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Sample records for large-scale correlation function

  1. On soft limits of large-scale structure correlation functions

    NASA Astrophysics Data System (ADS)

    Ben-Dayan, Ido; Konstandin, Thomas; Porto, Rafael A.; Sagunski, Laura

    2015-02-01

    We study soft limits of correlation functions for the density and velocity fields in the theory of structure formation. First, we re-derive the (resummed) consistency conditions at unequal times using the eikonal approximation. These are solely based on symmetry arguments and are therefore universal. Then, we explore the existence of equal-time relations in the soft limit which, on the other hand, depend on the interplay between soft and hard modes. We scrutinize two approaches in the literature: the time-flow formalism, and a background method where the soft mode is absorbed into a locally curved cosmology. The latter has been recently used to set up (angular averaged) `equal-time consistency relations'. We explicitly demonstrate that the time-flow relations and `equal-time consistency conditions' are only fulfilled at the linear level, and fail at next-to-leading order for an Einstein de-Sitter universe. While applied to the velocities both proposals break down beyond leading order, we find that the `equal-time consistency conditions' quantitatively approximates the perturbative results for the density contrast. Thus, we generalize the background method to properly incorporate the effect of curvature in the density and velocity fluctuations on short scales, and discuss the reasons behind this discrepancy. We conclude with a few comments on practical implementations and future directions.

  2. 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.

  3. An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

    PubMed Central

    Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

    2016-01-01

    Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

  4. 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.

  5. Spatial dependence of correlation functions in the decay problem for a passive scalar in a large-scale velocity field

    SciTech Connect

    Vergeles, S. S.

    2006-04-15

    Statistical characteristics of a passive scalar advected by a turbulent velocity field are considered in the decay problem with a low scalar diffusivity {kappa} (large Prandtl number v/{kappa}, where v is kinematic viscosity). A regime in which the scalar correlation length remains smaller than the velocity correlation length is analyzed. The equal-time correlation functions of the scalar field are found to vary according to power laws and have angular singularities reflecting locally layered distribution of the scalar in space.

  6. Do Large-Scale Topological Features Correlate with Flare Properties?

    NASA Astrophysics Data System (ADS)

    DeRosa, Marc L.; Barnes, Graham

    2016-05-01

    In this study, we aim to identify whether the presence or absence of particular topological features in the large-scale coronal magnetic field are correlated with whether a flare is confined or eruptive. To this end, we first determine the locations of null points, spine lines, and separatrix surfaces within the potential fields associated with the locations of several strong flares from the current and previous sunspot cycles. We then validate the topological skeletons against large-scale features in observations, such as the locations of streamers and pseudostreamers in coronagraph images. Finally, we characterize the topological environment in the vicinity of the flaring active regions and identify the trends involving their large-scale topologies and the properties of the associated flares.

  7. Large-scale cortical correlation structure of spontaneous oscillatory activity

    PubMed Central

    Hipp, Joerg F.; Hawellek, David J.; Corbetta, Maurizio; Siegel, Markus; Engel, Andreas K.

    2013-01-01

    Little is known about the brain-wide correlation of electrophysiological signals. Here we show that spontaneous oscillatory neuronal activity exhibits frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography (MEG). Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz), and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency specific power-envelope correlations. PMID:22561454

  8. Ongoing dynamics in large-scale functional connectivity predict perception

    PubMed Central

    Sadaghiani, Sepideh; Poline, Jean-Baptiste; Kleinschmidt, Andreas; D’Esposito, Mark

    2015-01-01

    Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency. PMID:26106164

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

    DOE PAGESBeta

    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

  10. Large-scale functional connectivity networks in the rodent brain.

    PubMed

    Gozzi, Alessandro; Schwarz, Adam J

    2016-02-15

    Resting-state functional Magnetic Resonance Imaging (rsfMRI) of the human brain has revealed multiple large-scale neural networks within a hierarchical and complex structure of coordinated functional activity. These distributed neuroanatomical systems provide a sensitive window on brain function and its disruption in a variety of neuropathological conditions. The study of macroscale intrinsic connectivity networks in preclinical species, where genetic and environmental conditions can be controlled and manipulated with high specificity, offers the opportunity to elucidate the biological determinants of these alterations. While rsfMRI methods are now widely used in human connectivity research, these approaches have only relatively recently been back-translated into laboratory animals. Here we review recent progress in the study of functional connectivity in rodent species, emphasising the ability of this approach to resolve large-scale brain networks that recapitulate neuroanatomical features of known functional systems in the human brain. These include, but are not limited to, a distributed set of regions identified in rats and mice that may represent a putative evolutionary precursor of the human default mode network (DMN). The impact and control of potential experimental and methodological confounds are also critically discussed. Finally, we highlight the enormous potential and some initial application of connectivity mapping in transgenic models as a tool to investigate the neuropathological underpinnings of the large-scale connectional alterations associated with human neuropsychiatric and neurological conditions. We conclude by discussing the translational potential of these methods in basic and applied neuroscience. PMID:26706448

  11. The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological implications of the large-scale two-point correlation function

    NASA Astrophysics Data System (ADS)

    Sánchez, Ariel G.; Scóccola, C. G.; Ross, A. J.; Percival, W.; Manera, M.; Montesano, F.; Mazzalay, X.; Cuesta, A. J.; Eisenstein, D. J.; Kazin, E.; McBride, C. K.; Mehta, K.; Montero-Dorta, A. D.; Padmanabhan, N.; Prada, F.; Rubiño-Martín, J. A.; Tojeiro, R.; Xu, X.; Magaña, M. Vargas; Aubourg, E.; Bahcall, N. A.; Bailey, S.; Bizyaev, D.; Bolton, A. S.; Brewington, H.; Brinkmann, J.; Brownstein, J. R.; Gott, J. Richard; Hamilton, J. C.; Ho, S.; Honscheid, K.; Labatie, A.; Malanushenko, E.; Malanushenko, V.; Maraston, C.; Muna, D.; Nichol, R. C.; Oravetz, D.; Pan, K.; Ross, N. P.; Roe, N. A.; Reid, B. A.; Schlegel, D. J.; Shelden, A.; Schneider, D. P.; Simmons, A.; Skibba, R.; Snedden, S.; Thomas, D.; Tinker, J.; Wake, D. A.; Weaver, B. A.; Weinberg, David H.; White, Martin; Zehavi, I.; Zhao, G.

    2012-09-01

    We obtain constraints on cosmological parameters from the spherically averaged redshift-space correlation function of the CMASS Data Release 9 (DR9) sample of the Baryonic Oscillation Spectroscopic Survey (BOSS). We combine this information with additional data from recent cosmic microwave background (CMB), supernova and baryon acoustic oscillation measurements. Our results show no significant evidence of deviations from the standard flat Λ cold dark matter model, whose basic parameters can be specified by Ωm = 0.285 ± 0.009, 100 Ωb = 4.59 ± 0.09, ns = 0.961 ± 0.009, H0 = 69.4 ± 0.8 km s-1 Mpc-1 and σ8 = 0.80 ± 0.02. The CMB+CMASS combination sets tight constraints on the curvature of the Universe, with Ωk = -0.0043 ± 0.0049, and the tensor-to-scalar amplitude ratio, for which we find r < 0.16 at the 95 per cent confidence level (CL). These data show a clear signature of a deviation from scale invariance also in the presence of tensor modes, with ns < 1 at the 99.7 per cent CL. We derive constraints on the fraction of massive neutrinos of fν < 0.049 (95 per cent CL), implying a limit of ∑mν < 0.51 eV. We find no signature of a deviation from a cosmological constant from the combination of all data sets, with a constraint of wDE = -1.033 ± 0.073 when this parameter is assumed time-independent, and no evidence of a departure from this value when it is allowed to evolve as wDE(a) = w0 + wa(1 - a). The achieved accuracy on our cosmological constraints is a clear demonstration of the constraining power of current cosmological observations.

  12. Development of large-scale functional brain networks in children.

    PubMed

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-07-01

    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

  13. 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

  14. 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. PMID:23353650

  15. 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].

  16. 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.

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

    PubMed

    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. PMID:27494095

  18. Large-scale correlations between QSOs and galaxies - an effect caused by gravitational lensing?

    NASA Astrophysics Data System (ADS)

    Bartelmann, M.; Schneider, P.

    1993-02-01

    Large-scale correlations between Lick galaxies and radio-loud, distant QSOs have been observed and interpreted in terms of gravitational lensing (Fugmann 1990). We argue that, if gravitational lensing is indeed responsible for such correlations, this is a most remarkable observation, and try to understand whether lensing may account for it. To do so, we use the lensing properties of a model for dark matter inhomogeneities on large scales, based on the adhesion approximation, to construct artificial QSO samples. (Model) galaxy counts in the vicinity of the (synthetic) sample QSOs are then subjected to rank-order statistical analyses. We find that statistically significant large-scale correlations between QSOs and galaxies can indeed be caused by gravitational lensing, but the amplitude of this effect depends sensitively on the assumed intrinsic luminosity function of the QSOs, the flux threshold of the (synthetic) sample, and the source redshift. We conclude that gravitational lensing can indeed account for QSO-galaxy associations on angular scales as large as some ten arc minutes. We also find that this effect can only be understood in terms of lensing by dark matter inhomogeneities.

  19. Development of large-scale functional networks over the lifespan.

    PubMed

    Schlee, Winfried; Leirer, Vera; Kolassa, Stephan; Thurm, Franka; Elbert, Thomas; Kolassa, Iris-Tatjana

    2012-10-01

    The development of large-scale functional organization of the human brain across the lifespan is not well understood. Here we used magnetoencephalographic recordings of 53 adults (ages 18-89) to characterize functional brain networks in the resting state. Slow frequencies engage larger networks than higher frequencies and show different development over the lifespan. Networks in the delta (2-4 Hz) frequency range decrease, while networks in the beta/gamma frequency range (> 16 Hz) increase in size with advancing age. Results show that the right frontal lobe and the temporal areas in both hemispheres are important relay stations in the expanding high-frequency networks. Neuropsychological tests confirmed the tendency of cognitive decline with older age. The decrease in visual memory and visuoconstructive functions was strongly associated with the age-dependent enhancement of functional connectivity in both temporal lobes. Using functional network analysis this study elucidates important neuronal principles underlying age-related cognitive decline paving mental deterioration in senescence. PMID:22236372

  20. Functional interactions between large-scale networks during memory search.

    PubMed

    Kragel, James E; Polyn, Sean M

    2015-03-01

    Neuroimaging studies have identified two major large-scale brain networks, the default mode network (DMN) and the dorsal attention network (DAN), which are engaged for internally and externally directed cognitive tasks respectively, and which show anticorrelated activity during cognitively demanding tests and at rest. We identified these brain networks using independent component analysis (ICA) of functional magnetic resonance imaging data, and examined their interactions during the free-recall task, a self-initiated memory search task in which retrieval is performed in the absence of external cues. Despite the internally directed nature of the task, the DAN showed transient engagement in the seconds leading up to successful retrieval. ICA revealed a fractionation of the DMN into 3 components. A posteromedial network increased engagement during memory search, while the two others showed suppressed activity during memory search. Cooperative interactions between this posteromedial network, a right-lateralized frontoparietal control network, and a medial prefrontal network were maintained during memory search. The DAN demonstrated heterogeneous task-dependent shifts in functional coupling with various subnetworks within the DMN. This functional reorganization suggests a broader role of the DAN in the absence of externally directed cognition, and highlights the contribution of the posteromedial network to episodic retrieval. PMID:24084128

  1. Large-Scale Functional Purification of Recombinant HIV-1 Capsid

    PubMed Central

    Jin, Debi; Wong, Melanie; Leavitt, Stephanie; Brendza, Katherine M.; Liu, Xiaohong; Sakowicz, Roman

    2013-01-01

    During human immunodeficiency virus type-1 (HIV-1) virion maturation, capsid proteins undergo a major rearrangement to form a conical core that protects the viral nucleoprotein complexes. Mutations in the capsid sequence that alter the stability of the capsid core are deleterious to viral infectivity and replication. Recently, capsid assembly has become an attractive target for the development of a new generation of anti-retroviral agents. Drug screening efforts and subsequent structural and mechanistic studies require gram quantities of active, homogeneous and pure protein. Conventional means of laboratory purification of Escherichia coli expressed recombinant capsid protein rely on column chromatography steps that are not amenable to large-scale production. Here we present a function-based purification of wild-type and quadruple mutant capsid proteins, which relies on the inherent propensity of capsid protein to polymerize and depolymerize. This method does not require the packing of sizable chromatography columns and can generate double-digit gram quantities of functionally and biochemically well-behaved proteins with greater than 98% purity. We have used the purified capsid protein to characterize two known assembly inhibitors in our in-house developed polymerization assay and to measure their binding affinities. Our capsid purification procedure provides a robust method for purifying large quantities of a key protein in the HIV-1 life cycle, facilitating identification of the next generation anti-HIV agents. PMID:23472130

  2. Large-scale functional purification of recombinant HIV-1 capsid.

    PubMed

    Hung, Magdeleine; Niedziela-Majka, Anita; Jin, Debi; Wong, Melanie; Leavitt, Stephanie; Brendza, Katherine M; Liu, Xiaohong; Sakowicz, Roman

    2013-01-01

    During human immunodeficiency virus type-1 (HIV-1) virion maturation, capsid proteins undergo a major rearrangement to form a conical core that protects the viral nucleoprotein complexes. Mutations in the capsid sequence that alter the stability of the capsid core are deleterious to viral infectivity and replication. Recently, capsid assembly has become an attractive target for the development of a new generation of anti-retroviral agents. Drug screening efforts and subsequent structural and mechanistic studies require gram quantities of active, homogeneous and pure protein. Conventional means of laboratory purification of Escherichia coli expressed recombinant capsid protein rely on column chromatography steps that are not amenable to large-scale production. Here we present a function-based purification of wild-type and quadruple mutant capsid proteins, which relies on the inherent propensity of capsid protein to polymerize and depolymerize. This method does not require the packing of sizable chromatography columns and can generate double-digit gram quantities of functionally and biochemically well-behaved proteins with greater than 98% purity. We have used the purified capsid protein to characterize two known assembly inhibitors in our in-house developed polymerization assay and to measure their binding affinities. Our capsid purification procedure provides a robust method for purifying large quantities of a key protein in the HIV-1 life cycle, facilitating identification of the next generation anti-HIV agents. PMID:23472130

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

    NASA Technical Reports Server (NTRS)

    Frieman, Joshua A.; Gaztanaga, Enrique

    1993-01-01

    The consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear regime are analyzed. Several variations of the standard Omega = 1 cold dark matter model with scale-invariant primordial perturbations were recently introduced to obtain more power on large scales, R(sub p) is approximately 20 h(sup -1) Mpc, e.g., low-matter-density (non-zero 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, etal. It is shown 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 hierarchical amplitudes Q(sub J) at large scales, r is approximately greater than 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.

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

    SciTech Connect

    Frieman, J.A.; Gaztanaga, E.

    1993-06-19

    The authors analyze the consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear 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} {approximately}20 h{sup {minus}1} Mpc, e.g., low-matter-density (non-zero cosmological constant) models, {open_quote}tilted{close_quote} 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. The authors 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 hierarchical amplitudes Q{sub J} at large scales, r {approx_gt} 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.

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

    SciTech Connect

    Frieman, J.A. ); Gaztanaga, E. )

    1993-06-19

    The authors analyze the consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear 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] [approximately]20 h[sup [minus]1] Mpc, e.g., low-matter-density (non-zero cosmological constant) models, [open quote]tilted[close quote] 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. The authors 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 hierarchical amplitudes Q[sub J] at large scales, r [approx gt] 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.

  6. Generating mock data sets for large-scale Lyman-α forest correlation measurements

    SciTech Connect

    Font-Ribera, Andreu; McDonald, Patrick; Miralda-Escudé, Jordi E-mail: pvmcdonald@lbl.gov

    2012-01-01

    Massive spectroscopic surveys of high-redshift quasars yield large numbers of correlated Lyα absorption spectra that can be used to measure large-scale structure. Simulations of these surveys are required to accurately interpret the measurements of correlations and correct for systematic errors. An efficient method to generate mock realizations of Lyα forest surveys is presented which generates a field over the lines of sight to the survey sources only, instead of having to generate it over the entire three-dimensional volume of the survey. The method can be calibrated to reproduce the power spectrum and one-point distribution function of the transmitted flux fraction, as well as the redshift evolution of these quantities, and is easily used for modeling any survey systematic effects. We present an example of how these mock surveys are applied to predict the measurement errors in a survey with similar parameters as the BOSS quasar survey in SDSS-III.

  7. 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. PMID:26165867

  8. 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.

  9. Dynamic competition between large-scale functional networks differentiates fear conditioning and extinction in humans.

    PubMed

    Marstaller, Lars; Burianová, Hana; Reutens, David C

    2016-07-01

    The high evolutionary value of learning when to respond to threats or when to inhibit previously learned associations after changing threat contingencies is reflected in dedicated networks in the animal and human brain. Recent evidence further suggests that adaptive learning may be dependent on the dynamic interaction of meta-stable functional brain networks. However, it is still unclear which functional brain networks compete with each other to facilitate associative learning and how changes in threat contingencies affect this competition. The aim of this study was to assess the dynamic competition between large-scale networks related to associative learning in the human brain by combining a repeated differential conditioning and extinction paradigm with independent component analysis of functional magnetic resonance imaging data. The results (i) identify three task-related networks involved in initial and sustained conditioning as well as extinction, and demonstrate that (ii) the two main networks that underlie sustained conditioning and extinction are anti-correlated with each other and (iii) the dynamic competition between these two networks is modulated in response to changes in associative contingencies. These findings provide novel evidence for the view that dynamic competition between large-scale functional networks differentiates fear conditioning from extinction learning in the healthy brain and suggest that dysfunctional network dynamics might contribute to learning-related neuropsychiatric disorders. PMID:27079532

  10. Correlation of /sup 137/Cs leachability from small-scale to large-scale waste forms

    SciTech Connect

    Morcos, N.; Dayal, R.; Milian, L.; Weiss, A.J.

    1982-01-01

    A study correlating the leachability of /sup 137/Cs from small-scale to large-scale cement forms was performed. The waste forms consisted of (a) organic ion exchange resins incorporated in Portland I cement, with a waste-to-cement ratio of 0.6 and a water-to-cement ratio of 0.4 (as free water) and (b) boric acid waste (12% solution) incorporated in Portland III cement, with a waste-to-cement ratio of 0.7. /sup 137/Cs was added to both waste types prior to solidification. The sample dimensions varied from 1 in. x 1 in. to 22 in. x 22 in. (diameter x height). Leach data extending over a period of 260 days were obtained using a modified IAEA leach test. A method based on semi-infinite plane source diffusion model was applied to interpret the leach data. A derived mathematical expression allows prediction of the amount of /sup 137/Cs leached from the forms as a function of leaching time and waste form dimensions. A reasonably good agreement between the experimental and calculated data was obtained. 4 figures, 6 tables.

  11. Covariance of cross-correlations: towards efficient measures for large-scale structure

    NASA Astrophysics Data System (ADS)

    Smith, Robert E.

    2009-12-01

    We study the covariance of the cross-power spectrum of different tracers for the large-scale structure. We develop the counts-in-cells framework for the multitracer approach, and use this to derive expressions for the full non-Gaussian covariance matrix. We show that for the usual autopower statistic, besides the off-diagonal covariance generated through gravitational mode-coupling, the discreteness of the tracers and their associated sampling distribution can generate strong off-diagonal covariance, and that this becomes the dominant source of covariance as spatial frequencies become larger than the fundamental mode of the survey volume. On comparison with the derived expressions for the cross-power covariance, we show that the off-diagonal terms can be suppressed, if one cross-correlates a high tracer-density sample with a low one. Taking the effective estimator efficiency to be proportional to the signal-to-noise ratio (S/N), we show that, to probe clustering as a function of physical properties of the sample, i.e. cluster mass or galaxy luminosity, the cross-power approach can outperform the autopower one by factors of a few. We confront the theory with measurements of the mass-mass, halo-mass and halo-halo power spectra from a large ensemble of N-body simulations. We show that there is a significant S/N advantage to be gained from using the cross-power approach when studying the bias of rare haloes. The analysis is repeated in configuration space and again S/N improvement is found. We estimate the covariance matrix for these samples, and find strong off-diagonal contributions. The covariance depends on halo mass, with higher mass samples having stronger covariance. In agreement with theory, we show that the covariance is suppressed for the cross-power. This work points the way towards improved estimators for studying the clustering of tracers as a function of their physical properties.

  12. Accelerated Block Preconditioned Gradient method for large scale wave functions calculations in Density Functional Theory

    SciTech Connect

    Fattebert, J.-L.

    2010-01-20

    An Accelerated Block Preconditioned Gradient (ABPG) method is proposed to solve electronic structure problems in Density Functional Theory. This iterative algorithm is designed to solve directly the non-linear Kohn-Sham equations for accurate discretization schemes involving a large number of degrees of freedom. It makes use of an acceleration scheme similar to what is known as RMM-DIIS in the electronic structure community. The method is illustrated with examples of convergence for large scale applications using a finite difference discretization and multigrid preconditioning.

  13. 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.

  14. Moffatt-drift-driven large-scale dynamo due to fluctuations with non-zero correlation times

    NASA Astrophysics Data System (ADS)

    Singh, Nishant K.

    2016-07-01

    We present a theory of large-scale dynamo action in a turbulent flow that has stochastic, zero-mean fluctuations of the $\\alpha$ parameter. Particularly interesting is the possibility of the growth of the mean magnetic field due to Moffatt drift, which is expected to be finite in a statistically anisotropic turbulence. We extend the Kraichnan-Moffatt model to explore effects of finite memory of $\\alpha$ fluctuations, in a spirit similar to that of Sridhar & Singh (2014), hereafter SS14. Using the first-order smoothing approximation, we derive a linear integro-differential equation governing the dynamics of the large-scale magnetic field, which is non-perturbative in the $\\alpha$-correlation time $\\tau_{\\alpha}$. We recover earlier results in the exactly solvable white-noise (WN) limit where the Moffatt drift does not contribute to the dynamo growth/decay. To study finite memory effects, we reduce the integro-differential equation to a partial differential equation by assuming that the $\\tau_{\\alpha}$ be small but nonzero and the large-scale magnetic field is slowly varying. We derive the dispersion relation and provide explicit expression for the growth rate as a function of four independent parameters. When $\\tau_{\\alpha}\

  15. Exploring Large-Scale Cross-Correlation for Teleseismic and Regional Seismic Event Characterization

    NASA Astrophysics Data System (ADS)

    Hauk, T. F.; Dodge, D. A.; Addair, T.; Walter, W. R.; Myers, S. C.; Ford, S. R.; Harris, D. B.; Ruppert, S. D.

    2013-12-01

    The decrease in cost of digital storage space and computation power invites new methods of seismic data processing. At Lawrence Livermore National Laboratory (LLNL), we operate a research database of seismic events and waveforms for nuclear explosion monitoring and other applications. The LLNL database contains several million events associated with more than 330 million waveforms at thousands of stations. We are using this database to explore the power of seismic waveform correlation to quantify signal similarities, to discover new events not in catalogs, and to more accurately locate events and identify source types. The results presented here are preliminary, and apply mostly to a subset of seismicity in Eurasia and North America. Much more remains to be done to understand and make use of these results. We computed the waveform correlation for event pairs in the LLNL database in 15 frequency bands and for 8 phase windows. The correlation coefficient exceeds 0.6 for over 370 million waveform pairs. Overall, about 16% of the events in our waveform database correlate with one or more events on at least one channel. However, at very short distances, this number rises to as high as 55%. At distances > 20 degrees the percent of correlated events ranges from ~1% to 10%. The majority of correlated waveforms are found at relatively small (< 10 degrees) station-event separations in short-period bands. Most correlations at teleseismic distances are in long-period bands. Also, for most events, correlated traces are found at only a few stations. The mean magnitude of correlated events is about 1 unit lower than the mean of the events in our waveform database and the standard deviation of the magnitude difference of correlated events is 0.6. Apparently, large-scale correlation processing is most likely to work well for small events of similar magnitude. We have clustered the correlation results in both short- and long-period bands and have identified 439 long-period and 1333

  16. Correlated z-values and the accuracy of large-scale statistical estimates.

    PubMed

    Efron, Bradley

    2010-09-01

    We consider large-scale studies in which there are hundreds or thousands of correlated cases to investigate, each represented by its own normal variate, typically a z-value. A familiar example is provided by a microarray experiment comparing healthy with sick subjects' expression levels for thousands of genes. This paper concerns the accuracy of summary statistics for the collection of normal variates, such as their empirical cdf or a false discovery rate statistic. It seems like we must estimate an N by N correlation matrix, N the number of cases, but our main result shows that this is not necessary: good accuracy approximations can be based on the root mean square correlation over all N · (N - 1)/2 pairs, a quantity often easily estimated. A second result shows that z-values closely follow normal distributions even under non-null conditions, supporting application of the main theorem. Practical application of the theory is illustrated for a large leukemia microarray study. PMID:21052523

  17. Correlated z-values and the accuracy of large-scale statistical estimates

    PubMed Central

    Efron, Bradley

    2009-01-01

    We consider large-scale studies in which there are hundreds or thousands of correlated cases to investigate, each represented by its own normal variate, typically a z-value. A familiar example is provided by a microarray experiment comparing healthy with sick subjects' expression levels for thousands of genes. This paper concerns the accuracy of summary statistics for the collection of normal variates, such as their empirical cdf or a false discovery rate statistic. It seems like we must estimate an N by N correlation matrix, N the number of cases, but our main result shows that this is not necessary: good accuracy approximations can be based on the root mean square correlation over all N · (N − 1)/2 pairs, a quantity often easily estimated. A second result shows that z-values closely follow normal distributions even under non-null conditions, supporting application of the main theorem. Practical application of the theory is illustrated for a large leukemia microarray study. PMID:21052523

  18. 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…

  19. 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…

  20. 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.

  1. 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. PMID:24579202

  2. 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.

  3. 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.

  4. 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. PMID:26662457

  5. 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. PMID:26741799

  6. RCSLenS: a new estimator for large-scale galaxy-matter correlations

    NASA Astrophysics Data System (ADS)

    Buddendiek, A.; Schneider, P.; Hildebrandt, H.; Blake, C.; Choi, A.; Erben, T.; Heymans, C.; van Waerbeke, L.; Viola, M.; Harnois-Deraps, J.; Koens, L.; Nakajima, R.

    2016-03-01

    We present measurements of the galaxy bias b and the galaxy-matter cross-correlation coefficient r for the Baryon Oscillation Spectroscopic Survey LOWZ luminous red galaxy sample. Using a new statistical weak lensing analysis of the Red Cluster Sequence Lensing Survey (RCSLenS), we find the bias properties of this sample to be higher than previously reported with b=2.45_{-0.05}^{+0.05} and r=1.64_{-0.16}^{+0.17} on scales between 3 and 20 arcmin. We repeat the measurement for angular scales of 20 arcmin ≤ ϑ ≤ 70 arcmin, which yields b=2.39_{-0.07}^{+0.07} and r=1.24_{-0.25}^{+0.26}. This is the first application of a data compression analysis using a complete set of discrete estimators for galaxy-galaxy lensing and galaxy clustering. As cosmological data sets grow, our new method of data compression will become increasingly important in order to interpret joint weak lensing and galaxy clustering measurements and to estimate the data covariance. In future studies, this formalism can be used as a tool to study the large-scale structure of the Universe to yield a precise determination of cosmological parameters.

  7. 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

  8. 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.

  9. 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.

  10. Topological Properties of Combinational Logic Functions for Very Large Scale Integrated Circuits

    NASA Astrophysics Data System (ADS)

    Hiteshue, Elizabeth; Irvin, Kelsey; Lanzerotti, Mary; Vernizzi, Graziano; Kujawski, Joseph; Weatherwax, Allan

    2014-03-01

    This talk presents topological properties of combinational logic functions implemented with basic logic gates. Combinational logic can be implemented in very large scale integrated circuits, including high-performance microprocessors. Prior work has produced an historically-equivalent (HE) interpretation of Mr. E. F. Rent's 1960 memos for today's complex circuitry, an application to modern microprocessors, and topological constraints for electronic circuits. This talk will examine combinational logic blocks which may exhibit different connectivity and will evaluate their topological properties.

  11. 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%.

  12. Rapid separable analysis of higher order correlators in large-scale structure

    NASA Astrophysics Data System (ADS)

    Fergusson, J. R.; Regan, D. M.; Shellard, E. P. S.

    2012-09-01

    We present an efficient separable approach to the estimation and reconstruction of the bispectrum and the trispectrum from observational (or simulated) large-scale structure data. This is developed from general cosmic microwave background (poly)spectra methods that exploit the fact that the bispectrum and trispectrum in the literature can be represented by a separable mode expansion that converges rapidly (with nmax⁡=O(30) terms). The underlying methodology can encompass a wide variety of modal types, including polynomials, trigonometric functions, wavelets, and bins. With an effective grid resolution lmax⁡ (number of particles/grid points N=lmax⁡3), we present a bispectrum estimator that requires only O(nmax⁡×lmax⁡3) operations, along with a corresponding method for direct bispectrum reconstruction. This method is extended to the trispectrum revealing an estimator that requires only O(nmax⁡4/3×lmax⁡3) operations. The complexity in calculating the trispectrum in this method is now involved in the original decomposition and orthogonalization process that need only be performed once for each model. However, for nondiagonal trispectra these processes present little extra difficulty and may be performed in O(lmax⁡4) operations. A discussion of how the methodology may be applied to the quadspectrum is also given. An efficient algorithm for the generation of arbitrary non-Gaussian initial conditions for use in N-body codes using this separable approach is described. This prescription allows for the production of non-Gaussian initial conditions for arbitrary bispectra and trispectra. A brief outline of the key issues involved in parameter estimation, particularly in the nonlinear regime, is also given.

  13. The large-scale correlations of multicell densities and profiles: implications for cosmic variance estimates

    NASA Astrophysics Data System (ADS)

    Codis, Sandrine; Bernardeau, Francis; Pichon, Christophe

    2016-08-01

    In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of their two-point correlation function to the two-point correlation of the underlying dark matter distribution. They describe how cell densities are spatially correlated. They are computed here via the so-called large deviation principle in the quasi-linear regime. Their large-separation limit is presented and successfully compared to simulations for density and density slopes: this regime is shown to be rapidly reached allowing to get sub-percent precision for a wide range of densities and variances. The corresponding asymptotic limit provides an estimate of the cosmic variance of standard concentric cell statistics applied to finite surveys. More generally, no assumption on the separation is required for some specific moments of the two-point statistics, for instance when predicting the generating function of cumulants containing any powers of concentric densities in one location and one power of density at some arbitrary distance from the rest. This exact `one external leg' cumulant generating function is used in particular to probe the rate of convergence of the large-separation approximation.

  14. 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

  15. Large-Scale Brain Network Coupling Predicts Acute Nicotine Abstinence Effects on Craving and Cognitive Function

    PubMed Central

    Lerman, Caryn; Gu, Hong; Loughead, James; Ruparel, Kosha; Yang, Yihong; Stein, Elliot A.

    2014-01-01

    IMPORTANCE Interactions of large-scale brain networks may underlie cognitive dysfunctions in psychiatric and addictive disorders. OBJECTIVES To test the hypothesis that the strength of coupling among 3 large-scale brain networks–salience, executive control, and default mode–will reflect the state of nicotine withdrawal (vs smoking satiety) and will predict abstinence-induced craving and cognitive deficits and to develop a resource allocation index (RAI) that reflects the combined strength of interactions among the 3 large-scale networks. DESIGN, SETTING, AND PARTICIPANTS A within-subject functional magnetic resonance imaging study in an academic medical center compared resting-state functional connectivity coherence strength after 24 hours of abstinence and after smoking satiety. We examined the relationship of abstinence-induced changes in the RAI with alterations in subjective, behavioral, and neural functions. We included 37 healthy smoking volunteers, aged 19 to 61 years, for analyses. INTERVENTIONS Twenty-four hours of abstinence vs smoking satiety. MAIN OUTCOMES AND MEASURES Inter-network connectivity strength (primary) and the relationship with subjective, behavioral, and neural measures of nicotine withdrawal during abstinence vs smoking satiety states (secondary). RESULTS The RAI was significantly lower in the abstinent compared with the smoking satiety states (left RAI, P = .002; right RAI, P = .04), suggesting weaker inhibition between the default mode and salience networks. Weaker inter-network connectivity (reduced RAI) predicted abstinence-induced cravings to smoke (r = −0.59; P = .007) and less suppression of default mode activity during performance of a subsequent working memory task (ventromedial prefrontal cortex, r = −0.66, P = .003; posterior cingulate cortex, r = −0.65, P = .001). CONCLUSIONS AND RELEVANCE Alterations in coupling of the salience and default mode networks and the inability to disengage from the default mode network may

  16. 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

  17. Cholinergic and serotonergic modulations differentially affect large-scale functional networks in the mouse brain.

    PubMed

    Shah, Disha; Blockx, Ines; Keliris, Georgios A; Kara, Firat; Jonckers, Elisabeth; Verhoye, Marleen; Van der Linden, Annemie

    2016-07-01

    Resting-state functional MRI (rsfMRI) is a widely implemented technique used to investigate large-scale topology in the human brain during health and disease. Studies in mice provide additional advantages, including the possibility to flexibly modulate the brain by pharmacological or genetic manipulations in combination with high-throughput functional connectivity (FC) investigations. Pharmacological modulations that target specific neurotransmitter systems, partly mimicking the effect of pathological events, could allow discriminating the effect of specific systems on functional network disruptions. The current study investigated the effect of cholinergic and serotonergic antagonists on large-scale brain networks in mice. The cholinergic system is involved in cognitive functions and is impaired in, e.g., Alzheimer's disease, while the serotonergic system is involved in emotional and introspective functions and is impaired in, e.g., Alzheimer's disease, depression and autism. Specific interest goes to the default-mode-network (DMN), which is studied extensively in humans and is affected in many neurological disorders. The results show that both cholinergic and serotonergic antagonists impaired the mouse DMN-like network similarly, except that cholinergic modulation additionally affected the retrosplenial cortex. This suggests that both neurotransmitter systems are involved in maintaining integrity of FC within the DMN-like network in mice. Cholinergic and serotonergic modulations also affected other functional networks, however, serotonergic modulation impaired the frontal and thalamus networks more extensively. In conclusion, this study demonstrates the utility of pharmacological rsfMRI in animal models to provide insights into the role of specific neurotransmitter systems on functional networks in neurological disorders. PMID:26195064

  18. Highly efficient and large-scale generation of functional dopamine neurons from human embryonic stem cells.

    PubMed

    Cho, Myung Soo; Lee, Young-Eun; Kim, Ji Young; Chung, Seungsoo; Cho, Yoon Hee; Kim, Dae-Sung; Kang, Sang-Moon; Lee, Haksup; Kim, Myung-Hwa; Kim, Jeong-Hoon; Leem, Joong Woo; Oh, Sun Kyung; Choi, Young Min; Hwang, Dong-Youn; Chang, Jin Woo; Kim, Dong-Wook

    2008-03-01

    We developed a method for the efficient generation of functional dopaminergic (DA) neurons from human embryonic stem cells (hESCs) on a large scale. The most unique feature of this method is the generation of homogeneous spherical neural masses (SNMs) from the hESC-derived neural precursors. These SNMs provide several advantages: (i) they can be passaged for a long time without losing their differentiation capability into DA neurons; (ii) they can be coaxed into DA neurons at much higher efficiency than that from previous reports (86% tyrosine hydroxylase-positive neurons/total neurons); (iii) the induction of DA neurons from SNMs only takes 14 days; and (iv) no feeder cells are required during differentiation. These advantages allowed us to obtain a large number of DA neurons within a short time period and minimized potential contamination of unwanted cells or pathogens coming from the feeder layer. The highly efficient differentiation may not only enhance the efficacy of the cell therapy but also reduce the potential tumor formation from the undifferentiated residual hESCs. In line with this effect, we have never observed any tumor formation from the transplanted animals used in our study. When grafted into a parkinsonian rat model, the hESC-derived DA neurons elicited clear behavioral recovery in three behavioral tests. In summary, our study paves the way for the large-scale generation of purer and functional DA neurons for future clinical applications. PMID:18305158

  19. Highly efficient and large-scale generation of functional dopamine neurons from human embryonic stem cells

    PubMed Central

    Cho, Myung Soo; Lee, Young-Eun; Kim, Ji Young; Chung, Seungsoo; Cho, Yoon Hee; Kim, Dae-Sung; Kang, Sang-Moon; Lee, Haksup; Kim, Myung-Hwa; Kim, Jeong-Hoon; Leem, Joong Woo; Oh, Sun Kyung; Choi, Young Min; Hwang, Dong-Youn; Chang, Jin Woo; Kim, Dong-Wook

    2008-01-01

    We developed a method for the efficient generation of functional dopaminergic (DA) neurons from human embryonic stem cells (hESCs) on a large scale. The most unique feature of this method is the generation of homogeneous spherical neural masses (SNMs) from the hESC-derived neural precursors. These SNMs provide several advantages: (i) they can be passaged for a long time without losing their differentiation capability into DA neurons; (ii) they can be coaxed into DA neurons at much higher efficiency than that from previous reports (86% tyrosine hydroxylase-positive neurons/total neurons); (iii) the induction of DA neurons from SNMs only takes 14 days; and (iv) no feeder cells are required during differentiation. These advantages allowed us to obtain a large number of DA neurons within a short time period and minimized potential contamination of unwanted cells or pathogens coming from the feeder layer. The highly efficient differentiation may not only enhance the efficacy of the cell therapy but also reduce the potential tumor formation from the undifferentiated residual hESCs. In line with this effect, we have never observed any tumor formation from the transplanted animals used in our study. When grafted into a parkinsonian rat model, the hESC-derived DA neurons elicited clear behavioral recovery in three behavioral tests. In summary, our study paves the way for the large-scale generation of purer and functional DA neurons for future clinical applications. PMID:18305158

  20. From Correlation to Causality: Statistical Approaches to Learning Regulatory Relationships in Large-Scale Biomolecular Investigations.

    PubMed

    Ness, Robert O; Sachs, Karen; Vitek, Olga

    2016-03-01

    Causal inference, the task of uncovering regulatory relationships between components of biomolecular pathways and networks, is a primary goal of many high-throughput investigations. Statistical associations between observed protein concentrations can suggest an enticing number of hypotheses regarding the underlying causal interactions, but when do such associations reflect the underlying causal biomolecular mechanisms? The goal of this perspective is to provide suggestions for causal inference in large-scale experiments, which utilize high-throughput technologies such as mass-spectrometry-based proteomics. We describe in nontechnical terms the pitfalls of inference in large data sets and suggest methods to overcome these pitfalls and reliably find regulatory associations. PMID:26731284

  1. Nengo: a Python tool for building large-scale functional brain models

    PubMed Central

    Bekolay, Trevor; Bergstra, James; Hunsberger, Eric; DeWolf, Travis; Stewart, Terrence C.; Rasmussen, Daniel; Choo, Xuan; Voelker, Aaron Russell; Eliasmith, Chris

    2014-01-01

    Neuroscience currently lacks a comprehensive theory of how cognitive processes can be implemented in a biological substrate. The Neural Engineering Framework (NEF) proposes one such theory, but has not yet gathered significant empirical support, partly due to the technical challenge of building and simulating large-scale models with the NEF. Nengo is a software tool that can be used to build and simulate large-scale models based on the NEF; currently, it is the primary resource for both teaching how the NEF is used, and for doing research that generates specific NEF models to explain experimental data. Nengo 1.4, which was implemented in Java, was used to create Spaun, the world's largest functional brain model (Eliasmith et al., 2012). Simulating Spaun highlighted limitations in Nengo 1.4's ability to support model construction with simple syntax, to simulate large models quickly, and to collect large amounts of data for subsequent analysis. This paper describes Nengo 2.0, which is implemented in Python and overcomes these limitations. It uses simple and extendable syntax, simulates a benchmark model on the scale of Spaun 50 times faster than Nengo 1.4, and has a flexible mechanism for collecting simulation results. PMID:24431999

  2. 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.

  3. 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.

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

    DOE PAGESBeta

    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

  5. 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.

  6. 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.

  7. Large-Scale Functional Networks Identified from Resting-State EEG Using Spatial ICA

    PubMed Central

    2016-01-01

    Several methods have been applied to EEG or MEG signals to detect functional networks. In recent works using MEG/EEG and fMRI data, temporal ICA analysis has been used to extract spatial maps of resting-state networks with or without an atlas-based parcellation of the cortex. Since the links between the fMRI signal and the electromagnetic signals are not fully established, and to avoid any bias, we examined whether EEG alone was able to derive the spatial distribution and temporal characteristics of functional networks. To do so, we propose a two-step original method: 1) An individual multi-frequency data analysis including EEG-based source localisation and spatial independent component analysis, which allowed us to characterize the resting-state networks. 2) A group-level analysis involving a hierarchical clustering procedure to identify reproducible large-scale networks across the population. Compared with large-scale resting-state networks obtained with fMRI, the proposed EEG-based analysis revealed smaller independent networks thanks to the high temporal resolution of EEG, hence hierarchical organization of networks. The comparison showed a substantial overlap between EEG and fMRI networks in motor, premotor, sensory, frontal, and parietal areas. However, there were mismatches between EEG-based and fMRI-based networks in temporal areas, presumably resulting from a poor sensitivity of fMRI in these regions or artefacts in the EEG signals. The proposed method opens the way for studying the high temporal dynamics of networks at the source level thanks to the high temporal resolution of EEG. It would then become possible to study detailed measures of the dynamics of connectivity. PMID:26785116

  8. 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.

  9. 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.

  10. Dissociated large-scale functional connectivity networks of the precuneus in medication-naïve first-episode depression.

    PubMed

    Peng, Daihui; Liddle, Elizabeth B; Iwabuchi, Sarina J; Zhang, Chen; Wu, Zhiguo; Liu, Jun; Jiang, Kaida; Xu, Lin; Liddle, Peter F; Palaniyappan, Lena; Fang, Yiru

    2015-06-30

    An imbalance in neural activity within large-scale networks appears to be an important pathophysiological aspect of depression. Yet, there is little consensus regarding the abnormality within the default mode network (DMN) in major depressive disorder (MDD). In the present study, 16 first-episode, medication-naïve patients with MDD and 16 matched healthy controls underwent functional magnetic resonance imaging (fMRI) at rest. With the precuneus (a central node of the DMN) as a seed region, functional connectivity (FC) was measured across the entire brain. The association between the FC of the precuneus and overall symptom severity was assessed using the Hamilton Depression Rating Scale. Patients with MDD exhibited a more negative relationship between the precuneus and the non-DMN regions, including the sensory processing regions (fusiform gyrus, postcentral gyrus) and the secondary motor cortex (supplementary motor area and precentral gyrus). Moreover, greater severity of depression was associated with greater anti-correlation between the precuneus and the temporo-parietal junction as well as stronger positive connectivity between the precuneus and the dorsomedial prefrontal cortex. These results indicate that dissociated large-scale networks of the precuneus may contribute to the clinical expression of depression in MDD. PMID:25957017

  11. 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. PMID:25974630

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

    PubMed Central

    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. PMID:25974630

  13. 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.

  14. 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.

  15. Galaxy clustering on large scales.

    PubMed

    Efstathiou, G

    1993-06-01

    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

  16. Stress-induced alterations in large-scale functional networks of the rodent brain.

    PubMed

    Henckens, Marloes J A G; van der Marel, Kajo; van der Toorn, Annette; Pillai, Anup G; Fernández, Guillén; Dijkhuizen, Rick M; Joëls, Marian

    2015-01-15

    Stress-related psychopathology is associated with altered functioning of large-scale brain networks. Animal research into chronic stress, one of the most prominent environmental risk factors for development of psychopathology, has revealed molecular and cellular mechanisms potentially contributing to human mental disease. However, so far, these studies have not addressed the system-level changes in extended brain networks, thought to critically contribute to mental disorders. We here tested the effects of chronic stress exposure (10 days immobilization) on the structural integrity and functional connectivity patterns in the brain, using high-resolution structural MRI, diffusion kurtosis imaging, and resting-state functional MRI, while confirming the expected changes in neuronal dendritic morphology using Golgi-staining. Stress effectiveness was confirmed by a significantly lower body weight and increased adrenal weight. In line with previous research, stressed animals displayed neuronal dendritic hypertrophy in the amygdala and hypotrophy in the hippocampal and medial prefrontal cortex. Using independent component analysis of resting-state fMRI data, we identified ten functional connectivity networks in the rodent brain. Chronic stress appeared to increase connectivity within the somatosensory, visual, and default mode networks. Moreover, chronic stress exposure was associated with an increased volume and diffusivity of the lateral ventricles, whereas no other volumetric changes were observed. This study shows that chronic stress exposure in rodents induces alterations in functional network connectivity strength which partly resemble those observed in stress-related psychopathology. Moreover, these functional consequences of stress seem to be more prominent than the effects on gross volumetric change, indicating their significance for future research. PMID:25462693

  17. Nonorthogonal generalized hybrid Wannier functions for large-scale DFT simulations

    NASA Astrophysics Data System (ADS)

    Greco, Andrea; Freeland, John W.; Mostofi, Arash A.

    Semiconductor-based thin-films have applications in microelectronics,from transistors to nanocapacitors. Many properties of such devices strongly depend on the details of the interface between a metallic electrode and the thin-film semiconductor/insulator. Hybrid Wannier Functions (WFs), extended in the surface plane, but localized along the direction normal to the surface/interface, have been successfully used to explore the properties of such heterostructures layered along a given direction, and are a natural way to study systems that are at the same time a 2D conductor (in plane) and a 1D insulator (out of plane). Current state-of-the art implementations of Hybrid WFs rely on first performing a traditional cubic-scaling density-functional theory (DFT) calculation. This unfavourable scaling precludes the applicability of this method to the large length scales typically associated with processes in realistic structures. To overcome this limitation we extend the concept of Hybrid WFs to nonorthogonal orbitals that are directly optimized in situ in the electronic structure calculation. We implement this method in the ONETEP large-scale DFT code and we apply it to realistic heterostructure systems, showing it is able to provide plane-wave accuracy but at reduced computational cost. The authors would like to acknowledge support from the EPSRC, the Centre for Doctoral Training in Theory and Simulation of Materials, and Argonne National Laboratory.

  18. 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

    2016-07-01

    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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Environmental correlates of large-scale spatial variation in the δ13C of marine animals

    NASA Astrophysics Data System (ADS)

    Barnes, Carolyn; Jennings, Jon. T. Barry, Simon

    2009-02-01

    Carbon stable isotopes can be used to trace the sources of energy supporting food chains and to estimate the contribution of different sources to a consumer's diet. However, the δ13C signature of a consumer is not sufficient to infer source without an appropriate isotopic baseline, because there is no way to determine if differences in consumer δ13C reflect source changes or baseline variation. Describing isotopic baselines is a considerable challenge when applying stable isotope techniques at large spatial scales and/or to interconnected food chains in open marine environments. One approach is to use filter-feeding consumers to integrate the high frequency and small-scale variation in the isotopic signature of phytoplankton and provide a surrogate baseline, but it can be difficult to sample a single consumer species at large spatial scales owing to rarity and/or discontinuous distribution. Here, we use the isotopic signature of a widely distributed filter-feeder (the queen scallop Aequipecten opercularis) in the north-eastern Atlantic to develop a model linking base δ13C to environmental variables. Remarkably, a single variable model based on bottom temperature has good predictive power and predicts scallop δ13C with mean error of only 0.6‰ (3%). When the model was used to predict an isotopic baseline in parts of the overall study region where scallop were not consistently sampled, the model accounted for 76% and 79% of the large-scale spatial variability (10 1-10 4 km) of the δ13C of two fish species (dab Limanda limanda and whiting Merlangus merlangius) and 44% of the δ13C variability in a mixed fish community. The results show that source studies would be significantly biased if a single baseline were applied to food webs at larger scales. Further, when baseline δ13C cannot be directly measured, a calculated baseline value can eliminate a large proportion of the unexplained variation in δ13C at higher trophic levels.

  4. Insights into allosteric control of vinculin function from its large scale conformational dynamics.

    PubMed

    Chen, Yiwen; Dokholyan, Nikolay V

    2006-09-29

    Vinculin is an important constituent of both cell-cell and cell-matrix junctions, where it plays crucial roles in the regulation of cell adhesion and migration. When activated, it mediates the linkage between cadherins (cell-cell) or integrins (cell-matrix) and the actin cytoskeleton through interactions with various proteins. The activation of vinculin requires structural conversions from an autoinhibited conformation to the "open" conformations in which the occluded binding sites of its different ligands become exposed, while the structural dynamics underlying the vinculin activation remains largely unknown. Here we report the first computational study of large scale conformational dynamics of full-length vinculin. We find that the "holding" and "releasing" motions between vinculin tail and pincer-like structure formed by first three domains of vinculin are the dominant motions near the native state of vinculin, indicating that an inherent flexibility of vinculin has a large influence on its allostery. We also find a cooperative dissociation between the head and tail domains of vinculin with increasing temperature in both thermodynamic and kinetic simulations, implying that vinculin may function as an allosteric switch in response to external signals. We show that the kinetics of vinculin unfolding exhibits specific sequential patterns, suggesting that a sophisticated interplay between domains may synergistically contribute to vinculin activation. We further find that the interaction between vinculin-binding site peptide from talin and vinculin significantly destabilizes the intramolecular head-tail interactions, suggesting a direct role of talin binding in vinculin activation. PMID:16891659

  5. Relationship Between Large-Scale Functional and Structural Covariance Networks in Idiopathic Generalized Epilepsy

    PubMed Central

    Zhang, Zhiqiang; Mantini, Dante; Xu, Qiang; Wang, Zhengge; Chen, Guanghui; Jiao, Qing; Zang, Yu-Feng

    2013-01-01

    Abstract The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic–clonic seizures. PMID:23510272

  6. 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.

  7. 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

  8. Aging and large-scale functional networks: white matter integrity, gray matter volume, and functional connectivity in the resting state.

    PubMed

    Marstaller, L; Williams, M; Rich, A; Savage, G; Burianová, H

    2015-04-01

    Healthy aging is accompanied by neurobiological changes that affect the brain's functional organization and the individual's cognitive abilities. The aim of this study was to investigate the effect of global age-related differences in the cortical white and gray matter on neural activity in three key large-scale networks. We used functional-structural covariance network analysis to assess resting state activity in the default mode network (DMN), the fronto-parietal network (FPN), and the salience network (SN) of young and older adults. We further related this functional activity to measures of cortical thickness and volume derived from structural MRI, as well as to measures of white matter integrity (fractional anisotropy [FA], mean diffusivity [MD], and radial diffusivity [RD]) derived from diffusion-weighted imaging. First, our results show that, in the direct comparison of resting state activity, young but not older adults reliably engage the SN and FPN in addition to the DMN, suggesting that older adults recruit these networks less consistently. Second, our results demonstrate that age-related decline in white matter integrity and gray matter volume is associated with activity in prefrontal nodes of the SN and FPN, possibly reflecting compensatory mechanisms. We suggest that age-related differences in gray and white matter properties differentially affect the ability of the brain to engage and coordinate large-scale functional networks that are central to efficient cognitive functioning. PMID:25644420

  9. Exploring the Light-Capturing Properties of Photosynthetic Chlorophyll Clusters Using Large-Scale Correlated Calculations.

    PubMed

    Suomivuori, Carl-Mikael; Winter, Nina O C; Hättig, Christof; Sundholm, Dage; Kaila, Ville R I

    2016-06-14

    Chlorophylls are light-capturing units found in photosynthetic proteins. We study here the ground and excited state properties of monomeric, dimeric, and tetrameric models of the special chlorophyll/bacteriochlorophyll (Chl/BChl) pigment (P) centers P700 and P680/P870 of type I and type II photosystems, respectively. In the excited state calculations, we study the performance of the algebraic diagrammatic construction through second-order (ADC(2)) method in combination with the reduced virtual space (RVS) approach and the recently developed Laplace-transformed scaled-opposite-spin (LT-SOS) algorithm, which allows us, for the first time, to address multimeric effects at correlated ab initio levels using large basis sets. At the LT-SOS-RVS-ADC(2)/def2-TZVP level, we obtain vertical excitation energies (VEEs) of 2.00-2.07 and 1.52-1.62 eV for the P680/P700 and the P870 pigment models, respectively, which agree well with the experimental absorption maxima of 1.82, 1.77, and 1.43 eV for P680, P700, and P870, respectively. In the P680/P870 models, we find that the photoexcitation leads to a π → π* transition in which the exciton is delocalized between the adjacent Chl/BChl molecules of the central pair, whereas the exciton is localized to a single chlorophyll molecule in the P700 model. Consistent with experiments, the calculated excitonic splittings between the central pairs of P680, P700, and P870 models are 80, 200, and 400 cm(-1), respectively. The calculations show that the electron affinity of the radical cation of the P680 model is 0.4 V larger than for the P870 model and 0.2 V larger than for P700. The chromophore stacking interaction is found to strongly influence the electron localization properties of the light-absorbing pigments, which may help to elucidate mechanistic details of the charge separation process in type I and type II photosystems. PMID:27153186

  10. 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.

  11. 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. PMID:26512872

  12. Ising-like dynamics in large-scale functional brain networks

    NASA Astrophysics Data System (ADS)

    Fraiman, Daniel; Balenzuela, Pablo; Foss, Jennifer; Chialvo, Dante R.

    2009-06-01

    Brain “rest” is defined—more or less unsuccessfully—as the state in which there is no explicit brain input or output. This work focuses on the question of whether such state can be comparable to any known dynamical state. For that purpose, correlation networks from human brain functional magnetic resonance imaging are contrasted with correlation networks extracted from numerical simulations of the Ising model in two dimensions at different temperatures. For the critical temperature Tc , striking similarities appear in the most relevant statistical properties, making the two networks indistinguishable from each other. These results are interpreted here as lending support to the conjecture that the dynamics of the functioning brain is near a critical point.

  13. REIONIZATION ON LARGE SCALES. II. DETECTING PATCHY REIONIZATION THROUGH CROSS-CORRELATION OF THE COSMIC MICROWAVE BACKGROUND

    SciTech Connect

    Natarajan, A.; Battaglia, N.; Trac, H.; Pen, U.-L.; Loeb, A.

    2013-10-20

    We investigate the effect of patchy reionization on the cosmic microwave background (CMB) temperature. An anisotropic optical depth τ( n-hat ) alters the TT power spectrum on small scales l > 2000. We make use of the correlation between the matter density and the reionization redshift fields to construct full sky maps of τ( n-hat ). Patchy reionization transfers CMB power from large scales to small scales, resulting in a non-zero cross correlation between large and small angular scales. We show that the patchy τ correlator is sensitive to small root mean square (rms) values τ{sub rms} ∼ 0.003 seen in our maps. We include frequency-independent secondaries such as CMB lensing and kinetic Sunyaev-Zel'dovich (kSZ) terms, and show that patchy τ may still be detected at high significance. Reionization models that predict different values of τ{sub rms} may be distinguished even for the same mean value (τ). It is more difficult to detect patchy τ in the presence of larger secondaries such as the thermal Sunyaev-Zel'dovich, radio background, and the cosmic infrared background. In this case, we show that patchy τ may be detected if these frequency-dependent secondaries are minimized to ∼< 5 μK (rms) by means of a multi-frequency analysis. We show that the patchy τ correlator provides information that is complementary to what may be obtained from the polarization and the kSZ power spectra.

  14. Large-scale runoff routing with an aggregated network-response function

    NASA Astrophysics Data System (ADS)

    Gong, L.; Widén-Nilsson, E.; Halldin, S.; Xu, C.-Y.

    2009-04-01

    SummaryThe accuracy of runoff routing for global water-balance models and land-surface schemes is limited by the low spatial resolution of flow networks. Many such networks have been developed for specific models at specific spatial resolutions. However, although low-resolution networks can be derived by up-scaling algorithms from high-resolution datasets, such low-resolution networks are inherently incoherent, and slight differences in their spatial resolution can cause significant deviations in routing dynamics. By neglecting convective delay, storage-based routing algorithms produce artificially early arriving peaks on large scales. A theoretical comparison between a diffusion-wave-routing algorithm and linear-reservoir-routing (LRR) algorithm on a 30-km cell demonstrated that the commonly used LRR method consistently underestimates the travel time through the cells. A new aggregated network-response-function ( NRF) routing algorithm was proposed in this study and evaluated against a conventional flow-net-based cell-to-cell LRR algorithm. The evaluation was done for the 25,325 km 2 Dongjiang (East River) basin, a tributary to the Pearl River in southern China well equipped with hydrological and meteorological stations. The NRF method transfers high-resolution delay dynamics, instead of networks, to any lower spatial resolution where runoff is generated. It preserves, over all scales, the spatially distributed time-delay information in the 1-km HYDRO1k flow network in the form of simple cell-response functions for any low-resolution grid. The NRF routing was shown to be scale independent for latitude-longitude resolutions ranging from 5' to 1°. This scale independency allowed a study of input heterogeneity on modelled discharge modelled with a daily version of the WASMOD-M water-balance model. The model efficiency of WASMOD-M-generated daily discharge at the Boluo gauging station in the Dongjiang basin in south China was constantly high (0.89) within the whole

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

    PubMed Central

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

    2016-01-01

    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. PMID:26961596

  16. 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

    2016-01-01

    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. PMID:26961596

  17. 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. PMID:21893524

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

    PubMed Central

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

    2015-01-01

    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. PMID:26105073

  19. 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

    2015-09-01

    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. PMID:26105073

  20. Large-scale Probabilistic Functional Modes from resting state fMRI

    PubMed Central

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

    2015-01-01

    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. PMID:25598050

  1. 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.

  2. Estimating Large-Scale Network Convergence in the Human Functional Connectome.

    PubMed

    Bell, Peter T; Shine, James M

    2015-11-01

    The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, posterior parietal cortex, dorsal prefrontal cortex, along with the caudate head, anterior claustrum, and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the individual resting-state networks in the brain, revealing the heterogeneity by which individual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain. PMID:26005099

  3. Large-scale atomistic simulations of nanostructured materials based on divide-and-conquer density functional theory

    NASA Astrophysics Data System (ADS)

    Shimojo, F.; Ohmura, S.; Nakano, A.; Kalia, R. K.; Vashishta, P.

    2011-05-01

    A linear-scaling algorithm based on a divide-and-conquer (DC) scheme is designed to perform large-scale molecular-dynamics simulations, in which interatomic forces are computed quantum mechanically in the framework of the density functional theory (DFT). This scheme is applied to the thermite reaction at an Al/Fe2O3 interface. It is found that mass diffusion and reaction rate at the interface are enhanced by a concerted metal-oxygen flip mechanism. Preliminary simulations are carried out for an aluminum particle in water based on the conventional DFT, as a target system for large-scale DC-DFT simulations. A pair of Lewis acid and base sites on the aluminum surface preferentially catalyzes hydrogen production in a low activation-barrier mechanism found in the simulations.

  4. Large-scale atomistic simulations of nanostructured materials based on divide-and-conquer density functional theory

    NASA Astrophysics Data System (ADS)

    Shimojo, F.; Ohmura, S.; Nakano, A.; Kalia, R. K.; Vashishta, P.

    2011-05-01

    A linear-scaling algorithm based on a divide-and-conquer (DC) scheme is designed to perform large-scale molecular-dynamics simulations, in which interatomic forces are computed quantum mechanically in the framework of the density functional theory (DFT). This scheme is applied to the thermite reaction at an Al/Fe2O3 interface. It is found that mass diffusion and reaction rate at the interface are enhanced by a concerted metal-oxygen flip mechanism. Preliminary simulations are carried out for an aluminum particle in water based on the conventional DFT, as a target system for large-scale DC-DFT simulations. A pair of Lewis acid and base sites on the aluminum surface preferentially catalyzes hydrogen production in a low activation-barrier mechanism found in the simulations

  5. Large Scale Computing

    NASA Astrophysics Data System (ADS)

    Capiluppi, Paolo

    2005-04-01

    Large Scale Computing is acquiring an important role in the field of data analysis and treatment for many Sciences and also for some Social activities. The present paper discusses the characteristics of Computing when it becomes "Large Scale" and the current state of the art for some particular application needing such a large distributed resources and organization. High Energy Particle Physics (HEP) Experiments are discussed in this respect; in particular the Large Hadron Collider (LHC) Experiments are analyzed. The Computing Models of LHC Experiments represent the current prototype implementation of Large Scale Computing and describe the level of maturity of the possible deployment solutions. Some of the most recent results on the measurements of the performances and functionalities of the LHC Experiments' testing are discussed.

  6. 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

    2014-05-01

    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. PMID:24936458

  7. 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.

  8. Insights into Hox Protein Function from a Large Scale Combinatorial Analysis of Protein Domains

    PubMed Central

    Karlsson, Daniel; Dixit, Richa; Saadaoui, Mehdi; Monier, Bruno; Brun, Christine; Thor, Stefan; Vijayraghavan, K.; Perrin, Laurent; Pradel, Jacques; Graba, Yacine

    2011-01-01

    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. PMID:22046139

  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. PMID:22046139

  10. Spatiotemporal reconfiguration of large-scale brain functional networks during propofol-induced loss of consciousness.

    PubMed

    Schröter, Manuel S; Spoormaker, Victor I; Schorer, Anna; Wohlschläger, Afra; Czisch, Michael; Kochs, Eberhard F; Zimmer, Claus; Hemmer, Bernhard; Schneider, Gerhard; Jordan, Denis; Ilg, Rüdiger

    2012-09-12

    Applying graph theoretical analysis of spontaneous BOLD fluctuations in functional magnetic resonance imaging (fMRI), we investigated whole-brain functional connectivity of 11 healthy volunteers during wakefulness and propofol-induced loss of consciousness (PI-LOC). After extraction of regional fMRI time series from 110 cortical and subcortical regions, we applied a maximum overlap discrete wavelet transformation and investigated changes in the brain's intrinsic spatiotemporal organization. During PI-LOC, we observed a breakdown of subcortico-cortical and corticocortical connectivity. Decrease of connectivity was pronounced in thalamocortical connections, whereas no changes were found for connectivity within primary sensory cortices. Graph theoretical analyses revealed significant changes in the degree distribution and local organization metrics of brain functional networks during PI-LOC: compared with a random network, normalized clustering was significantly increased, as was small-worldness. Furthermore we observed a profound decline in long-range connections and a reduction in whole-brain spatiotemporal integration, supporting a topological reconfiguration during PI-LOC. Our findings shed light on the functional significance of intrinsic brain activity as measured by spontaneous BOLD signal fluctuations and help to understand propofol-induced loss of consciousness. PMID:22973006

  11. Size-dependent species removal impairs ecosystem functioning in a large-scale tropical field experiment.

    PubMed

    Dangles, Olivier; Carpio, Carlos; Woodward, Guy

    2012-12-01

    A major challenge of ecological research is to assess the functional consequences of species richness loss over time and space in global biodiversity hotspots, where extinctions are happening at an unprecedented rate. To address this issue, greater realism needs to be incorporated into both conceptual and experimental approaches. Here we propose a conceptual model that incorporates body size as a critical aspect of community responses to environmental change, which we tested in the Western Amazonian rain forest, one of the most speciose ecosystems on the planet. We employed an exclosure removal experiment (replicated under 10 microhabitats and four climatic conditions) in which we manipulated access to two types of resource by the whole community of dung and carrion beetles (> 60 species), depending on their size. Our 400 independent measurements revealed that changes in the number of species and functional groups, and temporal patterns in community composition, all affected resource burial rates, a key ecosystem process. Further, the functional contribution of species diversity in each size class was tightly dependent on beetle abundance, and while the role of large species could be performed by abundant smaller ones, and other naturally occurring decomposers, this was not the case when environmental conditions were harsher. These results demonstrate, for the first time in an animal assemblage in a tropical ecosystem, that although species may appear functionally redundant under one set of environmental conditions, many species would be needed to maintain ecosystem functioning at multiple temporal and spatial scales. This highlights the potential fragility of these systems to the ongoing global "Sixth Great Extinction," whose effects are likely to be especially pronounced in the Tropics. PMID:23431592

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

    USGS Publications Warehouse

    Symstad, A.J.; Chapin, F. S., III; Wall, D.H.; Gross, K.L.; Huenneke, L.F.; Mittelbach, G.G.; Peters, D.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.

  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. Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

    PubMed

    Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

    2016-07-12

    We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design. PMID:27248370

  15. Differences in human cortical gene expression match the temporal properties of large-scale functional networks.

    PubMed

    Cioli, Claudia; Abdi, Hervé; Beaton, Derek; Burnod, Yves; Mesmoudi, Salma

    2014-01-01

    We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring--Visual-Sensorimotor-Auditory (VSA)--comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring--Parieto-Temporo-Frontal (PTF)--comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found--with correspondence analysis--that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins--coded by genes that most differentiate the rings--were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium channels SCNA3

  16. Differences in Human Cortical Gene Expression Match the Temporal Properties of Large-Scale Functional Networks

    PubMed Central

    Cioli, Claudia; Abdi, Hervé; Beaton, Derek; Burnod, Yves; Mesmoudi, Salma

    2014-01-01

    We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring–Visual-Sensorimotor-Auditory (VSA)–comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring–Parieto-Temporo-Frontal (PTF)–comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found–with correspondence analysis–that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins–coded by genes that most differentiate the rings–were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium

  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. 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.

  19. 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

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

    NASA Astrophysics Data System (ADS)

    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.

  1. 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

    2016-01-01

    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

  2. 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

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

    PubMed

    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

  4. 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

    2015-01-01

    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

  5. 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

  6. Efficient derivation of functional dopaminergic neurons from human embryonic stem cells on a large scale.

    PubMed

    Cho, Myung-Soo; Hwang, Dong-Youn; Kim, Dong-Wook

    2008-01-01

    Cell-replacement therapy using human embryonic stem cells (hESCs) holds great promise in treating Parkinson's disease. We have recently reported a highly efficient method to generate functional dopaminergic (DA) neurons from hESCs. Our method includes a unique step, the formation of spherical neural masses (SNMs), and offers the highest yield of DA neurons ever achieved so far. In this report, we describe our method step by step, covering not only how to differentiate hESCs into DA neurons at a high yield, but also how to amplify, freeze and thaw the SNMs, which are the key structures that make our protocol unique and advantageous. Although the whole process of generation of DA neurons from hESCs takes about 2 months, only 14 d are needed to derive DA neurons from the SNMs. PMID:19008875

  7. 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

  8. Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity.

    PubMed

    Thompson, Garth John; Pan, Wen-Ju; Magnuson, Matthew Evan; Jaeger, Dieter; Keilholz, Shella Dawn

    2014-01-01

    Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders. PMID:24071524

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

    DOE PAGESBeta

    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 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

  10. Electron Transport and Related Nonequilibrium Distribution Functions in Large Scale ICF Plasma

    NASA Astrophysics Data System (ADS)

    Rozmus, W.; Chapman, T.; Brantov, A. V.; Winjum, B.; Berger, R.; Brunner, S.; Bychenkov, V. Yu.; Tableman, A.

    2014-10-01

    Using the Vlasov-Fokker Fokker-Planck (VFP) code OSHUN and higher order perturbative solutions to the VFP equation, we have studied electron distribution functions (EDF) in inhomogeneous and hot hohlraum plasmas of relevant to the current ICF experiments. For these inhomogeneous ICF plasmas characterized by with the temperature and density gradients consistent with the high flux model [M. D. Rosen et al., HEDP 7, 180 (2011)], nonequilibrium EDF often display unphysical properties related to first and second order derivatives at larger velocities. These EDF strongly modify the linear plasma response, including Lanadau damping of Langmuir waves, electrostatic fluctuation levels, and instability gain coefficients We have found that Langmuir waves propagating in the direction of the heat flow have increased Lanadau damping compared to damping calculated from a Maxwellian EDF, while Langmuir waves propagating in the direction of the temperature gradients are far less damped as compared to damping calculated from the Maxwellian EDF. These effects have been discussed in the context of stimulated Raman scattering, Langmuir decay instability and Thomson scattering experiments.

  11. Decoding the Role of the Insula in Human Cognition: Functional Parcellation and Large-Scale Reverse Inference

    PubMed Central

    Yarkoni, Tal; Khaw, Mel Win; Sanfey, Alan G.

    2013-01-01

    Recent work has indicated that the insula may be involved in goal-directed cognition, switching between networks, and the conscious awareness of affect and somatosensation. However, these findings have been limited by the insula’s remarkably high base rate of activation and considerable functional heterogeneity. The present study used a relatively unbiased data-driven approach combining resting-state connectivity-based parcellation of the insula with large-scale meta-analysis to understand how the insula is anatomically organized based on functional connectivity patterns as well as the consistency and specificity of the associated cognitive functions. Our findings support a tripartite subdivision of the insula and reveal that the patterns of functional connectivity in the resting-state analysis appear to be relatively conserved across tasks in the meta-analytic coactivation analysis. The function of the networks was meta-analytically “decoded” using the Neurosynth framework and revealed that while the dorsoanterior insula is more consistently involved in human cognition than ventroanterior and posterior networks, each parcellated network is specifically associated with a distinct function. Collectively, this work suggests that the insula is instrumental in integrating disparate functional systems involved in processing affect, sensory-motor processing, and general cognition and is well suited to provide an interface between feelings, cognition, and action. PMID:22437053

  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. Development of a large-scale functional brain network during human non-rapid eye movement sleep.

    PubMed

    Spoormaker, Victor I; Schröter, Manuel S; Gleiser, Pablo M; Andrade, Katia C; Dresler, Martin; Wehrle, Renate; Sämann, Philipp G; Czisch, Michael

    2010-08-25

    Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization of slow-frequency blood oxygen level-dependent (BOLD) signal fluctuations during wakeful resting. In this study, we used graph theoretical measures to explore how physiological changes during sleep are reflected in functional connectivity and small-world network properties of a large-scale, low-frequency functional brain network. Twenty-five young and healthy participants fell asleep during a 26.7 min fMRI scan with simultaneous polysomnography. A maximum overlap discrete wavelet transformation was applied to fMRI time series extracted from 90 cortical and subcortical regions in normalized space after residualization of the raw signal against unspecific sources of signal fluctuations; functional connectivity analysis focused on the slow-frequency BOLD signal fluctuations between 0.03 and 0.06 Hz. We observed that in the transition from wakefulness to light sleep, thalamocortical connectivity was sharply reduced, whereas corticocortical connectivity increased; corticocortical connectivity subsequently broke down in slow-wave sleep. Local clustering values were closest to random values in light sleep, whereas slow-wave sleep was characterized by the highest clustering ratio (gamma). Our findings support the hypothesis that changes in consciousness in the descent to sleep are subserved by reduced thalamocortical connectivity at sleep onset and a breakdown of general connectivity in slow-wave sleep, with both processes limiting the capacity of the brain to integrate information across functional modules. PMID:20739559

  14. Large-scale functional network reorganization in 22q11.2 deletion syndrome revealed by modularity analysis.

    PubMed

    Scariati, Elisa; Schaer, Marie; Karahanoglu, Isik; Schneider, Maude; Richiardi, Jonas; Debbané, Martin; Van De Ville, Dimitri; Eliez, Stephan

    2016-09-01

    The 22q11.2 deletion syndrome (22q11DS) is associated with cognitive impairments and a 41% risk of developing schizophrenia. While several studies performed on patients with 22q11DS showed the presence of abnormal functional connectivity in this syndrome, how these alterations affect large-scale network organization is still unknown. Here we performed a network modularity analysis on whole-brain functional connectomes derived from the resting-state fMRI of 40 patients with 22q11DS and 41 healthy control participants, aged between 9 and 30 years old. We then split the sample at 18 years old to obtain two age subgroups and repeated the modularity analyses. We found alterations of modular communities affecting the visuo-spatial network and the anterior cingulate cortex (ACC) in both age groups. These results corroborate previous structural and functional studies in 22q11DS that showed early impairment of visuo-spatial processing regions. Furthermore, as ACC has been linked to the development of psychotic symptoms in 22q11DS, the early impairment of its functional connectivity provide further support that ACC alterations may provide potential biomarkers for an increased risk of schizophrenia. Finally, we found an abnormal modularity partition of the dorsolateral prefrontal cortex (DLPFC) only in adults with 22q11DS, suggesting the presence of an abnormal development of functional network communities during adolescence in 22q11DS. PMID:27371790

  15. 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

  16. Optimization of a large-scale gene disruption protocol in Dictyostelium and analysis of conserved genes of unknown function

    PubMed Central

    Torija, Patricia; Robles, Alicia; Escalante, Ricardo

    2006-01-01

    Background Development of the post-genomic age in Dictyostelium will require the existence of rapid and reliable methods to disrupt genes that would allow the analysis of entire gene families and perhaps the possibility to undertake the complete knock-out analysis of all the protein-coding genes present in Dictyostelium genome. Results Here we present an optimized protocol based on the previously described construction of gene disruption vectors by in vitro transposition. Our method allows a rapid selection of the construct by a simple PCR approach and subsequent sequencing. Disruption constructs were amplified by PCR and the products were directly transformed in Dictyostelium cells. The selection of homologous recombination events was also performed by PCR. We have constructed 41 disruption vectors to target genes of unknown function, highly conserved between Dictyostelium and human, but absent from the genomes of S. cerevisiae and S. pombe. 28 genes were successfully disrupted. Conclusion This is the first step towards the understanding of the function of these conserved genes and exemplifies the easiness to undertake large-scale disruption analysis in Dictyostelium. PMID:16945142

  17. 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

  18. 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.

  19. 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.

  20. Large-Scale Genome-Wide Association Studies and Meta-Analyses of Longitudinal Change in Adult Lung Function

    PubMed Central

    Tang, Wenbo; Kowgier, Matthew; Loth, Daan W.; Soler Artigas, María; Joubert, Bonnie R.; Hodge, Emily; Gharib, Sina A.; Smith, Albert V.; Ruczinski, Ingo; Gudnason, Vilmundur; Mathias, Rasika A.; Harris, Tamara B.; Hansel, Nadia N.; Launer, Lenore J.; Barnes, Kathleen C.; Hansen, Joyanna G.; Albrecht, Eva; Aldrich, Melinda C.; Allerhand, Michael; Barr, R. Graham; Brusselle, Guy G.; Couper, David J.; Curjuric, Ivan; Davies, Gail; Deary, Ian J.; Dupuis, Josée; Fall, Tove; Foy, Millennia; Franceschini, Nora; Gao, Wei; Gläser, Sven; Gu, Xiangjun; Hancock, Dana B.; Heinrich, Joachim; Hofman, Albert; Imboden, Medea; Ingelsson, Erik; James, Alan; Karrasch, Stefan; Koch, Beate; Kritchevsky, Stephen B.; Kumar, Ashish; Lahousse, Lies; Li, Guo; Lind, Lars; Lindgren, Cecilia; Liu, Yongmei; Lohman, Kurt; Lumley, Thomas; McArdle, Wendy L.; Meibohm, Bernd; Morris, Andrew P.; Morrison, Alanna C.; Musk, Bill; North, Kari E.; Palmer, Lyle J.; Probst-Hensch, Nicole M.; Psaty, Bruce M.; Rivadeneira, Fernando; Rotter, Jerome I.; Schulz, Holger; Smith, Lewis J.; Sood, Akshay; Starr, John M.; Strachan, David P.; Teumer, Alexander; Uitterlinden, André G.; Völzke, Henry; Voorman, Arend; Wain, Louise V.; Wells, Martin T.; Wilk, Jemma B.; Williams, O. Dale; Heckbert, Susan R.; Stricker, Bruno H.; London, Stephanie J.; Fornage, Myriam; Tobin, Martin D.; O′Connor, George T.; Hall, Ian P.; Cassano, Patricia A.

    2014-01-01

    Background Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. Methods We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. Results The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10-7). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10-8) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. Conclusions In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function. PMID:24983941

  1. Use of allele-specific FAIRE to determine functional regulatory polymorphism using large-scale genotyping arrays.

    PubMed

    Smith, Andrew J P; Howard, Philip; Shah, Sonia; Eriksson, Per; Stender, Stefan; Giambartolomei, Claudia; Folkersen, Lasse; Tybjærg-Hansen, Anne; Kumari, Meena; Palmen, Jutta; Hingorani, Aroon D; Talmud, Philippa J; Humphries, Steve E

    2012-01-01

    Following the widespread use of genome-wide association studies (GWAS), focus is turning towards identification of causal variants rather than simply genetic markers of diseases and traits. As a step towards a high-throughput method to identify genome-wide, non-coding, functional regulatory variants, we describe the technique of allele-specific FAIRE, utilising large-scale genotyping technology (FAIRE-gen) to determine allelic effects on chromatin accessibility and regulatory potential. FAIRE-gen was explored using lymphoblastoid cells and the 50,000 SNP Illumina CVD BeadChip. The technique identified an allele-specific regulatory polymorphism within NR1H3 (coding for LXR-α), rs7120118, coinciding with a previously GWAS-identified SNP for HDL-C levels. This finding was confirmed using FAIRE-gen with the 200,000 SNP Illumina Metabochip and verified with the established method of TaqMan allelic discrimination. Examination of this SNP in two prospective Caucasian cohorts comprising 15,000 individuals confirmed the association with HDL-C levels (combined beta = 0.016; p = 0.0006), and analysis of gene expression identified an allelic association with LXR-α expression in heart tissue. Using increasingly comprehensive genotyping chips and distinct tissues for examination, FAIRE-gen has the potential to aid the identification of many causal SNPs associated with disease from GWAS. PMID:22916038

  2. Large-scale mutagenesis of the mouse to understand the genetic bases of nervous system structure and function

    PubMed Central

    Goldowitz, Dan; Frankel, Wayne N.; Takahashi, Joseph S.; Holtz-Vitaterna, Martha; Bult, Carol; Kibbe, Warren A.; Snoddy, Jay; Li, Yanxia; Pretel, Stephanie; Yates, Jeana; Swanson, Douglas J.

    2013-01-01

    N-ethyl-N-nitrosourea (ENU) mutagenesis is presented as a powerful approach to developing models for human disease. The efforts of three NIH Mutagenesis Centers established for the detection of neuroscience-related phenotypes are described. Each center has developed an extensive panel of phenotype screens that assess nervous system structure and function. In particular, these screens focus on complex behavioral traits from drug and alcohol responses to circadian rhythms to epilepsy. Each of these centers has developed a bioinformatics infrastructure to track the extensive number of transactions that are inherent in these large-scale projects. Over 100 new mouse mutant lines have been defined through the efforts of these three mutagenesis centers and are presented to the research community via the centralized Web presence of the Neuromice.org consortium (http://www.neuromice.org). This community resource provides visitors with the ability to search for specific mutant phenotypes, to view the genetic and phenotypic details of mutant mouse lines, and to order these mice for use in their own research program. PMID:15582151

  3. 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.

  4. Large scale characterization of unsaturated soil properties in a semi-arid region combining infiltration, pedotransfer functions and evaporation tests

    NASA Astrophysics Data System (ADS)

    Shabou, Marouen; Angulo-Jaramillo, Rafael; Lassabatère, Laurent; Boulet, Gilles; Mougenot, Bernard; Lili Chabaane, Zohra; Zribi, Mehrez

    2016-04-01

    Water resource management is a major issue in semi-arid regions, especially where irrigated agriculture is dominant on soils with highly variable clay content. Indeed, topsoil clay content has a significant importance on infiltration and evaporation processes and therefore in the estimation of the volume of water needed for crops. In this poster we present several methods to estimate wilting point, field capacity volumetric water contents and saturated hydraulic conductivity of the Kairouan plain (680 km2), central Tunisia (North Africa). The first method relies on the Beerkan Estimation of Soil Transfer parameters (BEST) method, which consists in local estimate of unsaturated soil hydraulic properties from a single-ring infiltration test, combined with the use of pedotransfer functions applied to the Kairouan plain different soil types. Results are obtained over six different topsoil texture classes along the Kairouan plain. Saturated hydraulic conductivity is high for coarse textured and some of the fine textured soils due to shrinkage cracking-macropore soil structure. The saturated hydraulic conductivity values are respectively 1.31E-5 m.s-1 and 1.71E-05 m.s-1. The second method is based on evaporation tests on different test plots. It consists of analyzing soil moisture profile changes during the dry down periods to detect the time-to-stress that can be obtained from observation of soil moisture variation, albedo measurements and variation of soil temperature. Results show that the estimated parameters with the evaporation method are close to those obtained by combining the BEST method and pedotransfer functions. The results validate that combining local infiltration tests and pedotransfer functions is a promising tool for the large scale hydraulic characterization of region with strong spatial variability of soils properties.

  5. 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

  6. Large-scale inhomogeneities and galaxy statistics

    NASA Technical Reports Server (NTRS)

    Schaeffer, R.; Silk, J.

    1984-01-01

    The density fluctuations associated with the formation of large-scale cosmic pancake-like and filamentary structures are evaluated using the Zel'dovich approximation for the evolution of nonlinear inhomogeneities in the expanding universe. It is shown that the large-scale nonlinear density fluctuations in the galaxy distribution due to pancakes modify the standard scale-invariant correlation function xi(r) at scales comparable to the coherence length of adiabatic fluctuations. The typical contribution of pancakes and filaments to the J3 integral, and more generally to the moments of galaxy counts in a volume of approximately (15-40 per h Mpc)exp 3, provides a statistical test for the existence of large scale inhomogeneities. An application to several recent three dimensional data sets shows that despite large observational uncertainties over the relevant scales characteristic features may be present that can be attributed to pancakes in most, but not all, of the various galaxy samples.

  7. Ways to improve your correlation functions

    NASA Technical Reports Server (NTRS)

    Hamilton, A. J. S.

    1993-01-01

    This paper describes a number of ways to improve on the standard method for measuring the two-point correlation function of large scale structure in the Universe. Issues addressed are: (1) the problem of the mean density, and how to solve it; (2) how to estimate the uncertainty in a measured correlation function; (3) minimum variance pair weighting; (4) unbiased estimation of the selection function when magnitudes are discrete; and (5) analytic computation of angular integrals in background pair counts.

  8. Positive-selection and ligation-independent cloning vectors for large scale in planta expression for plant functional genomics.

    PubMed

    Oh, Sang-Keun; Kim, Saet-Byul; Yeom, Seon-In; Lee, Hyun-Ah; Choi, Doil

    2010-12-01

    Transient expression is an easy, rapid and powerful technique for producing proteins of interest in plants. Recombinational cloning is highly efficient but has disadvantages, including complicated, time consuming cloning procedures and expensive enzymes for large-scale gene cloning. To overcome these limitations, we developed new ligation-independent cloning (LIC) vectors derived from binary vectors including tobacco mosaic virus (pJL-TRBO), potato virus X (pGR106) and the pBI121 vector-based pMBP1. LIC vectors were modified to enable directional cloning of PCR products without restriction enzyme digestion or ligation reactions. In addition, the ccdB gene, which encodes a potent cell-killing protein, was introduced between the two LIC adapter sites in the pJL-LIC, pGR-LIC, and pMBP-LIC vectors for the efficient selection of recombinant clones. This new vector does not require restriction enzymes, alkaline phosphatase, or DNA ligase for cloning. To clone, the three LIC vectors are digested with SnaBI and treated with T4 DNA polymerase, which includes 3' to 5' exonuclease activity in the presence of only one dNTP (dGTP for the inserts and dCTP for the vector). To make recombinants, the vector plasmid and the insert PCR fragment were annealed at room temperature for 20 min prior to transformation into the host. Bacterial transformation was accomplished with 100% efficiency. To validate the new LIC vector systems, we were used to coexpressed the Phytophthora AVR and potato resistance (R) genes in N. benthamiana by infiltration of Agrobacterium. Coexpressed AVR and R genes in N. benthamiana induced the typical hypersensitive cell death resulting from in vivo interaction of the two proteins. These LIC vectors could be efficiently used for high-throughput cloning and laboratory-scale in planta expression. These vectors could provide a powerful tool for high-throughput transient expression assays for functional genomic studies in plants. PMID:21340673

  9. Large-scale developing of simple sequence repeat markers and probing its correlation with ramie (Boehmeria nivea L.) fiber quality.

    PubMed

    Chen, Jie; Yu, Runqing; Liu, Lijun; Wang, Bo; Peng, Dingxiang

    2016-04-01

    Marker-assisted selection is an important component of the discipline of molecular breeding. Using DNA markers to assist in plant breeding, the efficiency and precision could be greatly increased. However, the scarcity number of identified DNA markers has hindered the research and the breeding process of ramie (Boehmeria nivea L.) in many aspects, especially fiber quality, one of the top-priority breeding objectives of ramie. In this study, 4230 SSR loci were identified in 3969 unigenes (6.80 % of 58,369), which were de novo assembled from the transcriptome involving different ramie fiber developmental stages. Among these SSRs, the dinucleotides (1599, 37.80 %) and trinucleotides (772, 18.25 %) were most abundant; the motifs AG/CT (1140, 26.94 %), AT/AT (407, 9.62 %) and AGA/TCT (246, 8.31 %) comprised the three most abundant repeats. A total of 2431 primer pairs were designed flanking the SSRs and 1050 of them were employed in PCR amplification for their usefulness using three ramie cultivars. The results showed that 88.10 % of these primers could generate positive PCR bands in any of the three cultivars. Further phylogenetic analysis that conducted from the PCR amplification of 52 specifically sifted SSR primers within 17 cultivars approved that the possible correlation may exist between the primers and ramie fiber quality. These developed SSR markers could be applied in downstream studies, like genetic and physical maps, quantitative trait loci mapping, genetic diversity studies and cultivar fingerprinting, and breeding processes of ramie with better fiber quality under further confirmation of the correlation with ramie fiber quality. PMID:26577947

  10. Large scale analysis of pediatric antiviral CD8+ T cell populations reveals sustained, functional and mature responses

    PubMed Central

    Komatsu, Haruki; Inui, Ayano; Sogo, Tsuyoshi; Fujisawa, Tomoo; Nagasaka, Hironori; Nonoyama, Shigeaki; Sierro, Sophie; Northfield, John; Lucas, Michaela; Vargas, Anita; Klenerman, Paul

    2006-01-01

    Background Cellular immunity plays a crucial role in cytomegalovirus (CMV) infection and substantial populations of CMV-specific T cells accumulate throughout life. However, although CMV infection occurs during childhood, relatively little is know about the typical quantity and quality of T cell responses in pediatric populations. Methods One thousand and thirty-six people (Male/Female = 594/442, Age: 0–19 yr.; 959 subjects, 20–29 yr.; 77 subjects) were examined for HLA typing. All of 1036 subjects were tested for HLA-A2 antigen. Of 1036 subjects, 887 were also tested for HLA-A23, 24 antigens. In addition, 50 elderly people (Male/Female = 11/39, Age: 60–92 yr.) were also tested for HLA-A2 antigen. We analyzed the CD8+ T cell responses to CMV, comparing these to responses in children and young. The frequencies, phenotype and function CD8+ T cells for two imunodominant epitopes from pp65 were measured. Results We observed consistently high frequency and phenotypically "mature" (CD27 low, CD28 low, CD45RA+) CMV-specific CD8+ T cell responses in children, including those studied in the first year of life. These CD8+ T cells retained functionality across all age groups, and showed evidence of memory "inflation" only in later adult life. Conclusion CMV consistently elicits a very strong CD8+ T cell response in infants and large pools of CMV specific CD8+ T cells are maintained throughout childhood. The presence of CMV may considerably mould the CD8+ T cell compartment over time, but the relative frequencies of CMV-specific cells do not show the evidence of a population-level increase during childhood and adulthood. This contrast with the marked expansion ("inflation") of such CD8+ T cells in older adults. This study indicates that large scale analysis of peptide specific T cell responses in infants is readily possible. The robust nature of the responses observed suggests vaccine strategies aimed at priming and boosting CD8+ T cells against major pathogens

  11. Adolescents’ Use of Indoor Tanning: A Large-Scale Evaluation of Psychosocial, Environmental, and Policy-Level Correlates

    PubMed Central

    Woodruff, Susan I.; Slymen, Donald J.; Sallis, James F.; Forster, Jean L.; Clapp, Elizabeth J.; Hoerster, Katherine D.; Pichon, Latrice C.; Weeks, John R.; Belch, George E.; Weinstock, Martin A.; Gilmer, Todd

    2011-01-01

    Objectives. We evaluated psychosocial, built-environmental, and policy-related correlates of adolescents’ indoor tanning use. Methods. We developed 5 discrete data sets in the 100 most populous US cities, based on interviews of 6125 adolescents (aged 14–17 years) and their parents, analysis of state indoor tanning laws, interviews with enforcement experts, computed density of tanning facilities, and evaluations of these 3399 facilities’ practices regarding access by youths. After univariate analyses, we constructed multilevel models with generalized linear mixed models (GLMMs). Results. In the past year, 17.1% of girls and 3.2% of boys had used indoor tanning. The GLMMs indicated that several psychosocial or demographic variables significantly predicted use, including being female, older, and White; having a larger allowance and a parent who used indoor tanning and allowed their adolescent to use it; and holding certain beliefs about indoor tanning's consequences. Living within 2 miles of a tanning facility also was a significant predictor. Residing in a state with youth-access legislation was not significantly associated with use. Conclusions. Current laws appear ineffective in reducing indoor tanning; bans likely are needed. Parents have an important role in prevention efforts. PMID:21421947

  12. Study and enhancement of large-scale exact-diagonalization for strongly correlated systems on emerging hybrid architectures

    NASA Astrophysics Data System (ADS)

    Thakur, Bhupender; Tam, Ka-Ming; Ragavan, Kaushik; Jarrell, Mark; Moreno, Juana

    2012-02-01

    Exact diagonalization(ED) provides a powerful machinery for the study of many strongly correlated systems, in which other methods fail to provide unbiased results. In addition, the ED method has also been employed as a cluster solver for dynamical mean field approaches. The two main obstacles for the ED are the storage of the basis vector and the computationally intensive matrix-vector multiplication. With the Graphics Processing Unit (GPU) platform becoming more widely accessible, the challenge now is to effectively scale the ED method to use hybrid CPU-GPU node topology, which is fast becoming the default route to exascale computing. The goal of this study is to develop a highly scalable and efficient implementation of the ED method on this next generation infrastructure, via GPU accelerated modules. We compare the performance of our implementation with that of the conventional CPU implementation via the study of the Hubbard-Anderson model, where Quantum Monte Carlo method suffers from severe minus sign problem.

  13. 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.

  14. Modulation of large-scale brain networks by transcranial direct current stimulation evidenced by resting-state functional MRI

    PubMed Central

    Peña-Gómez, Cleofé; Sala-Lonch, Roser; Junqué, Carme; Clemente, Immaculada C.; Vidal, Dídac; Bargalló, Núria; Falcón, Carles; Valls-Solé, Josep; Pascual-Leone, Álvaro; Bartrés-Faz, David

    2013-01-01

    Background Brain areas interact mutually to perform particular complex brain functions such as memory or language. Furthermore, under resting-state conditions several spatial patterns have been identified that resemble functional systems involved in cognitive functions. Among these, the default-mode network (DMN), which is consistently deactivated during task periods and is related to a variety of cognitive functions, has attracted most attention. In addition, in resting-state conditions some brain areas engaged in focused attention (such as the anticorrelated network, AN) show a strong negative correlation with DMN; as task demand increases, AN activity rises, and DMN activity falls. Objective We combined transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) to investigate these brain network dynamics. Methods Ten healthy young volunteers underwent four blocks of resting-state fMRI (10-minutes), each of them immediately after 20 minutes of sham or active tDCS (2 mA), on two different days. On the first day the anodal electrode was placed over the left dorsolateral prefrontal cortex (DLPFC) (part of the AN) with the cathode over the contralateral supraorbital area, and on the second day, the electrode arrangement was reversed (anode right-DLPFC, cathode left-supraorbital). Results After active stimulation, functional network connectivity revealed increased synchrony within the AN components and reduced synchrony in the DMN components. Conclusions Our study reveals a reconfiguration of intrinsic brain activity networks after active tDCS. These effects may help to explain earlier reports of improvements in cognitive functions after anodal-tDCS, where increasing cortical excitability may have facilitated reconfiguration of functional brain networks to address upcoming cognitive demands. PMID:21962981

  15. Interpretation of large-scale deviations from the Hubble flow

    NASA Astrophysics Data System (ADS)

    Grinstein, B.; Politzer, H. David; Rey, S.-J.; Wise, Mark B.

    1987-03-01

    The theoretical expectation for large-scale streaming velocities relative to the Hubble flow is expressed in terms of statistical correlation functions. Only for objects that trace the mass would these velocities have a simple cosmological interpretation. If some biasing effects the objects' formation, then nonlinear gravitational evolution is essential to predicting the expected large-scale velocities, which also depend on the nature of the biasing.

  16. Large-scale functional brain network changes in taxi drivers: evidence from resting-state fMRI.

    PubMed

    Wang, Lubin; Liu, Qiang; Shen, Hui; Li, Hong; Hu, Dewen

    2015-03-01

    Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving-related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting-state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8-min resting-state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi-driving years. Our findings may provide new insight into how the brain supports driving behavior. PMID:25338709

  17. 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. PMID:25989417

  18. 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

  19. Functions of slags and gravels as substrates in large-scale demonstration constructed wetland systems for polluted river water treatment.

    PubMed

    Ge, Yuan; Wang, Xiaochang; Zheng, Yucong; Dzakpasu, Mawuli; Zhao, Yaqian; Xiong, Jiaqing

    2015-09-01

    The choice of substrates with high adsorption capacity, yet readily available and economical is vital for sustainable pollutants removal in constructed wetlands (CWs). Two identical large-scale demonstration horizontal subsurface flow (HSSF) CWs (surface area, 340 m(2); depth, 0.6 m; HLR, 0.2 m/day) with gravel or slag substrates were evaluated for their potential use in remediating polluted urban river water in the prevailing climate of northwest China. Batch experiments to elucidate phosphorus adsorption mechanisms indicated a higher adsorption capacity of slag (3.15 g/kg) than gravel (0.81 g/kg), whereby circa 20 % more total phosphorus (TP) removal was recorded in HSSF-slag than HSSF-gravel. TP removal occurred predominantly via CaO-slag dissolution followed by Ca phosphate precipitation. Moreover, average removals of chemical oxygen demand and biochemical oxygen demand were approximately 10 % higher in HSSF-slag than HSSF-gravel. Nevertheless, TP adsorption by slag seemed to get quickly saturated over the monitoring period, and the removal efficiency of the HSSF-slag approached that of the HSSF-gravel after 1-year continuous operation. In contrast, the two CWs achieved similar nitrogen removal during the 2-year monitoring period. Findings also indicated that gravel provided better support for the development of other wetland components such as biomass, whereby the biomass production and the amount of total nitrogen (TN; 43.1-59.0 g/m(2)) and TP (4.15-5.75 g/m(2)) assimilated by local Phragmites australis in HSSF-gravel were higher than that in HSSF-slag (41.2-52.0 g/m(2) and 3.96-4.07 g/m(2), respectively). Overall, comparable pollutant removal rates could be achieved in large-scale HSSF CWs with either gravel or slag as substrate and provide a possible solution for polluted urban river remediation in northern China. PMID:25916476

  20. The large-scale cross-correlation of Damped Lyman alpha systems with the Lyman alpha forest: first measurements from BOSS

    SciTech Connect

    Font-Ribera, Andreu; Miralda-Escudé, Jordi; Arnau, Eduard; Carithers, Bill; Ross, Nicholas P.; White, Martin; Lee, Khee-Gan; Noterdaeme, Pasquier; Pâris, Isabelle; Petitjean, Patrick; Rollinde, Emmanuel; Rich, James; Schneider, Donald P.; York, Donald G. E-mail: miralda@icc.ub.edu

    2012-11-01

    We present the first measurement of the large-scale cross-correlation of Lyα forest absorption and Damped Lyman α systems (DLA), using the 9th Data Release of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is clearly detected on scales up to 40h{sup −1}Mpc and is well fitted by the linear theory prediction of the standard Cold Dark Matter model of structure formation with the expected redshift distortions, confirming its origin in the gravitational evolution of structure. The amplitude of the DLA-Lyα cross-correlation depends on only one free parameter, the bias factor of the DLA systems, once the Lyα forest bias factors are known from independent Lyα forest correlation measurements. We measure the DLA bias factor to be b{sub D} = (2.17±0.20)β{sub F}{sup 0.22}, where the Lyα forest redshift distortion parameter β{sub F} is expected to be above unity. This bias factor implies a typical host halo mass for DLAs that is much larger than expected in present DLA models, and is reproduced if the DLA cross section scales with halo mass as M{sub h}{sup α}, with α = 1.1±0.1 for β{sub F} = 1. Matching the observed DLA bias factor and rate of incidence requires that atomic gas remains extended in massive halos over larger areas than predicted in present simulations of galaxy formation, with typical DLA proper sizes larger than 20 kpc in host halos of masses ∼ 10{sup 12}M{sub ☉}. We infer that typical galaxies at z ≅ 2 to 3 are surrounded by systems of atomic clouds that are much more extended than the luminous parts of galaxies and contain ∼ 10% of the baryons in the host halo.

  1. 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.

  2. Dendrochronological Modeling and Reconstruction of Large-Scale Climate Variability in Recent Centuries and its Relation to Atmospheric Forcing Functions.

    NASA Astrophysics Data System (ADS)

    D'Arrigo, Rosanne Dorothy

    Tree-ring chronologies from boreal treeline and other sites have been used to reconstruct patterns of climate variability, their relationship to known forcing functions, and climate as modeled using these forcings. Northern Hemisphere temperatures reconstructed for the past three hundred years agree with other proxy data and with temperature derived from a radiative-convective model incorporating volcanic, solar and CO_2 forcings. Superposed epoch analysis shows the effects of volcanism on tree growth and spectral analysis indicated periodicities which might be related to solar or other cycles. Comparison of the reconstructed temperatures with recent instrumental records reveals that the temperature departures within the past decade of elevated atmospheric trace gases levels exceed the "natural" variations in the tree-ring data in past centuries. A CO_2 fertilization effect is not detected in this data through 1973. This issue is further investigated for a high-elevation lodgepole pine site from California. Climate response models indicate that a recent growth increase cannot be completely explained by past climate-growth relationships. The contribution of atmosphere-biosphere CO_2 exchange of boreal forests to Pt. Barrow, Alaska CO_2 amplitudes is found to be significant using a 3 -D tracer model which employs an exchange function based on remote sensing photosynthetic indices. Positive correlations between variations in these amplitudes and tree-ring data suggest that tree-rings may be used as indicators of CO _2 uptake and remote sensing estimates of photosynthetic activity. The northern chronologies show patterns of variation which have climatic implications. Their coefficient of variation reveals periods of agreement/disagreement among the sites which in turn indicate varying periods of spatial coherence in atmospheric circulation patterns. Included among the years of highest variation is 1816, one year following the Tambora eruption. The tree growth anomalies

  3. 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.

    2010-08-01

    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, cloud fraction as derived considering a typical large-scale model grid box), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, terminal fall speed, 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 rationale for characterizing this variability is to provide an observational basis to which model outputs can be compared for the different regimes or large-scale characteristics and from which new parameterizations accounting for the large-scale context can be derived. The mean vertical variability of ice cloud occurrence and microphysical properties is large (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). Our results also indicate that, at least in the northern Australian region, the upper part of the troposphere can be split into three distinct layers characterized by different statistically-dominant microphysical processes. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is found to be large

  4. Correlation of generation interval and scale of large-scale submarine landslides using 3D seismic data off Shimokita Peninsula, Northeast Japan

    NASA Astrophysics Data System (ADS)

    Nakamura, Yuki; Ashi, Juichiro; Morita, Sumito

    2016-04-01

    To clarify timing and scale of past submarine landslides is important to understand formation processes of the landslides. The study area is in a part of continental slope of the Japan Trench, where a number of large-scale submarine landslide (slump) deposits have been identified in Pliocene and Quaternary formations by analysing METI's 3D seismic data "Sanrikuoki 3D" off Shimokita Peninsula (Morita et al., 2011). As structural features, swarm of parallel dikes which are likely dewatering paths formed accompanying the slumping deformation, and slip directions are basically perpendicular to the parallel dikes. Therefore, parallel dikes are good indicator for estimation of slip directions. Slip direction of each slide was determined one kilometre grid in the survey area of 40 km x 20 km. The remarkable slip direction varies from Pliocene to Quaternary in the survey area. Parallel dike structure is also available for the distinguishment of the slump deposit and normal deposit on time slice images. By tracing outline of slump deposits at each depth, we identified general morphology of the overall slump deposits, and calculated the volume of the extracted slump deposits so as to estimate the scale of each event. We investigated temporal and spatial variation of depositional pattern of the slump deposits. Calculating the generation interval of the slumps, some periodicity is likely recognized, especially large slump do not occur in succession. Additionally, examining the relationship of the cumulative volume and the generation interval, certain correlation is observed in Pliocene and Quaternary. Key words: submarine landslides, 3D seismic data, Shimokita Peninsula

  5. 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

  6. 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

  7. Dynamic multi-swarm particle swarm optimizer using parallel PC cluster systems for global optimization of large-scale multimodal functions

    NASA Astrophysics Data System (ADS)

    Fan, Shu-Kai S.; Chang, Ju-Ming

    2010-05-01

    This article presents a novel parallel multi-swarm optimization (PMSO) algorithm with the aim of enhancing the search ability of standard single-swarm PSOs for global optimization of very large-scale multimodal functions. Different from the existing multi-swarm structures, the multiple swarms work in parallel, and the search space is partitioned evenly and dynamically assigned in a weighted manner via the roulette wheel selection (RWS) mechanism. This parallel, distributed framework of the PMSO algorithm is developed based on a master-slave paradigm, which is implemented on a cluster of PCs using message passing interface (MPI) for information interchange among swarms. The PMSO algorithm handles multiple swarms simultaneously and each swarm performs PSO operations of its own independently. In particular, one swarm is designated for global search and the others are for local search. The first part of the experimental comparison is made among the PMSO, standard PSO, and two state-of-the-art algorithms (CTSS and CLPSO) in terms of various un-rotated and rotated benchmark functions taken from the literature. In the second part, the proposed multi-swarm algorithm is tested on large-scale multimodal benchmark functions up to 300 dimensions. The results of the PMSO algorithm show great promise in solving high-dimensional problems.

  8. Large-scale real-space density-functional calculations: Moiré-induced electron localization in graphene

    SciTech Connect

    Oshiyama, Atsushi Iwata, Jun-Ichi; Uchida, Kazuyuki; Matsushita, Yu-Ichiro

    2015-03-21

    We show that our real-space finite-difference scheme allows us to perform density-functional calculations for nanometer-scale targets containing more than 100 000 atoms. This real-space scheme is applied to twisted bilayer graphene, clarifying that Moiré pattern induced in the slightly twisted bilayer graphene drastically modifies the atomic and electronic structures.

  9. Managing and analysing data from a large-scale study on Framingham Offspring relating brain structure to cognitive function.

    PubMed

    Massaro, Joseph M; D'Agostino, Ralph B; Sullivan, Lisa M; Beiser, Alexa; DeCarli, Charles; Au, Rhoda; Elias, Merrill F; Wolf, Philip A

    2004-01-30

    At the Framingham Heart Study under separate research grant funding from the National Institute of Aging, NIH, we are gathering brain structure and cognitive information on the Framingham Offspring, creating one of the largest known data sets to assess changes in brain structure associated with normative ageing and cognitive decline. Subject recruitment, data collection, data management and statistical analysis require a collaborative integrated effort on the part of the Framingham project team. Here we describe this effort, as well as the various brain structure and cognitive function parameters we are now collecting. We are currently performing analyses of data collected through 2002, and we discuss the statistical issues arising relating brain structure parameters to cognitive function. PMID:14716734

  10. Large-scale first principles and tight-binding density functional theory calculations on hydrogen-passivated silicon nanorods

    NASA Astrophysics Data System (ADS)

    Zonias, Nicholas; Lagoudakis, Pavlos; Skylaris, Chris-Kriton

    2010-01-01

    We present a computational study by density functional theory (DFT) of entire silicon nanorods with up to 1648 atoms without any periodicity or symmetry imposed. The nanorods have been selected to have varying aspect ratios and levels of surface passivation with hydrogen. The structures of the nanorods have been optimized using a density functional tight-binding approach, while energies and electronic properties have been computed using linear-scaling DFT with plane-wave accuracy with the ONETEP (Skylaris et al 2005 J. Chem. Phys. 122 084119) program. The aspect ratio and surface passivation (1 × 1 and 2 × 1 reconstructions) along with the size of the nanorods which leads to quantum confinement along all three dimensions, significantly affect their electronic properties. The structures of the nanorods also show interesting behaviour as, depending on their characteristics, they can in certain areas retain the structure of bulk silicon while in other parts significantly deviate from it.

  11. Use of large-scale expression cloning screens in the Xenopus laevis tadpole to identify gene function.

    PubMed

    Grammer, T C; Liu, K J; Mariani, F V; Harland, R M

    2000-12-15

    We have conducted an expression cloning screen of approximately 50, 000 cDNAs from a tadpole stage Xenopus laevis cDNA library to functionally identify genes affecting a wide range of cellular and developmental processes. Fifty-seven cDNAs were isolated for their ability to alter gross tadpole morphology or the expression patterns of tissue-specific markers. Thirty-seven of the cDNAs have not been previously described for Xenopus, and 15 of these show little or no similarity to sequences in the NCBI database. The screen and the identified genes are presented in this paper to demonstrate the power, ease, speed, and flexibility of expression cloning in the X. laevis embryo. Future screens such as this one can be done on a larger scale and will complement the sequence-based screens and genome-sequencing projects which are producing a large body of novel genes without ascribed functions. PMID:11112324

  12. A large-scale collection of phenotypic data describing an insertional mutant population to facilitate functional analysis of rice genes

    PubMed Central

    Iwasaki, Yukimoto; Kitano, Hidemi; Itoh, Jun-Ichi; Maekawa, Masahiko; Murata, Kazumasa; Yatou, Osamu; Nagato, Yasuo; Hirochika, Hirohiko

    2006-01-01

    In order to facilitate the functional analysis of rice genes, we produced about 50,000 insertion lines with the endogenous retrotransposon Tos17. Phenotypes of these lines in the M2 generation were observed in the field and characterized based on 53 phenotype descriptors. Nearly half of the lines showed more than one mutant phenotype. The most frequently observed phenotype was low fertility, followed by dwarfism. Phenotype data with photographs of each line are stored in the Tos17 mutant panel web-based database with a dataset of sequences flanking Tos17 insertion points in the rice genome (http://tos.nias.affrc.go.jp/). This combination of phenotypic and flanking sequence data will stimulate the functional analysis of rice genes. PMID:17180734

  13. 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…

  14. Large-Scale, High-Resolution Multielectrode-Array Recording Depicts Functional Network Differences of Cortical and Hippocampal Cultures

    PubMed Central

    Ito, Shinya; Yeh, Fang-Chin; Hiolski, Emma; Rydygier, Przemyslaw; Gunning, Deborah E.; Hottowy, Pawel; Timme, Nicholas; Litke, Alan M.; Beggs, John M.

    2014-01-01

    Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array system to record the activity from hundreds of neurons in organotypic cultures of cortico-hippocampal brain slices from mice. To probe the network structure, we employed a wavelet transform of the cross-correlogram to categorize the functional connectivity in different frequency ranges. With this method we directly compare, for the first time, in any preparation, the neuronal network structures of cortex and hippocampus, on the scale of hundreds of neurons, with sub-millisecond time resolution. Among the three frequency ranges that we investigated, the lower two frequency ranges (gamma (30–80 Hz) and beta (12–30 Hz) range) showed similar network structure between cortex and hippocampus, but there were many significant differences between these structures in the high frequency range (100–1000 Hz). The high frequency networks in cortex showed short tailed degree-distributions, shorter decay length of connectivity density, smaller clustering coefficients, and positive assortativity. Our results suggest that our method can characterize frequency dependent differences of network architecture from different brain regions. Crucially, because these differences between brain regions require millisecond temporal scales to be observed and characterized, these results underscore the importance of high temporal resolution recordings for the understanding of functional networks in neuronal systems. PMID:25126851

  15. Large-scale intrinsic functional network organization along the long axis of the human medial temporal lobe.

    PubMed

    Qin, Shaozheng; Duan, Xujun; Supekar, Kaustubh; Chen, Huafu; Chen, Tianwen; Menon, Vinod

    2016-07-01

    The medial temporal lobe (MTL), encompassing the hippocampus and parahippocampal gyrus (PHG), is a heterogeneous structure which plays a critical role in memory and cognition. Here, we investigate functional architecture of the human MTL along the long axis of the hippocampus and PHG. The hippocampus showed stronger connectivity with striatum, ventral tegmental area and amygdala-regions important for integrating reward and affective signals, whereas the PHG showed stronger connectivity with unimodal and polymodal association cortices. In the hippocampus, the anterior node showed stronger connectivity with the anterior medial temporal lobe and the posterior node showed stronger connectivity with widely distributed cortical and subcortical regions including those involved in sensory and reward processing. In the PHG, differences were characterized by a gradient of increasing anterior-to-posterior connectivity with core nodes of the default mode network. Left and right MTL connectivity patterns were remarkably similar, except for stronger left than right MTL connectivity with regions in the left MTL, the ventral striatum and default mode network. Graph theoretical analysis of MTL-based networks revealed higher node centrality of the posterior, compared to anterior and middle hippocampus. The PHG showed prominent gradients in both node degree and centrality along its anterior-to-posterior axis. Our findings highlight several novel aspects of functional heterogeneity in connectivity along the long axis of the human MTL and provide new insights into how its network organization supports integration and segregation of signals from distributed brain areas. The implications of our findings for a principledunderstanding of distributed pathways that support memory and cognition are discussed. PMID:26336951

  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. Linking X-ray AGN with dark matter halos: a model compatible with AGN luminosity function and large-scale clustering properties

    NASA Astrophysics Data System (ADS)

    Hütsi, Gert; Gilfanov, Marat; Sunyaev, Rashid

    2014-01-01

    Aims: Our goal is to find a minimalistic model that describes the luminosity function and large-scale clustering bias of X-ray-selected active galactic nuclei in the general framework of the concordance ΛCDM model. Methods: We assume that a simple population-averaged scaling relation between the AGN X-ray luminosity LX and the host dark matter halo mass Mh exists. With such a relation, the AGN X-ray luminosity function can be computed from the halo mass function. Using the concordance ΛCDM halo mass function for the latter, we obtain the Mh - LX relation required to match the redshift-dependent AGN X-ray luminosity function known from X-ray observations. Results: We find that with a simple power-law-scaling Mh ∝ LΓ(z), our model can successfully reproduce the observed X-ray luminosity function. Furthermore, we automatically obtain predictions for the large-scale AGN clustering amplitudes and their dependence on the luminosity and redshift, which seem to be compatible with AGN clustering measurements. Our model also includes the redshift-dependent AGN duty cycle, which peaks at the redshift z ≃ 1, and its peak value is consistent with unity, suggesting that on average there is no more than one AGN per dark matter halo. For a typical X-ray-selected AGN at z ~ 1, our best-fit Mh - LX scaling implies low Eddington ratio LX/LEdd ~ 10-4 - 10-3 (2-10 keV band, no bolometric correction applied) and correspondingly high mass-growth e-folding times, suggesting that typical X-ray AGN are dominantly fueled via relatively inefficient "hot-halo" accretion mode.

  18. Identification of Genes Important for Cutaneous Function Revealed by a Large Scale Reverse Genetic Screen in the Mouse

    PubMed Central

    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.

    2014-01-01

    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. PMID:25340873

  19. 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.

  20. 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.

  1. Synthesis of small and large scale dynamos

    NASA Astrophysics Data System (ADS)

    Subramanian, Kandaswamy

    Using a closure model for the evolution of magnetic correlations, we uncover an interesting plausible saturated state of the small-scale fluctuation dynamo (SSD) and a novel analogy between quantum mechanical tunnelling and the generation of large-scale fields. Large scale fields develop via the α-effect, but as magnetic helicity can only change on a resistive timescale, the time it takes to organize the field into large scales increases with magnetic Reynolds number. This is very similar to the results which obtain from simulations using the full MHD equations.

  2. The Lyman-α forest in three dimensions: measurements of large scale flux correlations from BOSS 1st-year data

    SciTech Connect

    Slosar, Anže; Font-Ribera, Andreu; Pieri, Matthew M.; Rich, James; Goff, Jean-Marc Le; Charlassier, Romain; Aubourg, Éric; Busca, Nicolas; Hamilton, Jean-Christophe; Carithers, Bill; Cortês, Marina; Ho, Shirley; McDonald, Patrick; Croft, Rupert; Dawson, Kyle S.; Eisenstein, Daniel; Lee, Khee-Gan; Lupton, Robert; Medolin, Bumbarija; and others

    2011-09-01

    Using a sample of approximately 14,000 z > 2.1 quasars observed in the first year of the Baryon Oscillation Spectroscopic Survey (BOSS), we measure the three-dimensional correlation function of absorption in the Lyman-α forest. The angle-averaged correlation function of transmitted flux (F = e{sup −τ}) is securely detected out to comoving separations of 60 h{sup −1}Mpc, the first detection of flux correlations across widely separated sightlines. A quadrupole distortion of the redshift-space correlation function by peculiar velocities, the signature of the gravitational instability origin of structure in the Lyman-α forest, is also detected at high significance. We obtain a good fit to the data assuming linear theory redshift-space distortion and linear bias of the transmitted flux, relative to the matter fluctuations of a standard ΛCDM cosmological model (inflationary cold dark matter with a cosmological constant). At 95% confidence, we find a linear bias parameter 0.16 < b < 0.24 and redshift-distortion parameter 0.44 < β < 1.20, at central redshift z = 2.25, with a well constrained combination b(1+β) = 0.336±0.012. The errors on β are asymmetric, with β = 0 excluded at over 5σ confidence level. The value of β is somewhat low compared to theoretical predictions, and our tests on synthetic data suggest that it is depressed (relative to expectations for the Lyman-α forest alone) by the presence of high column density systems and metal line absorption. These results set the stage for cosmological parameter determinations from three-dimensional structure in the Lyman-α forest, including anticipated constraints on dark energy from baryon acoustic oscillations.

  3. The Lyman-α forest in three dimensions: measurements of large scale flux correlations from BOSS 1st-year data

    NASA Astrophysics Data System (ADS)

    Slosar, Anže; Font-Ribera, Andreu; Pieri, Matthew M.; Rich, James; Le Goff, Jean-Marc; Aubourg, Éric; Brinkmann, Jon; Busca, Nicolas; Carithers, Bill; Charlassier, Romain; Cortês, Marina; Croft, Rupert; Dawson, Kyle S.; Eisenstein, Daniel; Hamilton, Jean-Christophe; Ho, Shirley; Lee, Khee-Gan; Lupton, Robert; McDonald, Patrick; Medolin, Bumbarija; Muna, Demitri; Miralda-Escudé, Jordi; Myers, Adam D.; Nichol, Robert C.; Palanque-Delabrouille, Nathalie; Pâris, Isabelle; Petitjean, Patrick; Piškur, Yodovina; Rollinde, Emmanuel; Ross, Nicholas P.; Schlegel, David J.; Schneider, Donald P.; Sheldon, Erin; Weaver, Benjamin A.; Weinberg, David H.; Yeche, Christophe; York, Donald G.

    2011-09-01

    Using a sample of approximately 14,000 z > 2.1 quasars observed in the first year of the Baryon Oscillation Spectroscopic Survey (BOSS), we measure the three-dimensional correlation function of absorption in the Lyman-α forest. The angle-averaged correlation function of transmitted flux (F = e-τ) is securely detected out to comoving separations of 60 h-1Mpc, the first detection of flux correlations across widely separated sightlines. A quadrupole distortion of the redshift-space correlation function by peculiar velocities, the signature of the gravitational instability origin of structure in the Lyman-α forest, is also detected at high significance. We obtain a good fit to the data assuming linear theory redshift-space distortion and linear bias of the transmitted flux, relative to the matter fluctuations of a standard ΛCDM cosmological model (inflationary cold dark matter with a cosmological constant). At 95% confidence, we find a linear bias parameter 0.16 < b < 0.24 and redshift-distortion parameter 0.44 < β < 1.20, at central redshift z = 2.25, with a well constrained combination b(1+β) = 0.336±0.012. The errors on β are asymmetric, with β = 0 excluded at over 5σ confidence level. The value of β is somewhat low compared to theoretical predictions, and our tests on synthetic data suggest that it is depressed (relative to expectations for the Lyman-α forest alone) by the presence of high column density systems and metal line absorption. These results set the stage for cosmological parameter determinations from three-dimensional structure in the Lyman-α forest, including anticipated constraints on dark energy from baryon acoustic oscillations.

  4. A one-step approach to the large-scale synthesis of functionalized MoS2 nanosheets by ionic liquid assisted grinding

    NASA Astrophysics Data System (ADS)

    Zhang, Wentao; Wang, Yanru; Zhang, Daohong; Yu, Shaoxuan; Zhu, Wenxin; Wang, Jing; Zheng, Fangqing; Wang, Shuaixing; Wang, Jianlong

    2015-05-01

    A prerequisite for exploiting most proposed applications for MoS2 is the availability of water-dispersible functionalized MoS2 nanosheets in large quantities. Here we report one-step synthesis and surface functionalization of MoS2 nanosheets by a facile ionic liquid assisted grinding method in the presence of chitosan. The selected ionic liquid with suitable surface energy could efficiently overcome the van der Waals force between the MoS2 layers. Meanwhile, chitosan molecules bind to the plane of MoS2 sheets non-covalently, which prevents the reassembling of exfoliated MoS2 sheets and facilitates the exfoliation progress. The obtained chitosan functionalized MoS2 nanosheets possess favorable stability and biocompatibility, which renders them as promising and biocompatible near-infrared agents for photothermal ablation of cancer. This contribution provides a facile way for the green, one-step and large-scale synthesis of advanced functional MoS2 materials.A prerequisite for exploiting most proposed applications for MoS2 is the availability of water-dispersible functionalized MoS2 nanosheets in large quantities. Here we report one-step synthesis and surface functionalization of MoS2 nanosheets by a facile ionic liquid assisted grinding method in the presence of chitosan. The selected ionic liquid with suitable surface energy could efficiently overcome the van der Waals force between the MoS2 layers. Meanwhile, chitosan molecules bind to the plane of MoS2 sheets non-covalently, which prevents the reassembling of exfoliated MoS2 sheets and facilitates the exfoliation progress. The obtained chitosan functionalized MoS2 nanosheets possess favorable stability and biocompatibility, which renders them as promising and biocompatible near-infrared agents for photothermal ablation of cancer. This contribution provides a facile way for the green, one-step and large-scale synthesis of advanced functional MoS2 materials. Electronic supplementary information (ESI) available: The

  5. Lagrangian space consistency relation for large scale structure

    NASA Astrophysics Data System (ADS)

    Horn, Bart; Hui, Lam; Xiao, Xiao

    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 & Riotto and Peloso & 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.

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

    PubMed

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

    2016-04-01

    Variants inCACNA1Athat encodes the pore-forming α1-subunit of human voltage-gated Cav2.1 (P/Q-type) Ca(2+)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 theCaenorhabditis elegansstrain CB55, which carries a truncating mutation in theunc-2gene, the worm ortholog for the humanCACNA1A 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 ofunc-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 theC. elegansneurons. 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 tounc-2/CACNA1A, further confirming the involvement of the transforming growth factor β pathway and adding a novel signaling cascade, the Notch pathway. PMID:27005779

  7. 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

  8. Challenges for Large Scale Simulations

    NASA Astrophysics Data System (ADS)

    Troyer, Matthias

    2010-03-01

    With computational approaches becoming ubiquitous the growing impact of large scale computing on research influences both theoretical and experimental work. I will review a few examples in condensed matter physics and quantum optics, including the impact of computer simulations in the search for supersolidity, thermometry in ultracold quantum gases, and the challenging search for novel phases in strongly correlated electron systems. While only a decade ago such simulations needed the fastest supercomputers, many simulations can now be performed on small workstation clusters or even a laptop: what was previously restricted to a few experts can now potentially be used by many. Only part of the gain in computational capabilities is due to Moore's law and improvement in hardware. Equally impressive is the performance gain due to new algorithms - as I will illustrate using some recently developed algorithms. At the same time modern peta-scale supercomputers offer unprecedented computational power and allow us to tackle new problems and address questions that were impossible to solve numerically only a few years ago. While there is a roadmap for future hardware developments to exascale and beyond, the main challenges are on the algorithmic and software infrastructure side. Among the problems that face the computational physicist are: the development of new algorithms that scale to thousands of cores and beyond, a software infrastructure that lifts code development to a higher level and speeds up the development of new simulation programs for large scale computing machines, tools to analyze the large volume of data obtained from such simulations, and as an emerging field provenance-aware software that aims for reproducibility of the complete computational workflow from model parameters to the final figures. Interdisciplinary collaborations and collective efforts will be required, in contrast to the cottage-industry culture currently present in many areas of computational

  9. Understanding the recurrent large-scale green tide in the Yellow Sea: temporal and spatial correlations between multiple geographical, aquacultural and biological factors.

    PubMed

    Liu, Feng; Pang, Shaojun; Chopin, Thierry; Gao, Suqin; Shan, Tifeng; Zhao, Xiaobo; Li, Jing

    2013-02-01

    The coast of Jiangsu Province in China - where Ulva prolifera has always been firstly spotted before developing into green tides - is uniquely characterized by a huge intertidal radial mudflat. Results showed that: (1) propagules of U. prolifera have been consistently present in seawater and sediments of this mudflat and varied with locations and seasons; (2) over 50,000 tons of fermented chicken manure have been applied annually from March to May in coastal animal aquaculture ponds and thereafter the waste water has been discharged into the radial mudflat intensifying eutrophication; and (3) free-floating U. prolifera could be stranded in any floating infrastructures in coastal waters including large scale Porphyra farming rafts. For a truly integrated management of the coastal zone, reduction in nutrient inputs, and control of the effluents of the coastal pond systems, are needed to control eutrophication and prevent green tides in the future. PMID:23176870

  10. The LOSS OF APOMEIOSIS (LOA) locus in Hieracium praealtum can function independently of the associated large-scale repetitive chromosomal structure.

    PubMed

    Kotani, Yoshiko; Henderson, Steven T; Suzuki, Go; Johnson, Susan D; Okada, Takashi; Siddons, Hayley; Mukai, Yasuhiko; Koltunow, Anna M G

    2014-02-01

    Apomixis or asexual seed formation in Hieracium praealtum (Asteraceae) is controlled by two independent dominant loci. One of these, the LOSS OF APOMEIOSIS (LOA) locus, controls apomixis initiation, mitotic embryo sac formation (apospory) and suppression of the sexual pathway. The LOA locus is found near the end of a hemizygous chromosome surrounded by extensive repeats extending along the chromosome arm. Similar apomixis-carrying chromosome structures have been found in some apomictic grasses, suggesting that the extensive repetitive sequences may be functionally relevant to apomixis. Fluorescence in situ hybridization (FISH) was used to examine chromosomes of apomeiosis deletion mutants and rare recombinants in the critical LOA region arising from a cross between sexual Hieracium pilosella and apomictic H. praealtum. The combined analyses of aposporous and nonaposporous recombinant progeny and chromosomal karyotypes were used to determine that the functional LOA locus can be genetically separated from the very extensive repeat regions found on the LOA-carrying chromosome. The large-scale repetitive sequences associated with the LOA locus in H. praealtum are not essential for apospory or suppression of sexual megasporogenesis (female meiosis). PMID:24400904

  11. 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.

  12. Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models.

    PubMed

    Penner, Jacob; Ford, Kristen A; Taylor, Reggie; Schaefer, Betsy; Théberge, Jean; Neufeld, Richard W J; Osuch, Elizabeth A; Menon, Ravi S; Rajakumar, Nagalingam; Allman, John M; Williamson, Peter C

    2016-01-01

    Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls. PMID:27064387

  13. Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models

    PubMed Central

    Penner, Jacob; Ford, Kristen A.; Taylor, Reggie; Schaefer, Betsy; Théberge, Jean; Neufeld, Richard W. J.; Osuch, Elizabeth A.; Menon, Ravi S.; Rajakumar, Nagalingam; Allman, John M.; Williamson, Peter C.

    2016-01-01

    Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls. PMID:27064387

  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. Cosmic string and formation of large scale structure.

    NASA Astrophysics Data System (ADS)

    Fang, L.-Z.; Xiang, S.-P.

    Cosmic string formed due to phase transition in the early universe may be the cause of galaxy formation and clustering. The advantage of string model is that it can give a consistent explanation of all observed results related to large scale structure, such as correlation functions of galaxies, clusters and superclusters, the existence of voids and/or bubbles, anisotropy of cosmic background radiation. A systematic review on string model has been done.

  16. GICUDA: A parallel program for 3D correlation imaging of large scale gravity and gravity gradiometry data on graphics processing units with CUDA

    NASA Astrophysics Data System (ADS)

    Chen, Zhaoxi; Meng, Xiaohong; Guo, Lianghui; Liu, Guofeng

    2012-09-01

    The 3D correlation imaging for gravity and gravity gradiometry data provides a rapid approach to the equivalent estimation of objective bodies with different density contrasts in the subsurface. The subsurface is divided into a 3D regular grid, and then a cross correlation between the observed data and the theoretical gravity anomaly due to a point mass source is calculated at each grid node. The resultant correlation coefficients are adopted to describe the equivalent mass distribution in a quantitate probability sense. However, when the size of the survey data is large, it is still computationally expensive. With the advent of the CUDA, GPUs lead to a new path for parallel computing, which have been widely applied in seismic processing, astronomy, molecular dynamics simulation, fluid mechanics and some other fields. We transfer the main time-consuming program of 3D correlation imaging into GPU device, where the program can be executed in a parallel way. The synthetic and real tests have been performed to validate the correctness of our code on NVIDIA GTX 550. The precision evaluation and performance speedup comparison of the CPU and GPU implementations are illustrated with different sizes of gravity data. When the size of grid nodes and observed data sets is 1024×1024×1 and 1024×1024, the speed up can reach to 81.5 for gravity data and 90.7 for gravity vertical gradient data respectively, thus providing the basis for the rapid interpretation of gravity and gravity gradiometry data.

  17. Three Large-Scale Functional Brain Networks from Resting-State Functional MRI in Subjects with Different Levels of Cognitive Impairment

    PubMed Central

    Joo, Soo Hyun; Lim, Hyun Kook

    2016-01-01

    Normal aging and to a greater degree degenerative brain diseases such as Alzheimer's disease (AD), cause changes in the brain's structure and function. Degenerative changes in brain structure and decline in its function are associated with declines in cognitive ability. Early detection of AD is a key priority in dementia services and research. However, depending on the disease progression, neurodegenerative manifestations, such as cerebral atrophy, are detected late in course of AD. Functional changes in the brain may be an indirect indicator of trans-synaptic activity and they usually appear prior to structural changes in AD. Resting-state functional magnetic resonance imaging (RS-fMRI) has recently been highlighted as a new technique for interrogating intrinsic functional connectivity networks. Among the majority of RS-fMRI studies, the default mode network (DMN), salience network (SN), and central executive network (CEN) gained particular focus because alterations to their functional connectivity were observed in subjects who had AD, who had mild cognitive impairment (MCI), or who were at high risk for AD. Herein, we present a review of the current research on changes in functional connectivity, as measured by RS-fMRI. We focus on the DMN, SN, and CEN to describe RS-fMRI results from three groups: normal healthy aging, MCI and AD. PMID:26766941

  18. Three Large-Scale Functional Brain Networks from Resting-State Functional MRI in Subjects with Different Levels of Cognitive Impairment.

    PubMed

    Joo, Soo Hyun; Lim, Hyun Kook; Lee, Chang Uk

    2016-01-01

    Normal aging and to a greater degree degenerative brain diseases such as Alzheimer's disease (AD), cause changes in the brain's structure and function. Degenerative changes in brain structure and decline in its function are associated with declines in cognitive ability. Early detection of AD is a key priority in dementia services and research. However, depending on the disease progression, neurodegenerative manifestations, such as cerebral atrophy, are detected late in course of AD. Functional changes in the brain may be an indirect indicator of trans-synaptic activity and they usually appear prior to structural changes in AD. Resting-state functional magnetic resonance imaging (RS-fMRI) has recently been highlighted as a new technique for interrogating intrinsic functional connectivity networks. Among the majority of RS-fMRI studies, the default mode network (DMN), salience network (SN), and central executive network (CEN) gained particular focus because alterations to their functional connectivity were observed in subjects who had AD, who had mild cognitive impairment (MCI), or who were at high risk for AD. Herein, we present a review of the current research on changes in functional connectivity, as measured by RS-fMRI. We focus on the DMN, SN, and CEN to describe RS-fMRI results from three groups: normal healthy aging, MCI and AD. PMID:26766941

  19. Large Scale Nanolaminate Deformable Mirror

    SciTech Connect

    Papavasiliou, A; Olivier, S; Barbee, T; Miles, R; Chang, K

    2005-11-30

    This work concerns the development of a technology that uses Nanolaminate foils to form light-weight, deformable mirrors that are scalable over a wide range of mirror sizes. While MEMS-based deformable mirrors and spatial light modulators have considerably reduced the cost and increased the capabilities of adaptive optic systems, there has not been a way to utilize the advantages of lithography and batch-fabrication to produce large-scale deformable mirrors. This technology is made scalable by using fabrication techniques and lithography that are not limited to the sizes of conventional MEMS devices. Like many MEMS devices, these mirrors use parallel plate electrostatic actuators. This technology replicates that functionality by suspending a horizontal piece of nanolaminate foil over an electrode by electroplated nickel posts. This actuator is attached, with another post, to another nanolaminate foil that acts as the mirror surface. Most MEMS devices are produced with integrated circuit lithography techniques that are capable of very small line widths, but are not scalable to large sizes. This technology is very tolerant of lithography errors and can use coarser, printed circuit board lithography techniques that can be scaled to very large sizes. These mirrors use small, lithographically defined actuators and thin nanolaminate foils allowing them to produce deformations over a large area while minimizing weight. This paper will describe a staged program to develop this technology. First-principles models were developed to determine design parameters. Three stages of fabrication will be described starting with a 3 x 3 device using conventional metal foils and epoxy to a 10-across all-metal device with nanolaminate mirror surfaces.

  20. Investigating the correlation between white matter and microvasculature changes in aging using large scale optical coherence tomography and confocal fluorescence imaging combined with tissue sectioning

    NASA Astrophysics Data System (ADS)

    Castonguay, Alexandre; Avti, Pramod K.; Moeini, Mohammad; Pouliot, Philippe; Tabatabaei, Maryam S.; Bélanger, Samuel; Lesage, Frédéric

    2015-03-01

    Here, we present a serial OCT/confocal scanner for histological study of the mouse brain. Three axis linear stages combined with a sectioning vibratome allows to cut thru the entire biological tissue and to image every section at a microscopic resolution. After acquisition, each OCT volume and confocal image is re-stitched with adjacent acquisitions to obtain a reconstructed, digital volume of the imaged tissue. This imaging platform was used to investigate correlations between white matter and microvasculature changes in aging mice. Three age groups were used in this study (4, 12, 24 months). At sacrifice, mice were transcardially perfused with a FITC containing gel. The dual imaging capability of the system allowed to reveal different contrast information: OCT imaging reveals changes in refractive indices giving contrast between white and grey matter in the mouse brain, while transcardial perfusion of a FITC shows microsvasculature in the brain with confocal imaging.

  1. A METHOD TO SEARCH FOR CORRELATIONS OF ULTRA-HIGH ENERGY COSMIC-RAY MASSES WITH THE LARGE-SCALE STRUCTURES IN THE LOCAL GALAXY DENSITY FIELD

    SciTech Connect

    Ivanov, A. A.

    2013-02-15

    One of the main goals of investigations using present and future giant extensive air shower (EAS) arrays is the mass composition of ultra-high energy cosmic rays (UHECRs). A new approach to the problem is presented, combining the analysis of arrival directions with the statistical test of the paired EAS samples. One of the ideas of the method is to search for possible correlations between UHECR masses and their separate sources; for instance, if there are two sources in different areas of the celestial sphere injecting different nuclei, but the fluxes are comparable so that arrival directions are isotropic, then the aim is to reveal a difference in the mass composition of cosmic-ray fluxes. The method is based on a non-parametric statistical test-the Wilcoxon signed-rank routine-which does not depend on the populations fitting any parameterized distributions. Two particular algorithms are proposed: first, using measurements of the depth of the EAS maximum position in the atmosphere; and second, relying on the age variance of air showers initiated by different primary particles. The formulated method is applied to the Yakutsk array data, in order to demonstrate the possibility of searching for a difference in average mass composition between the two UHECR sets, arriving particularly from the supergalactic plane and a complementary region.

  2. Very Large Scale Integration (VLSI).

    ERIC Educational Resources Information Center

    Yeaman, Andrew R. J.

    Very Large Scale Integration (VLSI), the state-of-the-art production techniques for computer chips, promises such powerful, inexpensive computing that, in the future, people will be able to communicate with computer devices in natural language or even speech. However, before full-scale VLSI implementation can occur, certain salient factors must be…

  3. Pd(0)-Catalyzed Direct C-H Functionalization of 2-H-4-Benzylidene Imidazolones: Friendly and Large-Scale Access to GFP and Kaede Protein Fluorophores.

    PubMed

    Muselli, Mickaël; Baudequin, Christine; Perrio, Cécile; Hoarau, Christophe; Bischoff, Laurent

    2016-04-11

    The first one-pot synthesis of N-substituted 2-H-4-benzylidene imidazolones and their subsequent palladium-catalyzed and copper-assisted direct C2-H arylation and alkenylation with aryl- and alkenylhalides are described. This innovative synthesis is step-economical, azide-free, high yielding, highly flexible in the introduction of a variety of electronically different groups, and can be operated on large-scale. Moreover, the method allows direct access to C2-arylated or alkenylated imidazolone-based green fluorescent protein (GFP) and Kaede protein fluorophores, including ortho-hydroxylated models. PMID:26960963

  4. Is Traumatic Brain Injury Associated with Reduced Inter-Hemispheric Functional Connectivity? A Study of Large-Scale Resting State Networks following Traumatic Brain Injury.

    PubMed

    Rigon, Arianna; Duff, Melissa C; McAuley, Edward; Kramer, Arthur F; Voss, Michelle W

    2016-06-01

    Traumatic brain injury (TBI) often has long-term debilitating sequelae in cognitive and behavioral domains. Understanding how TBI impacts functional integrity of brain networks that underlie these domains is key to guiding future approaches to TBI rehabilitation. In the current study, we investigated the differences in inter-hemispheric functional connectivity (FC) of resting state networks (RSNs) between chronic mild-to-severe TBI patients and normal comparisons (NC), focusing on two externally oriented networks (i.e., the fronto-parietal network [FPN] and the executive control network [ECN]), one internally oriented network (i.e., the default mode network [DMN]), and one somato-motor network (SMN). Seed voxel correlation analysis revealed that TBI patients displayed significantly less FC between lateralized seeds and both homologous and non-homologous regions in the opposite hemisphere for externally oriented networks but not for DMN or SMN; conversely, TBI patients showed increased FC within regions of the DMN, especially precuneus and parahippocampal gyrus. Region of interest correlation analyses confirmed the presence of significantly higher inter-hemispheric FC in NC for the FPN (p < 0.01), and ECN (p < 0.05), but not for the DMN (p > 0.05) or SMN (p > 0.05). Further analysis revealed that performance on a neuropsychological test measuring organizational skills and visuo-spatial abilities administered to the TBI group, the Rey-Osterrieth Complex Figure Test, positively correlated with FC between the right FPN and homologous regions. Our findings suggest that distinct RSNs display specific patterns of aberrant FC following TBI; this represents a step forward in the search for biomarkers useful for early diagnosis and treatment of TBI-related cognitive impairment. PMID:25719433

  5. Significance of Input Correlations in Striatal Function

    PubMed Central

    Yim, Man Yi; Aertsen, Ad; Kumar, Arvind

    2011-01-01

    The striatum is the main input station of the basal ganglia and is strongly associated with motor and cognitive functions. Anatomical evidence suggests that individual striatal neurons are unlikely to share their inputs from the cortex. Using a biologically realistic large-scale network model of striatum and cortico-striatal projections, we provide a functional interpretation of the special anatomical structure of these projections. Specifically, we show that weak pairwise correlation within the pool of inputs to individual striatal neurons enhances the saliency of signal representation in the striatum. By contrast, correlations among the input pools of different striatal neurons render the signal representation less distinct from background activity. We suggest that for the network architecture of the striatum, there is a preferred cortico-striatal input configuration for optimal signal representation. It is further enhanced by the low-rate asynchronous background activity in striatum, supported by the balance between feedforward and feedback inhibitions in the striatal network. Thus, an appropriate combination of rates and correlations in the striatal input sets the stage for action selection presumably implemented in the basal ganglia. PMID:22125480

  6. Fractals and cosmological large-scale structure

    NASA Technical Reports Server (NTRS)

    Luo, Xiaochun; Schramm, David N.

    1992-01-01

    Observations of galaxy-galaxy and cluster-cluster correlations as well as other large-scale structure can be fit with a 'limited' fractal with dimension D of about 1.2. This is not a 'pure' fractal out to the horizon: the distribution shifts from power law to random behavior at some large scale. If the observed patterns and structures are formed through an aggregation growth process, the fractal dimension D can serve as an interesting constraint on the properties of the stochastic motion responsible for limiting the fractal structure. In particular, it is found that the observed fractal should have grown from two-dimensional sheetlike objects such as pancakes, domain walls, or string wakes. This result is generic and does not depend on the details of the growth process.

  7. Effective theory of squeezed correlation functions

    NASA Astrophysics Data System (ADS)

    Mirbabayi, Mehrdad; Simonović, Marko

    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 klong/kshort. 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 (klong/kshort)Δ with Δ < 1—where local non-Gaussianity corresponds to Δ = 0.

  8. On the analysis of large-scale genomic structures.

    PubMed

    Oiwa, Nestor Norio; Goldman, Carla

    2005-01-01

    We apply methods from statistical physics (histograms, correlation functions, fractal dimensions, and singularity spectra) to characterize large-scale structure of the distribution of nucleotides along genomic sequences. We discuss the role of the extension of noncoding segments ("junk DNA") for the genomic organization, and the connection between the coding segment distribution and the high-eukaryotic chromatin condensation. The following sequences taken from GenBank were analyzed: complete genome of Xanthomonas campestri, complete genome of yeast, chromosome V of Caenorhabditis elegans, and human chromosome XVII around gene BRCA1. The results are compared with the random and periodic sequences and those generated by simple and generalized fractal Cantor sets. PMID:15858230

  9. Microfluidic large-scale integration.

    PubMed

    Thorsen, Todd; Maerkl, Sebastian J; Quake, Stephen R

    2002-10-18

    We developed high-density microfluidic chips that contain plumbing networks with thousands of micromechanical valves and hundreds of individually addressable chambers. These fluidic devices are analogous to electronic integrated circuits fabricated using large-scale integration. A key component of these networks is the fluidic multiplexor, which is a combinatorial array of binary valve patterns that exponentially increases the processing power of a network by allowing complex fluid manipulations with a minimal number of inputs. We used these integrated microfluidic networks to construct the microfluidic analog of a comparator array and a microfluidic memory storage device whose behavior resembles random-access memory. PMID:12351675

  10. Large scale structure in universes dominated by cold dark matter

    NASA Technical Reports Server (NTRS)

    Bond, J. Richard

    1986-01-01

    The theory of Gaussian random density field peaks is applied to a numerical study of the large-scale structure developing from adiabatic fluctuations in models of biased galaxy formation in universes with Omega = 1, h = 0.5 dominated by cold dark matter (CDM). The angular anisotropy of the cross-correlation function demonstrates that the far-field regions of cluster-scale peaks are asymmetric, as recent observations indicate. These regions will generate pancakes or filaments upon collapse. One-dimensional singularities in the large-scale bulk flow should arise in these CDM models, appearing as pancakes in position space. They are too rare to explain the CfA bubble walls, but pancakes that are just turning around now are sufficiently abundant and would appear to be thin walls normal to the line of sight in redshift space. Large scale streaming velocities are significantly smaller than recent observations indicate. To explain the reported 700 km/s coherent motions, mass must be significantly more clustered than galaxies with a biasing factor of less than 0.4 and a nonlinear redshift at cluster scales greater than one for both massive neutrino and cold models.

  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. 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.

  13. 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

  14. Large scale topography of Io

    NASA Technical Reports Server (NTRS)

    Gaskell, R. W.; Synnott, S. P.

    1987-01-01

    To investigate the large scale topography of the Jovian satellite Io, both limb observations and stereographic techniques applied to landmarks are used. The raw data for this study consists of Voyager 1 images of Io, 800x800 arrays of picture elements each of which can take on 256 possible brightness values. In analyzing this data it was necessary to identify and locate landmarks and limb points on the raw images, remove the image distortions caused by the camera electronics and translate the corrected locations into positions relative to a reference geoid. Minimizing the uncertainty in the corrected locations is crucial to the success of this project. In the highest resolution frames, an error of a tenth of a pixel in image space location can lead to a 300 m error in true location. In the lowest resolution frames, the same error can lead to an uncertainty of several km.

  15. 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.

  16. Redshift distortions of galaxy correlation functions

    NASA Technical Reports Server (NTRS)

    Fry, J. N.; Gaztanaga, Enrique

    1994-01-01

    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 r(sub 0) and power index gamma of the two-point correlations, bar-xi(sub 0) = (r(sub 0)/r)(exp gamma), and as the hierarchical amplitudes of the three- and four-point functions, S(sub 3) = bar-xi(sub 3)/bar-xi(exp 2)(sub 2) and S(sub 4) = bar-xi(sub 4)/bar-xi(exp 3)(sub 2). We find a characteristic distortion for bar-xi(sub 2), 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 Omega(exp 4/7)/b approximately equal to 1. We estimate Omega(exp 4/7)/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-xi(sub 3) and bar-xi(sub 4) suffer similar redshift distortions but in such a way that, within the accuracy of our ananlysis, the normalized amplitudes S(sub 3) and S(sub 4) are insensitive to this effect. The hierarchical amplitudes S(sub 3) and S(sub 4) are constant as a function of scale between 1 and 12 Mpc and have similar values in all samples and catalogs, S(sub 3) approximately equal to 2 and S(sub 4) approximately equal to 6, despite the fact that bar-xi(sub 2), bar-xi(sub 3), and bar-xi(sub 4) differ from one sample to another by large factors (up to a factor of 4 in bar-xi(sub 2), 8 for bar-xi(sub 3), and 12 for bar-xi(sub 4)). The agreement between the independent estimations of S(sub 3) and S(sub 4) is remarkable given the different criteria in the selection of galaxies and also the difference in the

  17. 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…

  18. Large Scale Homing in Honeybees

    PubMed Central

    Pahl, Mario; Zhu, Hong; Tautz, Jürgen; Zhang, Shaowu

    2011-01-01

    Honeybee foragers frequently fly several kilometres to and from vital resources, and communicate those locations to their nest mates by a symbolic dance language. Research has shown that they achieve this feat by memorizing landmarks and the skyline panorama, using the sun and polarized skylight as compasses and by integrating their outbound flight paths. In order to investigate the capacity of the honeybees' homing abilities, we artificially displaced foragers to novel release spots at various distances up to 13 km in the four cardinal directions. Returning bees were individually registered by a radio frequency identification (RFID) system at the hive entrance. We found that homing rate, homing speed and the maximum homing distance depend on the release direction. Bees released in the east were more likely to find their way back home, and returned faster than bees released in any other direction, due to the familiarity of global landmarks seen from the hive. Our findings suggest that such large scale homing is facilitated by global landmarks acting as beacons, and possibly the entire skyline panorama. PMID:21602920

  19. 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.

  20. 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. PMID:26623658

  1. Strategies for Interactive Visualization of Large Scale Climate Simulations

    NASA Astrophysics Data System (ADS)

    Xie, J.; Chen, C.; Ma, K.; Parvis

    2011-12-01

    With the advances in computational methods and supercomputing technology, climate scientists are able to perform large-scale simulations at unprecedented resolutions. These simulations produce data that are time-varying, multivariate, and volumetric, and the data may contain thousands of time steps with each time step having billions of voxels and each voxel recording dozens of variables. Visualizing such time-varying 3D data to examine correlations between different variables thus becomes a daunting task. We have been developing strategies for interactive visualization and correlation analysis of multivariate data. The primary task is to find connection and correlation among data. Given the many complex interactions among the Earth's oceans, atmosphere, land, ice and biogeochemistry, and the sheer size of observational and climate model data sets, interactive exploration helps identify which processes matter most for a particular climate phenomenon. We may consider time-varying data as a set of samples (e.g., voxels or blocks), each of which is associated with a vector of representative or collective values over time. We refer to such a vector as a temporal curve. Correlation analysis thus operates on temporal curves of data samples. A temporal curve can be treated as a two-dimensional function where the two dimensions are time and data value. It can also be treated as a point in the high-dimensional space. In this case, to facilitate effective analysis, it is often necessary to transform temporal curve data from the original space to a space of lower dimensionality. Clustering and segmentation of temporal curve data in the original or transformed space provides us a way to categorize and visualize data of different patterns, which reveals connection or correlation of data among different variables or at different spatial locations. We have employed the power of GPU to enable interactive correlation visualization for studying the variability and correlations of a

  2. 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

  3. 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. PMID:26167799

  4. 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

  5. A multi-ingredient dietary supplement abolishes large-scale brain cell loss, improves sensory function, and prevents neuronal atrophy in aging mice.

    PubMed

    Lemon, J A; Aksenov, V; Samigullina, R; Aksenov, S; Rodgers, W H; Rollo, C D; Boreham, D R

    2016-06-01

    Transgenic growth hormone mice (TGM) are a recognized model of accelerated aging with characteristics including chronic oxidative stress, reduced longevity, mitochondrial dysfunction, insulin resistance, muscle wasting, and elevated inflammatory processes. Growth hormone/IGF-1 activate the Target of Rapamycin known to promote aging. TGM particularly express severe cognitive decline. We previously reported that a multi-ingredient dietary supplement (MDS) designed to offset five mechanisms associated with aging extended longevity, ameliorated cognitive deterioration and significantly reduced age-related physical deterioration in both normal mice and TGM. Here we report that TGM lose more than 50% of cells in midbrain regions, including the cerebellum and olfactory bulb. This is comparable to severe Alzheimer's disease and likely explains their striking age-related cognitive impairment. We also demonstrate that the MDS completely abrogates this severe brain cell loss, reverses cognitive decline and augments sensory and motor function in aged mice. Additionally, histological examination of retinal structure revealed markers consistent with higher numbers of photoreceptor cells in aging and supplemented mice. We know of no other treatment with such efficacy, highlighting the potential for prevention or amelioration of human neuropathologies that are similarly associated with oxidative stress, inflammation and cellular dysfunction. Environ. Mol. Mutagen. 57:382-404, 2016. © 2016 Wiley Periodicals, Inc. PMID:27199101

  6. 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. PMID:23606244

  7. 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.

  8. IMPROVING CORRELATION FUNCTION FITTING WITH RIDGE REGRESSION: APPLICATION TO CROSS-CORRELATION RECONSTRUCTION

    SciTech Connect

    Matthews, Daniel J.; Newman, Jeffrey A. E-mail: janewman@pitt.edu

    2012-02-01

    Cross-correlation techniques provide a promising avenue for calibrating photometric redshifts and determining redshift distributions using spectroscopy which is systematically incomplete (e.g., current deep spectroscopic surveys fail to obtain secure redshifts for 30%-50% or more of the galaxies targeted). In this paper, we improve on the redshift distribution reconstruction methods from our previous work by incorporating full covariance information into our correlation function fits. Correlation function measurements are strongly covariant between angular or spatial bins, and accounting for this in fitting can yield substantial reduction in errors. However, frequently the covariance matrices used in these calculations are determined from a relatively small set (dozens rather than hundreds) of subsamples or mock catalogs, resulting in noisy covariance matrices whose inversion is ill-conditioned and numerically unstable. We present here a method of conditioning the covariance matrix known as ridge regression which results in a more well behaved inversion than other techniques common in large-scale structure studies. We demonstrate that ridge regression significantly improves the determination of correlation function parameters. We then apply these improved techniques to the problem of reconstructing redshift distributions. By incorporating full covariance information, applying ridge regression, and changing the weighting of fields in obtaining average correlation functions, we obtain reductions in the mean redshift distribution reconstruction error of as much as {approx}40% compared to previous methods. We provide a description of POWERFIT, an IDL code for performing power-law fits to correlation functions with ridge regression conditioning that we are making publicly available.

  9. Contamination cannot explain the lack of large-scale power in the cosmic microwave background radiation

    SciTech Connect

    Bunn, Emory F.; Bourdon, Austin

    2008-12-15

    Several anomalies appear to be present in the large-angle cosmic microwave background (CMB) anisotropy maps of the Wilkinson Microwave Anisotropy Probe. One of these is a lack of large-scale power. Because the data otherwise match standard models extremely well, it is natural to consider perturbations of the standard model as possible explanations. We show that, as long as the source of the perturbation is statistically independent of the source of the primary CMB anisotropy, no such model can explain this large-scale power deficit. On the contrary, any such perturbation always reduces the probability of obtaining any given low value of large-scale power. We rigorously prove this result when the lack of large-scale power is quantified with a quadratic statistic, such as the quadrupole moment. When a statistic based on the integrated square of the correlation function is used instead, we present strong numerical evidence in support of the result. The result applies to models in which the geometry of spacetime is perturbed (e.g., an ellipsoidal universe) as well as explanations involving local contaminants, undiagnosed foregrounds, or systematic errors. Because the large-scale power deficit is arguably the most significant of the observed anomalies, explanations that worsen this discrepancy should be regarded with great skepticism, even if they help in explaining other anomalies such as multipole alignments.

  10. Large scale water lens for solar concentration.

    PubMed

    Mondol, A S; Vogel, B; Bastian, G

    2015-06-01

    Properties of large scale water lenses for solar concentration were investigated. These lenses were built from readily available materials, normal tap water and hyper-elastic linear low density polyethylene foil. Exposed to sunlight, the focal lengths and light intensities in the focal spot were measured and calculated. Their optical properties were modeled with a raytracing software based on the lens shape. We have achieved a good match of experimental and theoretical data by considering wavelength dependent concentration factor, absorption and focal length. The change in light concentration as a function of water volume was examined via the resulting load on the foil and the corresponding change of shape. The latter was extracted from images and modeled by a finite element simulation. PMID:26072893

  11. 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

  12. 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.

  13. Ultrahigh energy cosmic ray probes of large scale structure and magnetic fields

    NASA Astrophysics Data System (ADS)

    Sigl, Günter; Miniati, Francesco; Enßlin, Torsten A.

    2004-08-01

    We study signatures of a structured universe in the multi-pole moments, auto-correlation function, and cluster statistics of ultrahigh energy cosmic rays above 1019 eV. We compare scenarios where the sources are distributed homogeneously or according to the baryon density distribution obtained from a cosmological large scale structure simulation. The influence of extragalactic magnetic fields is studied by comparing the case of negligible fields with fields expected to be produced along large scale shocks with a maximal strength consistent with observations. We confirm that strongly magnetized observers would predict considerable anisotropy on large scales, which is already in conflict with current data. In the best fit scenario only the sources are strongly magnetized, although deflection can still be considerable, of order 20° up to 1020 eV, and a pronounced GZK cutoff is predicted. We then discuss signatures for future large scale full-sky detectors such as the Pierre Auger and EUSO projects. Auto-correlations are sensitive to the source density only if magnetic fields do not significantly affect propagation. In contrast, for a weakly magnetized observer, degree scale auto-correlations below a certain level indicate magnetized discrete sources. It may be difficult even for next generation experiments to distinguish between structured and unstructured source distributions.

  14. Identifying Large-Scale Brain Networks in Fragile X Syndrome

    PubMed Central

    Hall, Scott S.; Jiang, Heidi; Reiss, Allan L.; Greicius, Michael D.

    2014-01-01

    IMPORTANCE Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS. OBJECTIVE To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10–23 years) included 17 males and females with FXS and 16 males and females serving as controls. MAIN OUTCOMES AND MEASURES Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression. RESULTS Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS. CONCLUSIONS AND RELEVANCE Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that

  15. Correlation, functional analysis and optical pattern recognition

    SciTech Connect

    Dickey, F.M.; Lee, M.L.; Stalker, K.T.

    1994-03-01

    Correlation integrals have played a central role in optical pattern recognition. The success of correlation, however, has been limited. What is needed is a mathematical operation more complex than correlation. Suitably complex operations are the functionals defined on the Hilbert space of Lebesgue square integrable functions. Correlation is a linear functional of a parameter. In this paper, we develop a representation of functionals in terms of inner products or equivalently correlation functions. We also discuss the role of functionals in neutral networks. Having established a broad relation of correlation to pattern recognition, we discuss the computation of correlation functions using acousto-optics.

  16. 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.

  17. Boundary anomalies and correlation functions

    NASA Astrophysics Data System (ADS)

    Huang, Kuo-Wei

    2016-08-01

    It was shown recently that boundary terms of conformal anomalies recover the universal contribution to the entanglement entropy and also play an important role in the boundary monotonicity theorem of odd-dimensional quantum field theories. Motivated by these results, we investigate relationships between boundary anomalies and the stress tensor correlation functions in conformal field theories. In particular, we focus on how the conformal Ward identity and the renormalization group equation are modified by boundary central charges. Renormalized stress tensors induced by boundary Weyl invariants are also discussed, with examples in spherical and cylindrical geometries.

  18. Unfolding large-scale maps.

    PubMed

    Jenkins, Glyn

    2003-12-01

    This is an account of the development and use of genetic maps, from humble beginnings at the hands of Thomas Hunt Morgan, to the sophistication of genome sequencing. The review charters the emergence of molecular marker maps exploiting DNA polymorphism, the renaissance of cytogenetics through the use of fluorescence in situ hybridisation, and the discovery and isolation of genes by map-based cloning. The historical significance of sequencing of DNA prefaces a section describing the sequencing of genomes, the ascendancy of particular model organisms, and the utility and limitations of comparative genomic and functional genomic approaches to further our understanding of the control of biological processes. Emphasis is given throughout the treatise as to how the structure and biological behaviour of the DNA molecule underpin the technological development and biological applications of maps. PMID:14663511

  19. Large-Scale Reform Comes of Age

    ERIC Educational Resources Information Center

    Fullan, Michael

    2009-01-01

    This article reviews the history of large-scale education reform and makes the case that large-scale or whole system reform policies and strategies are becoming increasingly evident. The review briefly addresses the pre 1997 period concluding that while the pressure for reform was mounting that there were very few examples of deliberate or…

  20. Large-scale infrared scene projectors

    NASA Astrophysics Data System (ADS)

    Murray, Darin A.

    1999-07-01

    Large-scale infrared scene projectors, typically have unique opto-mechanical characteristics associated to their application. This paper outlines two large-scale zoom lens assemblies with different environmental and package constraints. Various challenges and their respective solutions are discussed and presented.

  1. 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

  2. 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

  3. 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

    Finger, Holger; Bönstrup, Marlene; Cheng, Bastian; Messé, Arnaud; Hilgetag, Claus; Thomalla, Götz; Gerloff, Christian; König, Peter

    2016-08-01

    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

  4. Correlation functions in stochastic inflation

    NASA Astrophysics Data System (ADS)

    Vennin, Vincent; Starobinsky, Alexei A.

    2015-09-01

    Combining the stochastic and formalisms, we derive non-perturbative analytical expressions for all correlation functions of scalar perturbations in single-field, slow-roll inflation. The standard, classical formulas are recovered as saddle-point limits of the full results. This yields a classicality criterion that shows that stochastic effects are small only if the potential is sub-Planckian and not too flat. The saddle-point approximation also provides an expansion scheme for calculating stochastic corrections to observable quantities perturbatively in this regime. In the opposite regime, we show that a strong suppression in the power spectrum is generically obtained, and we comment on the physical implications of this effect.

  5. 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…

  6. Gravity and large-scale nonlocal bias

    NASA Astrophysics Data System (ADS)

    Chan, Kwan Chuen; Scoccimarro, Román; Sheth, Ravi K.

    2012-04-01

    For Gaussian primordial fluctuations the relationship between galaxy and matter overdensities, bias, is most often assumed to be local at the time of observation in the large-scale limit. This hypothesis is however unstable under time evolution, we provide proofs under several (increasingly more realistic) sets of assumptions. In the simplest toy model galaxies are created locally and linearly biased at a single formation time, and subsequently move with the dark matter (no velocity bias) conserving their comoving number density (no merging). We show that, after this formation time, the bias becomes unavoidably nonlocal and nonlinear at large scales. We identify the nonlocal gravitationally induced fields in which the galaxy overdensity can be expanded, showing that they can be constructed out of the invariants of the deformation tensor (Galileons), the main signature of which is a quadrupole field in second-order perturbation theory. In addition, we show that this result persists if we include an arbitrary evolution of the comoving number density of tracers. We then include velocity bias, and show that new contributions appear; these are related to the breaking of Galilean invariance of the bias relation, a dipole field being the signature at second order. We test these predictions by studying the dependence of halo overdensities in cells of fixed dark matter density: measurements in simulations show that departures from the mean bias relation are strongly correlated with the nonlocal gravitationally induced fields identified by our formalism, suggesting that the halo distribution at the present time is indeed more closely related to the mass distribution at an earlier rather than present time. However, the nonlocality seen in the simulations is not fully captured by assuming local bias in Lagrangian space. The effects on nonlocal bias seen in the simulations are most important for the most biased halos, as expected from our predictions. Accounting for these

  7. 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.

  8. Large Scale Computer Simulation of Erthocyte Membranes

    NASA Astrophysics Data System (ADS)

    Harvey, Cameron; Revalee, Joel; Laradji, Mohamed

    2007-11-01

    The cell membrane is crucial to the life of the cell. Apart from partitioning the inner and outer environment of the cell, they also act as a support of complex and specialized molecular machinery, important for both the mechanical integrity of the cell, and its multitude of physiological functions. Due to its relative simplicity, the red blood cell has been a favorite experimental prototype for investigations of the structural and functional properties of the cell membrane. The erythrocyte membrane is a composite quasi two-dimensional structure composed essentially of a self-assembled fluid lipid bilayer and a polymerized protein meshwork, referred to as the cytoskeleton or membrane skeleton. In the case of the erythrocyte, the polymer meshwork is mainly composed of spectrin, anchored to the bilayer through specialized proteins. Using a coarse-grained model, recently developed by us, of self-assembled lipid membranes with implicit solvent and using soft-core potentials, we simulated large scale red-blood-cells bilayers with dimensions ˜ 10-1 μm^2, with explicit cytoskeleton. Our aim is to investigate the renormalization of the elastic properties of the bilayer due to the underlying spectrin meshwork.

  9. Nonlinear density fluctuation field theory for large scale structure

    NASA Astrophysics Data System (ADS)

    Zhang, Yang; Miao, Hai-Xing

    2009-05-01

    We develop an effective field theory of density fluctuations for a Newtonian self-gravitating N-body system in quasi-equilibrium and apply it to a homogeneous universe with small density fluctuations. Keeping the density fluctuations up to second order, we obtain the nonlinear field equation of 2-pt correlation ξ(r), which contains 3-pt correlation and formal ultra-violet divergences. By the Groth-Peebles hierarchical ansatz and mass renormalization, the equation becomes closed with two new terms beyond the Gaussian approximation, and their coefficients are taken as parameters. The analytic solution is obtained in terms of the hypergeometric functions, which is checked numerically. With one single set of two fixed parameters, the correlation ξ(r) and the corresponding power spectrum P(κ) simultaneously match the results from all the major surveys, such as APM, SDSS, 2dfGRS, and REFLEX. The model gives a unifying understanding of several seemingly unrelated features of large scale structure from a field-theoretical perspective. The theory is worth extending to study the evolution effects in an expanding universe.

  10. Effects of small scale energy injection on large scales in turbulent reaction flows

    NASA Astrophysics Data System (ADS)

    Xuan, Yuan

    2014-11-01

    Turbulence causes the generation of eddies of various length scales. In turbulent non-reacting flows, most of the kinetic energy is contained in large scale turbulent structures and dissipated at small scales. This energy cascade process from large scales to small scales provides the foundation of a lot of turbulence models, especially for Large Eddy Simulations. However, in turbulent reacting flows, chemical energy is converted locally to heat and therefore deploys energy at the smallest scales. As such, effects of small scale energy injection due to combustion on large scale turbulent motion may become important. These effects are investigated in the case of auto-ignition under homogeneous isotropic turbulence. Impact of small scale heat release is examined by comparing various turbulent statistics (e.g. energy spectrum, two-point correlation functions, and structure functions) in the reacting case to the non-reacting case. Emphasis is placed on the identification of the most relevant turbulent quantities in reflecting such small-large scale interactions.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

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

    PubMed

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

    2016-01-01

    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. PMID:26898227

  16. 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.

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

    PubMed Central

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

    2016-01-01

    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. PMID:26898227

  18. 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.

  19. 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…

  20. 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.

  1. International space station. Large scale integration approach

    NASA Astrophysics Data System (ADS)

    Cohen, Brad

    The International Space Station is the most complex large scale integration program in development today. The approach developed for specification, subsystem development, and verification lay a firm basis on which future programs of this nature can be based. International Space Station is composed of many critical items, hardware and software, built by numerous International Partners, NASA Institutions, and U.S. Contractors and is launched over a period of five years. Each launch creates a unique configuration that must be safe, survivable, operable, and support ongoing assembly (assemblable) to arrive at the assembly complete configuration in 2003. The approaches to integrating each of the modules into a viable spacecraft and continue the assembly is a challenge in itself. Added to this challenge are the severe schedule constraints and lack of an "Iron Bird", which prevents assembly and checkout of each on-orbit configuration prior to launch. This paper will focus on the following areas: 1) Specification development process explaining how the requirements and specifications were derived using a modular concept driven by launch vehicle capability. Each module is composed of components of subsystems versus completed subsystems. 2) Approach to stage (each stage consists of the launched module added to the current on-orbit spacecraft) specifications. Specifically, how each launched module and stage ensures support of the current and future elements of the assembly. 3) Verification approach, due to the schedule constraints, is primarily analysis supported by testing. Specifically, how are the interfaces ensured to mate and function on-orbit when they cannot be mated before launch. 4) Lessons learned. Where can we improve this complex system design and integration task?

  2. Large Scale Commodity Clusters for Lattice QCD

    SciTech Connect

    A. Pochinsky; W. Akers; R. Brower; J. Chen; P. Dreher; R. Edwards; S. Gottlieb; D. Holmgren; P. Mackenzie; J. Negele; D. Richards; J. Simone; W. Watson

    2002-06-01

    We describe the construction of large scale clusters for lattice QCD computing being developed under the umbrella of the U.S. DoE SciDAC initiative. We discuss the study of floating point and network performance that drove the design of the cluster, and present our plans for future multi-Terascale facilities.

  3. 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.

  4. A Large Scale Computer Terminal Output Controller.

    ERIC Educational Resources Information Center

    Tucker, Paul Thomas

    This paper describes the design and implementation of a large scale computer terminal output controller which supervises the transfer of information from a Control Data 6400 Computer to a PLATO IV data network. It discusses the cost considerations leading to the selection of educational television channels rather than telephone lines for…

  5. Large-scale CFB combustion demonstration project

    SciTech Connect

    Nielsen, P.T.; Hebb, J.L.; Aquino, R.

    1998-07-01

    The Jacksonville Electric Authority's large-scale CFB demonstration project is described. Given the early stage of project development, the paper focuses on the project organizational structure, its role within the Department of Energy's Clean Coal Technology Demonstration Program, and the projected environmental performance. A description of the CFB combustion process in included.

  6. Large-scale CFB combustion demonstration project

    SciTech Connect

    Nielsen, P.T.; Hebb, J.L.; Aquino, R.

    1998-04-01

    The Jacksonville Electric Authority`s large-scale CFB demonstration project is described. Given the early stage of project development, the paper focuses on the project organizational structure, its role within the Department of Energy`s Clean Coal Technology Demonstration Program, and the projected environmental performance. A description of the CFB combustion process is included.

  7. 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…

  8. ARPACK: Solving large scale eigenvalue problems

    NASA Astrophysics Data System (ADS)

    Lehoucq, Rich; Maschhoff, Kristi; Sorensen, Danny; Yang, Chao

    2013-11-01

    ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems. The package is designed to compute a few eigenvalues and corresponding eigenvectors of a general n by n matrix A. It is most appropriate for large sparse or structured matrices A where structured means that a matrix-vector product w

  9. Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

    PubMed

    Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

    2015-12-01

    The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling. PMID:25563228

  10. The mean density and two-point correlation function for the CfA redshift survey slices

    NASA Technical Reports Server (NTRS)

    De Lapparent, Valerie; Geller, Margaret J.; Huchra, John P.

    1988-01-01

    The effect of large-scale inhomogeneities on the determination of the mean number density and the two-point spatial correlation function were investigated for two complete slices of the extension of the Center for Astrophysics (CfA) redshift survey (de Lapparent et al., 1986). It was found that the mean galaxy number density for the two strips is uncertain by 25 percent, more so than previously estimated. The large uncertainty in the mean density introduces substantial uncertainty in the determination of the two-point correlation function, particularly at large scale; thus, for the 12-deg slice of the CfA redshift survey, the amplitude of the correlation function at intermediate scales is uncertain by a factor of 2. The large uncertainties in the correlation functions might reflect the lack of a fair sample.

  11. 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.

  12. 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.

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

    DOE PAGESBeta

    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

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

    NASA Astrophysics Data System (ADS)

    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/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.

  15. RECONSTRUCTING THE SHAPE OF THE CORRELATION FUNCTION

    SciTech Connect

    Huffenberger, K. M.; Galeazzi, M.; Ursino, E.

    2013-06-01

    We develop an estimator for the correlation function which, in the ensemble average, returns the shape of the correlation function, even for signals that have significant correlations on the scale of the survey region. Our estimator is general and works in any number of dimensions. We develop versions of the estimator for both diffuse and discrete signals. As an application, we apply them to Monte Carlo simulations of X-ray background measurements. These include a realistic, spatially inhomogeneous population of spurious detector events. We discuss applying the estimator to the averaging of correlation functions evaluated on several small fields, and to other cosmological applications.

  16. 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.

  17. Large scale processes in the solar nebula.

    NASA Astrophysics Data System (ADS)

    Boss, A. P.

    Most proposed chondrule formation mechanisms involve processes occurring inside the solar nebula, so the large scale (roughly 1 to 10 AU) structure of the nebula is of general interest for any chrondrule-forming mechanism. Chondrules and Ca, Al-rich inclusions (CAIs) might also have been formed as a direct result of the large scale structure of the nebula, such as passage of material through high temperature regions. While recent nebula models do predict the existence of relatively hot regions, the maximum temperatures in the inner planet region may not be high enough to account for chondrule or CAI thermal processing, unless the disk mass is considerably greater than the minimum mass necessary to restore the planets to solar composition. Furthermore, it does not seem to be possible to achieve both rapid heating and rapid cooling of grain assemblages in such a large scale furnace. However, if the accretion flow onto the nebula surface is clumpy, as suggested by observations of variability in young stars, then clump-disk impacts might be energetic enough to launch shock waves which could propagate through the nebula to the midplane, thermally processing any grain aggregates they encounter, and leaving behind a trail of chondrules.

  18. Large-scale extraction of proteins.

    PubMed

    Cunha, Teresa; Aires-Barros, Raquel

    2002-01-01

    The production of foreign proteins using selected host with the necessary posttranslational modifications is one of the key successes in modern biotechnology. This methodology allows the industrial production of proteins that otherwise are produced in small quantities. However, the separation and purification of these proteins from the fermentation media constitutes a major bottleneck for the widespread commercialization of recombinant proteins. The major production costs (50-90%) for typical biological product resides in the purification strategy. There is a need for efficient, effective, and economic large-scale bioseparation techniques, to achieve high purity and high recovery, while maintaining the biological activity of the molecule. Aqueous two-phase systems (ATPS) allow process integration as simultaneously separation and concentration of the target protein is achieved, with posterior removal and recycle of the polymer. The ease of scale-up combined with the high partition coefficients obtained allow its potential application in large-scale downstream processing of proteins produced by fermentation. The equipment and the methodology for aqueous two-phase extraction of proteins on a large scale using mixer-settlerand column contractors are described. The operation of the columns, either stagewise or differential, are summarized. A brief description of the methods used to account for mass transfer coefficients, hydrodynamics parameters of hold-up, drop size, and velocity, back mixing in the phases, and flooding performance, required for column design, is also provided. PMID:11876297

  19. Large-scale behavior and statistical equilibria in rotating flows

    NASA Astrophysics Data System (ADS)

    Mininni, P. D.; Dmitruk, P.; Matthaeus, W. H.; Pouquet, A.

    2011-01-01

    We examine long-time properties of the ideal dynamics of three-dimensional flows, in the presence or not of an imposed solid-body rotation and with or without helicity (velocity-vorticity correlation). In all cases, the results agree with the isotropic predictions stemming from statistical mechanics. No accumulation of excitation occurs in the large scales, although, in the dissipative rotating case, anisotropy and accumulation, in the form of an inverse cascade of energy, are known to occur. We attribute this latter discrepancy to the linearity of the term responsible for the emergence of inertial waves. At intermediate times, inertial energy spectra emerge that differ somewhat from classical wave-turbulence expectations and with a trace of large-scale excitation that goes away for long times. These results are discussed in the context of partial two dimensionalization of the flow undergoing strong rotation as advocated by several authors.

  20. 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.

  1. Quantum Noise in Large-Scale Coherent Nonlinear Photonic Circuits

    NASA Astrophysics Data System (ADS)

    Santori, Charles; Pelc, Jason S.; Beausoleil, Raymond G.; Tezak, Nikolas; Hamerly, Ryan; Mabuchi, Hideo

    2014-06-01

    A semiclassical simulation approach is presented for studying quantum noise in large-scale photonic circuits incorporating an ideal Kerr nonlinearity. A circuit solver is used to generate matrices defining a set of stochastic differential equations, in which the resonator field variables represent random samplings of the Wigner quasiprobability distributions. Although the semiclassical approach involves making a large-photon-number approximation, tests on one- and two-resonator circuits indicate satisfactory agreement between the semiclassical and full-quantum simulation results in the parameter regime of interest. The semiclassical model is used to simulate random errors in a large-scale circuit that contains 88 resonators and hundreds of components in total and functions as a four-bit ripple counter. The error rate as a function of on-state photon number is examined, and it is observed that the quantum fluctuation amplitudes do not increase as signals propagate through the circuit, an important property for scalability.

  2. Correlation function studies for snow and ice

    NASA Technical Reports Server (NTRS)

    Vallese, F.; Kong, J. A.

    1981-01-01

    The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

  3. 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.

  4. Large-scale climatic control on European precipitation

    NASA Astrophysics Data System (ADS)

    Lavers, David; Prudhomme, Christel; Hannah, David

    2010-05-01

    Precipitation variability has a significant impact on society. Sectors such as agriculture and water resources management are reliant on predictable and reliable precipitation supply with extreme variability having potentially adverse socio-economic impacts. Therefore, understanding the climate drivers of precipitation is of human relevance. This research examines the strength, location and seasonality of links between precipitation and large-scale Mean Sea Level Pressure (MSLP) fields across Europe. In particular, we aim to evaluate whether European precipitation is correlated with the same atmospheric circulation patterns or if there is a strong spatial and/or seasonal variation in the strength and location of centres of correlations. The work exploits time series of gridded ERA-40 MSLP on a 2.5˚×2.5˚ grid (0˚N-90˚N and 90˚W-90˚E) and gridded European precipitation from the Ensemble project on a 0.5°×0.5° grid (36.25˚N-74.25˚N and 10.25˚W-24.75˚E). Monthly Spearman rank correlation analysis was performed between MSLP and precipitation. During winter, a significant MSLP-precipitation correlation dipole pattern exists across Europe. Strong negative (positive) correlation located near the Icelandic Low and positive (negative) correlation near the Azores High pressure centres are found in northern (southern) Europe. These correlation dipoles resemble the structure of the North Atlantic Oscillation (NAO). The reversal in the correlation dipole patterns occurs at the latitude of central France, with regions to the north (British Isles, northern France, Scandinavia) having a positive relationship with the NAO, and regions to the south (Italy, Portugal, southern France, Spain) exhibiting a negative relationship with the NAO. In the lee of mountain ranges of eastern Britain and central Sweden, correlation with North Atlantic MSLP is reduced, reflecting a reduced influence of westerly flow on precipitation generation as the mountains act as a barrier to moist

  5. Bootstrapping correlation functions in {N}=4 SYM

    NASA Astrophysics Data System (ADS)

    Chicherin, Dmitry; Doobary, Reza; Eden, Burkhard; Heslop, Paul; Korchemsky, Gregory P.; Sokatchev, Emery

    2016-03-01

    We describe a new approach to computing the chiral part of correlation functions of stress-tensor supermultiplets in {N}=4 SYM that relies on symmetries, analytic properties and the structure of the OPE only. We demonstrate that the correlation functions are given by a linear combination of chiral {N}=4 superconformal invariants accompanied by coefficient functions depending on the space-time coordinates only. We present the explicit construction of these invariants and show that the six-point correlation function is fixed in the Born approximation up to four constant coefficients by its symmetries. In addition, the known asymptotic structure of the correlation function in the light-like limit fixes unambiguously these coefficients up to an overall normalization. We demonstrate that the same approach can be applied to obtain a representation for the six-point NMHV amplitude that is free from any auxiliary gauge fixing parameters, does not involve spurious poles and manifests half of the dual superconformal symmetry.

  6. Correlation functions for extended mass galaxy clusters

    NASA Astrophysics Data System (ADS)

    Iqbal, Naseer; Ahmad, Naveel; Hamid, Mubashir; Masood, Tabasum

    2012-07-01

    The phenomenon of clustering of galaxies on the basis of correlation functions in an expanding Universe is studied by using equation of state, taking gravitational interaction between galaxies of extended nature into consideration. The partial differential equation for the extended mass structures of a two-point correlation function developed earlier by Iqbal, Ahmad & Khan is studied on the basis of assigned boundary conditions. The solution for the correlation function for extended structures satisfies the basic boundary conditions, which seem to be sufficient for understanding the phenomena, and provides a new insight into the gravitational clustering problem for extended mass structures.

  7. Large scale modelling of bankfull flow: An example for Europe

    NASA Astrophysics Data System (ADS)

    Schneider, Christof; Flörke, Martina; Eisner, Stephanie; Voss, Frank

    2011-10-01

    SummaryBankfull flow is a relevant parameter in the field of large scale modelling especially for the analysis of environmental flows and flood related hydrological processes. In our case, bankfull flow data were required within the SCENES project in order to analyse ecological important inundation events at selected grid cells of a European raster. In practise, the determination of bankfull flow is a complex task even on local scale. Subsequent to a literature survey of bankfull flow studies, this paper describes a method which can be applied to estimate bankfull flow on a global or continental grid cell raster. The method is based on the partial duration series approach taking into account a 40-years time series of daily discharge data modelled by the global water model WaterGAP. An increasing threshold censoring procedure, a declustering scheme and the generalised Pareto distribution are applied. Modelled bankfull flow values are then validated by different efficiency criteria against bankfull flows observed at gauging stations in Europe. Thereby, the impact of (i) the applied distribution function, (ii) the threshold setting in the partial duration series, (iii) the climate input data and (iv) applying the annual maxima series are evaluated and compared to the proposed approach. The results show that bankfull flow can be reasonably estimated with a high model efficiency ( E1 = 0.71) and weighted correlation ( ωr2 = 0.90) as well as a systematic overestimation of 22.8%. Finally it turned out that in our study focusing on hydrological extremes, the appliance of the daily climate input data is a basic requirement. While the choice of the distribution function had no significant impact on the final results, the threshold setting in the partial duration series was crucial.

  8. Constructing perturbation theory kernels for large-scale structure in generalized cosmologies

    NASA Astrophysics Data System (ADS)

    Taruya, Atsushi

    2016-07-01

    We present a simple numerical scheme for perturbation theory (PT) calculations of large-scale structure. Solving the evolution equations for perturbations numerically, we construct the PT kernels as building blocks of statistical calculations, from which the power spectrum and/or correlation function can be systematically computed. The scheme is especially applicable to the generalized structure formation including modified gravity, in which the analytic construction of PT kernels is intractable. As an illustration, we show several examples for power spectrum calculations in f (R ) gravity and Λ CDM models.

  9. FROM FINANCE TO COSMOLOGY: THE COPULA OF LARGE-SCALE STRUCTURE

    SciTech Connect

    Scherrer, Robert J.; Berlind, Andreas A.; Mao, Qingqing; McBride, Cameron K.

    2010-01-01

    Any multivariate distribution can be uniquely decomposed into marginal (one-point) distributions, and a function called the copula, which contains all of the information on correlations between the distributions. The copula provides an important new methodology for analyzing the density field in large-scale structure. We derive the empirical two-point copula for the evolved dark matter density field. We find that this empirical copula is well approximated by a Gaussian copula. We consider the possibility that the full n-point copula is also Gaussian and describe some of the consequences of this hypothesis. Future directions for investigation are discussed.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Nonthermal Components in the Large Scale Structure

    NASA Astrophysics Data System (ADS)

    Miniati, Francesco

    2004-12-01

    I address the issue of nonthermal processes in the large scale structure of the universe. After reviewing the properties of cosmic shocks and their role as particle accelerators, I discuss the main observational results, from radio to γ-ray and describe the processes that are thought be responsible for the observed nonthermal emissions. Finally, I emphasize the important role of γ-ray astronomy for the progress in the field. Non detections at these photon energies have already allowed us important conclusions. Future observations will tell us more about the physics of the intracluster medium, shocks dissipation and CR acceleration.

  15. 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.

  16. LARGE-SCALE STRUCTURE OF THE UNIVERSE AS A COSMIC STANDARD RULER

    SciTech Connect

    Park, Changbom; Kim, Young-Rae

    2010-06-01

    We propose to use the large-scale structure (LSS) of the universe as a cosmic standard ruler. This is possible because the pattern of large-scale distribution of matter is scale-dependent and does not change in comoving space during the linear-regime evolution of structure. By examining the pattern of LSS in several redshift intervals it is possible to reconstruct the expansion history of the universe, and thus to measure the cosmological parameters governing the expansion of the universe. The features of the large-scale matter distribution that can be used as standard rulers include the topology of LSS and the overall shapes of the power spectrum and correlation function. The genus, being an intrinsic topology measure, is insensitive to systematic effects such as the nonlinear gravitational evolution, galaxy biasing, and redshift-space distortion, and thus is an ideal cosmic ruler when galaxies in redshift space are used to trace the initial matter distribution. The genus remains unchanged as far as the rank order of density is conserved, which is true for linear and weakly nonlinear gravitational evolution, monotonic galaxy biasing, and mild redshift-space distortions. The expansion history of the universe can be constrained by comparing the theoretically predicted genus corresponding to an adopted set of cosmological parameters with the observed genus measured by using the redshift-comoving distance relation of the same cosmological model.

  17. Large-scale flow generation by inhomogeneous helicity

    NASA Astrophysics Data System (ADS)

    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.

  18. How Large Scales Flows May Influence Solar Activity

    NASA Technical Reports Server (NTRS)

    Hathaway, D. H.

    2004-01-01

    Large scale flows within the solar convection zone are the primary drivers of the Sun's magnetic activity cycle and play important roles in shaping the Sun's magnetic field. Differential rotation amplifies the magnetic field through its shearing action and converts poloidal field into toroidal field. Poleward meridional flow near the surface carries magnetic flux that reverses the magnetic poles at about the time of solar maximum. The deeper, equatorward meridional flow can carry magnetic flux back toward the lower latitudes where it erupts through the surface to form tilted active regions that convert toroidal fields into oppositely directed poloidal fields. These axisymmetric flows are themselves driven by large scale convective motions. The effects of the Sun's rotation on convection produce velocity correlations that can maintain both the differential rotation and the meridional circulation. These convective motions can also influence solar activity directly by shaping the magnetic field pattern. While considerable theoretical advances have been made toward understanding these large scale flows, outstanding problems in matching theory to observations still remain.

  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. The Large Scale Synthesis of Aligned Plate Nanostructures.

    PubMed

    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

  1. 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

  2. Large-scale quantum effects in biological systems

    NASA Astrophysics Data System (ADS)

    Mesquita, Marcus V.; Vasconcellos, Áurea R.; Luzzi, Roberto; Mascarenhas, Sergio

    Particular aspects of large-scale quantum effects in biological systems, such as biopolymers and also microtubules in the cytoskeleton of neurons which can have relevance in brain functioning, are discussed. The microscopic (quantum mechanical) and macroscopic (quantum statistical mechanical) aspects, and the emergence of complex behavior, are described. This phenomena consists of the large-scale coherent process of Fröhlich-Bose-Einstein condensation in open and sufficiently far-from-equilibrium biopolymers. Associated with this phenomenon is the presence of Schrödinger-Davydov solitons, which propagate, undistorted and undamped, when embedded in the Fröhlich-Bose-Einstein condensate, thus allowing for the transmission of signals at long distances, involving a question relevant to bioenergetics.

  3. Large-scale objective phenotyping of 3D facial morphology

    PubMed Central

    Hammond, Peter; Suttie, Michael

    2012-01-01

    Abnormal phenotypes have played significant roles in the discovery of gene function, but organized collection of phenotype data has been overshadowed by developments in sequencing technology. In order to study phenotypes systematically, large-scale projects with standardized objective assessment across populations are considered necessary. The report of the 2006 Human Variome Project meeting recommended documentation of phenotypes through electronic means by collaborative groups of computational scientists and clinicians using standard, structured descriptions of disease-specific phenotypes. In this report, we describe progress over the past decade in 3D digital imaging and shape analysis of the face, and future prospects for large-scale facial phenotyping. Illustrative examples are given throughout using a collection of 1107 3D face images of healthy controls and individuals with a range of genetic conditions involving facial dysmorphism. PMID:22434506

  4. 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.

  5. Large-scale Globally Propagating Coronal Waves

    NASA Astrophysics Data System (ADS)

    Warmuth, Alexander

    2015-09-01

    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. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

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

    PubMed

    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. 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. 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.

  15. Large-scale simulations of reionization

    SciTech Connect

    Kohler, Katharina; Gnedin, Nickolay Y.; Hamilton, Andrew J.S.; /JILA, Boulder

    2005-11-01

    We use cosmological simulations to explore the large-scale effects of reionization. Since reionization is a process that involves a large dynamic range--from galaxies to rare bright quasars--we need to be able to cover a significant volume of the universe in our simulation without losing the important small scale effects from galaxies. Here we have taken an approach that uses clumping factors derived from small scale simulations to approximate the radiative transfer on the sub-cell scales. Using this technique, we can cover a simulation size up to 1280h{sup -1} Mpc with 10h{sup -1} Mpc cells. This allows us to construct synthetic spectra of quasars similar to observed spectra of SDSS quasars at high redshifts and compare them to the observational data. These spectra can then be analyzed for HII region sizes, the presence of the Gunn-Peterson trough, and the Lyman-{alpha} forest.

  16. Large-scale databases of proper names.

    PubMed

    Conley, P; Burgess, C; Hage, D

    1999-05-01

    Few tools for research in proper names have been available--specifically, there is no large-scale corpus of proper names. Two corpora of proper names were constructed, one based on U.S. phone book listings, the other derived from a database of Usenet text. Name frequencies from both corpora were compared with human subjects' reaction times (RTs) to the proper names in a naming task. Regression analysis showed that the Usenet frequencies contributed to predictions of human RT, whereas phone book frequencies did not. In addition, semantic neighborhood density measures derived from the HAL corpus were compared with the subjects' RTs and found to be a better predictor of RT than was frequency in either corpus. These new corpora are freely available on line for download. Potentials for these corpora range from using the names as stimuli in experiments to using the corpus data in software applications. PMID:10495803

  17. Estimation of large-scale dimension densities.

    PubMed

    Raab, C; Kurths, J

    2001-07-01

    We propose a technique to calculate large-scale dimension densities in both higher-dimensional spatio-temporal systems and low-dimensional systems from only a few data points, where known methods usually have an unsatisfactory scaling behavior. This is mainly due to boundary and finite-size effects. With our rather simple method, we normalize boundary effects and get a significant correction of the dimension estimate. This straightforward approach is based on rather general assumptions. So even weak coherent structures obtained from small spatial couplings can be detected with this method, which is impossible by using the Lyapunov-dimension density. We demonstrate the efficiency of our technique for coupled logistic maps, coupled tent maps, the Lorenz attractor, and the Roessler attractor. PMID:11461376

  18. The challenge of large-scale structure

    NASA Astrophysics Data System (ADS)

    Gregory, S. A.

    1996-03-01

    The tasks that I have assumed for myself in this presentation include three separate parts. The first, appropriate to the particular setting of this meeting, is to review the basic work of the founding of this field; the appropriateness comes from the fact that W. G. Tifft made immense contributions that are not often realized by the astronomical community. The second task is to outline the general tone of the observational evidence for large scale structures. (Here, in particular, I cannot claim to be complete. I beg forgiveness from any workers who are left out by my oversight for lack of space and time.) The third task is to point out some of the major aspects of the field that may represent the clues by which some brilliant sleuth will ultimately figure out how galaxies formed.

  19. 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.

  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. Batteries for Large Scale Energy Storage

    SciTech Connect

    Soloveichik, Grigorii L.

    2011-07-15

    In recent years, with the deployment of renewable energy sources, advances in electrified transportation, and development in smart grids, the markets for large-scale stationary energy storage have grown rapidly. Electrochemical energy storage methods are strong candidate solutions due to their high energy density, flexibility, and scalability. This review provides an overview of mature and emerging technologies for secondary and redox flow batteries. New developments in the chemistry of secondary and flow batteries as well as regenerative fuel cells are also considered. Advantages and disadvantages of current and prospective electrochemical energy storage options are discussed. The most promising technologies in the short term are high-temperature sodium batteries with β”-alumina electrolyte, lithium-ion batteries, and flow batteries. Regenerative fuel cells and lithium metal batteries with high energy density require further research to become practical.

  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. Large-Scale Astrophysical Visualization on Smartphones

    NASA Astrophysics Data System (ADS)

    Becciani, U.; Massimino, P.; Costa, A.; Gheller, C.; Grillo, A.; Krokos, M.; Petta, C.

    2011-07-01

    Nowadays digital sky surveys and long-duration, high-resolution numerical simulations using high performance computing and grid systems produce multidimensional astrophysical datasets in the order of several Petabytes. Sharing visualizations of such datasets within communities and collaborating research groups is of paramount importance for disseminating results and advancing astrophysical research. Moreover educational and public outreach programs can benefit greatly from novel ways of presenting these datasets by promoting understanding of complex astrophysical processes, e.g., formation of stars and galaxies. We have previously developed VisIVO Server, a grid-enabled platform for high-performance large-scale astrophysical visualization. This article reviews the latest developments on VisIVO Web, a custom designed web portal wrapped around VisIVO Server, then introduces VisIVO Smartphone, a gateway connecting VisIVO Web and data repositories for mobile astrophysical visualization. We discuss current work and summarize future developments.

  4. The XMM Large Scale Structure Survey

    NASA Astrophysics Data System (ADS)

    Pierre, Marguerite

    2005-10-01

    We propose to complete, by an additional 5 deg2, the XMM-LSS Survey region overlying the Spitzer/SWIRE field. This field already has CFHTLS and Integral coverage, and will encompass about 10 deg2. The resulting multi-wavelength medium-depth survey, which complements XMM and Chandra deep surveys, will provide a unique view of large-scale structure over a wide range of redshift, and will show active galaxies in the full range of environments. The complete coverage by optical and IR surveys provides high-quality photometric redshifts, so that cosmological results can quickly be extracted. In the spirit of a Legacy survey, we will make the raw X-ray data immediately public. Multi-band catalogues and images will also be made available on short time scales.

  5. Estimation of large-scale dimension densities

    NASA Astrophysics Data System (ADS)

    Raab, Corinna; Kurths, Jürgen

    2001-07-01

    We propose a technique to calculate large-scale dimension densities in both higher-dimensional spatio-temporal systems and low-dimensional systems from only a few data points, where known methods usually have an unsatisfactory scaling behavior. This is mainly due to boundary and finite-size effects. With our rather simple method, we normalize boundary effects and get a significant correction of the dimension estimate. This straightforward approach is based on rather general assumptions. So even weak coherent structures obtained from small spatial couplings can be detected with this method, which is impossible by using the Lyapunov-dimension density. We demonstrate the efficiency of our technique for coupled logistic maps, coupled tent maps, the Lorenz attractor, and the Roessler attractor.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Introducing Large-Scale Innovation in Schools

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

  12. 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.

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

    PubMed

    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

  14. 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.

  15. 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.

  16. Long-time limit of correlation functions

    NASA Astrophysics Data System (ADS)

    Franosch, Thomas

    2014-08-01

    Auto-correlation functions in an equilibrium stochastic process are well-characterized by Bochner's theorem as Fourier transforms of a finite symmetric Borel measure. The existence of a long-time limit of these correlation functions depends on the spectral properties of the measure. Here we provide conditions applicable to a wide class of dynamical theories guaranteeing the existence of the long-time limit. We discuss the implications in the context of the mode-coupling theory of the glass transition where a non-trivial long-time limit signals an idealized glass state.

  17. Large-Scale Statistics for Cu Electromigration

    NASA Astrophysics Data System (ADS)

    Hauschildt, M.; Gall, M.; Hernandez, R.

    2009-06-01

    Even after the successful introduction of Cu-based metallization, the electromigration failure risk has remained one of the important reliability concerns for advanced process technologies. The observation of strong bimodality for the electron up-flow direction in dual-inlaid Cu interconnects has added complexity, but is now widely accepted. The failure voids can occur both within the via ("early" mode) or within the trench ("late" mode). More recently, bimodality has been reported also in down-flow electromigration, leading to very short lifetimes due to small, slit-shaped voids under vias. For a more thorough investigation of these early failure phenomena, specific test structures were designed based on the Wheatstone Bridge technique. The use of these structures enabled an increase of the tested sample size close to 675000, allowing a direct analysis of electromigration failure mechanisms at the single-digit ppm regime. Results indicate that down-flow electromigration exhibits bimodality at very small percentage levels, not readily identifiable with standard testing methods. The activation energy for the down-flow early failure mechanism was determined to be 0.83±0.02 eV. Within the small error bounds of this large-scale statistical experiment, this value is deemed to be significantly lower than the usually reported activation energy of 0.90 eV for electromigration-induced diffusion along Cu/SiCN interfaces. Due to the advantages of the Wheatstone Bridge technique, we were also able to expand the experimental temperature range down to 150° C, coming quite close to typical operating conditions up to 125° C. As a result of the lowered activation energy, we conclude that the down-flow early failure mode may control the chip lifetime at operating conditions. The slit-like character of the early failure void morphology also raises concerns about the validity of the Blech-effect for this mechanism. A very small amount of Cu depletion may cause failure even before a

  18. Locality of correlation in density functional theory

    NASA Astrophysics Data System (ADS)

    Burke, Kieron; Cancio, Antonio; Gould, Tim; Pittalis, Stefano

    2016-08-01

    The Hohenberg-Kohn density functional was long ago shown to reduce to the Thomas-Fermi (TF) approximation in the non-relativistic semiclassical (or large-Z) limit for all matter, i.e., the kinetic energy becomes local. Exchange also becomes local in this limit. Numerical data on the correlation energy of atoms support the conjecture that this is also true for correlation, but much less relevant to atoms. We illustrate how expansions around a large particle number are equivalent to local density approximations and their strong relevance to density functional approximations. Analyzing highly accurate atomic correlation energies, we show that EC → -AC ZlnZ + BCZ as Z → ∞, where Z is the atomic number, AC is known, and we estimate BC to be about 37 mhartree. The local density approximation yields AC exactly, but a very incorrect value for BC, showing that the local approximation is less relevant for the correlation alone. This limit is a benchmark for the non-empirical construction of density functional approximations. We conjecture that, beyond atoms, the leading correction to the local density approximation in the large-Z limit generally takes this form, but with BC a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed.

  19. Locality of correlation in density functional theory.

    PubMed

    Burke, Kieron; Cancio, Antonio; Gould, Tim; Pittalis, Stefano

    2016-08-01

    The Hohenberg-Kohn density functional was long ago shown to reduce to the Thomas-Fermi (TF) approximation in the non-relativistic semiclassical (or large-Z) limit for all matter, i.e., the kinetic energy becomes local. Exchange also becomes local in this limit. Numerical data on the correlation energy of atoms support the conjecture that this is also true for correlation, but much less relevant to atoms. We illustrate how expansions around a large particle number are equivalent to local density approximations and their strong relevance to density functional approximations. Analyzing highly accurate atomic correlation energies, we show that EC → -AC ZlnZ + BCZ as Z → ∞, where Z is the atomic number, AC is known, and we estimate BC to be about 37 mhartree. The local density approximation yields AC exactly, but a very incorrect value for BC, showing that the local approximation is less relevant for the correlation alone. This limit is a benchmark for the non-empirical construction of density functional approximations. We conjecture that, beyond atoms, the leading correction to the local density approximation in the large-Z limit generally takes this form, but with BC a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed. PMID:27497544

  20. Why large-scale seasonal streamflow forecasts are feasible

    NASA Astrophysics Data System (ADS)

    Bierkens, M. F.; Candogan Yossef, N.; Van Beek, L. P.

    2011-12-01

    Seasonal forecasts of precipitation and temperature, using either statistical or dynamic prediction, have been around for almost 2 decades. The skill of these forecasts differ both in space and time, with highest skill in areas heavily influenced by SST anomalies such as El Nino or areas where land surface properties have a major impact on e.g. Monsoon strength, such as the vegetation cover of the Sahel region or the snow cover of the Tibetan plateau. However, the skill of seasonal forecasts is limited in most regions, with anomaly correlation coefficients varying between 0.2 and 0.5 for 1-3 month precipitation totals. This raises the question whether seasonal hydrological forecasting is feasible. Here, we make the case that it is. Using the example of statistical forecasts of NAO-strength and related precipitation anomalies over Europe, we show that the skill of large-scale streamflow forecasts is generally much higher than the precipitation forecasts itself, provided that the initial state of the system is accurately estimated. In the latter case, even the precipitation climatology can produce skillful results. This is due to the inertia of the hydrological system rooted in the storage of soil moisture, groundwater and snow pack, as corroborated by a recent study using snow observations for seasonal streamflow forecasting in the Western US. These examples seem to suggest that for accurate seasonal hydrological forecasting, correct state estimation is more important than accurate seasonal meteorological forecasts. However, large-scale estimation of hydrological states is difficult and validation of large-scale hydrological models often reveals large biases in e.g. streamflow estimates. Fortunately, as shown with a validation study of the global model PCR-GLOBWB, these biases are of less importance when seasonal forecasts are evaluated in terms of their ability to reproduce anomalous flows and extreme events, i.e. by anomaly correlations or categorical quantile

  1. Curvature constraints from large scale structure

    NASA Astrophysics Data System (ADS)

    Di Dio, Enea; Montanari, Francesco; Raccanelli, Alvise; Durrer, Ruth; Kamionkowski, Marc; Lesgourgues, Julien

    2016-06-01

    We modified the CLASS code in order to include relativistic galaxy number counts in spatially curved geometries; we present the formalism and study the effect of relativistic corrections on spatial curvature. The new version of the code is now publicly available. Using a Fisher matrix analysis, we investigate how measurements of the spatial curvature parameter ΩK with future galaxy surveys are affected by relativistic effects, which influence observations of the large scale galaxy distribution. These effects include contributions from cosmic magnification, Doppler terms and terms involving the gravitational potential. As an application, we consider angle and redshift dependent power spectra, which are especially well suited for model independent cosmological constraints. We compute our results for a representative deep, wide and spectroscopic survey, and our results show the impact of relativistic corrections on spatial curvature parameter estimation. We show that constraints on the curvature parameter may be strongly biased if, in particular, cosmic magnification is not included in the analysis. Other relativistic effects turn out to be subdominant in the studied configuration. We analyze how the shift in the estimated best-fit value for the curvature and other cosmological parameters depends on the magnification bias parameter, and find that significant biases are to be expected if this term is not properly considered in the analysis.

  2. 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.

  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 wind turbine structures

    NASA Astrophysics Data System (ADS)

    Spera, David A.

    1988-05-01

    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.

  5. 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.

  6. 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

  7. 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

  8. Nonzero Density-Velocity Consistency Relations for Large Scale Structures.

    PubMed

    Rizzo, Luca Alberto; Mota, David F; Valageas, Patrick

    2016-08-19

    We present exact kinematic consistency relations for cosmological structures that do not vanish at equal times and can thus be measured in surveys. These rely on cross correlations between the density and velocity, or momentum, fields. Indeed, the uniform transport of small-scale structures by long-wavelength modes, which cannot be detected at equal times by looking at density correlations only, gives rise to a shift in the amplitude of the velocity field that could be measured. These consistency relations only rely on the weak equivalence principle and Gaussian initial conditions. They remain valid in the nonlinear regime and for biased galaxy fields. They can be used to constrain nonstandard cosmological scenarios or the large-scale galaxy bias. PMID:27588842

  9. Nonzero Density-Velocity Consistency Relations for Large Scale Structures

    NASA Astrophysics Data System (ADS)

    Rizzo, Luca Alberto; Mota, David F.; Valageas, Patrick

    2016-08-01

    We present exact kinematic consistency relations for cosmological structures that do not vanish at equal times and can thus be measured in surveys. These rely on cross correlations between the density and velocity, or momentum, fields. Indeed, the uniform transport of small-scale structures by long-wavelength modes, which cannot be detected at equal times by looking at density correlations only, gives rise to a shift in the amplitude of the velocity field that could be measured. These consistency relations only rely on the weak equivalence principle and Gaussian initial conditions. They remain valid in the nonlinear regime and for biased galaxy fields. They can be used to constrain nonstandard cosmological scenarios or the large-scale galaxy bias.

  10. N-point statistics of large-scale structure in the Zel'dovich approximation

    SciTech Connect

    Tassev, Svetlin

    2014-06-01

    Motivated by the results presented in a companion paper, here we give a simple analytical expression for the matter n-point functions in the Zel'dovich approximation (ZA) both in real and in redshift space (including the angular case). We present numerical results for the 2-dimensional redshift-space correlation function, as well as for the equilateral configuration for the real-space 3-point function. We compare those to the tree-level results. Our analysis is easily extendable to include Lagrangian bias, as well as higher-order perturbative corrections to the ZA. The results should be especially useful for modelling probes of large-scale structure in the linear regime, such as the Baryon Acoustic Oscillations. We make the numerical code used in this paper freely available.

  11. 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.

  12. 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.

  13. Large-scale changes in network interactions as a physiological signature of spatial neglect

    PubMed Central

    Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.

    2014-01-01

    The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode

  14. An informal paper on large-scale dynamic systems

    NASA Technical Reports Server (NTRS)

    Ho, Y. C.

    1975-01-01

    Large scale systems are defined as systems requiring more than one decision maker to control the system. Decentralized control and decomposition are discussed for large scale dynamic systems. Information and many-person decision problems are analyzed.

  15. The large-scale morphology of IRAS galaxies

    NASA Technical Reports Server (NTRS)

    Babul, Arif; Starkman, Glenn D.; Strauss, Michael A.

    1993-01-01

    At present, visual inspection is the only method for comparing the large-scale morphologies in the distribution of galaxies to those in model universes generated by N-body simulations. To remedy the situation, we have developed a set of three structure functions (S1, S2, S3) that quantify the degree of large-scale prolateness, oblateness, and sphericity/uniformity of a 3-D particle distribution and have applied them to a volume-limited (less than = 4000 km/s) sample of 699 IRAS galaxies with f sub 60 greater than 1.2 Jy. To determine the structure functions, we randomly select 500 galaxies as origins of spherical windows of radius R sub w, locate the centroid of the galaxies in the window (assuming all galaxies have equal mass) and then, compute the principal moments of inertia (I sub 1, I sub 2, I sub 3) about the centroid. Each S sub i is a function of (I sub 2)/(I sub 1) and (I sub 3)/I sub 1). S1, S2, and S3 tend to unity for highly prolate, oblate, and uniform distributions, respectively and tend to zero otherwise. The resulting 500 values of S sub i at each scale R sub w are used to construct a histogram.

  16. Complex modular structure of large-scale brain networks

    NASA Astrophysics Data System (ADS)

    Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

    2009-06-01

    Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. Systematic renormalization of the effective theory of Large Scale Structure

    NASA Astrophysics Data System (ADS)

    Akbar Abolhasani, Ali; Mirbabayi, Mehrdad; Pajer, Enrico

    2016-05-01

    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 k2 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.

  2. 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).

  3. Correlated Strength in the Nuclear Spectral Function

    SciTech Connect

    D. Rohe; C. S. Armstrong; R. Asaturyan; O. K. Baker; S. Bueltmann; C. Carasco; D. Day; R. Ent; H. C. Fenker; K. Garrow; A. Gasparian; P. Gueye; M. Hauger; A. Honegger; J. Jourdan; C. E. Keppel; G. Kubon; R. Lindgren; A. Lung; D. J. Mack; J. H. Mitchell; H. Mkrtchyan; D. Mocelj; K. Normand; T. Petitjean; O. Rondon; E. Segbefia; I. Sick; S. Stepanyan; L. Tang; F. Tiefenbacher; W. F. Vulcan; G. Warren; S. A. Wood; L. Yuan; M. Zeier; H. Zhu; B. Zihlmann

    2004-10-01

    We have carried out an (e,ep) experiment at high momentum transfer and in parallel kinematics to measure the strength of the nuclear spectral function S(k,E) at high nucleon momenta k and large removal energies E. This strength is related to the presence of short-range and tensor correlations, and was known hitherto only indirectly and with considerable uncertainty from the lack of strength in the independent-particle region. This experiment locates by direct measurement the correlated strength predicted by theory.

  4. Large-scale network-level processes during entrainment.

    PubMed

    Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan

    2016-03-15

    Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4-30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band "disconnecting" visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557

  5. Large-scale network-level processes during entrainment

    PubMed Central

    Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan

    2016-01-01

    Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4–30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band “disconnecting” visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557

  6. 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. PMID:27133613

  7. 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

  8. Large-Scale Chaos and Fluctuations in Active Nematics

    NASA Astrophysics Data System (ADS)

    Ngo, Sandrine; Peshkov, Anton; Aranson, Igor S.; Bertin, Eric; Ginelli, Francesco; Chaté, Hugues

    2014-07-01

    We show that dry active nematics, e.g., collections of shaken elongated granular particles, exhibit large-scale spatiotemporal chaos made of interacting dense, ordered, bandlike structures in a parameter region including the linear onset of nematic order. These results are obtained from the study of both the well-known (deterministic) hydrodynamic equations describing these systems and of the self-propelled particle model they were derived from. We prove, in particular, that the chaos stems from the generic instability of the band solution of the hydrodynamic equations. Revisiting the status of the strong fluctuations and long-range correlations in the particle model, we show that the giant number fluctuations observed in the chaotic phase are a trivial consequence of density segregation. However anomalous, curvature-driven number fluctuations are present in the homogeneous quasiordered nematic phase and characterized by a nontrivial scaling exponent.

  9. Scaling and Criticality in Large-Scale Neuronal Activity

    NASA Astrophysics Data System (ADS)

    Linkenkaer-Hansen, K.

    The human brain during wakeful rest spontaneously generates large-scale neuronal network oscillations at around 10 and 20 Hz that can be measured non-invasively using magnetoencephalography (MEG) or electroencephalography (EEG). In this chapter, spontaneous oscillations are viewed as the outcome of a self-organizing stochastic process. The aim is to introduce the general prerequisites for stochastic systems to evolve to the critical state and to explain their neurophysiological equivalents. I review the recent evidence that the theory of self-organized criticality (SOC) may provide a unifying explanation for the large variability in amplitude, duration, and recurrence of spontaneous network oscillations, as well as the high susceptibility to perturbations and the long-range power-law temporal correlations in their amplitude envelope.

  10. Large scale motions of thermal transport in a turbulent channel

    NASA Astrophysics Data System (ADS)

    Dharmarathne, Suranga; Tutkun, Murat; Araya, Guillermo; Leonardi, Stefano; Castillo, Luciano

    2015-11-01

    The importance of large scale motions (LSMs) on thermal transport in a turbulent channel flow at friction number of 394 is investigated. Two-point correlation analysis reveals that LSM which significantly contribute to turbulence kinetic energy and scalar transport is a reminiscent of a hairpin packet. Low-order mode representation of the original fields using proper orthogonal decomposition (POD) unveils that the most dominant mode that transports is 3-4 channel half-heights long and such structure which contribute to scalar transport is 2-4 channel half-heights long. Consequently, the study discloses that LSMs are effective in transporting both streamwise component of turbulence kinetic energy and scalar variances.

  11. Large scale magnetic fields in galaxies at high redshifts

    NASA Astrophysics Data System (ADS)

    Bernet, M. L.; Miniati, F.; Lilly, S. J.; Kronberg, P. P.; Dessauges-Zavadsky, M.

    2012-09-01

    In a recent study we have used a large sample of extragalactic radio sources to investigate the redshift evolution of the Rotation Measure (RM) of polarized quasars up to z ≈ 3.0. We found that the dispersion in the RM distribution of quasars increases at higher redshifts and hypothesized that MgII intervening systems were responsible for the observed trend. To test this hypothesis, we have recently obtained high-resolution UVES/VLT spectra for 76 quasars in our sample and in the redshift range 0.6 < z < 2.0. We found a clear correlation between the presence of strong MgII systems and large RMs. This implies that normal galaxies at z ≈ 1 already had large-scale magnetic fields comparable to those seen today.

  12. 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.

  13. Simulating the large-scale structure of HI intensity maps

    NASA Astrophysics Data System (ADS)

    Seehars, Sebastian; Paranjape, Aseem; Witzemann, Amadeus; Refregier, Alexandre; Amara, Adam; Akeret, Joel

    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 20483 particles (particle mass 1.6 × 1011 Msolar / h). Using a conditional mass function to populate the simulated dark matter density field with halos below the mass resolution of the simulation (108 Msolar / h < Mhalo < 1013 Msolar / 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 lesssim z lesssim 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.

  14. Simulating subsurface heterogeneity improves large-scale water resources predictions

    NASA Astrophysics Data System (ADS)

    Hartmann, A. J.; Gleeson, T.; Wagener, T.; Wada, Y.

    2014-12-01

    Heterogeneity is abundant everywhere across the hydrosphere. It exists in the soil, the vadose zone and the groundwater. In large-scale hydrological models, subsurface heterogeneity is usually not considered. Instead average or representative values are chosen for each of the simulated grid cells, not incorporating any sub-grid variability. This may lead to unreliable predictions when the models are used for assessing future water resources availability, floods or droughts, or when they are used for recommendations for more sustainable water management. In this study we use a novel, large-scale model that takes into account sub-grid heterogeneity for the simulation of groundwater recharge by using statistical distribution functions. We choose all regions over Europe that are comprised by carbonate rock (~35% of the total area) because the well understood dissolvability of carbonate rocks (karstification) allows for assessing the strength of subsurface heterogeneity. Applying the model with historic data and future climate projections we show that subsurface heterogeneity lowers the vulnerability of groundwater recharge on hydro-climatic extremes and future changes of climate. Comparing our simulations with the PCR-GLOBWB model we can quantify the deviations of simulations for different sub-regions in Europe.

  15. Large-scale magnetic fields in magnetohydrodynamic turbulence.

    PubMed

    Alexakis, Alexandros

    2013-02-22

    High Reynolds number magnetohydrodynamic turbulence in the presence of zero-flux large-scale magnetic fields is investigated as a function of the magnetic field strength. For a variety of flow configurations, the energy dissipation rate [symbol: see text] follows the scaling [Symbol: see text] proportional U(rms)(3)/ℓ even when the large-scale magnetic field energy is twenty times larger than the kinetic energy. A further increase of the magnetic energy showed a transition to the [Symbol: see text] proportional U(rms)(2) B(rms)/ℓ scaling implying that magnetic shear becomes more efficient at this point at cascading the energy than the velocity fluctuations. Strongly helical configurations form nonturbulent helicity condensates that deviate from these scalings. Weak turbulence scaling was absent from the investigation. Finally, the magnetic energy spectra support the Kolmogorov spectrum k(-5/3) while kinetic energy spectra are closer to the Iroshnikov-Kraichnan spectrum k(-3/2) as observed in the solar wind. PMID:23473153

  16. 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.

  17. Effects of subsurface heterogeneity on large-scale hydrological predictions

    NASA Astrophysics Data System (ADS)

    Hartmann, Andreas; Gleeson, Tom; Wagener, Thorsten; Wada, Yoshihide

    2015-04-01

    Heterogeneity is abundant everywhere across the hydrosphere. It exists in the soil, the vadose zone and the groundwater producing preferential flow and complex threshold behavior. In large-scale hydrological models, subsurface heterogeneity is usually not considered. Instead average or representative values are chosen for each of the simulated grid cells, not incorporating any sub-grid variability. This may lead to unreliable predictions when the models are used for assessing future water resources availability, floods or droughts, or when they are used for recommendations for more sustainable water management. In this study we use a novel, large-scale model that takes into account sub-grid heterogeneity for the simulation of groundwater recharge by using statistical distribution functions. We choose all regions over Europe that are comprised by carbonate rock (~35% of the total area) because the well understood dissolvability of carbonate rocks (karstification) allows for assessing the strength of subsurface heterogeneity. Applying the model with historic data and future climate projections we show that subsurface heterogeneity results (1) in larger present-day groundwater recharge and (2) a greater vulnerability to climate in terms of long-term decrease and hydrological extremes.

  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. Correlation functions for describing and reconstructing soil microstructure: the use of directional correlation functions

    NASA Astrophysics Data System (ADS)

    Karsanina, Marina; Gerke, Kirill; Skvortsova, Elena; Mallants, Dirk

    2015-04-01

    Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and grain-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: (i) two-point probability functions, (ii) linear functions, and (iii) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity (i.e. superpositions of pores and microcracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, including for soil classification, pore

  20. Efficient multiobjective optimization scheme for large scale structures

    NASA Astrophysics Data System (ADS)

    Grandhi, Ramana V.; Bharatram, Geetha; Venkayya, V. B.

    1992-09-01

    This paper presents a multiobjective optimization algorithm for an efficient design of large scale structures. The algorithm is based on generalized compound scaling techniques to reach the intersection of multiple functions. Multiple objective functions are treated similar to behavior constraints. Thus, any number of objectives can be handled in the formulation. Pseudo targets on objectives are generated at each iteration in computing the scale factors. The algorithm develops a partial Pareto set. This method is computationally efficient due to the fact that it does not solve many single objective optimization problems in reaching the Pareto set. The computational efficiency is compared with other multiobjective optimization methods, such as the weighting method and the global criterion method. Trusses, plate, and wing structure design cases with stress and frequency considerations are presented to demonstrate the effectiveness of the method.

  1. Hierarchical features of large-scale cortical connectivity

    NASA Astrophysics Data System (ADS)

    da F. Costa, L.; Sporns, O.

    2005-12-01

    The analysis of complex networks has revealed patterns of organization in a variety of natural and artificial systems, including neuronal networks of the brain at multiple scales. In this paper, we describe a novel analysis of the large-scale connectivity between regions of the mammalian cerebral cortex, utilizing a set of hierarchical measurements proposed recently. We examine previously identified functional clusters of brain regions in macaque visual cortex and cat cortex and find significant differences between such clusters in terms of several hierarchical measures, revealing differences in how these clusters are embedded in the overall cortical architecture. For example, the ventral cluster of visual cortex maintains structurally more segregated, less divergent connections than the dorsal cluster, which may point to functionally different roles of their constituent brain regions.

  2. Density gradient expansion of correlation functions

    NASA Astrophysics Data System (ADS)

    van Leeuwen, Robert

    2013-04-01

    We present a general scheme based on nonlinear response theory to calculate the expansion of correlation functions such as the pair-correlation function or the exchange-correlation hole of an inhomogeneous many-particle system in terms of density derivatives of arbitrary order. We further derive a consistency condition that is necessary for the existence of the gradient expansion. This condition is used to carry out an infinite summation of terms involving response functions up to infinite order from which it follows that the coefficient functions of the gradient expansion can be expressed in terms of the local density profile rather than the background density around which the expansion is carried out. We apply the method to the calculation of the gradient expansion of the one-particle density matrix to second order in the density gradients and recover in an alternative manner the result of Gross and Dreizler [Gross and Dreizler, Z. Phys. AZPAADB0340-219310.1007/BF01413038 302, 103 (1981)], which was derived using the Kirzhnits method. The nonlinear response method is more general and avoids the turning point problem of the Kirzhnits expansion. We further give a description of the exchange hole in momentum space and confirm the wave vector analysis of Langreth and Perdew [Langreth and Perdew, Phys. Rev. BPRBMDO1098-012110.1103/PhysRevB.21.5469 21, 5469 (1980)] for this case. This is used to derive that the second-order gradient expansion of the system averaged exchange hole satisfies the hole sum rule and to calculate the gradient coefficient of the exchange energy without the need to regularize divergent integrals.

  3. Double inflation - A possible resolution of the large-scale structure problem

    NASA Technical Reports Server (NTRS)

    Turner, Michael S.; Villumsen, Jens V.; Vittorio, Nicola; Silk, Joseph; Juszkiewicz, Roman

    1987-01-01

    A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Omega = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of about 100 Mpc, while the small-scale structure over less than about 10 Mpc resembles that in a low-density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations.

  4. How Large Scale Flows in the Solar Convection Zone may Influence Solar Activity

    NASA Technical Reports Server (NTRS)

    Hathaway, D. H.

    2004-01-01

    Large scale flows within the solar convection zone are the primary drivers of the Sun s magnetic activity cycle. Differential rotation can amplify the magnetic field and convert poloidal fields into toroidal fields. Poleward meridional flow near the surface can carry magnetic flux that reverses the magnetic poles and can convert toroidal fields into poloidal fields. The deeper, equatorward meridional flow can carry magnetic flux toward the equator where it can reconnect with oppositely directed fields in the other hemisphere. These axisymmetric flows are themselves driven by large scale convective motions. The effects of the Sun s rotation on convection produce velocity correlations that can maintain the differential rotation and meridional circulation. These convective motions can influence solar activity themselves by shaping the large-scale magnetic field pattern. While considerable theoretical advances have been made toward understanding these large scale flows, outstanding problems in matching theory to observations still remain.

  5. 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

  6. 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.

  7. 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.

  8. Correlation functions for glass-forming systems

    PubMed

    Jacobs

    2000-07-01

    We present a simple, linear, partial-differential equation for the density-density correlation function in a glass-forming system. The equation is written down on the basis of fundamental and general considerations of linearity, symmetry, stability, thermodynamic irreversibility and consistency with the equation of continuity (i.e. , conservation of matter). The dynamical properties of the solutions show a change in behavior characteristic of the liquid-glass transition as a function of one of the parameters (temperature). The equation can be shown to lead to the simplest mode-coupling theory of glasses and provides a partial justification of this simplest theory. It provides also a method for calculating the space dependence of the correlation functions not available otherwise. The results suggest certain differences in behavior between glassy solids and glass-forming liquids which may be accessible to experiment. A brief discussion is presented of how the method can be applied to other systems such as sandpiles and vortex glasses in type II superconductors. PMID:11088609

  9. 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.

  10. Quasars as a Tracer of Large-scale Structures in the Distant Universe

    NASA Astrophysics Data System (ADS)

    Song, Hyunmi; Park, Changbom; Lietzen, Heidi; Einasto, Maret

    2016-08-01

    We study the dependence of the number density and properties of quasars on the background galaxy density using the currently largest spectroscopic data sets of quasars and galaxies. We construct a galaxy number density field smoothed over the variable smoothing scale of between approximately 10 and 20 h ‑1 Mpc over the redshift range 0.46 < z < 0.59 using the Sloan Digital Sky Survey (SDSS) Data Release 12 (DR12) Constant MASS galaxies. The quasar sample is prepared from the SDSS-I/II DR7. We examine the correlation of incidence of quasars with the large-scale background density and the dependence of quasar properties such as bolometric luminosity, black hole mass, and Eddington ratio on the large-scale density. We find a monotonic correlation between the quasar number density and large-scale galaxy number density, which is fitted well with a power-law relation, {n}Q\\propto {ρ }G0.618. We detect weak dependences of quasar properties on the large-scale density such as a positive correlation between black hole mass and density, and a negative correlation between luminosity and density. We discuss the possibility of using quasars as a tracer of large-scale structures at high redshifts, which may be useful for studies of the growth of structures in the high-redshift universe.

  11. Meson's correlation functions in a nuclear medium

    NASA Astrophysics Data System (ADS)

    Park, Chanyong

    2016-09-01

    We investigate meson's spectrum, decay constant and form factor in a nuclear medium through holographic two- and three-point correlation functions. To describe a nuclear medium composed of protons and neutrons, we consider a hard wall model on the thermal charged AdS geometry and show that due to the isospin interaction with a nuclear medium, there exist splittings of the meson's spectrum, decay constant and form factor relying on the isospin charge. In addition, we show that the ρ-meson's form factor describing an interaction with pseudoscalar fluctuation decreases when the nuclear density increases, while the interaction with a longitudinal part of an axial vector meson increases.

  12. Functional complexity in correlated electron matter

    NASA Astrophysics Data System (ADS)

    Bishop, A. R.

    2002-05-01

    We outline several themes which have now emerged in both organic and inorganic correlated electronic materials: the prevalence of intrinsic complexity realized in the coexistence or competition among broken-symmetry ground states; the origin of landscapes in coupled spin, charge and lattice (orbital) degrees-of-freedom; the importance of co-existing short- and long-range forces; and the importance of multiscale complexity for key material properties, including hierarchies of functional, connected scales, coupled intrinsic inhomogeneities in spin, charge and lattice, consequent intrinsic multiple timescales, and the importance of multifunctional “electro-elastic” materials.

  13. 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.

  14. 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.

  15. 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.

  16. Large-scale dimension densities for heart rate variability analysis.

    PubMed

    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 (rho (mu/ls) = 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 rho (mu/ls) (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. PMID:16711836

  17. Large-scale regional comparisons of ecosystem processes: Methods and approaches

    NASA Astrophysics Data System (ADS)

    Legendre, Louis; Niquil, Nathalie

    2013-01-01

    Large-scale regional marine ecosystems can be compared for various processes that include their structure and biodiversity, functioning, services, and effects on biogeochemical processes. The comparisons can proceed from data up, or from conceptual models down, or from a combination of models and data. This study proposes a typology of methods and approaches that are currently used, or could possibly be used for making large-scale ecosystem comparisons. The various methods and approaches are illustrated with examples drawn from the literature.

  18. DIF Detection and Interpretation in Large-Scale Science Assessments: Informing Item Writing Practices

    ERIC Educational Resources Information Center

    Zenisky, April L.; Hambleton, Ronald K.; Robin, Frederic

    2004-01-01

    Differential item functioning (DIF) analyses are a routine part of the development of large-scale assessments. Less common are studies to understand the potential sources of DIF. The goals of this study were (a) to identify gender DIF in a large-scale science assessment and (b) to look for trends in the DIF and non-DIF items due to content,…

  19. Characterizing unknown systematics in large scale structure surveys

    SciTech Connect

    Agarwal, Nishant; Ho, Shirley; Myers, Adam D.; Seo, Hee-Jong; Ross, Ashley J.; Bahcall, Neta; Brinkmann, Jonathan; Eisenstein, Daniel J.; Muna, Demitri; Palanque-Delabrouille, Nathalie; Yèche, Christophe; Petitjean, Patrick; Schneider, Donald P.; Streblyanska, Alina; Weaver, Benjamin A.

    2014-04-01

    Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.

  20. Probes of large-scale structure in the universe

    NASA Technical Reports Server (NTRS)

    Suto, Yasushi; Gorski, Krzysztof; Juszkiewicz, Roman; Silk, Joseph

    1988-01-01

    A general formalism is developed which shows that the gravitational instability theory for the origin of the large-scale structure of the universe is now capable of critically confronting observational results on cosmic background radiation angular anisotropies, large-scale bulk motions, and large-scale clumpiness in the galaxy counts. The results indicate that presently advocated cosmological models will have considerable difficulty in simultaneously explaining the observational results.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. First hints of large scale structures in the ultrahigh energy sky?

    SciTech Connect

    Cuoco, A.; Miele, G.; Serpico, Pasquale D.; /Fermilab

    2006-10-01

    The result of the recent publication [1] of a broad maximum around 25 degrees in the two-point autocorrelation function of ultra-high energy cosmic ray arrival directions has been intriguingly interpreted as the first imprint of the large scale structures (LSS) of baryonic matter in the near universe. We analyze this suggestion in light of the clustering properties expected from the PSCz astronomical catalogue of LSS. The chance probability of the signal is consistent within 2 {sigma} with the predictions based on the catalogue. No evidence for a significant cross-correlation of the observed events with known overdensities in the LSS is found, which may be due to the role of the galactic and extragalactic magnetic fields, and is however consistent with the limited statistics. The larger statistics to be collected by the Pierre Auger Observatory is needed to answer definitely the question.

  6. Detecting correlations among functional-sequence motifs

    NASA Astrophysics Data System (ADS)

    Pirino, Davide; Rigosa, Jacopo; Ledda, Alice; Ferretti, Luca

    2012-06-01

    Sequence motifs are words of nucleotides in DNA with biological functions, e.g., gene regulation. Identification of such words proceeds through rejection of Markov models on the expected motif frequency along the genome. Additional biological information can be extracted from the correlation structure among patterns of motif occurrences. In this paper a log-linear multivariate intensity Poisson model is estimated via expectation maximization on a set of motifs along the genome of E. coli K12. The proposed approach allows for excitatory as well as inhibitory interactions among motifs and between motifs and other genomic features like gene occurrences. Our findings confirm previous stylized facts about such types of interactions and shed new light on genome-maintenance functions of some particular motifs. We expect these methods to be applicable to a wider set of genomic features.

  7. Detecting correlations among functional-sequence motifs.

    PubMed

    Pirino, Davide; Rigosa, Jacopo; Ledda, Alice; Ferretti, Luca

    2012-06-01

    Sequence motifs are words of nucleotides in DNA with biological functions, e.g., gene regulation. Identification of such words proceeds through rejection of Markov models on the expected motif frequency along the genome. Additional biological information can be extracted from the correlation structure among patterns of motif occurrences. In this paper a log-linear multivariate intensity Poisson model is estimated via expectation maximization on a set of motifs along the genome of E. coli K12. The proposed approach allows for excitatory as well as inhibitory interactions among motifs and between motifs and other genomic features like gene occurrences. Our findings confirm previous stylized facts about such types of interactions and shed new light on genome-maintenance functions of some particular motifs. We expect these methods to be applicable to a wider set of genomic features. PMID:23005179

  8. Large-scale reconstruction and phylogenetic analysis of metabolic environments

    PubMed Central

    Borenstein, Elhanan; Kupiec, Martin; Feldman, Marcus W.; Ruppin, Eytan

    2008-01-01

    The topology of metabolic networks may provide important insights not only into the metabolic capacity of species, but also into the habitats in which they evolved. Here we introduce the concept of a metabolic network's “seed set”—the set of compounds that, based on the network topology, are exogenously acquired—and provide a methodological framework to computationally infer the seed set of a given network. Such seed sets form ecological “interfaces” between metabolic networks and their surroundings, approximating the effective biochemical environment of each species. Analyzing the metabolic networks of 478 species and identifying the seed set of each species, we present a comprehensive large-scale reconstruction of such predicted metabolic environments. The seed sets' composition significantly correlates with several basic properties characterizing the species' environments and agrees with biological observations concerning major adaptations. Species whose environments are highly predictable (e.g., obligate parasites) tend to have smaller seed sets than species living in variable environments. Phylogenetic analysis of the seed sets reveals the complex dynamics governing gain and loss of seeds across the phylogenetic tree and the process of transition between seed and non-seed compounds. Our findings suggest that the seed state is transient and that seeds tend either to be dropped completely from the network or to become non-seed compounds relatively fast. The seed sets also permit a successful reconstruction of a phylogenetic tree of life. The “reverse ecology” approach presented lays the foundations for studying the evolutionary interplay between organisms and their habitats on a large scale. PMID:18787117

  9. 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.

  10. 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

  11. 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

  12. Towards online multiresolution community detection in large-scale networks.

    PubMed

    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

  13. Large-scale asymmetric synthesis of a cathepsin S inhibitor.

    PubMed

    Lorenz, Jon C; Busacca, Carl A; Feng, XuWu; Grinberg, Nelu; Haddad, Nizar; Johnson, Joe; Kapadia, Suresh; Lee, Heewon; Saha, Anjan; Sarvestani, Max; Spinelli, Earl M; Varsolona, Rich; Wei, Xudong; Zeng, Xingzhong; Senanayake, Chris H

    2010-02-19

    A potent reversible inhibitor of the cysteine protease cathepsin-S was prepared on large scale using a convergent synthetic route, free of chromatography and cryogenics. Late-stage peptide coupling of a chiral urea acid fragment with a functionalized aminonitrile was employed to prepare the target, using 2-hydroxypyridine as a robust, nonexplosive replacement for HOBT. The two key intermediates were prepared using a modified Strecker reaction for the aminonitrile and a phosphonation-olefination-rhodium-catalyzed asymmetric hydrogenation sequence for the urea. A palladium-catalyzed vinyl transfer coupled with a Claisen reaction was used to produce the aldehyde required for the side chain. Key scale up issues, safety calorimetry, and optimization of all steps for multikilogram production are discussed. PMID:20102230

  14. 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.

  15. An Empirical Relation between the Large-scale Magnetic Field and the Dynamical Mass in Galaxies

    NASA Astrophysics Data System (ADS)

    Tabatabaei, F. S.; Martinsson, T. P. K.; Knapen, J. H.; Beckman, J. E.; Koribalski, B.; Elmegreen, B. G.

    2016-02-01

    The origin and evolution of cosmic magnetic fields as well as the influence of the magnetic fields on the evolution of galaxies are unknown. Though not without challenges, the dynamo theory can explain the large-scale coherent magnetic fields that govern galaxies, but observational evidence for the theory is so far very scarce. Putting together the available data of non-interacting, non-cluster galaxies with known large-scale magnetic fields, we find a tight correlation between the integrated polarized flux density, SPI, and the rotation speed, vrot, of galaxies. This leads to an almost linear correlation between the large-scale magnetic field \\bar{B} and vrot, assuming that the number of cosmic-ray electrons is proportional to the star formation rate, and a super-linear correlation assuming equipartition between magnetic fields and cosmic rays. This correlation cannot be attributed to an active linear α-Ω dynamo, as no correlation holds with global shear or angular speed. It indicates instead a coupling between the large-scale magnetic field and the dynamical mass of the galaxies, \\bar{B}˜ \\{M}{{dyn}}0.25-0.4. Hence, faster rotating and/or more massive galaxies have stronger large-scale magnetic fields. The observed \\bar{B}-{v}{{rot}} correlation shows that the anisotropic turbulent magnetic field dominates \\bar{B} in fast rotating galaxies as the turbulent magnetic field, coupled with gas, is enhanced and ordered due to the strong gas compression and/or local shear in these systems. This study supports a stationary condition for the large-scale magnetic field as long as the dynamical mass of galaxies is constant.

  16. 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.

  17. 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

  18. 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

  19. Large-scale magnetic fields, dark energy, and QCD

    SciTech Connect

    Urban, Federico R.; Zhitnitsky, Ariel R.

    2010-08-15

    Cosmological magnetic fields are being observed with ever increasing correlation lengths, possibly reaching the size of superclusters, therefore disfavoring the conventional picture of generation through primordial seeds later amplified by galaxy-bound dynamo mechanisms. In this paper we put forward a fundamentally different approach that links such large-scale magnetic fields to the cosmological vacuum energy. In our scenario the dark energy is due to the Veneziano ghost (which solves the U(1){sub A} problem in QCD). The Veneziano ghost couples through the triangle anomaly to the electromagnetic field with a constant which is unambiguously fixed in the standard model. While this interaction does not produce any physical effects in Minkowski space, it triggers the generation of a magnetic field in an expanding universe at every epoch. The induced energy of the magnetic field is thus proportional to cosmological vacuum energy: {rho}{sub EM{approx_equal}}B{sup 2{approx_equal}}(({alpha}/4{pi})){sup 2{rho}}{sub DE}, {rho}{sub DE} hence acting as a source for the magnetic energy {rho}{sub EM}. The corresponding numerical estimate leads to a magnitude in the nG range. There are two unique and distinctive predictions of our proposal: an uninterrupted active generation of Hubble size correlated magnetic fields throughout the evolution of the Universe; the presence of parity violation on the enormous scales 1/H, which apparently has been already observed in CMB. These predictions are entirely rooted into the standard model of particle physics.

  20. Large-scale recording of astrocyte activity

    PubMed Central

    Nimmerjahn, Axel; Bergles, Dwight E.

    2015-01-01

    Astrocytes are highly ramified glial cells found throughout the central nervous system (CNS). They express a variety of neurotransmitter receptors that can induce widespread chemical excitation, placing these cells in an optimal position to exert global effects on brain physiology. However, the activity patterns of only a small fraction of astrocytes have been examined and techniques to manipulate their behavior are limited. As a result, little is known about how astrocytes modulate CNS function on synaptic, microcircuit, or systems levels. Here, we review current and emerging approaches for visualizing and manipulating astrocyte activity in vivo. Deciphering how astrocyte network activity is controlled in different physiological and pathological contexts is critical for defining their roles in the healthy and diseased CNS. PMID:25665733

  1. The Challenge of Large-Scale Literacy Improvement

    ERIC Educational Resources Information Center

    Levin, Ben

    2010-01-01

    This paper discusses the challenge of making large-scale improvements in literacy in schools across an entire education system. Despite growing interest and rhetoric, there are very few examples of sustained, large-scale change efforts around school-age literacy. The paper reviews 2 instances of such efforts, in England and Ontario. After…

  2. INTERNATIONAL WORKSHOP ON LARGE-SCALE REFORESTATION: PROCEEDINGS

    EPA Science Inventory

    The purpose of the workshop was to identify major operational and ecological considerations needed to successfully conduct large-scale reforestation projects throughout the forested regions of the world. Large-scale" for this workshop means projects where, by human effort, approx...

  3. Using Large-Scale Assessment Scores to Determine Student Grades

    ERIC Educational Resources Information Center

    Miller, Tess

    2013-01-01

    Many Canadian provinces provide guidelines for teachers to determine students' final grades by combining a percentage of students' scores from provincial large-scale assessments with their term scores. This practice is thought to hold students accountable by motivating them to put effort into completing the large-scale assessment, thereby…

  4. Small-scale universality and large-scale diversity. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin, A. Krzywicki, and M. Zagorski

    NASA Astrophysics Data System (ADS)

    Ispolatov, Yaroslav

    2016-07-01

    Martin et al. undertook an arduous task of reviewing vast literature on evolution and functionality of directed biological networks and gene networks in particular. The literature is assessed addressing a question of whether a set of features particular for gene networks is repeatedly recreated among unrelated species driven by selection pressure or has evolved once and is being inherited. To argue for the former mechanism, Martin and colleagues explore the following examples: Scale-free out-degree distribution.

  5. Structure-function correlations in tyrosinases.

    PubMed

    Kanteev, Margarita; Goldfeder, Mor; Fishman, Ayelet

    2015-09-01

    Tyrosinases are metalloenzymes belonging to the type-3 copper protein family which contain two copper ions in the active site. They are found in various prokaryotes as well as in plants, fungi, arthropods, and mammals and are responsible for pigmentation, wound healing, radiation protection, and primary immune response. Tyrosinases perform two sequential enzymatic reactions: hydroxylation of monophenols and oxidation of diphenols to form quinones which polymerize spontaneously to melanin. Two other members of this family are catechol oxidases, which are prevalent mainly in plants and perform only the second oxidation step, and hemocyanins, which lack enzymatic activity and are oxygen carriers. In the last decade, several structures of plant and bacterial tyrosinases were determined, some with substrates or inhibitors, highlighting features and residues which are important for copper uptake and catalysis. This review summarizes the updated information on structure-function correlations in tyrosinases along with comparison to other type-3 copper proteins. PMID:26104241

  6. Structure–function correlations in tyrosinases

    PubMed Central

    Kanteev, Margarita; Goldfeder, Mor; Fishman, Ayelet

    2015-01-01

    Tyrosinases are metalloenzymes belonging to the type-3 copper protein family which contain two copper ions in the active site. They are found in various prokaryotes as well as in plants, fungi, arthropods, and mammals and are responsible for pigmentation, wound healing, radiation protection, and primary immune response. Tyrosinases perform two sequential enzymatic reactions: hydroxylation of monophenols and oxidation of diphenols to form quinones which polymerize spontaneously to melanin. Two other members of this family are catechol oxidases, which are prevalent mainly in plants and perform only the second oxidation step, and hemocyanins, which lack enzymatic activity and are oxygen carriers. In the last decade, several structures of plant and bacterial tyrosinases were determined, some with substrates or inhibitors, highlighting features and residues which are important for copper uptake and catalysis. This review summarizes the updated information on structure–function correlations in tyrosinases along with comparison to other type-3 copper proteins. PMID:26104241

  7. 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.

  8. 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.

  9. Stochastic pattern transitions in large scale swarms

    NASA Astrophysics Data System (ADS)

    Schwartz, Ira; Lindley, Brandon; Mier-Y-Teran, Luis

    2013-03-01

    We study the effects of time dependent noise and discrete, randomly distributed time delays on the dynamics of a large coupled system of self-propelling particles. Bifurcation analysis on a mean field approximation of the system reveals that the system possesses patterns with certain universal characteristics that depend on distinguished moments of the time delay distribution. We show both theoretically and numerically that although bifurcations of simple patterns, such as translations, change stability only as a function of the first moment of the time delay distribution, more complex bifurcating patterns depend on all of the moments of the delay distribution. In addition, we show that for sufficiently large values of the coupling strength and/or the mean time delay, there is a noise intensity threshold, dependent on the delay distribution width, that forces a transition of the swarm from a misaligned state into an aligned state. We show that this alignment transition exhibits hysteresis when the noise intensity is taken to be time dependent. Research supported by the Office of Naval Research

  10. The impact of temperature fluctuations on the large-scale clustering of the Lyα forest

    NASA Astrophysics Data System (ADS)

    Greig, Bradley; Bolton, James S.; Wyithe, J. Stuart B.

    2015-03-01

    We develop a semi-analytic method for assessing the impact of the large-scale IGM temperature fluctuations expected following He II reionization on three-dimensional clustering measurements of the Lyα forest. Our methodology builds upon the existing large volume, mock Lyα forest survey simulations presented by Greig et al. by including a prescription for a spatially inhomogeneous ionizing background, temperature fluctuations induced by patchy He II photoheating and the clustering of quasars. This approach enables us to achieve a dynamic range within our semi-analytic model substantially larger than currently feasible with computationally expensive, fully numerical simulations. The results agree well with existing numerical simulations, with large-scale temperature fluctuations introducing a scale-dependent increase in the spherically averaged 3D Lyα forest power spectrum of up to 20-30 per cent at wavenumbers k ˜ 0.02 Mpc- 1. Although these large-scale thermal fluctuations will not substantially impact upon the recovery of the baryon acoustic oscillation scale from existing and forthcoming dark energy spectroscopic surveys, any complete forward modelling of the broad-band term in the Lyα correlation function will none the less require their inclusion.

  11. 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.

  12. 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.

  13. Large-scale brain networks in cognition: emerging methods and principles.

    PubMed

    Bressler, Steven L; Menon, Vinod

    2010-06-01

    An understanding of how the human brain produces cognition ultimately depends on knowledge of large-scale brain organization. Although it has long been assumed that cognitive functions are attributable to the isolated operations of single brain areas, we demonstrate that the weight of evidence has now shifted in support of the view that cognition results from the dynamic interactions of distributed brain areas operating in large-scale networks. We review current research on structural and functional brain organization, and argue that the emerging science of large-scale brain networks provides a coherent framework for understanding of cognition. Critically, this framework allows a principled exploration of how cognitive functions emerge from, and are constrained by, core structural and functional networks of the brain. PMID:20493761

  14. Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

    PubMed

    Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

    2015-09-01

    With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques. PMID:25872214

  15. Interloper bias in future large-scale structure surveys

    NASA Astrophysics Data System (ADS)

    Pullen, Anthony R.; Hirata, Christopher M.; Doré, Olivier; Raccanelli, Alvise

    2016-02-01

    Next-generation spectroscopic surveys will map the large-scale structure of the observable universe, using emission line galaxies as tracers. While each survey will map the sky with a specific emission line, interloping emission lines can masquerade as the survey's intended emission line at different redshifts. Interloping lines from galaxies that are not removed can contaminate the power spectrum measurement, mixing correlations from various redshifts and diluting the true signal. We assess the potential for power spectrum contamination, finding that an interloper fraction worse than 0.2% could bias power spectrum measurements for future surveys by more than 10% of statistical errors, while also biasing power spectrum inferences. We also construct a formalism for predicting cosmological parameter measurement bias, demonstrating that a 0.15%-0.3% interloper fraction could bias the growth rate by more than 10% of the error, which can affect constraints on gravity from upcoming surveys. We use the COSMOS Mock Catalog (CMC), with the emission lines rescaled to better reproduce recent data, to predict potential interloper fractions for the Prime Focus Spectrograph (PFS) and the Wide-Field InfraRed Survey Telescope (WFIRST). We find that secondary line identification, or confirming galaxy redshifts by finding correlated emission lines, can remove interlopers for PFS. For WFIRST, we use the CMC to predict that the 0.2% target can be reached for the WFIRST Hα survey, but sensitive optical and near-infrared photometry will be required. For the WFIRST [O III] survey, the predicted interloper fractions reach several percent and their effects will have to be estimated and removed statistically (e.g., with deep training samples). These results are optimistic as the CMC does not capture the full set of correlations of galaxy properties in the real Universe, and they do not include blending effects. Mitigating interloper contamination will be crucial to the next generation of

  16. 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.

  17. 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.

  18. 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.

  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. 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.

  1. Large-scale Molecular Dynamics Simulations of Glancing Angle Deposition

    NASA Astrophysics Data System (ADS)

    Hubartt, Bradley; Liu, Xuejing; Amar, Jacques

    2013-03-01

    While a variety of methods have been developed to carry out atomistic simulations of thin-film growth at small deposition angles with respect to the substrate normal, due to the complex morphology as well as the existence of multiple scattering of depositing atoms by the growing thin-film, realistically modeling the deposition process for large deposition angles can be quite challenging. Accordingly, we have developed a computationally efficient method based on the use of a single graphical processing unit (GPU) to carry out molecular dynamics (MD) simulations of the deposition and growth of thin-films via glancing angle deposition. Using this method we have carried out large-scale MD simulations, based on an embedded-atom-method potential, of Cu/Cu(100) growth up to 20 monolayers for deposition angles ranging from 50° to 85° and for both random and fixed azimuthal angles. Our results for the thin-film porosity, roughness, lateral correlation length, and density vs height will be presented and compared with experiments. Results for the dependence of the microstructure, grain-size distribution, surface texture, and defect concentration on deposition angle will also be presented. Supported by NSF DMR-0907399

  2. Ectopically tethered CP190 induces large-scale chromatin decondensation

    PubMed Central

    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. PMID:24472778

  3. Large scale simulations of bidisperse emulsions and foams

    NASA Astrophysics Data System (ADS)

    Metsi, Efimia

    Emulsions and foams are of fundamental importance in a wide variety of industrial and natural processes. The macroscopic properties of these multiphase systems are determined by the viscous and interfacial interactions on the microscopic level. In previous research efforts, the realism of computer simulations has been limited by the cost of the computational algorithms which scale as O(N2), where N is the number of droplets. In our research, we have developed a novel, fast and efficient algorithm which scales as [O( N1n(N)]. The algorithm has been implemented to simulate the low Reynolds number flow of large-scale systems of monodisperse and bidisperse droplet suspensions. A comprehensive study has been performed to examine the effective viscosity of these systems as a function of the overall volume fraction, volume fraction of small droplets, Capillary number and droplet size ratio. Monodisperse systems exhibit disorder-order transitions at high volume fractions and low Capillary numbers. Bidisperse systems show a tendency toward cluster formation with small droplets interspersed among large droplets. To determine if the cluster formation leads to phase separation, simulations have been performed with the two droplet species arranged in ordered layers. It is found that the initial layers are destroyed, and the two phases mix, yielding clusters of small and large droplets. The mixing of the two phases and the cluster formation are investigated through linear and radial pairwise distribution functions of the two droplet species.

  4. Multi-time multi-scale correlation functions in hydrodynamic turbulence

    NASA Astrophysics Data System (ADS)

    Biferale, Luca; Calzavarini, Enrico; Toschi, Federico

    2011-08-01

    High Reynolds numbers Navier-Stokes equations are believed to break self-similarity concerning both spatial and temporal properties: correlation functions of different orders exhibit distinct decorrelation times and anomalous spatial scaling properties. Here, we present a systematic attempt to measure multi-time and multi-scale correlations functions, by using high Reynolds numbers numerical simulations of fully homogeneous and isotropic turbulent flow. The main idea is to set-up an ensemble of probing stations riding the flow, i.e., measuring correlations in a reference frame centered on the trajectory of distinct fluid particles (the quasi-Lagrangian reference frame introduced by Belinicher and L'vov [Sov. Phys. JETP 66, 303 (1987)]). In this way, we reduce the large-scale sweeping and measure the non-trivial temporal dynamics governing the turbulent energy transfer from large to small scales. We present evidences of the existence of the dynamic multiscaling properties of turbulence - first proposed by L'vov et al. [Phys. Rev. E 55, 7030 (1997)] - in which multi-time correlation functions are characterized by an infinite set of characteristic times.

  5. European river flow regimes: assessing space-time dynamics and links to large-scale climate

    NASA Astrophysics Data System (ADS)

    Hannah, D. M.; Kingston, D. G.; Laize, C.; Lavers, D. A.; Wilson, D.

    2011-12-01

    Given heightened concerns about climate change/ variability and human impacts on hydrology, there is a pressing need for research to quantify temporal variability and spatial structure in river flow regimes, and to establish hydroclimatological (climate-flow) associations as a basis for predicting future water stress. This paper draws together findings from studies undertaken at the UK and pan-European scale (using datasets of >100 stations with time series >25 years) and aims: (1) to demonstrate the utility of classification schemes for identifying space-time patterns in river flow regimes and (2) to explore the hydroclimatological relationships between large-scale atmospheric circulation and river flow response. Often, classification is undertaken prior to detailed analysis of large-scale patterns in river flow. In this paper, a suite of novel cluster analysis based methods are presented that identify hydrological regions as well as inter-annual river flow regime variation within regions. Statistical characteristics of the emergent classifications are analysed including geographical expression, teleconnections and presence of time-series trends. Results show that classification provides a useful general organising framework for large-scale hydrological research and facilitates systematic testing of hypotheses about drivers of hydrological variation across wide spatial domains. To investigate climate controls on space-time river flow variation, three methods for characterising atmospheric influences are considered: air-mass types, large-scale climate indices and gridded re-analyses (ECMWF ERA-40). A new air-mass classification for Europe (Spatial Synoptic Classification 2) is presented that classifies daily air-masses. Data are pooled by long-term flow regime regions to assess air-mass - flow regime (shape and magnitude) class associations across Europe; and multiple discriminant function analysis (MDFA) is used to model links between the categorical data. The

  6. 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.

  7. Large scale suppression of scalar power on a spatial condensation

    NASA Astrophysics Data System (ADS)

    Kouwn, Seyen; Kwon, O.-Kab; Oh, Phillial

    2015-03-01

    We consider a deformed single-field inflation model in terms of three SO(3) symmetric moduli fields. We find that spatially linear solutions for the moduli fields induce a phase transition during the early stage of the inflation and the suppression of scalar power spectrum at large scales. This suppression can be an origin of anomalies for large-scale perturbation modes in the cosmological observation.

  8. Large-scale motions in a plane wall jet

    NASA Astrophysics Data System (ADS)

    Gnanamanickam, Ebenezer; Jonathan, Latim; Shibani, Bhatt

    2015-11-01

    The dynamic significance of large-scale motions in turbulent boundary layers have been the focus of several recent studies, primarily focussing on canonical flows - zero pressure gradient boundary layers, flows within pipes and channels. This work presents an investigation into the large-scale motions in a boundary layer that is used as the prototypical flow field for flows with large-scale mixing and reactions, the plane wall jet. An experimental investigation is carried out in a plane wall jet facility designed to operate at friction Reynolds numbers Reτ > 1000 , which allows for the development of a significant logarithmic region. The streamwise turbulent intensity across the boundary layer is decomposed into small-scale (less than one integral length-scale δ) and large-scale components. The small-scale energy has a peak in the near-wall region associated with the near-wall turbulent cycle as in canonical boundary layers. However, eddies of large-scales are the dominating eddies having significantly higher energy, than the small-scales across almost the entire boundary layer even at the low to moderate Reynolds numbers under consideration. The large-scales also appear to amplitude and frequency modulate the smaller scales across the entire boundary layer.

  9. Can global hydrological models reproduce large scale river flood regimes?

    NASA Astrophysics Data System (ADS)

    Eisner, Stephanie; Flörke, Martina

    2013-04-01

    River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk

  10. 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

  11. 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

  12. Detectability of Large-Scale Solar Subsurface Flows

    NASA Astrophysics Data System (ADS)

    Woodard, M.

    2014-04-01

    The accuracy of helioseismic measurement is limited by the stochastic nature of solar oscillations. In this article I use a Gaussian statistical model of the global seismic wave field of the Sun to investigate the noise limitations of direct-modeling analysis of convection-zone-scale flows. The theoretical analysis of noise is based on hypothetical data that cover the entire photosphere, including the portions invisible from the Earth. Noise estimates are derived for measurements of the flow-dependent couplings of global-oscillation modes and for combinations of coupling measurements that isolate vector-spherical-harmonic components of the flow velocity. For current helioseismic observations, which sample only a fraction of the photosphere, the inferred detection limits are best regarded as optimistic limits. The flow-velocity fields considered in this work are assumed to be decomposable into vector-spherical-harmonic functions of degree less than five. The problem of measuring the general velocity field is shown to be similar enough to the well-studied problem of measuring differential rotation to permit rough estimates of flow-detection thresholds to be gleaned from past helioseismic analysis. I estimate that, with existing and anticipated helioseismic datasets, large-scale flow-velocity amplitudes of a few tens of should be detectable near the base of the convection zone.

  13. Economic dispatch control for large scale thermal power systems

    SciTech Connect

    Not Available

    1986-01-01

    A realistic model for economic dispatch control (EDC) which is valid for large scale thermal power system is described. This model properly accounts for the nonlinearities of the generation cost-curves introduced by the operation constraints of thermal units. The methodology of this model computes the optimal readjustments of generation schedules such that their total generation output meets the system demand, including the Area Control Error (ACE). The objective function to be minimized is the instantaneous operating cost of a power system subjected to several equality and inequality constraints, which represent the performance characteristics and operation limitations of the various units in the system as well as the active power loss in the transmission network. The generation cost curves and the active losses are represented using one of two models. The first model includes the exact piecewise linear curve formulation and the well known loss formula, while the second one considers a second order polynomial approximation of the generation cost curves and assumes that the active network losses are independent on the generation configuration and have constant percentage value from the total system demand. Each of these models has its merits to EDC strategies. 10 references, 7 figures, 3 tables.

  14. Large-Scale Molecular and Nanoelectronic Circuits & Associated Opportunities

    NASA Astrophysics Data System (ADS)

    Heath, Jim

    2007-03-01

    According to the International Technology Roadmap for Semiconductors (ITRS), by year 2020 it is expected that the most closely spaced metallic wires within a DRAM circuit will be patterned at a pitch of about 30 nm, implying that the conductors themselves will be of a width of around 15 nm. However, virtually every aspect of achieving this technology is considered to be `red,' meaning that there is no known solution. Nevertheless, ultra-high density (semiconductor and metallic) nanowire circuitry, fabricated at 2020 dimensions and beyond, would be expected to provide a host of value traditional (logic & memory) and nontraditional (sensing, thermoelectrics, etc.) functions. In this talk we will discuss the fabrication and testing of large scale circuitry (> 10^5 devices) aimed a these various applications. This will include a 160,000 bit memory circuit that is no larger than a white blood cell, high-performance, ultra-dense & energy efficient logic circuitry, nanowire sensing arrays, and high-performance silicon-based thermoelectric devices. We will also discuss how these circuits may be fabricated on a host of substrates, including plastic.

  15. Assessing large-scale wildlife responses to human infrastructure development.

    PubMed

    Torres, Aurora; Jaeger, Jochen A G; Alonso, Juan Carlos

    2016-07-26

    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

  16. 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. PMID:22727063

  17. 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.

  18. Soft-Pion theorems for large scale structure

    SciTech Connect

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

    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 and Riotto and Peloso and 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.

  19. 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.

  20. The large-scale landslide risk classification in catchment scale

    NASA Astrophysics Data System (ADS)

    Liu, Che-Hsin; Wu, Tingyeh; Chen, Lien-Kuang; Lin, Sheng-Chi

    2013-04-01

    The landslide disasters caused heavy casualties during Typhoon Morakot, 2009. This disaster is defined as largescale landslide due to the casualty numbers. This event also reflects the survey on large-scale landslide potential is so far insufficient and significant. The large-scale landslide potential analysis provides information about where should be focused on even though it is very difficult to distinguish. Accordingly, the authors intend to investigate the methods used by different countries, such as Hong Kong, Italy, Japan and Switzerland to clarify the assessment methodology. The objects include the place with susceptibility of rock slide and dip slope and the major landslide areas defined from historical records. Three different levels of scales are confirmed necessarily from country to slopeland, which are basin, catchment, and slope scales. Totally ten spots were classified with high large-scale landslide potential in the basin scale. The authors therefore focused on the catchment scale and employ risk matrix to classify the potential in this paper. The protected objects and large-scale landslide susceptibility ratio are two main indexes to classify the large-scale landslide risk. The protected objects are the constructions and transportation facilities. The large-scale landslide susceptibility ratio is based on the data of major landslide area and dip slope and rock slide areas. Totally 1,040 catchments are concerned and are classified into three levels, which are high, medium, and low levels. The proportions of high, medium, and low levels are 11%, 51%, and 38%, individually. This result represents the catchments with high proportion of protected objects or large-scale landslide susceptibility. The conclusion is made and it be the base material for the slopeland authorities when considering slopeland management and the further investigation.

  1. The anisotropic line correlation function as a probe of anisotropies in galaxy surveys

    NASA Astrophysics Data System (ADS)

    Eggemeier, A.; Battefeld, T.; Smith, R. E.; Niemeyer, J.

    2015-10-01

    We propose an anisotropic generalization of the line correlation function (ALCF) to separate and quantify phase information in the large-scale structure of galaxies. The line correlation function probes the strictly non-linear regime of structure formation and since phase information drops out of the power spectrum, the line correlation function provides a complementary tool to commonly used techniques based on two-point statistics. Furthermore, it is independent of linear bias as well as the Gaussian variance on the modulus of the density field and thus may also prove to be advantageous compared to the bispectrum or similar higher order statistics for certain cases. For future applications, it is vital, though, to be able to account for observational effects that cause anisotropies in the distribution of galaxies. Based on a number of numerical studies, we find that our ALCF is well suited to accomplish this task and we demonstrate how the Alcock-Paczyński effect and kinematical redshift-space distortions can in principle be measured via the ALCF.

  2. The two-point correlation function of randomly distributed Lyman alpha clouds

    NASA Technical Reports Server (NTRS)

    Fardal, Mark A.; Shull, J. Michael

    1993-01-01

    It is often assumed that Ly-alpha forest clouds are randomly distributed, intergalactic objects that are highly ionized by the UV background produced by quasars. If these assumptions are true, fluctuations in the UV background should produce a nonzero two point correlation function in the Ly-alpha forest. This effect, which is really just a generalization of the proximity effect, is more significant at high redshift (z is approximately 3-4) because the mean free path for UV photons is smaller there, and the fluctuations correspondingly larger. This effect was studied using both the semi-analytic techniques of Zuo's recent papers and Monte Carlo simulations. The correlation function is expected to have a small yet potentially measurable amplitude that is consistent with current upper limits. Furthermore, the signature of this effect is distinctive because the nonzero correlation function extends over the photon mean free path, which is larger than the expected scale of large-scale structure. Observations or upper limits on this effect could provide information about the source of the ionizing background at high redshifts and the nature of the Ly-alpha forest clouds.

  3. Coupled binary embedding for large-scale image retrieval.

    PubMed

    Zheng, Liang; Wang, Shengjin; Tian, Qi

    2014-08-01

    Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts. PMID:24951697

  4. 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.

  5. 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.

  6. Numerical prediction of blast-induced stress wave from large-scale underground explosion

    NASA Astrophysics Data System (ADS)

    Wu, Chengqing; Lu, Yong; Hao, Hong

    2004-01-01

    This paper presents a numerical model for predicting the dynamic response of rock mass subjected to large-scale underground explosion. The model is calibrated against data obtained from large-scale field tests. The Hugoniot equation of state for rock mass is adopted to calculate the pressure as a function of mass density. A piecewise linear Drucker-Prager strength criterion including the strain rate effect is employed to model the rock mass behaviour subjected to blast loading. A double scalar damage model accounting for both the compression and tension damage is introduced to simulate the damage zone around the charge chamber caused by blast loading. The model is incorporated into Autodyn3D through its user subroutines. The numerical model is then used to predict the dynamic response of rock mass, in terms of the peak particle velocity (PPV) and peak particle acceleration (PPA) attenuation laws, the damage zone, the particle velocity time histories and their frequency contents for large-scale underground explosion tests. The computed results are found in good agreement with the field measured data; hence, the proposed model is proven to be adequate for simulating the dynamic response of rock mass subjected to large-scale underground explosion. Extended numerical analyses indicate that, apart from the charge loading density, the stress wave intensity is also affected, but to a lesser extent, by the charge weight and the charge chamber geometry for large-scale underground explosions. Copyright

  7. Dissociable large-scale networks anchored in the right anterior insula subserve affective experience and attention1

    PubMed Central

    Touroutoglou, Alexandra; Hollenbeck, Mark; Dickerson, Bradford C.; Barrett, Lisa Feldman

    2012-01-01

    Meta-analytic summaries of neuroimaging studies point to at least two major functional-anatomic subdivisions within the anterior insula that contribute to the detection and processing of salient information: a dorsal region that is routinely active during attention tasks and a ventral region that is routinely active during affective experience. In two independent samples of cognitively normal human adults, we used intrinsic functional connectivity magnetic resonance imaging to demonstrate that the right dorsal and right ventral anterior insula are nodes in separable large-scale functional networks. Furthermore, stronger intrinsic connectivity within the right dorsal anterior insula network was associated with better performance on a task involving attention and processing speed whereas stronger connectivity within the right ventral anterior insula network was associated with more intense affective experience. These results support the hypothesis that the identification and manipulation of salient information is subserved by at least two brain networks anchored in the right anterior insula that exhibit distinct large-scale topography and dissociable behavioral correlates. PMID:22361166

  8. Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

    PubMed Central

    Hu, Ming; Qin, Zhaohui S.

    2009-01-01

    In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors. PMID:19214232

  9. Initial condition effects on large scale structure in numerical simulations of plane mixing layers

    NASA Astrophysics Data System (ADS)

    McMullan, W. A.; Garrett, S. J.

    2016-01-01

    In this paper, Large Eddy Simulations are performed on the spatially developing plane turbulent mixing layer. The simulated mixing layers originate from initially laminar conditions. The focus of this research is on the effect of the nature of the imposed fluctuations on the large-scale spanwise and streamwise structures in the flow. Two simulations are performed; one with low-level three-dimensional inflow fluctuations obtained from pseudo-random numbers, the other with physically correlated fluctuations of the same magnitude obtained from an inflow generation technique. Where white-noise fluctuations provide the inflow disturbances, no spatially stationary streamwise vortex structure is observed, and the large-scale spanwise turbulent vortical structures grow continuously and linearly. These structures are observed to have a three-dimensional internal geometry with branches and dislocations. Where physically correlated provide the inflow disturbances a "streaky" streamwise structure that is spatially stationary is observed, with the large-scale turbulent vortical structures growing with the square-root of time. These large-scale structures are quasi-two-dimensional, on top of which the secondary structure rides. The simulation results are discussed in the context of the varying interpretations of mixing layer growth that have been postulated. Recommendations are made concerning the data required from experiments in order to produce accurate numerical simulation recreations of real flows.

  10. 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

  11. Large-scale wind power farms as power plants

    NASA Astrophysics Data System (ADS)

    Gjengedal, Terje

    2005-07-01

    The integration of large-scale wind power into weak power systems raises several issues that must be clarified. Typically these include the practical connection to the network, integration with the network system, system stability, system operation, necessary installations and extensions of the network, etc. At the same time, careful attention must be paid to the functional requirements such wind farms should meet in order to enhance system responses. Different wind power technologies have different characteristics and control possibilities. In this article, three technologies have been studied with respect to their dynamic performance, and a transient stability study has been performed in order to illustrate the differences in the three technologies. The results clearly show that there are differences in behaviour and in control possibilities. Hence there are also differences in how well they can meet functional requirements. When discussing to what degree strict requirements should be imposed on wind power, it should be kept in mind that some requirements can be met with small or moderate costs, while others may be expensive or difficult to meet. Some requirements may also mean a reduction in generation and hence in revenues. Rather than imposing strict requirements on wind turbines as such, ancillary services should be met in the most suitable way. It is not obvious that the same requirements should apply to wind power in hydro power-dominated systems compared with, for instance, systems with a large share of nuclear or thermal power. It may well be cheaper to incorporate primary power control and system-stabilizing equipment in other power plants or grid points than in many small wind turbine generators. General conclusions cannot be made on this, but the issue should be the focal point of system operators everywhere. Copyright

  12. 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

  13. Unsaturated Hydraulic Conductivity for Evaporation in Large scale Heterogeneous Soils

    NASA Astrophysics Data System (ADS)

    Sun, D.; Zhu, J.

    2014-12-01

    In this study we aim to provide some practical guidelines of how the commonly used simple averaging schemes (arithmetic, geometric, or harmonic mean) perform in simulating large scale evaporation in a large scale heterogeneous landscape. Previous studies on hydraulic property upscaling focusing on steady state flux exchanges illustrated that an effective hydraulic property is usually more difficult to define for evaporation. This study focuses on upscaling hydraulic properties of large scale transient evaporation dynamics using the idea of the stream tube approach. Specifically, the two main objectives are: (1) if the three simple averaging schemes (i.e., arithmetic, geometric and harmonic means) of hydraulic parameters are appropriate in representing large scale evaporation processes, and (2) how the applicability of these simple averaging schemes depends on the time scale of evaporation processes in heterogeneous soils. Multiple realizations of local evaporation processes are carried out using HYDRUS-1D computational code (Simunek et al, 1998). The three averaging schemes of soil hydraulic parameters were used to simulate the cumulative flux exchange, which is then compared with the large scale average cumulative flux. The sensitivity of the relative errors to the time frame of evaporation processes is also discussed.

  14. 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.

  15. THE DETECTION OF THE LARGE-SCALE ALIGNMENT OF MASSIVE GALAXIES AT z {approx} 0.6

    SciTech Connect

    Li Cheng; Jing, Y. P.; Faltenbacher, A.; Wang Jie

    2013-06-10

    We report on the detection of the alignment between galaxies and large-scale structure at z {approx} 0.6 based on the CMASS galaxy sample from the Baryon Oscillation Spectroscopy Survey Data Release 9. We use two statistics to quantify the alignment signal: (1) the alignment two-point correlation function that probes the dependence of galaxy clustering at a given separation in redshift space on the projected angle ({theta}{sub p}) between the orientation of galaxies and the line connecting to other galaxies, and (2) the cos (2{theta})-statistic that estimates the average of cos (2{theta}{sub p}) for all correlated pairs at a given separation s. We find a significant alignment signal out to about 70 h {sup -1} Mpc in both statistics. Applications of the same statistics to dark matter halos of mass above 10{sup 12} h {sup -1} M{sub Sun} in a large cosmological simulation show scale-dependent alignment signals similar to the observation, but with higher amplitudes at all scales probed. We show that this discrepancy may be partially explained by a misalignment angle between central galaxies and their host halos, though detailed modeling is needed in order to better understand the link between the orientations of galaxies and host halos. In addition, we find systematic trends of the alignment statistics with the stellar mass of the CMASS galaxies, in the sense that more massive galaxies are more strongly aligned with the large-scale structure.

  16. 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

  17. The large scale microelectronics Computer-Aided Design and Test (CADAT) system

    NASA Technical Reports Server (NTRS)

    Gould, J. M.

    1978-01-01

    The CADAT system consists of a number of computer programs written in FORTRAN that provide the capability to simulate, lay out, analyze, and create the artwork for large scale microelectronics. The function of each software component of the system is described with references to specific documentation for each software component.

  18. On Applications of Rasch Models in International Comparative Large-Scale Assessments: A Historical Review

    ERIC Educational Resources Information Center

    Wendt, Heike; Bos, Wilfried; Goy, Martin

    2011-01-01

    Several current international comparative large-scale assessments of educational achievement (ICLSA) make use of "Rasch models", to address functions essential for valid cross-cultural comparisons. From a historical perspective, ICLSA and Georg Rasch's "models for measurement" emerged at about the same time, half a century ago. However, the…

  19. Density Functional Model for Nondynamic and Strong Correlation.

    PubMed

    Kong, Jing; Proynov, Emil

    2016-01-12

    A single-term density functional model for the left-right nondynamic/strong electron correlation is presented based on single-determinant Kohn-Sham density functional theory. It is derived from modeling the adiabatic connection for kinetic correlation energy based on physical arguments, with the correlation potential energy based on the Becke'13 model ( Becke, A.D. J. Chem. Phys . 2013 , 138 , 074109 ). This functional satisfies some known scaling relationships for correlation functionals. The fractional spin error is further reduced substantially with a new density-functional correction. Preliminary tests with self-consistent-field implementation show that the model, with only three empirical parameters, recovers the majority of left-right nondynamic/strong correlation upon bond dissociation and performs reasonably well for atomization energies and singlet-triplet energy splittings. This study also demonstrates the feasibility of developing DFT functionals for nondynamic and strong correlation within the single-determinant KS scheme. PMID:26636190

  20. Toward Improved Support for Loosely Coupled Large Scale Simulation Workflows

    SciTech Connect

    Boehm, Swen; Elwasif, Wael R; Naughton, III, Thomas J; Vallee, Geoffroy R

    2014-01-01

    High-performance computing (HPC) workloads are increasingly leveraging loosely coupled large scale simula- tions. Unfortunately, most large-scale HPC platforms, including Cray/ALPS environments, are designed for the execution of long-running jobs based on coarse-grained launch capabilities (e.g., one MPI rank per core on all allocated compute nodes). This assumption limits capability-class workload campaigns that require large numbers of discrete or loosely coupled simulations, and where time-to-solution is an untenable pacing issue. This paper describes the challenges related to the support of fine-grained launch capabilities that are necessary for the execution of loosely coupled large scale simulations on Cray/ALPS platforms. More precisely, we present the details of an enhanced runtime system to support this use case, and report on initial results from early testing on systems at Oak Ridge National Laboratory.

  1. Acoustic Studies of the Large Scale Ocean Circulation

    NASA Technical Reports Server (NTRS)

    Menemenlis, Dimitris

    1999-01-01

    Detailed knowledge of ocean circulation and its transport properties is prerequisite to an understanding of the earth's climate and of important biological and chemical cycles. Results from two recent experiments, THETIS-2 in the Western Mediterranean and ATOC in the North Pacific, illustrate the use of ocean acoustic tomography for studies of the large scale circulation. The attraction of acoustic tomography is its ability to sample and average the large-scale oceanic thermal structure, synoptically, along several sections, and at regular intervals. In both studies, the acoustic data are compared to, and then combined with, general circulation models, meteorological analyses, satellite altimetry, and direct measurements from ships. Both studies provide complete regional descriptions of the time-evolving, three-dimensional, large scale circulation, albeit with large uncertainties. The studies raise serious issues about existing ocean observing capability and provide guidelines for future efforts.

  2. Coupling between convection and large-scale circulation

    NASA Astrophysics Data System (ADS)

    Becker, T.; Stevens, B. B.; Hohenegger, C.

    2014-12-01

    The ultimate drivers of convection - radiation, tropospheric humidity and surface fluxes - are altered both by the large-scale circulation and by convection itself. A quantity to which all drivers of convection contribute is moist static energy, or gross moist stability, respectively. Therefore, a variance analysis of the moist static energy budget in radiative-convective equilibrium helps understanding the interaction of precipitating convection and the large-scale environment. In addition, this method provides insights concerning the impact of convective aggregation on this coupling. As a starting point, the interaction is analyzed with a general circulation model, but a model intercomparison study using a hierarchy of models is planned. Effective coupling parameters will be derived from cloud resolving models and these will in turn be related to assumptions used to parameterize convection in large-scale models.

  3. Large-scale current systems in the dayside Venus ionosphere

    NASA Technical Reports Server (NTRS)

    Luhmann, J. G.; Elphic, R. C.; Brace, L. H.

    1981-01-01

    The occasional observation of large-scale horizontal magnetic fields within the dayside ionosphere of Venus by the flux gate magnetometer on the Pioneer Venus orbiter suggests the presence of large-scale current systems. Using the measured altitude profiles of the magnetic field and the electron density and temperature, together with the previously reported neutral atmosphere density and composition, it is found that the local ionosphere can be described at these times by a simple steady state model which treats the unobserved quantities, such as the electric field, as parameters. When the model is appropriate, the altitude profiles of the ion and electron velocities and the currents along the satellite trajectory can be inferred. These results elucidate the configurations and sources of the ionospheric current systems which produce the observed large-scale magnetic fields, and in particular illustrate the effect of ion-neutral coupling in the determination of the current system at low altitudes.

  4. Magnetic Helicity and Large Scale Magnetic Fields: A Primer

    NASA Astrophysics Data System (ADS)

    Blackman, Eric G.

    2015-05-01

    Magnetic fields of laboratory, planetary, stellar, and galactic plasmas commonly exhibit significant order on large temporal or spatial scales compared to the otherwise random motions within the hosting system. Such ordered fields can be measured in the case of planets, stars, and galaxies, or inferred indirectly by the action of their dynamical influence, such as jets. Whether large scale fields are amplified in situ or a remnant from previous stages of an object's history is often debated for objects without a definitive magnetic activity cycle. Magnetic helicity, a measure of twist and linkage of magnetic field lines, is a unifying tool for understanding large scale field evolution for both mechanisms of origin. Its importance stems from its two basic properties: (1) magnetic helicity is typically better conserved than magnetic energy; and (2) the magnetic energy associated with a fixed amount of magnetic helicity is minimized when the system relaxes this helical structure to the largest scale available. Here I discuss how magnetic helicity has come to help us understand the saturation of and sustenance of large scale dynamos, the need for either local or global helicity fluxes to avoid dynamo quenching, and the associated observational consequences. I also discuss how magnetic helicity acts as a hindrance to turbulent diffusion of large scale fields, and thus a helper for fossil remnant large scale field origin models in some contexts. I briefly discuss the connection between large scale fields and accretion disk theory as well. The goal here is to provide a conceptual primer to help the reader efficiently penetrate the literature.

  5. Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

    NASA Astrophysics Data System (ADS)

    Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

    2014-05-01

    dates involving observations from multiple sites (rain gauges). The approach combines the POT (Peaks Over Threshold) with 'declustering' of the data to approximate independence based on the autocorrelation structure of each rainfall series. The cross correlation among sites is considered also to develop the event's criteria yielding a rational choice of the extreme dates given the 'spotty' nature of the intense convection. Based on the identified dates, we are developing a supporting tool for forecasting extreme rainfall based on the corresponding large-scale meteorological patterns (LSMPs). The LSMPs methodology focuses on the larger-scale patterns that the model are better able to forecast, as those larger-scale patterns create the conditions fostering the local EWE. Bootstrap resampling method is applied to highlight the key features that statistically significant with the extreme events. Grotjahn, R., and G. Faure. 2008: Composite Predictor Maps of Extraordinary Weather Events in the Sacramento California Region. Weather and Forecasting. 23: 313-335.

  6. Calibration of hydraulic parameters for large-scale vertical flow constructed wetlands

    NASA Astrophysics Data System (ADS)

    Maier, Uli; DeBiase, Cecilia; Baeder-Bederski, Oliver; Bayer, Peter

    2009-05-01

    SummaryConstructed wetlands for water cleanup have been in use for several years and are promising for cost-efficient remediation of large scale contamination. Within this study, flow conditions in layered vertical soil filters used for remediation of contaminated groundwater were investigated in detail by special discharge experiments and an attuned modeling study. Unsaturated water flow was measured in two vertical flow constructed wetlands for contaminated groundwater treatment at a site in eastern Germany. Numerical simulations were performed using the code MIN3P, in which variably saturated flow is based on the Richards equation. Soil hydraulic functions based on Van Genuchten coefficients and preferential flow characteristics were obtained by calibrating the model to measured data using self-adaptive evolution strategies with covariance matrix adaptation (CMA-ES). The presented inverse modeling procedure not only provides best fit parameterizations for separate and joint model objectives, but also utilizes the information from multiple restarts of the optimization algorithm to determine suitable parameter ranges and reveal potential correlations. The sequential automatic calibration is both straightforward and efficient even if different complex objective functions are considered.

  7. Corridors Increase Plant Species Richness at Large Scales

    SciTech Connect

    Damschen, Ellen I.; Haddad, Nick M.; Orrock,John L.; Tewksbury, Joshua J.; Levey, Douglas J.

    2006-09-01

    Habitat fragmentation is one of the largest threats to biodiversity. Landscape corridors, which are hypothesized to reduce the negative consequences of fragmentation, have become common features of ecological management plans worldwide. Despite their popularity, there is little evidence documenting the effectiveness of corridors in preserving biodiversity at large scales. Using a large-scale replicated experiment, we showed that habitat patches connected by corridors retain more native plant species than do isolated patches, that this difference increases over time, and that corridors do not promote invasion by exotic species. Our results support the use of corridors in biodiversity conservation.

  8. Large-scale ER-damper for seismic protection

    NASA Astrophysics Data System (ADS)

    McMahon, Scott; Makris, Nicos

    1997-05-01

    A large scale electrorheological (ER) damper has been designed, constructed, and tested. The damper consists of a main cylinder and a piston rod that pushes an ER-fluid through a number of stationary annular ducts. This damper is a scaled- up version of a prototype ER-damper which has been developed and extensively studied in the past. In this paper, results from comprehensive testing of the large-scale damper are presented, and the proposed theory developed for predicting the damper response is validated.

  9. Survey of decentralized control methods. [for large scale dynamic systems

    NASA Technical Reports Server (NTRS)

    Athans, M.

    1975-01-01

    An overview is presented of the types of problems that are being considered by control theorists in the area of dynamic large scale systems with emphasis on decentralized control strategies. Approaches that deal directly with decentralized decision making for large scale systems are discussed. It is shown that future advances in decentralized system theory are intimately connected with advances in the stochastic control problem with nonclassical information pattern. The basic assumptions and mathematical tools associated with the latter are summarized, and recommendations concerning future research are presented.

  10. Clearing and Labeling Techniques for Large-Scale Biological Tissues

    PubMed Central

    Seo, Jinyoung; Choe, Minjin; Kim, Sung-Yon

    2016-01-01

    Clearing and labeling techniques for large-scale biological tissues enable simultaneous extraction of molecular and structural information with minimal disassembly of the sample, facilitating the integration of molecular, cellular and systems biology across different scales. Recent years have witnessed an explosive increase in the number of such methods and their applications, reflecting heightened interest in organ-wide clearing and labeling across many fields of biology and medicine. In this review, we provide an overview and comparison of existing clearing and labeling techniques and discuss challenges and opportunities in the investigations of large-scale biological systems. PMID:27239813

  11. Large-scale liquid scintillation detectors for solar neutrinos

    NASA Astrophysics Data System (ADS)

    Benziger, Jay B.; Calaprice, Frank P.

    2016-04-01

    Large-scale liquid scintillation detectors are capable of providing spectral yields of the low energy solar neutrinos. These detectors require > 100 tons of liquid scintillator with high optical and radiopurity. In this paper requirements for low-energy neutrino detection by liquid scintillation are specified and the procedures to achieve low backgrounds in large-scale liquid scintillation detectors for solar neutrinos are reviewed. The designs, operations and achievements of Borexino, KamLAND and SNO+ in measuring the low-energy solar neutrino fluxes are reviewed.

  12. Contribution of peculiar shear motions to large-scale structure

    NASA Technical Reports Server (NTRS)

    Mueler, Hans-Reinhard; Treumann, Rudolf A.

    1994-01-01

    Self-gravitating shear flow instability simulations in a cold dark matter-dominated expanding Einstein-de Sitter universe have been performed. When the shear flow speed exceeds a certain threshold, self-gravitating Kelvin-Helmoholtz instability occurs, forming density voids and excesses along the shear flow layer which serve as seeds for large-scale structure formation. A possible mechanism for generating shear peculiar motions are velocity fluctuations induced by the density perturbations of the postinflation era. In this scenario, short scales grow earlier than large scales. A model of this kind may contribute to the cellular structure of the luminous mass distribution in the universe.

  13. Clearing and Labeling Techniques for Large-Scale Biological Tissues.

    PubMed

    Seo, Jinyoung; Choe, Minjin; Kim, Sung-Yon

    2016-06-30

    Clearing and labeling techniques for large-scale biological tissues enable simultaneous extraction of molecular and structural information with minimal disassembly of the sample, facilitating the integration of molecular, cellular and systems biology across different scales. Recent years have witnessed an explosive increase in the number of such methods and their applications, reflecting heightened interest in organ-wide clearing and labeling across many fields of biology and medicine. In this review, we provide an overview and comparison of existing clearing and labeling techniques and discuss challenges and opportunities in the investigations of large-scale biological systems. PMID:27239813

  14. Total energy equation leading to exchange-correlation functional

    NASA Astrophysics Data System (ADS)

    Liu, Feng; Wang, Tzu-Chiang

    2015-05-01

    By solving the total energy equation, we obtain the formula of exchange-correlation functional for the first time. This functional is usually determined by fitting experimental data or the numerical results of models. In the uniform electron gas limit, our exchange-correlation functional can exactly reproduce the results of Perdew-Zunger parameterization from the jellium model. By making use of a particular solution, our exchange-correlation functional could take into account the case of non-uniform electron density, and its validity can be confirmed through comparisons of the band structure, equilibrium lattice constant, and bulk modulus of aluminum and silicon. The absence of mechanical prescriptions for the systematic improvement of exchange-correlation functional hinders further development of density-functional theory (DFT), and the formula of exchange-correlation functional given in this study might provide a new perspective to help DFT out of this awkward situation.

  15. Ecosystem resilience despite large-scale altered hydroclimatic conditions.

    PubMed

    Ponce Campos, Guillermo E; Moran, M Susan; Huete, Alfredo; Zhang, Yongguang; Bresloff, Cynthia; Huxman, Travis E; Eamus, Derek; Bosch, David D; Buda, Anthony R; Gunter, Stacey A; Scalley, Tamara Heartsill; Kitchen, Stanley G; McClaran, Mitchel P; McNab, W Henry; Montoya, Diane S; Morgan, Jack A; Peters, Debra P C; Sadler, E John; Seyfried, Mark S; Starks, Patrick J

    2013-02-21

    Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought--that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands. PMID:23334410

  16. Large Scale Electronic Structure Calculations using Quantum Chemistry Methods

    NASA Astrophysics Data System (ADS)

    Scuseria, Gustavo E.

    1998-03-01

    This talk will address our recent efforts in developing fast, linear scaling electronic structure methods for large scale applications. Of special importance is our fast multipole method( M. C. Strain, G. E. Scuseria, and M. J. Frisch, Science 271), 51 (1996). (FMM) for achieving linear scaling for the quantum Coulomb problem (GvFMM), the traditional bottleneck in quantum chemistry calculations based on Gaussian orbitals. Fast quadratures(R. E. Stratmann, G. E. Scuseria, and M. J. Frisch, Chem. Phys. Lett. 257), 213 (1996). combined with methods that avoid the Hamiltonian diagonalization( J. M. Millam and G. E. Scuseria, J. Chem. Phys. 106), 5569 (1997) have resulted in density functional theory (DFT) programs that can be applied to systems containing many hundreds of atoms and ---depending on computational resources or level of theory-- to many thousands of atoms.( A. D. Daniels, J. M. Millam and G. E. Scuseria, J. Chem. Phys. 107), 425 (1997). Three solutions for the diagonalization bottleneck will be analyzed and compared: a conjugate gradient density matrix search (CGDMS), a Hamiltonian polynomial expansion of the density matrix, and a pseudo-diagonalization method. Besides DFT, our near-field exchange method( J. C. Burant, G. E. Scuseria, and M. J. Frisch, J. Chem. Phys. 105), 8969 (1996). for linear scaling Hartree-Fock calculations will be discussed. Based on these improved capabilities, we have also developed programs to obtain vibrational frequencies (via analytic energy second derivatives) and excitation energies (through time-dependent DFT) of large molecules like porphyn or C_70. Our GvFMM has been extended to periodic systems( K. N. Kudin and G. E. Scuseria, Chem. Phys. Lett., in press.) and progress towards a Gaussian-based DFT and HF program for polymers and solids will be reported. Last, we will discuss our progress on a Laplace-transformed \\cal O(N^2) second-order pertubation theory (MP2) method.

  17. Large-Scale Identification of Virulence Genes from Streptococcus pneumoniae

    PubMed Central

    Polissi, Alessandra; Pontiggia, Andrea; Feger, Georg; Altieri, Mario; Mottl, Harald; Ferrari, Livia; Simon, Daniel

    1998-01-01

    Streptococcus pneumoniae is the major cause of bacterial pneumonia, and it is also responsible for otitis media and meningitis in children. Apart from the capsule, the virulence factors of this pathogen are not completely understood. Recent technical advances in the field of bacterial pathogenesis (in vivo expression technology and signature-tagged mutagenesis [STM]) have allowed a large-scale identification of virulence genes. We have adapted to S. pneumoniae the STM technique, originally used for the discovery of Salmonella genes involved in pathogenicity. A library of pneumococcal chromosomal fragments (400 to 600 bp) was constructed in a suicide plasmid vector carrying unique DNA sequence tags and a chloramphenicol resistance marker. The recent clinical isolate G54 was transformed with this library. Chloramphenicol-resistant mutants were obtained by homologous recombination, resulting in genes inactivated by insertion of the suicide vector carrying a unique tag. In a mouse pneumonia model, 1.250 candidate clones were screened; 200 of these were not recovered from the lungs were therefore considered virulence-attenuated mutants. The regions flanking the chloramphenicol gene of the attenuated mutants were amplified by inverse PCR and sequenced. The sequence analysis showed that the 200 mutants had insertions in 126 different genes that could be grouped in six classes: (i) known pneumococcal virulence genes; (ii) genes involved in metabolic pathways; (iii) genes encoding proteases; (iv) genes coding for ATP binding cassette transporters; (v) genes encoding proteins involved in DNA recombination/repair; and (vi) DNA sequences that showed similarity to hypothetical genes with unknown function. To evaluate the virulence attenuation for each mutant, all 126 clones were individually analyzed in a mouse septicemia model. Not all mutants selected in the pneumonia model were confirmed in septicemia, thus indicating the existence of virulence factors specific for pneumonia

  18. From Systematic Errors to Cosmology Using Large-Scale Structure

    NASA Astrophysics Data System (ADS)

    Hunterer, Dragan

    We propose to carry out a two-pronged program to significantly improve links between galaxy surveys and constraints on primordial cosmology and fundamental physics. We will first develop the methodology to self-calibrate the survey, that is, determine the large-angle calibration systematics internally from the survey. We will use this information to correct biases that propagate from the largest to smal