to produce single-layer samples of graphene and bulk processing has not yet been achieved, despite strenuous efforts to develop a scalable production method. Here, we report a versatile solution-based process for the large-scale production of single-layer chemically converted graphene over the entire area of a silicon/SiO(2) wafer. By dispersing graphite oxide paper in pure hydrazine we were able to remove oxygen functionalities and restore the planar geometry of the single sheets. The chemically converted graphene sheets that were produced have the largest area reported to date (up to 20 x 40 microm), making them far easier to process. Field-effect devices have been fabricated by conventional photolithography, displaying currents that are three orders of magnitude higher than previously reported for chemically produced graphene. The size of these sheets enables a wide range of characterization techniques, including optical microscopy, scanning electron microscopy and atomic force microscopy, to be performed on the same specimen.

  6. High-throughput solution processing of large-scale graphene

    NASA Astrophysics Data System (ADS)

    Tung, Vincent C.; Allen, Matthew J.; Yang, Yang; Kaner, Richard B.

    2009-01-01

    The electronic properties of graphene, such as high charge carrier concentrations and mobilities, make it a promising candidate for next-generation nanoelectronic devices. In particular, electrons and holes can undergo ballistic transport on the sub-micrometre scale in graphene and do not suffer from the scale limitations of current MOSFET technologies. However, it is still difficult to produce single-layer samples of graphene and bulk processing has not yet been achieved, despite strenuous efforts to develop a scalable production method. Here, we report a versatile solution-based process for the large-scale production of single-layer chemically converted graphene over the entire area of a silicon/SiO2 wafer. By dispersing graphite oxide paper in pure hydrazine we were able to remove oxygen functionalities and restore the planar geometry of the single sheets. The chemically converted graphene sheets that were produced have the largest area reported to date (up to 20 × 40 µm), making them far easier to process. Field-effect devices have been fabricated by conventional photolithography, displaying currents that are three orders of magnitude higher than previously reported for chemically produced graphene. The size of these sheets enables a wide range of characterization techniques, including optical microscopy, scanning electron microscopy and atomic force microscopy, to be performed on the same specimen.

  7. River Seepage Conductance in Large-Scale Regional Studies.

    PubMed

    Morel-Seytoux, Hubert J; Miller, Calvin D; Miracapillo, Cinzia; Mehl, Steffen

    2016-12-20

    Flow exchange between surface and groundwater is of great importance be it for beneficial allocation and use of water resources or for the proper exercise of water rights. In large-scale regional studies, most numerical models use coarse grid sizes, which make it difficult to provide an accurate depiction of the phenomenon. In particular, a somewhat arbitrary leakance coefficient in a third type (i.e., Cauchy, General Head) boundary condition is used to calculate the seepage discharge as a function of the difference of head in the river and in the aquifer, whose value is often found by calibration. A different approach is presented to analytically estimate that leakance coefficient. It is shown that a simple equivalence can be deduced from the analytical solution for the empirical coefficient, so that it provides the accuracy of the analytical solution while the model maintains a very coarse grid, treating the water-table aquifer as a single calculation layer. Relating the empirical leakance coefficient to the exact conductance, derived from physical principles, provides a physical basis for the leakance coefficient. Factors such as normalized wetted perimeter, degree of penetration of the river, presence of a clogging layer, and anisotropy can be included with little computational demand. In addition the river coefficient in models such as MODFLOW, for example, can be easily modified when grid size is changed without need for recalibration.

  8. Process control of large-scale finite element simulation software

    SciTech Connect

    Spence, P.A.; Weingarten, L.I.; Schroder, K.; Tung, D.M.; Sheaffer, D.A.

    1996-02-01

    We have developed a methodology for coupling large-scale numerical codes with process control algorithms. Closed-loop simulations were demonstrated using the Sandia-developed finite element thermal code TACO and the commercially available finite element thermal-mechanical code ABAQUS. This new capability enables us to use computational simulations for designing and prototyping advanced process-control systems. By testing control algorithms on simulators before building and testing hardware, enormous time and cost savings can be realized. The need for a closed-loop simulation capability was demonstrated in a detailed design study of a rapid-thermal-processing reactor under development by CVC Products Inc. Using a thermal model of the RTP system as a surrogate for the actual hardware, we were able to generate response data needed for controller design. We then evaluated the performance of both the controller design and the hardware design by using the controller to drive the finite element model. The controlled simulations provided data on wafer temperature uniformity as a function of ramp rate, temperature sensor locations, and controller gain. This information, which is critical to reactor design, cannot be obtained from typical open-loop simulations.

  9. Large-scale clustering of CAGE tag expression data

    PubMed Central

    Shimokawa, Kazuro; Okamura-Oho, Yuko; Kurita, Takio; Frith, Martin C; Kawai, Jun; Carninci, Piero; Hayashizaki, Yoshihide

    2007-01-01

    Background Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. We have identified a huge number of TSSs mapped onto the mouse genome using the cap analysis of gene expression (CAGE) method. The standard hierarchical clustering algorithm, which gives us easily understandable graphical tree images, has difficulties in processing such huge amounts of TSS data and a better method to calculate and display the results is needed. Results We use a combination of hierarchical and non-hierarchical clustering to cluster expression profiles of TSSs based on a large amount of CAGE data to profit from the best of both methods. We processed the genome-wide expression data, including 159,075 TSSs derived from 127 RNA samples of various organs of mouse, and succeeded in categorizing them into 70–100 clusters. The clusters exhibited intriguing biological features: a cluster supergroup with a ubiquitous expression profile, tissue-specific patterns, a distinct distribution of non-coding RNA and functional TSS groups. Conclusion Our approach succeeded in greatly reducing the calculation cost, and is an appropriate solution for analyzing large-scale TSS usage data. PMID:17517134

  10. Tools for Interpreting Large-Scale Protein Profiling in Microbiology

    PubMed Central

    Hendrickson, E. L.; Lamont, R. J.; Hackett, M.

    2009-01-01

    Quantitative proteome analysis of microbial systems generates large datasets that can be difficult and time consuming to interpret. Fortunately, many of the data display and gene clustering tools developed to analyze large transcriptome microarray datasets are also applicable to proteomes. Plots of abundance ratio versus total signal or spectral counts can highlight regions of random error and putative change. Displaying data in the physical order of the genes in the genome sequence can highlight potential operons. At a basic level of transcriptional organization, identifying operons can give insights into regulatory pathways as well as provide corroborating evidence for proteomic results. Classification and clustering algorithms can group proteins together by their abundance changes under different conditions, helping to identify interesting expression patterns, but often work poorly with noisy data like that typically generated in a large-scale proteome analysis. Biological interpretation can be aided more directly by overlaying differential protein abundance data onto metabolic pathways, indicating pathways with altered activities. More broadly, ontology tools detect altered levels of protein abundance for different metabolic pathways, molecular functions and cellular localizations. In practice, pathway analysis and ontology are limited by the level of database curation associated with the organism of interest. PMID:18946006

  11. Large Scale Structure in the Epoch of Reionization

    NASA Astrophysics Data System (ADS)

    Koekemoer, Anton; Mould, Jeremy; Cooke, Jeffrey; Wyithe, Stuart; Lidman, Christopher; Trenti, Michele; Abbott, Tim; Kunder, Andrea; Barone-Nugent, Robert; Tescari, Edoardo; Katsianis, Antonios

    2014-02-01

    We propose to capitalize on the high red sensitivity and large field of view of DECam to detect the brightest and rarest galaxies at z=6-7. Our 2012 results show the signature of large scale structure with wavenumber of order 0.1 inverse Mpc in line with expectations of primordial non-gaussianity. But the signal to noise in one deep field from two nights' data is insufficient for a robust conclusion. Ten nights' data will do the job. These data will also constrain the galaxy contribution to reionization by enabling a tighter constraint on the full galaxy luminosity function, including the faint end. The observations will be executed with a cadence and depth that will enable the detection of super-luminous supernovae at z=6-7. Super-luminous supernovae are a recently observed class of supernovae that are 10-100x more luminous than typical supernovae. This class includes pair- instability supernovae that are a rare, third type of supernova explosion in which only 3 events are known. The proposed observations will greatly extend the current reach of supernovae research, examining their occurrence rate and properties near the epoch of reionization.

  12. Two-point correlation function for Dirichlet L-functions

    NASA Astrophysics Data System (ADS)

    Bogomolny, E.; Keating, J. P.

    2013-03-01

    The two-point correlation function for the zeros of Dirichlet L-functions at a height E on the critical line is calculated heuristically using a generalization of the Hardy-Littlewood conjecture for pairs of primes in arithmetic progression. The result matches the conjectured random-matrix form in the limit as E → ∞ and, importantly, includes finite-E corrections. These finite-E corrections differ from those in the case of the Riemann zeta-function, obtained in Bogomolny and Keating (1996 Phys. Rev. Lett. 77 1472), by certain finite products of primes which divide the modulus of the primitive character used to construct the L-function in question.

  13. Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

    PubMed

    Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

    2016-09-26

    In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication.

  14. Soft-Pion theorems for large scale structure

    NASA Astrophysics Data System (ADS)

    Horn, Bart; Hui, Lam; Xiao, Xiao

    2014-09-01

    Consistency relations — which relate an N-point function to a squeezed (N+1)-point function — are useful in large scale structure (LSS) because of their non-perturbative nature: they hold even if the N-point function is deep in the nonlinear regime, and even if they involve astrophysically messy galaxy observables. The non-perturbative nature of the consistency relations is guaranteed by the fact that they are symmetry statements, in which the velocity plays the role of the soft pion. In this paper, we address two issues: (1) how to derive the relations systematically using the residual coordinate freedom in the Newtonian gauge, and relate them to known results in ζ-gauge (often used in studies of inflation); (2) under what conditions the consistency relations are violated. In the non-relativistic limit, our derivation reproduces the Newtonian consistency relation discovered by Kehagias & Riotto and Peloso & Pietroni. More generally, there is an infinite set of consistency relations, as is known in ζ-gauge. There is a one-to-one correspondence between symmetries in the two gauges; in particular, the Newtonian consistency relation follows from the dilation and special conformal symmetries in ζ-gauge. We probe the robustness of the consistency relations by studying models of galaxy dynamics and biasing. We give a systematic list of conditions under which the consistency relations are violated; violations occur if the galaxy bias is non-local in an infrared divergent way. We emphasize the relevance of the adiabatic mode condition, as distinct from symmetry considerations. As a by-product of our investigation, we discuss a simple fluid Lagrangian for LSS.

  15. Local Large-Scale Structure and the Assumption of Homogeneity

    NASA Astrophysics Data System (ADS)

    Keenan, Ryan C.; Barger, Amy J.; Cowie, Lennox L.

    2016-10-01

    Our recent estimates of galaxy counts and the luminosity density in the near-infrared (Keenan et al. 2010, 2012) indicated that the local universe may be under-dense on radial scales of several hundred megaparsecs. Such a large-scale local under-density could introduce significant biases in the measurement and interpretation of cosmological observables, such as the inferred effects of dark energy on the rate of expansion. In Keenan et al. (2013), we measured the K-band luminosity density as a function of distance from us to test for such a local under-density. We made this measurement over the redshift range 0.01 < z < 0.2 (radial distances D ~ 50 - 800 h 70 -1 Mpc). We found that the shape of the K-band luminosity function is relatively constant as a function of distance and environment. We derive a local (z < 0.07, D < 300 h 70 -1 Mpc) K-band luminosity density that agrees well with previously published studies. At z > 0.07, we measure an increasing luminosity density that by z ~ 0.1 rises to a value of ~ 1.5 times higher than that measured locally. This implies that the stellar mass density follows a similar trend. Assuming that the underlying dark matter distribution is traced by this luminous matter, this suggests that the local mass density may be lower than the global mass density of the universe at an amplitude and on a scale that is sufficient to introduce significant biases into the measurement of basic cosmological observables. At least one study has shown that an under-density of roughly this amplitude and scale could resolve the apparent tension between direct local measurements of the Hubble constant and those inferred by Planck team. Other theoretical studies have concluded that such an under-density could account for what looks like an accelerating expansion, even when no dark energy is present.

  16. Toward correlating functional MRI and EEG sources

    NASA Astrophysics Data System (ADS)

    Singh, Manbir; Khosla, Deepak

    1996-04-01

    Though excellent spatial resolution (on the order of 1 mm) is obtainable in functional MRI (fMRI), its temporal resolution is limited to about 1 second by hemodynamics. On the other hand, magnetoencephalography (MEG) and electroencephalography (EEG) provide millisecond temporal resolution but a relatively crude (on the order of 1 cm) spatial resolution to localized sources. Thus, techniques that could combine the high temporal resolution of MEG or EEG with the high spatial resolution of fMRI would be of great significance in imaging the spatiotemporal distribution of neuronal activation. With the ultimate objective of combining fMRI and EEG activation studies, we have conducted experiments to determine how pixels activated in fMRI correlate with underlying EEG sources in a given subject during visual stimulation. Results of a three-subject study suggest good correlation between the center-of-gravity of activated pixels seen in fMRI and the center-of-gravity of regions localized through EEG measurements.

  17. Measurement of the effects of large scale anisotropy on the small scales of turbulence

    NASA Astrophysics Data System (ADS)

    Wijesinghe, Susantha W. A.

    This thesis reports measurements of anisotropy in a laboratory turbulent flow generated by two oscillating grids. It has recently been identified that SO(3) decomposition of Eulerian structure functions provides a powerful tool for analyzing anisotropy in turbulence. From 3D particle tracks obtained with stereoscpic high speed video, we measure the longitudinal Eulerian structure functions for which SO(3) decomposition becomes a spherical harmonic decomposition. This method allows us to measure the anisotropy in different sectors, specified by j and m of the spherical harmonics Yjm (theta, φ). In order to acquire huge data sets required for the full 3D measurement of anisotropy as a function of scale, we have upgraded the optical tracking system to four high speed cameras with a new real-time image compression system. We achieved compression ratios of 154--614 depending on the number of particles appearing in an image. Anisotropy measurements are performed at three different detection volumes in the tank for two grid frequencies where Reynolds numbers vary from Relambda = 132 to Relambda = 277. Increasing j sectors show faster decay of anisotropy as scale decreases, consistent with the idea that the small scales should become isotropic at very high Reynolds number. Measured anisotropic scaling exponents are also consistent with previous studies performed with numerical simulations and hot wire anemometry. By conditioning the different j sectors on the instantaneous large scale velocity, we are able to quantify the dependence of the anisotropy on the state of the large scales. The isotropic sector shows a strong dependence on the state of the large scales. For the isotropic sector, this strong dependence is the same at all length scales showing that the small scales do not become independent of the large scales and confirms previous work by Blum et al. However, for a given state of the large scales, the anisotropic sector diminishes toward smaller length scales

  18. The Internet As a Large-Scale Complex System

    NASA Astrophysics Data System (ADS)

    Park, Kihong; Willinger, Walter

    2005-06-01

    The Internet may be viewed as a "complex system" with diverse features and many components that can give rise to unexpected emergent phenomena, revealing much about its own engineering. This book brings together chapter contributions from a workshop held at the Santa Fe Institute in March 2001. This volume captures a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area. The Internet penetrates the socioeconomic fabric of everyday life; a broader and deeper grasp of the Internet may be needed to meet the challenges facing the future. The resulting empirical data have already proven to be invaluable for gaining novel insights into the network's spatio-temporal dynamics, and can be expected to become even more important when tryin to explain the Internet's complex and emergent behavior in terms of elementary networking-based mechanisms. The discoveries of fractal or self-similar network traffic traces, power-law behavior in network topology and World Wide Web connectivity are instances of unsuspected, emergent system traits. Another important factor at the heart of fair, efficient, and stable sharing of network resources is user behavior. Network systems, when habited by selfish or greedy users, take on the traits of a noncooperative multi-party game, and their stability and efficiency are integral to understanding the overall system and its dynamics. Lastly, fault-tolerance and robustness of large-scale network systems can exhibit spatial and temporal correlations whose effective analysis and management may benefit from rescaling techniques applied in certain physical and biological systems. The present book will bring together several of the leading workers involved in the analysis of complex systems with the future development of the Internet.

  19. Multi-Resolution Modeling of Large Scale Scientific Simulation Data

    SciTech Connect

    Baldwin, C; Abdulla, G; Critchlow, T

    2002-02-25

    Data produced by large scale scientific simulations, experiments, and observations can easily reach tera-bytes in size. The ability to examine data-sets of this magnitude, even in moderate detail, is problematic at best. Generally this scientific data consists of multivariate field quantities with complex inter-variable correlations and spatial-temporal structure. To provide scientists and engineers with the ability to explore and analyze such data sets we are using a twofold approach. First, we model the data with the objective of creating a compressed yet manageable representation. Second, with that compressed representation, we provide the user with the ability to query the resulting approximation to obtain approximate yet sufficient answers; a process called adhoc querying. This paper is concerned with a wavelet modeling technique that seeks to capture the important physical characteristics of the target scientific data. Our approach is driven by the compression, which is necessary for viable throughput, along with the end user requirements from the discovery process. Our work contrasts existing research which applies wavelets to range querying, change detection, and clustering problems by working directly with a decomposition of the data. The difference in this procedures is due primarily to the nature of the data and the requirements of the scientists and engineers. Our approach directly uses the wavelet coefficients of the data to compress as well as query. We will provide some background on the problem, describe how the wavelet decomposition is used to facilitate data compression and how queries are posed on the resulting compressed model. Results of this process will be shown for several problems of interest and we will end with some observations and conclusions about this research.

  20. Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

    NASA Technical Reports Server (NTRS)

    Over, Thomas, M.; Gupta, Vijay K.

    1994-01-01

    Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

  1. Recursive architecture for large-scale adaptive system

    NASA Astrophysics Data System (ADS)

    Hanahara, Kazuyuki; Sugiyama, Yoshihiko

    1994-09-01

    'Large scale' is one of major trends in the research and development of recent engineering, especially in the field of aerospace structural system. This term expresses the large scale of an artifact in general, however, it also implies the large number of the components which make up the artifact in usual. Considering a large scale system which is especially used in remote space or deep-sea, such a system should be adaptive as well as robust by itself, because its control as well as maintenance by human operators are not easy due to the remoteness. An approach to realizing this large scale, adaptive and robust system is to build the system as an assemblage of components which are respectively adaptive by themselves. In this case, the robustness of the system can be achieved by using a large number of such components and suitable adaptation as well as maintenance strategies. Such a system gathers many research's interest and their studies such as decentralized motion control, configurating algorithm and characteristics of structural elements are reported. In this article, a recursive architecture concept is developed and discussed towards the realization of large scale system which consists of a number of uniform adaptive components. We propose an adaptation strategy based on the architecture and its implementation by means of hierarchically connected processing units. The robustness and the restoration from degeneration of the processing unit are also discussed. Two- and three-dimensional adaptive truss structures are conceptually designed based on the recursive architecture.

  2. EINSTEIN'S SIGNATURE IN COSMOLOGICAL LARGE-SCALE STRUCTURE

    SciTech Connect

    Bruni, Marco; Hidalgo, Juan Carlos; Wands, David

    2014-10-10

    We show how the nonlinearity of general relativity generates a characteristic nonGaussian signal in cosmological large-scale structure that we calculate at all perturbative orders in a large-scale limit. Newtonian gravity and general relativity provide complementary theoretical frameworks for modeling large-scale structure in ΛCDM cosmology; a relativistic approach is essential to determine initial conditions, which can then be used in Newtonian simulations studying the nonlinear evolution of the matter density. Most inflationary models in the very early universe predict an almost Gaussian distribution for the primordial metric perturbation, ζ. However, we argue that it is the Ricci curvature of comoving-orthogonal spatial hypersurfaces, R, that drives structure formation at large scales. We show how the nonlinear relation between the spatial curvature, R, and the metric perturbation, ζ, translates into a specific nonGaussian contribution to the initial comoving matter density that we calculate for the simple case of an initially Gaussian ζ. Our analysis shows the nonlinear signature of Einstein's gravity in large-scale structure.

  3. APoc: large-scale identification of similar protein pockets

    PubMed Central

    Gao, Mu; Skolnick, Jeffrey

    2013-01-01

    Motivation: Most proteins interact with small-molecule ligands such as metabolites or drug compounds. Over the past several decades, many of these interactions have been captured in high-resolution atomic structures. From a geometric point of view, most interaction sites for grasping these small-molecule ligands, as revealed in these structures, form concave shapes, or ‘pockets’, on the protein’s surface. An efficient method for comparing these pockets could greatly assist the classification of ligand-binding sites, prediction of protein molecular function and design of novel drug compounds. Results: We introduce a computational method, APoc (Alignment of Pockets), for the large-scale, sequence order-independent, structural comparison of protein pockets. A scoring function, the Pocket Similarity Score (PS-score), is derived to measure the level of similarity between pockets. Statistical models are used to estimate the significance of the PS-score based on millions of comparisons of randomly related pockets. APoc is a general robust method that may be applied to pockets identified by various approaches, such as ligand-binding sites as observed in experimental complex structures, or predicted pockets identified by a pocket-detection method. Finally, we curate large benchmark datasets to evaluate the performance of APoc and present interesting examples to demonstrate the usefulness of the method. We also demonstrate that APoc has better performance than the geometric hashing-based method SiteEngine. Availability and implementation: The APoc software package including the source code is freely available at http://cssb.biology.gatech.edu/APoc. Contact: skolnick@gatech.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23335017

  4. Spatiotemporal dynamics of large-scale brain activity

    NASA Astrophysics Data System (ADS)

    Neuman, Jeremy

    Understanding the dynamics of large-scale brain activity is a tough challenge. One reason for this is the presence of an incredible amount of complexity arising from having roughly 100 billion neurons connected via 100 trillion synapses. Because of the extremely high number of degrees of freedom in the nervous system, the question of how the brain manages to properly function and remain stable, yet also be adaptable, must be posed. Neuroscientists have identified many ways the nervous system makes this possible, of which synaptic plasticity is possibly the most notable one. On the other hand, it is vital to understand how the nervous system also loses stability, resulting in neuropathological diseases such as epilepsy, a disease which affects 1% of the population. In the following work, we seek to answer some of these questions from two different perspectives. The first uses mean-field theory applied to neuronal populations, where the variables of interest are the percentages of active excitatory and inhibitory neurons in a network, to consider how the nervous system responds to external stimuli, self-organizes and generates epileptiform activity. The second method uses statistical field theory, in the framework of single neurons on a lattice, to study the concept of criticality, an idea borrowed from physics which posits that in some regime the brain operates in a collectively stable or marginally stable manner. This will be examined in two different neuronal networks with self-organized criticality serving as the overarching theme for the union of both perspectives. One of the biggest problems in neuroscience is the question of to what extent certain details are significant to the functioning of the brain. These details give rise to various spatiotemporal properties that at the smallest of scales explain the interaction of single neurons and synapses and at the largest of scales describe, for example, behaviors and sensations. In what follows, we will shed some

  5. Emergence of coherent structures and large-scale flows in motile suspensions.

    PubMed

    Saintillan, David; Shelley, Michael J

    2012-03-07

    The emergence of coherent structures, large-scale flows and correlated dynamics in suspensions of motile particles such as swimming micro-organisms or artificial microswimmers is studied using direct particle simulations. A detailed model is proposed for a slender rod-like particle that propels itself in a viscous fluid by exerting a prescribed tangential stress on its surface, and a method is devised for the efficient calculation of hydrodynamic interactions in large-scale suspensions of such particles using slender-body theory and a smooth particle-mesh Ewald algorithm. Simulations are performed with periodic boundary conditions for various system sizes and suspension volume fractions, and demonstrate a transition to large-scale correlated motions in suspensions of rear-actuated swimmers, or Pushers, above a critical volume fraction or system size. This transition, which is not observed in suspensions of head-actuated swimmers, or Pullers, is seen most clearly in particle velocity and passive tracer statistics. These observations are consistent with predictions from our previous mean-field kinetic theory, one of which states that instabilities will arise in uniform isotropic suspensions of Pushers when the product of the linear system size with the suspension volume fraction exceeds a given threshold. We also find that the collective dynamics of Pushers result in giant number fluctuations, local alignment of swimmers and strongly mixing flows. Suspensions of Pullers, which evince no large-scale dynamics, nonetheless display interesting deviations from the random isotropic state.

  6. Large-scale horizontal flows in the solar photosphere. III. Effects on filament destabilization

    NASA Astrophysics Data System (ADS)

    Roudier, T.; Švanda, M.; Meunier, N.; Keil, S.; Rieutord, M.; Malherbe, J. M.; Rondi, S.; Molodij, G.; Bommier, V.; Schmieder, B.

    2008-03-01

    Aims:We study the influence of large-scale photospheric motions on the destabilization of an eruptive filament, observed on October 6, 7, and 8, 2004, as part of an international observing campaign (JOP 178). Methods: Large-scale horizontal flows were investigated from a series of MDI full-disc Dopplergrams and magnetograms. From the Dopplergrams, we tracked supergranular flow patterns using the local correlation tracking (LCT) technique. We used both LCT and manual tracking of isolated magnetic elements to obtain horizontal velocities from magnetograms. Results: We find that the measured flow fields obtained by the different methods are well-correlated on large scales. The topology of the flow field changed significantly during the filament eruptive phase, suggesting a possible coupling between the surface flow field and the coronal magnetic field. We measured an increase in the shear below the point where the eruption starts and a decrease in shear after the eruption. We find a pattern in the large-scale horizontal flows at the solar surface that interact with differential rotation. Conclusions: We conclude that there is probably a link between changes in surface flow and the disappearance of the eruptive filament.

  7. Modeling the three-point correlation function

    SciTech Connect

    Marin, Felipe; Wechsler, Risa; Frieman, Joshua A.; Nichol, Robert; /Portsmouth U., ICG

    2007-04-01

    We present new theoretical predictions for the galaxy three-point correlation function (3PCF) using high-resolution dissipationless cosmological simulations of a flat {Lambda}CDM Universe which resolve galaxy-size halos and subhalos. We create realistic mock galaxy catalogs by assigning luminosities and colors to dark matter halos and subhalos, and we measure the reduced 3PCF as a function of luminosity and color in both real and redshift space. As galaxy luminosity and color are varied, we find small differences in the amplitude and shape dependence of the reduced 3PCF, at a level qualitatively consistent with recent measurements from the SDSS and 2dFGRS. We confirm that discrepancies between previous 3PCF measurements can be explained in part by differences in binning choices. We explore the degree to which a simple local bias model can fit the simulated 3PCF. The agreement between the model predictions and galaxy 3PCF measurements lends further credence to the straightforward association of galaxies with CDM halos and subhalos.

  8. A method of orbital analysis for large-scale first-principles simulations.

    PubMed

    Ohwaki, Tsukuru; Otani, Minoru; Ozaki, Taisuke

    2014-06-28

    An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF4).

  9. A method of orbital analysis for large-scale first-principles simulations

    NASA Astrophysics Data System (ADS)

    Ohwaki, Tsukuru; Otani, Minoru; Ozaki, Taisuke

    2014-06-01

    An efficient method of calculating the natural bond orbitals (NBOs) based on a truncation of the entire density matrix of a whole system is presented for large-scale density functional theory calculations. The method recovers an orbital picture for O(N) electronic structure methods which directly evaluate the density matrix without using Kohn-Sham orbitals, thus enabling quantitative analysis of chemical reactions in large-scale systems in the language of localized Lewis-type chemical bonds. With the density matrix calculated by either an exact diagonalization or O(N) method, the computational cost is O(1) for the calculation of NBOs associated with a local region where a chemical reaction takes place. As an illustration of the method, we demonstrate how an electronic structure in a local region of interest can be analyzed by NBOs in a large-scale first-principles molecular dynamics simulation for a liquid electrolyte bulk model (propylene carbonate + LiBF4).

  10. Large-scale, high-resolution neurophysiological maps underlying FMRI of macaque temporal lobe.

    PubMed

    Issa, Elias B; Papanastassiou, Alex M; DiCarlo, James J

    2013-09-18

    Maps obtained by functional magnetic resonance imaging (fMRI) are thought to reflect the underlying spatial layout of neural activity. However, previous studies have not been able to directly compare fMRI maps to high-resolution neurophysiological maps, particularly in higher level visual areas. Here, we used a novel stereo microfocal x-ray system to localize thousands of neural recordings across monkey inferior temporal cortex (IT), construct large-scale maps of neuronal object selectivity at subvoxel resolution, and compare those neurophysiology maps with fMRI maps from the same subjects. While neurophysiology maps contained reliable structure at the sub-millimeter scale, fMRI maps of object selectivity contained information at larger scales (>2.5 mm) and were only partly correlated with raw neurophysiology maps collected in the same subjects. However, spatial smoothing of neurophysiology maps more than doubled that correlation, while a variety of alternative transforms led to no significant improvement. Furthermore, raw spiking signals, once spatially smoothed, were as predictive of fMRI maps as local field potential signals. Thus, fMRI of the inferior temporal lobe reflects a spatially low-passed version of neurophysiology signals. These findings strongly validate the widespread use of fMRI for detecting large (>2.5 mm) neuronal domains of object selectivity but show that a complete understanding of even the most pure domains (e.g., faces vs nonface objects) requires investigation at fine scales that can currently only be obtained with invasive neurophysiological methods.

  11. Unified Access Architecture for Large-Scale Scientific Datasets

    NASA Astrophysics Data System (ADS)

    Karna, Risav

    2014-05-01

    Data-intensive sciences have to deploy diverse large scale database technologies for data analytics as scientists have now been dealing with much larger volume than ever before. While array databases have bridged many gaps between the needs of data-intensive research fields and DBMS technologies (Zhang 2011), invocation of other big data tools accompanying these databases is still manual and separate the database management's interface. We identify this as an architectural challenge that will increasingly complicate the user's work flow owing to the growing number of useful but isolated and niche database tools. Such use of data analysis tools in effect leaves the burden on the user's end to synchronize the results from other data manipulation analysis tools with the database management system. To this end, we propose a unified access interface for using big data tools within large scale scientific array database using the database queries themselves to embed foreign routines belonging to the big data tools. Such an invocation of foreign data manipulation routines inside a query into a database can be made possible through a user-defined function (UDF). UDFs that allow such levels of freedom as to call modules from another language and interface back and forth between the query body and the side-loaded functions would be needed for this purpose. For the purpose of this research we attempt coupling of four widely used tools Hadoop (hadoop1), Matlab (matlab1), R (r1) and ScaLAPACK (scalapack1) with UDF feature of rasdaman (Baumann 98), an array-based data manager, for investigating this concept. The native array data model used by an array-based data manager provides compact data storage and high performance operations on ordered data such as spatial data, temporal data, and matrix-based data for linear algebra operations (scidbusr1). Performances issues arising due to coupling of tools with different paradigms, niche functionalities, separate processes and output

  12. Modulation analysis of large-scale discrete vortices.

    PubMed

    Cisneros, Luis A; Minzoni, Antonmaria A; Panayotaros, Panayotis; Smyth, Noel F

    2008-09-01

    The behavior of large-scale vortices governed by the discrete nonlinear Schrödinger equation is studied. Using a discrete version of modulation theory, it is shown how vortices are trapped and stabilized by the self-consistent Peierls-Nabarro potential that they generate in the lattice. Large-scale circular and polygonal vortices are studied away from the anticontinuum limit, which is the limit considered in previous studies. In addition numerical studies are performed on large-scale, straight structures, and it is found that they are s