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Sample records for large-scale correlation function

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

    SciTech Connect

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

    2014-08-01

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

  2. Modelling the large-scale redshift-space 3-point correlation function of galaxies

    NASA Astrophysics Data System (ADS)

    Slepian, Zachary; Eisenstein, Daniel J.

    2017-08-01

    We present a configuration-space model of the large-scale galaxy 3-point correlation function (3PCF) based on leading-order perturbation theory and including redshift-space distortions (RSD). This model should be useful in extracting distance-scale information from the 3PCF via the baryon acoustic oscillation method. We include the first redshift-space treatment of biasing by the baryon-dark matter relative velocity. Overall, on large scales the effect of RSD is primarily a renormalization of the 3PCF that is roughly independent of both physical scale and triangle opening angle; for our adopted Ωm and bias values, the rescaling is a factor of ∼1.8. We also present an efficient scheme for computing 3PCF predictions from our model, important for allowing fast exploration of the space of cosmological parameters in future analyses.

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

    PubMed

    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

  5. 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.

  6. The large-scale three-point correlation function of the SDSS BOSS DR12 CMASS galaxies

    NASA Astrophysics Data System (ADS)

    Slepian, Zachary; Eisenstein, Daniel J.; Beutler, Florian; Chuang, Chia-Hsun; Cuesta, Antonio J.; Ge, Jian; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; McBride, Cameron K.; Nichol, Robert C.; Percival, Will J.; Rodríguez-Torres, Sergio; Ross, Ashley J.; Scoccimarro, Román; Seo, Hee-Jong; Tinker, Jeremy; Tojeiro, Rita; Vargas-Magaña, Mariana

    2017-06-01

    We report a measurement of the large-scale three-point correlation function of galaxies using the largest data set for this purpose to date, 777 202 luminous red galaxies in the Sloan Digital Sky Survey Baryon Acoustic Oscillation Spectroscopic Survey (SDSS BOSS) DR12 CMASS sample. This work exploits the novel algorithm of Slepian & Eisenstein to compute the multipole moments of the 3PCF in O(N^2) time, with N the number of galaxies. Leading-order perturbation theory models the data well in a compressed basis where one triangle side is integrated out. We also present an accurate and computationally efficient means of estimating the covariance matrix. With these techniques, the redshift-space linear and non-linear bias are measured, with 2.6 per cent precision on the former if σ8 is fixed. The data also indicate a 2.8σ preference for the BAO, confirming the presence of BAO in the three-point function.

  7. The large-scale functional connectivity correlates of consciousness and arousal during the healthy and pathological human sleep cycle.

    PubMed

    Tagliazucchi, Enzo; van Someren, Eus J W

    2017-06-12

    Advances in neuroimaging have greatly improved our understanding of human sleep from a systems neuroscience perspective. However, cognition and awareness are reduced during sleep, hindering the applicability of standard task-based paradigms. Methods recently developed to study spontaneous brain activity fluctuations have proven useful to overcome this limitation. In this review, we focus on the concept of functional connectivity (FC, i.e. statistical covariance between brain activity signals) and its application to functional magnetic resonance imaging (fMRI) data acquired during sleep. We discuss how FC analyses of endogenous brain activity during sleep have contributed towards revealing the large-scale neural networks associated with arousal and conscious awareness. We argue that the neuroimaging of deep sleep can be used to evaluate the predictions of theories of consciousness; at the same time, we highlight some apparent limitations of deep sleep as an experimental model of unconsciousness. In resting state fMRI experiments, the onset of sleep can be regarded as the object of interest but also as an undesirable confound. We discuss a series of articles contributing towards the disambiguation of wakefulness from sleep on the basis of fMRI-derived dynamic FC, and then outline a plan for the development of more general and data-driven sleep classifiers. To complement our review of studies investigating the brain systems of arousal and consciousness during healthy sleep, we then turn to pathological and abnormal sleep patterns. We review the current literature on sleep deprivation studies and sleep disorders, adopting the critical stance that lack of independent vigilance monitoring during fMRI experiments is liable for false positives related to atypical sleep propensity in clinical and sleep-deprived populations. Finally, we discuss multimodal neuroimaging as a promising future direction to achieve a better understanding of the large-scale FC of the brain during

  8. 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.

  9. Detection of Baryon Acoustic Oscillation features in the large-scale 3-point correlation function of SDSS BOSS DR12 CMASS galaxies

    DOE PAGES

    Slepian, Zachary; Slosar, Anze; Eisenstein, Daniel J.; ...

    2017-03-01

    We present the large-scale 3-point correlation function (3PCF) of the SDSS DR12 CMASS sample of 777,202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of Baryon Acoustic Oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z=0.57 to 1.7% precision (statistical plus systematic). We find DV = 2024 ± 29Mpc (stat) ± 20Mpc(sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from the 2-pointmore » correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10%; reconstruction appears to lower the independence of the distance measurements. In conclusion, fitting a model including tidal tensor bias yields a moderate significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.« less

  10. Detection of baryon acoustic oscillation features in the large-scale three-point correlation function of SDSS BOSS DR12 CMASS galaxies

    NASA Astrophysics Data System (ADS)

    Slepian, Zachary; Eisenstein, Daniel J.; Brownstein, Joel R.; Chuang, Chia-Hsun; Gil-Marín, Héctor; Ho, Shirley; Kitaura, Francisco-Shu; Percival, Will J.; Ross, Ashley J.; Rossi, Graziano; Seo, Hee-Jong; Slosar, Anže; Vargas-Magaña, Mariana

    2017-08-01

    We present the large-scale three-point correlation function (3PCF) of the Sloan Digital Sky Survey DR12 Constant stellar Mass (CMASS) sample of 777 202 Luminous Red Galaxies, the largest-ever sample used for a 3PCF or bispectrum measurement. We make the first high-significance (4.5σ) detection of baryon acoustic oscillations (BAO) in the 3PCF. Using these acoustic features in the 3PCF as a standard ruler, we measure the distance to z = 0.57 to 1.7 per cent precision (statistical plus systematic). We find DV = 2024 ± 29 Mpc (stat) ± 20 Mpc (sys) for our fiducial cosmology (consistent with Planck 2015) and bias model. This measurement extends the use of the BAO technique from the two-point correlation function (2PCF) and power spectrum to the 3PCF and opens an avenue for deriving additional cosmological distance information from future large-scale structure redshift surveys such as DESI. Our measured distance scale from the 3PCF is fairly independent from that derived from the pre-reconstruction 2PCF and is equivalent to increasing the length of BOSS by roughly 10 per cent; reconstruction appears to lower the independence of the distance measurements. Fitting a model including tidal tensor bias yields a moderate-significance (2.6σ) detection of this bias with a value in agreement with the prediction from local Lagrangian biasing.

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

    NASA Astrophysics Data System (ADS)

    Livadiotis, George; McComas, David J.

    2014-05-01

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

  12. Exploiting large-scale correlations to detect continuous gravitational waves.

    PubMed

    Pletsch, Holger J; Allen, Bruce

    2009-10-30

    Fully coherent searches (over realistic ranges of parameter space and year-long observation times) for unknown sources of continuous gravitational waves are computationally prohibitive. Less expensive hierarchical searches divide the data into shorter segments which are analyzed coherently, then detection statistics from different segments are combined incoherently. The novel method presented here solves the long-standing problem of how best to do the incoherent combination. The optimal solution exploits large-scale parameter-space correlations in the coherent detection statistic. Application to simulated data shows dramatic sensitivity improvements compared with previously available (ad hoc) methods, increasing the spatial volume probed by more than 2 orders of magnitude at lower computational cost.

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

    SciTech Connect

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

    2016-03-15

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

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

    DOE PAGES

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

    2016-03-15

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-01-01

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

  17. 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].

  18. 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.

  19. 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

  20. 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.

  1. Large scale cross-correlations in Internet traffic

    NASA Astrophysics Data System (ADS)

    Barthélemy, Marc; Gondran, Bernard; Guichard, Eric

    2002-11-01

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

  2. Large scale cross-correlations in Internet traffic.

    PubMed

    Barthélemy, Marc; Gondran, Bernard; Guichard, Eric

    2002-11-01

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

  3. 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. Copyright © 2012 Elsevier Inc. All rights reserved.

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

    PubMed

    Do, Thanh-Toan; Cheung, Ngai-Man

    2017-03-23

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

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

    SciTech Connect

    Wolstenhulme, Richard; Bonvin, Camille; Obreschkow, Danail

    2015-05-10

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

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

    NASA Technical Reports Server (NTRS)

    Frieman, Joshua A.; Gaztanaga, Enrique

    1994-01-01

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

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Frieman, Joshua A.; Gaztanaga, Enrique

    1994-01-01

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

  9. 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.

  10. 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.

  11. 3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation

    NASA Astrophysics Data System (ADS)

    Chen, Z.; Meng, X.; Guo, L.; Liu, G.

    2011-12-01

    In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and

  12. 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.

  13. Large scale production of short functionalized carbon nanotubes

    NASA Astrophysics Data System (ADS)

    Kónya, Z.; Vesselenyi, I.; Niesz, K.; Kukovecz, A.; Demortier, A.; Fonseca, A.; Delhalle, J.; Mekhalif, Z.; Nagy, J. B.; Koós, A. A.; Osváth, Z.; Kocsonya, A.; Biró, L. P.; Kiricsi, I.

    2002-07-01

    A simple mechano-chemical modification of multiwall carbon nanotubes is described. The use of ball-milling in specific atmosphere allows us to introduce functional groups like thiol, amine, amide, carbonyl, chlorine, etc. onto carbon nanotubes. The resulted functional groups are characterized using infrared spectroscopy and X-ray photoelectron spectroscopy.

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Brown, Shea; Farnsworth, Damon; Rudnick, Lawrence

    2010-02-01

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

  16. Large-scale chemical dissection of mitochondrial function.

    PubMed

    Wagner, Bridget K; Kitami, Toshimori; Gilbert, Tamara J; Peck, David; Ramanathan, Arvind; Schreiber, Stuart L; Golub, Todd R; Mootha, Vamsi K

    2008-03-01

    Mitochondrial oxidative phosphorylation (OXPHOS) is under the control of both mitochondrial (mtDNA) and nuclear genomes and is central to energy homeostasis. To investigate how its function and regulation are integrated within cells, we systematically combined four cell-based assays of OXPHOS physiology with multiplexed measurements of nuclear and mtDNA gene expression across 2,490 small-molecule perturbations in cultured muscle. Mining the resulting compendium revealed, first, that protein synthesis inhibitors can decouple coordination of nuclear and mtDNA transcription; second, that a subset of HMG-CoA reductase inhibitors, combined with propranolol, can cause mitochondrial toxicity, yielding potential clues about the etiology of statin myopathy; and, third, that structurally diverse microtubule inhibitors stimulate OXPHOS transcription while suppressing reactive oxygen species, via a transcriptional mechanism involving PGC-1alpha and ERRalpha, and thus may be useful in treating age-associated degenerative disorders. Our screening compendium can be used as a discovery tool both for understanding mitochondrial biology and toxicity and for identifying novel therapeutics.

  17. 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. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

  18. 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.

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

    PubMed

    Boughn, Stephen; Crittenden, Robert

    2004-01-01

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

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

    SciTech Connect

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

    2008-08-15

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

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

    PubMed

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

    2011-04-06

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

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

    PubMed

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

    2011-10-01

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

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

    SciTech Connect

    Hero, Alfred O.; Rajaratnam, Bala

    2015-12-09

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

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

    DOE PAGES

    Hero, Alfred O.; Rajaratnam, Bala

    2015-12-09

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

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

    PubMed

    Hero, Alfred O; Rajaratnam, Bala

    2016-01-01

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

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

    PubMed Central

    Hero, Alfred O.; Rajaratnam, Bala

    2015-01-01

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

  7. Large-scale changes in global wetlandscape function - do we know them?

    NASA Astrophysics Data System (ADS)

    Thorslund, J.; Jarsjo, J.; Destouni, G.

    2016-12-01

    The global ecosystem services provided to humans by wetlands have been valued among the top three biomes in the world, for instance exceeding the total value of terrestrial forests and coral reefs. Various aspects of global change may however affect wetland functionality, and thereby also the associated services of wetland ecosystems and their economic values, including changes in climate, water use, land use, demographic influences, and other global change drivers. Quantification and projection of such global services thus require corresponding large-scale understanding of the functionality of wetlandscapes (landscape-catchment systems with multiple wetlands) and its possible alteration under global change. A key question for global change research is if the large-scale impacts on wetlandscapes and their ecosystem services and associated values are assessed and evaluated at relevant scales. We here analyze long-term hydroclimatic data, expert judgments for 21 wetlandscapes across the world, and 21,433 wetland-related scientific articles to investigate if and how ongoing research actually addresses large-scale dynamics. From this analysis, hydroclimatic change emerges as a key change driver and coastal protection emerges as a key function that both remain largely uninvestigated in relation to such large-scale wetlandscape aspects. Overall, the present results identify essential research gaps for a range of water-related drivers of global change and their relations to the large-scale function and service potential of wetlandscapes.

  8. 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.

  9. Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

    PubMed

    Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura Km; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido Kw; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

    2016-11-01

    Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that

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

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

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

    SciTech Connect

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

    2005-03-15

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

  12. 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.

  13. 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…

  14. 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…

  15. 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…

  16. 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…

  17. GENASIS Basics: Object-oriented utilitarian functionality for large-scale physics simulations (Version 2)

    NASA Astrophysics Data System (ADS)

    Cardall, Christian Y.; Budiardja, Reuben D.

    2017-05-01

    GenASiS Basics provides Fortran 2003 classes furnishing extensible object-oriented utilitarian functionality for large-scale physics simulations on distributed memory supercomputers. This functionality includes 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. This revision -Version 2 of Basics - makes mostly minor additions to functionality and includes some simplifying name changes.

  18. 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.

  19. Response function of the large-scale structure of the universe to the small scale inhomogeneities

    NASA Astrophysics Data System (ADS)

    Nishimichi, Takahiro; Bernardeau, Francis; Taruya, Atsushi

    2016-11-01

    In order to infer the impact of the small-scale physics to the large-scale properties of the universe, we use a series of cosmological N-body simulations of self-gravitating matter inhomogeneities to measure, for the first time, the response function of such a system defined as a functional derivative of the nonlinear power spectrum with respect to its linear counterpart. Its measured shape and amplitude are found to be in good agreement with perturbation theory predictions except for the coupling from small to large-scale perturbations. The latter is found to be significantly damped, following a Lorentzian form. These results shed light on validity regime of perturbation theory calculations giving a useful guideline for regularization of small scale effects in analytical modeling. Most importantly our result indicates that the statistical properties of the large-scale structure of the universe are remarkably insensitive to the details of the small-scale physics, astrophysical or gravitational, paving the way for the derivation of robust estimates of theoretical uncertainties on the determination of cosmological parameters from large-scale survey observations.

  20. 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.

  1. 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.

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

    PubMed Central

    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 (≈89%) of the original associations. PMID:14566057

  3. 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.

  4. 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.

  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.

  6. Correlations Between Large-scale Flow Structures and Acoustic Signatures in an Axisymmetric Jet

    NASA Astrophysics Data System (ADS)

    Magstadt, Andrew; Berry, Matthew; Berger, Zachary; Shea, Patrick; Glauser, Mark

    2014-11-01

    In a test campaign studying jet noise, simultaneous far-field acoustic measurements and near-field particle imaging velocimetry (PIV) data were sampled from a supersonic underexpanded axisymmetric jet operating at a Reynolds number of 1.3×106 . Using overlapping snapshots from three adjacent cameras, separate images of the velocity field were stitched together to form an uninterrupted window. Centered about the axis of the jet, the effective field of view spanned two jet diameters in the cross-stream direction (r) and seven diameters in the streamwise direction (z) . This area proved to be sufficiently large to capture important scales of supersonic flow relevant to noise generation. Specifically, Proper Orthogonal Decomposition (POD) has extracted particular energy modes thought to be associated with the large-scale instability wave, shock cells, and turbulent mixing characteristic of supersonic noise. As example, time-dependent modal correlations present evidence linking the existence of shock cells to screech tones. From the data gathered, these experimental and analytical techniques are believed to be valuable tools in isolating energy-based flow structures relevant to noise generation. The authors would like to thank Spectral Energies for their continued support of research at Syracuse University.

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

    PubMed

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

    2016-01-01

    To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. 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. 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. 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.

  8. 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

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

    PubMed

    Brown, Shoshana D; Babbitt, Patricia C

    2012-01-02

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

  10. 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.

  11. 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.

  12. 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%.

  13. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2012-07-31

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

  16. 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

  17. 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.

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

    PubMed

    Trinh, Hung-Cuong; Kwon, Yung-Keun

    2015-11-01

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

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

    PubMed

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

    2016-12-01

    Aberrant functional interactions between several large-scale networks, especially the central executive network (CEN), the default mode network (DMN) and the salience network (SN), have been postulated as core pathophysiologic features of schizophrenia; however, the attributing factors of which remain unclear. The study employed resting-state fMRI with 77 participants (42 patients and 35 controls). We performed dynamic functional connectivity (DFC) and functional connectivity (FC) analyses to explore the connectivity patterns of these networks. Furthermore, we performed a structural equation model (SEM) analysis to explore the possible role of the SN in modulating network interactions. The results were as follows: (1) The inter-network connectivity showed decreased connectivity strength and increased time-varying instability in schizophrenia; (2) The SN manifested schizophrenic intra-network dysfunctions in both the FC and DFC patterns; (3) The connectivity properties of the SN were effective in discriminating controls from patients; (4) In patients, the dynamic intra-SN connectivity negatively predicted the inter-network FC, and this effect was mediated by intra-SN connectivity strength. These findings suggest that schizophrenia show systematic deficits in temporal stability of large-scale network connectivity. Furthermore, aberrant network interactions in schizophrenia could be attributed to instable intra-SN connectivity and the dysfunction of the SN may be an intrinsic biomarker of the disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2009-04-01

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

  1. FLIGHT: database and tools for the integration and cross-correlation of large-scale RNAi phenotypic datasets

    PubMed Central

    Sims, David; Bursteinas, Borisas; Gao, Qiong; Zvelebil, Marketa; Baum, Buzz

    2006-01-01

    FLIGHT () is a new database designed to help researchers browse and cross-correlate data from large-scale RNAi studies. To date, the majority of these functional genomic screens have been carried out using Drosophila cell lines. These RNAi screens follow 100 years of classical Drosophila genetics, but have already revealed their potential by ascribing an impressive number of functions to known and novel genes. This has in turn given rise to a pressing need for tools to simplify the analysis of the large amount of phenotypic information generated. FLIGHT aims to do this by providing users with a gene-centric view of screen results and by making it possible to cluster phenotypic data to identify genes with related functions. Additionally, FLIGHT provides microarray expression data for many of the Drosophila cell lines commonly used in RNAi screens. This, together with information about cell lines, protocols and dsRNA primer sequences, is intended to help researchers design their own cell-based screens. Finally, although the current focus of FLIGHT is Drosophila, the database has been designed to facilitate the comparison of functional data across species and to help researchers working with other systems navigate their way through the fly genome. PMID:16381916

  2. Captured metagenomics: large-scale targeting of genes based on 'sequence capture' reveals functional diversity in soils.

    PubMed

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

    2015-12-01

    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. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  3. 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

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

    PubMed

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

    2016-01-01

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

  5. Large-scale network functional interactions during distraction and reappraisal in remitted bipolar and unipolar patients.

    PubMed

    Lois, Giannis; Gerchen, Martin F; Kirsch, Peter; Kanske, Philipp; Schönfelder, Sandra; Wessa, Michèle

    2017-09-27

    The human brain is organized into large-scale networks that dynamically interact with each other. Extensive evidence has shown characteristic changes in certain large-scale networks during transitions from internally directed to externally directed attention. The aim of the present study was to compare these context-dependent network interactions during emotion regulation and to examine potential alterations in remitted unipolar and bipolar disorder patients. We employed a multi-region generalized psychophysiological interactions analysis to quantify connectivity changes during distraction vs reappraisal pair-wise across 90 regions placed throughout the four networks of interest (default-mode, frontoparietal, salience, and dorsal attention networks). Using network contingency analysis and permutation testing, we estimated the likelihood that the number of significant condition-dependent connectivity changes in every pair of networks exceeds the number expected by chance. We first examined the pattern of functional connectivity in 42 healthy subjects (sample I) and then compared these connectivity patterns across healthy individuals (n=23) and remitted bipolar (n=21) and unipolar disorder patients (n=21) in an independent sample II. In sample I, distraction compared to reappraisal was characterized by reduced connectivity within the default-mode network and between the default-mode and two cognitive control networks and increased connectivity among the cognitive control networks. In sample II, both patient groups exhibited abnormally increased default-mode intra- and inter-network connectivity during distraction compared to reappraisal. The present study highlights the role of large-scale network interactions in emotion regulation and provides preliminary evidence of default-mode inter- and intra-network connectivity impairments in remitted bipolar and unipolar patients during emotion regulation. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

    PubMed Central

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

    2014-01-01

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

  7. 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

  8. 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.

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

    DOE PAGES

    Cardall, Christian Y.; Budiardja, Reuben D.

    2015-06-11

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

  10. 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.

  11. PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes

    PubMed Central

    Conde, Lucía; Vaquerizas, Juan M.; Dopazo, Hernán; Arbiza, Leonardo; Reumers, Joke; Rousseau, Frederic; Schymkowitz, Joost; Dopazo, Joaquín

    2006-01-01

    We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user's data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through and through . PMID:16845085

  12. Linkages between microbial functional potential and wastewater constituents in large-scale membrane bioreactors for municipal wastewater treatment.

    PubMed

    Sun, Yanmei; Shen, Yue-xiao; Liang, Peng; Zhou, Jizhong; Yang, Yunfeng; Huang, Xia

    2014-06-01

    Large-scale membrane bioreactors (MBRs) have been widely used for the municipal wastewater treatment, whose performance relies on microbial communities of activated sludge. Nevertheless, microbial functional structures in MBRs remain little understood. To gain insight into functional genes and their steering environmental factors, we adopted GeoChip, a high-throughput microarray-based tool, to examine microbial genes in four large-scale, in-operation MBRs located in Beijing, China. The results revealed substantial microbial gene heterogeneity (43.7-85.1% overlaps) among different MBRs. Mantel tests indicated that microbial nutrient cycling genes were significantly (P < 0.05) correlated to influent COD, [Formula: see text] -N, TP or sulfate, which signified the importance of microbial mediation of wastewater constituent removal. In addition, functional genes shared by all four MBRs contained a large number of genes involved in antibiotics resistance, metal resistance and organic remediation, suggesting that they were required for degradation or resistance to toxic compounds in wastewater. The linkages between microbial functional structures and environmental variables were also unveiled by the finding of hydraulic retention time, influent COD, [Formula: see text] -N, mixed liquid temperature and humic substances as major factors shaping microbial communities. Together, the results presented demonstrate the utility of GeoChip-based microarray approach in examining microbial communities of wastewater treatment plants and provide insights into the forces driving important processes of element cycling. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. 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.

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  17. A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

    PubMed Central

    Araya, Carlos L.; Fowler, Douglas M.; Chen, Wentao; Muniez, Ike; Kelly, Jeffery W.; Fields, Stanley

    2012-01-01

    The ability of a protein to carry out a given function results from fundamental physicochemical properties that include the protein’s structure, mechanism of action, and thermodynamic stability. Traditional approaches to study these properties have typically required the direct measurement of the property of interest, oftentimes a laborious undertaking. Although protein properties can be probed by mutagenesis, this approach has been limited by its low throughput. Recent technological developments have enabled the rapid quantification of a protein’s function, such as binding to a ligand, for numerous variants of that protein. Here, we measure the ability of 47,000 variants of a WW domain to bind to a peptide ligand and use these functional measurements to identify stabilizing mutations without directly assaying stability. Our approach is rooted in the well-established concept that protein function is closely related to stability. Protein function is generally reduced by destabilizing mutations, but this decrease can be rescued by stabilizing mutations. Based on this observation, we introduce partner potentiation, a metric that uses this rescue ability to identify stabilizing mutations, and identify 15 candidate stabilizing mutations in the WW domain. We tested six candidates by thermal denaturation and found two highly stabilizing mutations, one more stabilizing than any previously known mutation. Thus, physicochemical properties such as stability are latent within these large-scale protein functional data and can be revealed by systematic analysis. This approach should allow other protein properties to be discovered. PMID:23035249

  18. Large-scale sparse functional networks from resting state fMRI.

    PubMed

    Li, Hongming; Satterthwaite, Theodore D; Fan, Yong

    2017-08-01

    Delineation of large-scale functional networks (FNs) from resting state functional MRI data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific FNs that are comparable across subjects, existing brain decomposition techniques typically adopt heuristic strategies or assume a specific statistical distribution for the FNs across subjects, and therefore might yield biased results. Here we present a novel data-driven method for detecting subject specific FNs while establishing group level correspondence. Our method simultaneously computes subject specific FNs for a group of subjects regularized by group sparsity, to generate subject specific FNs that are spatially sparse and share common spatial patterns across subjects. Our method is built upon non-negative matrix decomposition techniques, enhanced by a data locality regularization term that makes the decomposition robust to imaging noise and improves spatial smoothness and functional coherences of the subject specific FNs. Our method also adopts automatic relevance determination techniques to eliminate redundant FNs in order to generate a compact set of informative sparse FNs. We have validated our method based on simulated, task fMRI, and resting state fMRI datasets. The experimental results have demonstrated our method could obtain subject specific, sparse, non-negative FNs with improved functional coherence, providing enhanced ability for characterizing the functional brain of individual subjects. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Cognitive Effort and Schizophrenia Modulate Large-Scale Functional Brain Connectivity

    PubMed Central

    Brandt, Christine Lycke; Kaufmann, Tobias; Agartz, Ingrid; Hugdahl, Kenneth; Jensen, Jimmy; Ueland, Torill; Haatveit, Beathe; Skatun, Kristina C.; Doan, Nhat Trung; Melle, Ingrid; Andreassen, Ole A.; Westlye, Lars T.

    2015-01-01

    Schizophrenia (SZ) is characterized by cognitive dysfunction and disorganized thought, in addition to hallucinations and delusions, and is regarded a disorder of brain connectivity. Recent efforts have been made to characterize the underlying brain network organization and interactions. However, to which degree connectivity alterations in SZ vary across different levels of cognitive effort is unknown. Utilizing independent component analysis (ICA) and methods for delineating functional connectivity measures from functional magnetic resonance imaging (fMRI) data, we investigated the effects of cognitive effort, SZ and their interactions on between-network functional connectivity during 2 levels of cognitive load in a large and well-characterized sample of SZ patients (n = 99) and healthy individuals (n = 143). Cognitive load influenced a majority of the functional connections, including but not limited to fronto-parietal and default-mode networks, reflecting both decreases and increases in between-network synchronization. Reduced connectivity in SZ was identified in 2 large-scale functional connections across load conditions, with a particular involvement of an insular network. The results document an important role of interactions between insular, default-mode, and visual networks in SZ pathophysiology. The interplay between brain networks was robustly modulated by cognitive effort, but the reduced functional connectivity in SZ, primarily related to an insular network, was independent of cognitive load, indicating a relatively general brain network-level dysfunction. PMID:25731885

  20. 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.

  1. 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.

  2. Large scale mapping of forests with a protection function against rockfall and avalanches

    NASA Astrophysics Data System (ADS)

    Toe, David; Berger, Fréderic

    2014-05-01

    On mountain slopes, forest can play an important role to protect human lives and facilities against natural hazards. Silvicultural strategies and interventions to maintain or improve protection forest structures are of first interest. Up to now no large scale mapping of forest with a protection function against rockfalls and snow avalanches exist in France. The objectives of the study is to develop decision support tools for rockfall protection forest management. Two Geographic Information System based models which automatically map forests with a protection function against rockfalls and snow avalanches have been developed. These devices have been used to map forest with protection function in the French Alps. The first model, RollFree, calculates the maximum rockfall run out zone using the energy line principle. Forest with protection function are mapped crossing data on rockfall hazard, the forest cover and the socio-economical issues of a county. The second model, AvaLine, mapped the maximum run out zones of snow avalanches. Forests located in a departure zone of an avalanche that endangered an issue are mapped as protection forests. Results showed that forests with a protection function against rockfall can represent up to 30 percents of the forest cover in a county. In addition, forests with a protection function against avalanches can represent up to 7 percents of the total forested area. The two models developed present the advantages of a fast computational time and need only few input parameters such as a DEM, a map of the issues and a map of the forest cover. However it remain difficult to estimate precisely the error on the area mapped as protection forest on the all county. A first campaign of validation was done in the Vercor Regional natural park for forest with a protection function against rockfall. The study show that the model can overestimate the protection forest mapping up to 12 percent. Up to now no similar study was done for protection

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

    NASA Astrophysics Data System (ADS)

    Kanungo, Bikash; Gavini, Vikram

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

  4. 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.

  5. New constraints on parametrised modified gravity from correlations of the CMB with large scale structure

    SciTech Connect

    Giannantonio, Tommaso; Martinelli, Matteo; Melchiorri, Alessandro; Silvestri, Alessandra E-mail: matteo.martinelli@roma1.infn.it E-mail: alessandro.melchiorri@roma1.infn.it

    2010-04-01

    We study the effects of modified theories of gravity on the cosmic microwave background (CMB) anisotropies power spectrum, and in particular on its large scales, where the integrated Sachs-Wolfe (ISW) effect is important. Starting with a general parametrisation, we then specialise to f(R) theories and theories with Yukawa-type interactions between dark matter particles. In these models, the evolution of the metric potentials is altered, and the contribution to the ISW effect can differ significantly from that in the standard model of cosmology. We proceed to compare these predictions with observational data for the CMB and the ISW, performing a full Monte Carlo Markov chain (MCMC) analysis. In the case of f(R) theories, the result is an upper limit on the lengthscale associated to the extra scalar degree of freedom characterising these theories. With the addition of data from the Hubble diagram of Type Ia supernovae, we obtain an upper limit on the lengthscale of the theory of B{sub 0} < 0.4, or correspondingly λ{sub 1} < 1900 Mpc/h at 95% c.l. improving previous CMB constraints. For Yukawa-type models we get a bound on the coupling 0.75 < β{sub 1} < 1.25 at the 95% c.l. We also discuss the implications of the assumed priors on the estimation of modified gravity parameters, showing that a marginally less conservative choice improves the f(R) constraints to λ{sub 1} < 1400 Mpc/h, corresponding to B{sub 0} < 0.2 at 95% c.l.

  6. 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.

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

    PubMed

    Hu, Wei; Lin, Lin; Yang, Chao

    2015-09-28

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

  8. The challenge of establishing decomposition functional types to estimate heterotrophic respiration at large scales

    NASA Astrophysics Data System (ADS)

    Bond-Lamberty, B. P.; Epron, D.; Harden, J. W.; Harmon, M.; Hoffman, F. M.; Kumar, J.; McGuire, A. D.; Vargas, R.

    2016-12-01

    Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at large scales. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step would be the development of "Decomposition Functional Types" (DFTs). Analogous to established plant functional types (PFTs) and proposed ecosystem functional types, DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. DFTs should be developed using bottom-up, data-driven analyses that will depend heavily on established databases and remote sensing products. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities, all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR.

  9. 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.

  10. Galaxy clustering on large scales.

    PubMed Central

    Efstathiou, G

    1993-01-01

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

  11. 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.

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

    PubMed

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

    2016-07-05

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

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

    PubMed Central

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

    2014-01-01

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

  14. 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

  15. 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.

  16. 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.

  17. Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function.

    PubMed

    Schneider, Nadine; Hindle, Sally; Lange, Gudrun; Klein, Robert; Albrecht, Jürgen; Briem, Hans; Beyer, Kristin; Claußen, Holger; Gastreich, Marcus; Lemmen, Christian; Rarey, Matthias

    2012-06-01

    The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.

  18. Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function

    NASA Astrophysics Data System (ADS)

    Schneider, Nadine; Hindle, Sally; Lange, Gudrun; Klein, Robert; Albrecht, Jürgen; Briem, Hans; Beyer, Kristin; Claußen, Holger; Gastreich, Marcus; Lemmen, Christian; Rarey, Matthias

    2012-06-01

    The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects the Gibbs free energy of binding while only considering the essential interactions of protein-ligand complexes. The greatest benefit of HYDE is that it yields a very intuitive atom-based score, which can be mapped onto the ligand and protein atoms. This allows the direct visualization of the score and consequently facilitates analysis of protein-ligand complexes during the lead optimization process. In this study, we validated our new scoring function by applying it in large-scale docking experiments. We could successfully predict the correct binding mode in 93% of complexes in redocking calculations on the Astex diverse set, while our performance in virtual screening experiments using the DUD dataset showed significant enrichment values with a mean AUC of 0.77 across all protein targets with little or no structural defects. As part of these studies, we also carried out a very detailed analysis of the data that revealed interesting pitfalls, which we highlight here and which should be addressed in future benchmark datasets.

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Bardal, L. M.; Sætran, L. R.

    2016-09-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  4. Correlation microphone for measuring airframe noise in large-scale wind tunnels

    NASA Technical Reports Server (NTRS)

    Ahtye, W. F.; Kojima, G. K.

    1976-01-01

    A correlation microphone arrangement was used in the test section of the Ames 7- by 10-Foot and 40- by 80-Foot Wind Tunnels in an attempt to reject the reverberant and wind noise. The tests in the 7- by 10-foot wind tunnel covered a frequency range from 400 Hz to 8 kHz while the tests in the 40- by 80-foot tunnel covered the range from 31.5 to 800 Hz. Examination of the experimental data plus calculations of cross-correlations due to reflective noise indicate that the correlation microphone is effective in rejecting microphone wind noise and reverberant noise even at low frequencies, and that the low-frequency background noise monitored by the correlation microphone is reflected noise with a preferred direction from the tunnel drive system. Design studies indicate that this tunnel drive noise can be reduced substantially through suitable modification of the drive fans and acoustical treatment of the nacelles that house these fans.

  5. Frequency-specific alterations of large-scale functional brain networks in patients with Alzheimer's disease.

    PubMed

    Qin, Yuan-Yuan; Li, Ya-Peng; Zhang, Shun; Xiong, Ying; Guo, Lin-Ying; Yang, Shi-Qi; Yao, Yi-Hao; Li, Wei; Zhu, Wen-Zhen

    2015-03-05

    Previous studies have indicated that the cognitive deficits in patients with Alzheimer's disease (AD) may be due to topological deteriorations of the brain network. However, whether the selection of a specific frequency band could impact the topological properties is still not clear. Our hypothesis is that the topological properties of AD patients are also frequency-specific. Resting state functional magnetic resonance imaging data from 10 right-handed moderate AD patients (mean age: 64.3 years; mean mini mental state examination [MMSE]: 18.0) and 10 age and gender-matched healthy controls (mean age: 63.6 years; mean MMSE: 28.2) were enrolled in this study. The global efficiency, the clustering coefficient (CC), the characteristic path length (CpL), and "small-world" property were calculated in a wide range of thresholds and averaged within each group, at three different frequency bands (0.01-0.06 Hz, 0.06-0.11 Hz, and 0.11-0.25 Hz). At lower-frequency bands (0.01-0.06 Hz, 0.06-0.11 Hz), the global efficiency, the CC and the "small-world" properties of AD patients decreased compared to controls. While at higher-frequency bands (0.11-0.25 Hz), the CpL was much longer, and the "small-world" property was disrupted in AD, particularly at a higher threshold. The topological properties changed with different frequency bands, suggesting the existence of disrupted global and local functional organization associated with AD. This study demonstrates that the topological alterations of large-scale functional brain networks in AD patients are frequency dependent, thus providing fundamental support for optimal frequency selection in future related research.

  6. Assessing the functional consequence of loss of function variants using electronic medical record and large-scale genomics consortium efforts

    PubMed Central

    Sleiman, Patrick; Bradfield, Jonathan; Mentch, Frank; Almoguera, Berta; Connolly, John; Hakonarson, Hakon

    2014-01-01

    Estimates from large scale genome sequencing studies indicate that each human carries up to 20 genetic variants that are predicted to results in loss of function (LOF) of protein-coding genes. While some are known disease-causing variants or common, tolerated, LOFs in non-essential genes, the majority remain of unknown consequence. We explore the possibility of using imputed GWAS data from large biorepositories such as the electronic medical record and genomics (eMERGE) consortium to determine the effects of rare LOFs. Here, we show that two hypocholesterolemia-associated LOF mutations in the PCSK9 gene can be accurately imputed into large-scale GWAS datasets which raises the possibility of assessing LOFs through genomics-linked medical records. PMID:24808909

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

    PubMed

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

    2013-10-01

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

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

    PubMed

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

    2016-12-01

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

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

    PubMed

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

    2014-10-15

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

  10. 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.

  11. Functional connectivity of large-scale brain networks in patients with anti-NMDA receptor encephalitis: an observational study.

    PubMed

    Peer, Michael; Prüss, Harald; Ben-Dayan, Inbal; Paul, Friedemann; Arzy, Shahar; Finke, Carsten

    2017-10-01

    In anti-NMDA receptor (NMDAR) encephalitis, antibody-mediated dysfunction of NMDARs causes severe neuropsychiatric symptoms, including psychosis, memory deficits, and movement disorders. However, it remains elusive how antibody-mediated NMDAR dysfunction leads to these symptoms, and whether the symptoms arise from impairment in specific brain regions and the interactions between impaired regions. In this observational study, we recruited 43 patients with anti-NMDAR encephalitis from a tertiary university hospital and 43 age-matched and sex-matched healthy controls without a history of neurological or psychiatric disorders, who were recruited from the general population of Berlin. We used structural and resting-state functional MRI to investigate alterations in connectivity in all participants. We did functional connectivity analyses, including large-scale network analysis, whole-brain pair-wise connectivity, and machine-learning classification, and compared the results with patients' functional impairment. Although structural MRI was normal in 31 (72%) of the 43 patients, we observed widespread alterations of functional connectivity that correlated with clinical measures. These alterations included impaired hippocampal functional connectivity, decoupling of the medial temporal and the default-mode networks, and an overall impairment of frontotemporal connections. Furthermore, functional connectivity was impaired within distributed large-scale networks, including sensorimotor, frontoparietal, lateral-temporal, and visual networks. Memory impairment correlated with hippocampal and medial-temporal-lobe network connectivity, whereas schizophrenia-like symptoms were associated with functional connectivity changes in frontoparietal networks. Machine-learning analyses corroborated these findings and identified frontoparietal and frontotemporal connections as reliably discriminating features between patients and controls, yielding an overall accuracy of 81%. This study

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

    SciTech Connect

    Nohadani, O; Roy, A; Das, I

    2015-06-15

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

  13. 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

  14. Improved Large-Scale Slope Analysis on Mars Based on Correlation of Slopes Derived with Different Baselines

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Wu, B.

    2017-07-01

    The surface slopes of planetary bodies are important factors for exploration missions, such as landing site selection and rover manoeuvre. Generally, high-resolution digital elevation models (DEMs) such as those generated from the HiRISE images on Mars are preferred to generate detailed slopes with a better fidelity of terrain features. Unfortunately, high-resolution datasets normally only cover small area and are not always available. While lower resolution datasets, such as MOLA, provide global coverage of the Martian surface. Slopes generated from the low-resolution DEM will be based on a large baseline and be smoothed from the real situation. In order to carry out slope analysis at large scale on Martian surface based low-resolution data such as MOLA data, while alleviating the smoothness problem of slopes due to its low resolution, this paper presents an amplifying function of slopes derived from low-resolution DEMs based on the relationships between DEM resolutions and slopes. First, slope maps are derived from the HiRISE DEM (meter-level resolution DEM generated from HiRISE images) and a series of down-sampled HiRISE DEMs. The latter are used to simulate low-resolution DEMs. Then the high-resolution slope map is down- sampled to the same resolution with the slope map from the lower-resolution DEMs. Thus, a comparison can be conducted pixel-wise. For each pixel on the slope map derived from the lower-resolution DEM, it can reach the same value with the down-sampled HiRISE slope by multiplying an amplifying factor. Seven sets of HiRISE images with representative terrain types are used for correlation analysis. It shows that the relationship between the amplifying factors and the original MOLA slopes can be described by the exponential function. Verifications using other datasets show that after applying the proposed amplifying function, the updated slope maps give better representations of slopes on Martian surface compared with the original slopes.

  15. Voids and superstructures: correlations and induced large-scale velocity flows

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

    The expanding complex pattern of filaments, walls and voids build the evolving cosmic web with material flowing from underdense on to high density regions. Here, we explore the dynamical behaviour of voids and galaxies in void shells relative to neighbouring overdense superstructures, using the Millenium simulation and the main galaxy catalogue in Sloan Digital Sky Survey data. We define a correlation measure to estimate the tendency of voids to be located at a given distance from a superstructure. We find voids-in-clouds (S-types) preferentially located closer to superstructures than voids-in-voids (R-types) although we obtain that voids within ∼40 h-1 Mpc of superstructures are infalling in a similar fashion independently of void type. Galaxies residing in void shells show infall towards the closest superstructure, along with the void global motion, with a differential velocity component depending on their relative position in the shell with respect to the direction to the superstructure. This effect is produced by void expansion and therefore is stronger for R-types. We also find that galaxies in void shells facing the superstructure flow towards the overdensities faster than galaxies elsewhere at the same relative distance to the superstructure. The results obtained for the simulation are also reproduced for the Sky Survey Data Release data with a linearized velocity field implementation.

  16. 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

    2015-04-02

    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. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  17. 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.

  18. 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.

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

    PubMed

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

    2011-09-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    PubMed

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

    2011-09-01

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

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

    NASA Technical Reports Server (NTRS)

    Kashlinsky, A.

    1991-01-01

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

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

    PubMed

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

    2009-01-01

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

  4. 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.

  5. Stability analysis and H infinity controller design of fuzzy large-scale systems based on piecewise Lyapunov functions.

    PubMed

    Zhang, Hongbin; Li, Chunguang; Liao, Xiaofeng

    2006-06-01

    This paper presents a novel approach to stability analysis of a fuzzy large-scale system in which the system is composed of a number of Takagi-Sugeno (T-S) fuzzy subsystems with interconnections. The stability analysis is based on Lyapunov functions that are continuous and piecewise quadratic. It is shown that the stability of the fuzzy large-scale systems can be established if a piecewise Lyapunov function can be constructed, and, moreover, the function can be obtained by solving a set of linear matrix inequalities (LMIs) that are numerically feasible. It is also demonstrated via a numerical example that the stability result based on the piecewise quadratic Lyapunov functions is less conservative than that based on the common quadratic Lyapunov functions. The H infinity controllers can also be designed by solving a set of LMIs based on these powerful piecewise quadratic Lyapunov functions.

  6. Prevalence, Nature, and Correlates of Sleep Problems Among Children with Fragile X Syndrome Based on a Large Scale Parent Survey

    PubMed Central

    Kronk, Rebecca; Bishop, Ellen E.; Raspa, Melissa; Bickel, Julie O.; Mandel, Daniel A.; Bailey, Donald B.

    2010-01-01

    Study Objectives: This study reports on current child sleep difficulties reported by parents of children with Fragile X syndrome (FXS). We address prevalence and type of sleep problems (e.g., difficulty falling asleep, frequent awakenings); type and effectiveness of medical and behavioral treatments (e.g., medication, surgery, environmental changes); and explore specific child and family characteristics (e.g., child age, child gender, co-occurring conditions) as possible predictors of child sleep difficulties. Design/Participants: This study is part of a larger survey addressing needs of families with children with FXS. This article focuses on the families who responded to the survey sleep questions, had one or more children with the full mutation FXS, and who reside in the United States. The mean age for male and female children in this group was 15 years and 16 years respectively (N = 1,295). Results: Parents reported that 32% of the children with FXS currently experience sleep difficulties; 84% of those children are reported to have ≥ 2 current sleep problems. Problems falling asleep and frequent night awakenings were the most frequently reported difficulties; 47% of males and 40% of females received ≥1 medication to help with sleep. Children with more problematic health or behavioral characteristics had a higher likelihood of having current sleep problems. Conclusions: Our survey provides the most representative sample to date of sleep problems in children with FXS or any other neurodevelopmental disability. This large scale survey establishes a foundation for the prevalence of sleep disorders in children with FXS. Citation: Kronk R; Bishop EE; Raspa M; Bickel JO; Mandel DA; Bailey DB. Prevalence, nature, and correlates of sleep problems among children with fragile x syndrome based on a large scale parent survey. SLEEP 2010;33(5):679-687. PMID:20469810

  7. 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

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

    PubMed

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

    2016-03-10

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

  9. NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia.

    PubMed

    Anticevic, Alan; Gancsos, Mark; Murray, John D; Repovs, Grega; Driesen, Naomi R; Ennis, Debra J; Niciu, Mark J; Morgan, Peter T; Surti, Toral S; Bloch, Michael H; Ramani, Ramachandran; Smith, Mark A; Wang, Xiao-Jing; Krystal, John H; Corlett, Philip R

    2012-10-09

    Glutamatergic neurotransmission mediated by N-methyl-d-aspartate (NMDA) receptors is vital for the cortical computations underlying cognition and might be disrupted in severe neuropsychiatric illnesses such as schizophrenia. Studies on this topic have been limited to processes in local circuits; however, cognition involves large-scale brain systems with multiple interacting regions. A prominent feature of the human brain's global architecture is the anticorrelation of default-mode vs. task-positive systems. Here, we show that administration of an NMDA glutamate receptor antagonist, ketamine, disrupted the reciprocal relationship between these systems in terms of task-dependent activation and connectivity during performance of delayed working memory. Furthermore, the degree of this disruption predicted task performance and transiently evoked symptoms characteristic of schizophrenia. We offer a parsimonious hypothesis for this disruption via biophysically realistic computational modeling, namely cortical disinhibition. Together, the present findings establish links between glutamate's role in the organization of large-scale anticorrelated neural systems, cognition, and symptoms associated with schizophrenia in humans.

  10. Arctic Ice Algae Distribution as Function of Large Scale Sea Ice Variables

    NASA Astrophysics Data System (ADS)

    Flores, H.; Castellani, G.; Lange, B. A.; David, C.; Katlein, C.; Peeken, I.; Nicolaus, M.; Losch, M. J.; van Franeker, J. A.

    2016-02-01

    One of the most pronounced impacts of climate change is the declining sea ice cover in the Arctic Ocean, which has implications for sea-ice associated ecosystems that are strongly dependent on carbon produced by ice algae. In order to understand these ecosystems there is a need to understand the interaction between the physical and biological components of sea ice. Our current understanding of Arctic sea ice algae is based on observations with limited spatial coverage. Therefore, we aim to model the spatial distribution of ice-algae on a basin scale. Current sea-ice-ocean models do allow the representation of sea-ice variability on a scale of few km. Large scale characteristics of sea ice such as age, deformation, and snow cover, do affect the small scale ice properties, such as salinity, porosity, light transmission. The latter directly affect the sea ice algae content, but to what extent is not yet well understood. In this work we present a new parameterization for the sea-ice algae content developed with the aim to model the algae content and variability based on large scale sea-ice characteristics. This parameterization is tuned with data collected during a ship-based campaign to the Eastern Central Arctic in summer 2012. Sea-ice thickness and under-ice spectral surveys over different sea ice regimes were conducted with a Surface and Under Ice Trawl (SUIT) and a Remote Operated Vehicle (ROV). In addition, ice cores were extracted at several sites for chl a analysis. We use a coupled sea-ice-ocean model with a spatial scale of 10 km and we show here the results for the temporal evolution of algae content in sea ice.

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

    PubMed

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

    2011-10-13

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed Central

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

    2007-01-01

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

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

    PubMed

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

    2007-10-31

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

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

    PubMed

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

    2015-09-02

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

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

    PubMed

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

    2015-04-01

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

  17. A general explanation on the correlation of dark matter halo spin with the large-scale environment

    NASA Astrophysics Data System (ADS)

    Wang, Peng; Kang, Xi

    2017-06-01

    Both simulations and observations have found that the spin of halo/galaxy is correlated with the large-scale environment, and particularly the spin of halo flips in filament. A consistent picture of halo spin evolution in different environments is still lacked. Using N-body simulation, we find that halo spin with its environment evolves continuously from sheet to cluster, and the flip of halo spin happens both in filament and nodes. The flip in filament can be explained by halo formation time and migrating time when its environment changes from sheet to filament. For low-mass haloes, they form first in sheets and migrate into filaments later, so their mass and spin growth inside filament are lower, and the original spin is still parallel to filament. For high-mass haloes, they migrate into filaments first, and most of their mass and spin growth are obtained in filaments, so the resulted spin is perpendicular to filament. Our results well explain the overall evolution of cosmic web in the cold dark matter model and can be tested using high-redshift data. The scenario can also be tested against alternative models of dark matter, such as warm/hot dark matter, where the structure formation will proceed in a different way.

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

    PubMed

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

    2017-03-01

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

  19. Large-scale production of functional human serum albumin from transgenic rice seeds.

    PubMed

    He, Yang; Ning, Tingting; Xie, Tingting; Qiu, Qingchuan; Zhang, Liping; Sun, Yunfang; Jiang, Daiming; Fu, Kai; Yin, Fei; Zhang, Wenjing; Shen, Lang; Wang, Hui; Li, Jianjun; Lin, Qishan; Sun, Yunxia; Li, Hongzhen; Zhu, Yingguo; Yang, Daichang

    2011-11-22

    Human serum albumin (HSA) is widely used in clinical and cell culture applications. Conventional production of HSA from human blood is limited by the availability of blood donation and the high risk of viral transmission from donors. Here, we report the production of Oryza sativa recombinant HSA (OsrHSA) from transgenic rice seeds. The level of OsrHSA reached 10.58% of the total soluble protein of the rice grain. Large-scale production of OsrHSA generated protein with a purity >99% and a productivity rate of 2.75 g/kg brown rice. Physical and biochemical characterization of OsrHSA revealed it to be equivalent to plasma-derived HSA (pHSA). The efficiency of OsrHSA in promoting cell growth and treating liver cirrhosis in rats was similar to that of pHSA. Furthermore, OsrHSA displays similar in vitro and in vivo immunogenicity as pHSA. Our results suggest that a rice seed bioreactor produces cost-effective recombinant HSA that is safe and can help to satisfy an increasing worldwide demand for human serum albumin.

  20. Decoding the Large-Scale Structure of Brain Function by Classifying Mental States Across Individuals

    PubMed Central

    Poldrack, Russell A.; Halchenko, Yaroslav; Hanson, Stephen José

    2010-01-01

    Brain-imaging research has largely focused on localizing patterns of activity related to specific mental processes, but recent work has shown that mental states can be identified from neuroimaging data using statistical classifiers. We investigated whether this approach could be extended to predict the mental state of an individual using a statistical classifier trained on other individuals, and whether the information gained in doing so could provide new insights into how mental processes are organized in the brain. Using a variety of classifier techniques, we achieved cross-validated classification accuracy of 80% across individuals (chance = 13%). Using a neural network classifier, we recovered a low-dimensional representation common to all the cognitive-perceptual tasks in our data set, and we used an ontology of cognitive processes to determine the cognitive concepts most related to each dimension. These results revealed a small organized set of large-scale networks that map cognitive processes across a highly diverse set of mental tasks, suggesting a novel way to characterize the neural basis of cognition. PMID:19883493

  1. Large-scale production of functional human serum albumin from transgenic rice seeds

    PubMed Central

    He, Yang; Ning, Tingting; Xie, Tingting; Qiu, Qingchuan; Zhang, Liping; Sun, Yunfang; Jiang, Daiming; Fu, Kai; Yin, Fei; Zhang, Wenjing; Shen, Lang; Wang, Hui; Li, Jianjun; Lin, Qishan; Sun, Yunxia; Li, Hongzhen; Zhu, Yingguo; Yang, Daichang

    2011-01-01

    Human serum albumin (HSA) is widely used in clinical and cell culture applications. Conventional production of HSA from human blood is limited by the availability of blood donation and the high risk of viral transmission from donors. Here, we report the production of Oryza sativa recombinant HSA (OsrHSA) from transgenic rice seeds. The level of OsrHSA reached 10.58% of the total soluble protein of the rice grain. Large-scale production of OsrHSA generated protein with a purity >99% and a productivity rate of 2.75 g/kg brown rice. Physical and biochemical characterization of OsrHSA revealed it to be equivalent to plasma-derived HSA (pHSA). The efficiency of OsrHSA in promoting cell growth and treating liver cirrhosis in rats was similar to that of pHSA. Furthermore, OsrHSA displays similar in vitro and in vivo immunogenicity as pHSA. Our results suggest that a rice seed bioreactor produces cost-effective recombinant HSA that is safe and can help to satisfy an increasing worldwide demand for human serum albumin. PMID:22042856

  2. 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.

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

    PubMed

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

    2014-05-06

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

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

    PubMed

    Barrett, Lisa Feldman; Satpute, Ajay Bhaskar

    2013-06-01

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

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

    PubMed

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

    2008-08-29

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

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

    PubMed Central

    Barrett, Lisa Feldman; Satpute, Ajay

    2013-01-01

    Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

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

    PubMed Central

    Thompson, William Hedley; Fransson, Peter

    2016-01-01

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

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

    PubMed

    Grayson, David S; Fair, Damien A

    2017-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

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

    PubMed

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

    2012-01-01

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

  12. Pattern Classification of Large-Scale Functional Brain Networks: Identification of Informative Neuroimaging Markers for Epilepsy

    PubMed Central

    Zhang, ZhiQiang; Lu, WenLian; Lu, GuangMing; Feng, Jianfeng

    2012-01-01

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

  13. 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.

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

    PubMed

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

    2014-10-21

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

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

    PubMed Central

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

    2016-01-01

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

  17. 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

  18. Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

    PubMed

    Jansen, Iris E; Ye, Hui; Heetveld, Sasja; Lechler, Marie C; Michels, Helen; Seinstra, Renée I; Lubbe, Steven J; Drouet, Valérie; Lesage, Suzanne; Majounie, Elisa; Gibbs, J Raphael; Nalls, Mike A; Ryten, Mina; Botia, Juan A; Vandrovcova, Jana; Simon-Sanchez, Javier; Castillo-Lizardo, Melissa; Rizzu, Patrizia; Blauwendraat, Cornelis; Chouhan, Amit K; Li, Yarong; Yogi, Puja; Amin, Najaf; van Duijn, Cornelia M; Morris, Huw R; Brice, Alexis; Singleton, Andrew B; David, Della C; Nollen, Ellen A; Jain, Shushant; Shulman, Joshua M; Heutink, Peter

    2017-01-30

    Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies.

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

    PubMed Central

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

    2014-01-01

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

  20. 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.

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

    USGS Publications Warehouse

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

    2003-01-01

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

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

    PubMed

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

    2009-02-01

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

  3. 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.

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

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2014-11-25

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

  6. Quasi-three dimensional modeling of functionally-integrated elements of large-scale integrated circuits

    NASA Astrophysics Data System (ADS)

    Petrosyants, K. O.; Gurov, A. I.

    1984-08-01

    Functional integration allows a substantial reduction in the number of metallized connections and contact areas to the individual regions of a semiconductor structure, and realization of the basic connections between the elements within the semiconductor volume. Planning of a functionally integrated structure (FIS), which assures device parameters optimum for circuit engineering applications, is unthinkable without consideration of sufficient precise machine models. A series of models concerned with the special features of construction of FIS of various types was developed. A quasi-three dimensional model is presented of the functionally integrated elements of a bipolar BIS, which are multilayer semiconductor structures with an arbitrarily arranged diffused region and metallized contacts, controlled by a current or voltage. The model is described by a system of differential equations in partial derivatives of the elliptical type with integral limitations. A numerical algorithm uses a Newtonian procedure of quasilinearization in conjunction with a block method of upper relaxation. The model is realized in FORTRAN IV for a unified system of computers, intended to solve a wide range of problems which originate during planning of BIS, in particular choice of the optimum versions of topology, routes, and the electrical regime of the elements.

  7. Large Scale Brain Functional Networks Support Sentence Comprehension: Evidence from Both Explicit and Implicit Language Tasks

    PubMed Central

    Feng, Gangyi; Huang, Ruiwang; Wang, Suiping

    2013-01-01

    Previous studies have indicated that sentences are comprehended via widespread brain regions in the fronto-temporo-parietal network in explicit language tasks (e.g., semantic congruency judgment tasks), and through restricted temporal or frontal regions in implicit language tasks (e.g., font size judgment tasks). This discrepancy has raised questions regarding a common network for sentence comprehension that acts regardless of task effect and whether different tasks modulate network properties. To this end, we constructed brain functional networks based on 27 subjects’ fMRI data that was collected while performing explicit and implicit language tasks. We found that network properties and network hubs corresponding to the implicit language task were similar to those associated with the explicit language task. We also found common hubs in occipital, temporal and frontal regions in both tasks. Compared with the implicit language task, the explicit language task resulted in greater global efficiency and increased integrated betweenness centrality of the left inferior frontal gyrus, which is a key region related to sentence comprehension. These results suggest that brain functional networks support both explicit and implicit sentence comprehension; in addition, these two types of language tasks may modulate the properties of brain functional networks. PMID:24244653

  8. Structural Basis of Large-Scale Functional Connectivity in the Mouse.

    PubMed

    Grandjean, Joanes; Zerbi, Valerio; Balsters, Joshua Henk; Wenderoth, Nicole; Rudin, Markus

    2017-08-23

    Translational neuroimaging requires approaches and techniques that can bridge between multiple different species and disease states. One candidate method that offers insights into the brain's functional connectivity (FC) is resting-state fMRI (rs-fMRI). In both humans and nonhuman primates, patterns of FC (often referred to as the functional connectome) have been related to the underlying structural connectivity (SC; also called the structural connectome). Given the recent rise in preclinical neuroimaging of mouse models, it is an important question whether the mouse functional connectome conforms to the underlying SC. Here, we compared FC derived from rs-fMRI in female mice with the underlying monosynaptic structural connectome as provided by the Allen Brain Connectivity Atlas. We show that FC between interhemispheric homotopic cortical and hippocampal areas, as well as in cortico-striatal pathways, emerges primarily via monosynaptic structural connections. In particular, we demonstrate that the striatum (STR) can be segregated according to differential rs-fMRI connectivity patterns that mirror monosynaptic connectivity with isocortex. In contrast, for certain subcortical networks, FC emerges along polysynaptic pathways as shown for left and right STR, which do not share direct anatomical connections, but high FC is putatively driven by a top-down cortical control. Finally, we show that FC involving cortico-thalamic pathways is limited, possibly confounded by the effect of anesthesia, small regional size, and tracer injection volume. These findings provide a critical foundation for using rs-fMRI connectivity as a translational tool to study complex brain circuitry interactions and their pathology due to neurological or psychiatric diseases across species.SIGNIFICANCE STATEMENT A comprehensive understanding of how the anatomical architecture of the brain, often referred to as the "connectome," corresponds to its function is arguably one of the biggest challenges

  9. 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.

  10. 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

  11. 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

  12. Measuring Cluster Stability in a Large Scale Phylogenetic Analysis of Functional Genes in Metagenomes Using pplacer.

    PubMed

    Land, Tyler A; Fizzano, Perry; Kodner, Robin B

    2016-01-01

    Analysis of metagenomic sequence data requires a multi-stage workflow. The results of each intermediate step possess an inherent uncertainty and potentially impact the as-yet-unmeasured statistical significance of downstream analyses. Here, we describe our phylogenetic analysis pipeline which uses the pplacer program to place many shotgun sequences corresponding to a single functional gene onto a fixed phylogenetic tree. We then use the squash clustering method to compare multiple samples with respect to that gene. We approximate the statistical significance of each gene's clustering result by measuring its cluster stability, the consistency of that clustering result when the probabilistic placements made by pplacer are systematically reassigned and then clustered again, as measured by the adjusted Rand Index. We find that among the genes investigated, the majority of analyses are stable, based on the average adjusted Rand Index. We investigated properties of each gene that may explain less stable results. These genes tended to have less convex reference trees, less total reads recruited to the gene, and a greater Expected Distance between Placement Locations as given by pplacer when examined in aggregate. However, for an individual functional gene, these measures alone do not predict cluster stability.

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

    PubMed

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

    2015-04-01

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

  14. 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

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

    PubMed

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

    2016-04-01

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

  16. 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

  17. Evidence for large-scale gene-by-smoking interaction effects on pulmonary function.

    PubMed

    Aschard, Hugues; Tobin, Martin D; Hancock, Dana B; Skurnik, David; Sood, Akshay; James, Alan; Vernon Smith, Albert; Manichaikul, Ani W; Campbell, Archie; Prins, Bram P; Hayward, Caroline; Loth, Daan W; Porteous, David J; Strachan, David P; Zeggini, Eleftheria; O'Connor, George T; Brusselle, Guy G; Boezen, H Marike; Schulz, Holger; Deary, Ian J; Hall, Ian P; Rudan, Igor; Kaprio, Jaakko; Wilson, James F; Wilk, Jemma B; Huffman, Jennifer E; Hua Zhao, Jing; de Jong, Kim; Lyytikäinen, Leo-Pekka; Wain, Louise V; Jarvelin, Marjo-Riitta; Kähönen, Mika; Fornage, Myriam; Polasek, Ozren; Cassano, Patricia A; Barr, R Graham; Rawal, Rajesh; Harris, Sarah E; Gharib, Sina A; Enroth, Stefan; Heckbert, Susan R; Lehtimäki, Terho; Gyllensten, Ulf; Society Scientific Group, Understanding; Jackson, Victoria E; Gudnason, Vilmundur; Tang, Wenbo; Dupuis, Josée; Soler Artigas, María; Joshi, Amit D; London, Stephanie J; Kraft, Peter

    2017-01-12

    Smoking is the strongest environmental risk factor for reduced pulmonary function. The genetic component of various pulmonary traits has also been demonstrated, and at least 26 loci have been reproducibly associated with either FEV1 (forced expiratory volume in 1 second) or FEV1/FVC (FEV1/forced vital capacity). Although the main effects of smoking and genetic loci are well established, the question of potential gene-by-smoking interaction effect remains unanswered. The aim of the present study was to assess, using a genetic risk score approach, whether the effect of these 26 loci on pulmonary function is influenced by smoking. We evaluated the interaction between smoking exposure, considered as either ever vs never or pack-years, and a 26-single nucleotide polymorphisms (SNPs) genetic risk score in relation to FEV1 or FEV1/FVC in 50 047 participants of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and SpiroMeta consortia. We identified an interaction (βint = -0.036, 95% confidence interval, -0.040 to -0.032, P = 0.00057) between an unweighted 26 SNP genetic risk score and smoking status (ever/never) on the FEV1/FVC ratio. In interpreting this interaction, we showed that the genetic risk of falling below the FEV 1: /FVC threshold used to diagnose chronic obstructive pulmonary disease is higher among ever smokers than among never smokers. A replication analysis in two independent datasets, although not statistically significant, showed a similar trend in the interaction effect. This study highlights the benefit of using genetic risk scores for identifying interactions missed when studying individual SNPs and shows, for the first time, that persons with the highest genetic risk for low FEV1/FVC may be more susceptible to the deleterious effects of smoking. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.

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

    NASA Astrophysics Data System (ADS)

    Cortes-Huerto, R.; Ballone, P.

    2010-05-01

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

  19. 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

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

    PubMed

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

    2015-07-28

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

  1. Dynamic changes in large-scale functional network organization during autobiographical memory retrieval.

    PubMed

    Inman, Cory S; James, G Andrew; Vytal, Katherine; Hamann, Stephan

    2017-09-23

    Autobiographical memory (AM), episodic memory for life events, involves the orchestration of multiple dynamic cognitive processes, including memory access and subsequent elaboration. Previous neuroimaging studies have contrasted memory access and elaboration processes in terms of regional brain activation and connectivity within large, multi-region networks. Although interactions between key memory-related regions such as the hippocampus and prefrontal cortex (PFC) have been shown to play an important role in AM retrieval, it remains unclear how such connectivity between specific, individual regions involved in AM retrieval changes dynamically across the retrieval process and how these changes relate to broader memory networks throughout the whole brain. The present functional magnetic resonance imaging (fMRI) study sought to assess the specific changes in interregional connectivity patterns across the AM retrieval processes to understand network level mechanisms of AM retrieval and further test current theoretical accounts of dynamic AM retrieval processes. We predicted that dynamic connections would reflect two hypothesized memory processes, with initial processes reflecting memory-access related connections between regions such as the anterior hippocampal and ventrolateral PFC regions, and later processes reflecting elaboration-related connections between dorsolateral frontal working memory regions and parietal-occipital visual imagery regions. One week prior to fMRI scanning, fifteen healthy adult participants generated AMs using personally selected cue words. During scanning, participants were cued to retrieve the AMs. We used a moving-window functional connectivity analysis and graph theoretic measures to examine dynamic changes in the strength and centrality of connectivity among regions involved in AM retrieval. Consistent with predictions, early, access-related processing primarily involved a ventral frontal to temporal-parietal network associated with

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

    DOE PAGES

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

    2016-02-02

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

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

    SciTech Connect

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

    2016-02-02

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

  4. MCbiclust: a novel algorithm to discover large-scale functionally related gene sets from massive transcriptomics data collections.

    PubMed

    Bentham, Robert B; Bryson, Kevin; Szabadkai, Gyorgy

    2017-09-06

    The potential to understand fundamental biological processes from gene expression data has grown in parallel with the recent explosion of the size of data collections. However, to exploit this potential, novel analytical methods are required, capable of discovering large co-regulated gene networks. We found current methods limited in the size of correlated gene sets they could discover within biologically heterogeneous data collections, hampering the identification of multi-gene controlled fundamental cellular processes such as energy metabolism, organelle biogenesis and stress responses. Here we describe a novel biclustering algorithm called Massively Correlated Biclustering (MCbiclust) that selects samples and genes from large datasets with maximal correlated gene expression, allowing regulation of complex networks to be examined. The method has been evaluated using synthetic data and applied to large bacterial and cancer cell datasets. We show that the large biclusters discovered, so far elusive to identification by existing techniques, are biologically relevant and thus MCbiclust has great potential in the analysis of transcriptomics data to identify large-scale unknown effects hidden within the data. The identified massive biclusters can be used to develop improved transcriptomics based diagnosis tools for diseases caused by altered gene expression, or used for further network analysis to understand genotype-phenotype correlations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

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

    2017-03-11

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

  9. Large Scale Nonlinear Programming.

    DTIC Science & Technology

    1978-06-15

    KEY WORDS (Conhinu. as, t.n.t.. aid. if nic••iary aid ld.ntify by block n,a,b.r) L. In,~~~ IP!CIE LARGE SCALE OPTIMIZATION APPLICATIONS OF NONLINEAR ... NONLINEAR PROGRAMMING by Garth P. McCormick 1. Introduction The general mathematical programming ( optimization ) problem can be stated in the following form...because the difficulty in solving a general nonlinear optimization problem has a~ much to do with the nature of the functions involved as it does with the

  10. 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

  11. 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.

  12. A novel large-scale plasma source: two discharge modes and their correlation to the production of aqueous reactive species

    NASA Astrophysics Data System (ADS)

    Wang, Bingchuan; Liu, Dingxin; Zhang, Zhiquan; Li, Qiaosong; Liu, Zhijie; Guo, Li; Wang, Xiaohua; Kong, Michael G.

    2017-08-01

    In this paper, a novel large-scale plasma source is put forward, which can generate two modes of discharge, i.e. the surface dielectric barrier discharge and the plasma jet array, by just varying the helium gas flow rate. It is found that the discharge power changes a little with the increasing gas flow rate, but the densities of reactive species in the gas phase and in the treated water change a lot. In particular, the gaseous O3 has its density decreasing while the aqueous O3 has its concentration increasing with the increasing gas flow rate. In the plasma-treated water, the reactive nitrogen species such as nitrite and nitrate have their concentrations first increasing and then decreasing, while the reactive oxygen species such as H2O2, O3 and OH have their concentrations increasing monotonically, implying that the plasma source is well-adaptive for different application requirements.

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

    PubMed Central

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  15. The large-scale distribution of galaxies

    NASA Technical Reports Server (NTRS)

    Geller, Margaret J.

    1989-01-01

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

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

    PubMed Central

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

    2009-01-01

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

  17. Stability analysis and H(infinity) controller design of discrete-time fuzzy large-scale systems based on piecewise Lyapunov functions.

    PubMed

    Zhang, Hongbin; Feng, Gang

    2008-10-01

    This paper is concerned with stability analysis and H(infinity) decentralized control of discrete-time fuzzy large-scale systems based on piecewise Lyapunov functions. The fuzzy large-scale systems consist of J interconnected discrete-time Takagi-Sugeno (T-S) fuzzy subsystems, and the stability analysis is based on Lyapunov functions that are piecewise quadratic. It is shown that the stability of the discrete-time fuzzy large-scale systems can be established if a piecewise quadratic Lyapunov function can be constructed, and moreover, the function can be obtained by solving a set of linear matrix inequalities (LMIs) that are numerically feasible. The H(infinity) controllers are also designed by solving a set of LMIs based on these powerful piecewise quadratic Lyapunov functions. It is demonstrated via numerical examples that the stability and controller synthesis results based on the piecewise quadratic Lyapunov functions are less conservative than those based on the common quadratic Lyapunov functions.

  18. A new method for large-scale assessment of change in ecosystem functioning in relation to land degradation

    NASA Astrophysics Data System (ADS)

    Horion, Stephanie; Ivits, Eva; Verzandvoort, Simone; Fensholt, Rasmus

    2017-04-01

    Ongoing pressures on European land are manifold with extreme climate events and non-sustainable use of land resources being amongst the most important drivers altering the functioning of the ecosystems. The protection and conservation of European natural capital is one of the key objectives of the 7th Environmental Action Plan (EAP). The EAP stipulates that European land must be managed in a sustainable way by 2020 and the UN Sustainable development goals define a Land Degradation Neutral world as one of the targets. This implies that land degradation (LD) assessment of European ecosystems must be performed repeatedly allowing for the assessment of the current state of LD as well as changes compared to a baseline adopted by the UNCCD for the objective of land degradation neutrality. However, scientifically robust methods are still lacking for large-scale assessment of LD and repeated consistent mapping of the state of terrestrial ecosystems. Historical land degradation assessments based on various methods exist, but methods are generally non-replicable or difficult to apply at continental scale (Allan et al. 2007). The current lack of research methods applicable at large spatial scales is notably caused by the non-robust definition of LD, the scarcity of field data on LD, as well as the complex inter-play of the processes driving LD (Vogt et al., 2011). Moreover, the link between LD and changes in land use (how land use changes relates to change in vegetation productivity and ecosystem functioning) is not straightforward. In this study we used the segmented trend method developed by Horion et al. (2016) for large-scale systematic assessment of hotspots of change in ecosystem functioning in relation to LD. This method alleviates shortcomings of widely used linear trend model that does not account for abrupt change, nor adequately captures the actual changes in ecosystem functioning (de Jong et al. 2013; Horion et al. 2016). Here we present a new methodology for

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

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  2. A large-scale, gene-driven mutagenesis approach for the functional analysis of the mouse genome

    PubMed Central

    Hansen, Jens; Floss, Thomas; Van Sloun, Petra; Füchtbauer, Ernst-Martin; Vauti, Franz; Arnold, Hans-Hennig; Schnütgen, Frank; Wurst, Wolfgang; von Melchner, Harald; Ruiz, Patricia

    2003-01-01

    A major challenge of the postgenomic era is the functional characterization of every single gene within the mammalian genome. In an effort to address this challenge, we assembled a collection of mutations in mouse embryonic stem (ES) cells, which is the largest publicly accessible collection of such mutations to date. Using four different gene-trap vectors, we generated 5,142 sequences adjacent to the gene-trap integration sites (gene-trap sequence tags; http://genetrap.de) from >11,000 ES cell clones. Although most of the gene-trap vector insertions occurred randomly throughout the genome, we found both vector-independent and vector-specific integration “hot spots.” Because >50% of the hot spots were vector-specific, we conclude that the most effective way to saturate the mouse genome with gene-trap insertions is by using a combination of gene-trap vectors. When a random sample of gene-trap integrations was passaged to the germ line, 59% (17 of 29) produced an observable phenotype in transgenic mice, a frequency similar to that achieved by conventional gene targeting. Thus, gene trapping allows a large-scale and cost-effective production of ES cell clones with mutations distributed throughout the genome, a resource likely to accelerate genome annotation and the in vivo modeling of human disease. PMID:12904583

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

    PubMed

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

    2017-03-10

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

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

    PubMed

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

    2017-03-15

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

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

    PubMed

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

    2014-01-01

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

  6. Cattle mammary bioreactor generated by a novel procedure of transgenic cloning for large-scale production of functional human lactoferrin.

    PubMed

    Yang, Penghua; Wang, Jianwu; Gong, Guochun; Sun, Xiuzhu; Zhang, Ran; Du, Zhuo; Liu, Ying; Li, Rong; Ding, Fangrong; Tang, Bo; Dai, Yunping; Li, Ning

    2008-01-01

    Large-scale production of biopharmaceuticals by current bioreactor techniques is limited by low transgenic efficiency and low expression of foreign proteins. In general, a bacterial artificial chromosome (BAC) harboring most regulatory elements is capable of overcoming the limitations, but transferring BAC into donor cells is difficult. We describe here the use of cattle mammary bioreactor to produce functional recombinant human lactoferrin (rhLF) by a novel procedure of transgenic cloning, which employs microinjection to generate transgenic somatic cells as donor cells. Bovine fibroblast cells were co-microinjected for the first time with a 150-kb BAC carrying the human lactoferrin gene and a marker gene. The resulting transfection efficiency of up to 15.79 x 10(-2) percent was notably higher than that of electroporation and lipofection. Following somatic cell nuclear transfer, we obtained two transgenic cows that secreted rhLF at high levels, 2.5 g/l and 3.4 g/l, respectively. The rhLF had a similar pattern of glycosylation and proteolytic susceptibility as the natural human counterpart. Biochemical analysis revealed that the iron-binding and releasing properties of rhLF were identical to that of native hLF. Importantly, an antibacterial experiment further demonstrated that rhLF was functional. Our results indicate that co-microinjection with a BAC and a marker gene into donor cells for somatic cell cloning indeed improves transgenic efficiency. Moreover, the cattle mammary bioreactors generated with this novel procedure produce functional rhLF on an industrial scale.

  7. Cattle Mammary Bioreactor Generated by a Novel Procedure of Transgenic Cloning for Large-Scale Production of Functional Human Lactoferrin

    PubMed Central

    Yang, Penghua; Wang, Jianwu; Gong, Guochun; Sun, Xiuzhu; Zhang, Ran; Du, Zhuo; Liu, Ying; Li, Rong; Ding, Fangrong; Tang, Bo; Dai, Yunping; Li, Ning

    2008-01-01

    Large-scale production of biopharmaceuticals by current bioreactor techniques is limited by low transgenic efficiency and low expression of foreign proteins. In general, a bacterial artificial chromosome (BAC) harboring most regulatory elements is capable of overcoming the limitations, but transferring BAC into donor cells is difficult. We describe here the use of cattle mammary bioreactor to produce functional recombinant human lactoferrin (rhLF) by a novel procedure of transgenic cloning, which employs microinjection to generate transgenic somatic cells as donor cells. Bovine fibroblast cells were co-microinjected for the first time with a 150-kb BAC carrying the human lactoferrin gene and a marker gene. The resulting transfection efficiency of up to 15.79×10−2 percent was notably higher than that of electroporation and lipofection. Following somatic cell nuclear transfer, we obtained two transgenic cows that secreted rhLF at high levels, 2.5 g/l and 3.4 g/l, respectively. The rhLF had a similar pattern of glycosylation and proteolytic susceptibility as the natural human counterpart. Biochemical analysis revealed that the iron-binding and releasing properties of rhLF were identical to that of native hLF. Importantly, an antibacterial experiment further demonstrated that rhLF was functional. Our results indicate that co-microinjection with a BAC and a marker gene into donor cells for somatic cell cloning indeed improves transgenic efficiency. Moreover, the cattle mammary bioreactors generated with this novel procedure produce functional rhLF on an industrial scale. PMID:18941633

  8. 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

  9. 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.

  10. 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.

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

    NASA Astrophysics Data System (ADS)

    Kanungo, Bikash; Gavini, Vikram

    2017-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  13. Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

    NASA Astrophysics Data System (ADS)

    DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

    2017-02-01

    We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

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

    PubMed

    Seino, Junji; Nakai, Hiromi

    2013-07-21

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

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

    SciTech Connect

    Seino, Junji; Nakai, Hiromi

    2013-07-21

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

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

    PubMed Central

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

    2011-01-01

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

  17. 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

  18. 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.

  19. Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism.

    PubMed

    Duan, Xujun; Chen, Heng; He, Changchun; Long, Zhiliang; Guo, Xiaonan; Zhou, Yuanyue; Uddin, Lucina Q; Chen, Huafu

    2017-10-03

    Although evidence is accumulating that autism spectrum disorder (ASD) is associated with disruption of functional connections between and within brain networks, it remains largely unknown whether these abnormalities are related to specific frequency bands. To address this question, network contingency analysis was performed on brain functional connectomes obtained from 213 adolescent participants across nine sites in the Autism Brain Imaging Data Exchange (ABIDE) multisite sample, to determine the disrupted connections between and within seven major cortical networks in adolescents with ASD at Slow-5, Slow-4 and Slow-3 frequency bands and further assess whether the aberrant intra- and inter-network connectivity varied as a function of ASD symptoms. Overall under-connectivity within and between large-scale intrinsic networks in ASD was revealed across the three frequency bands. Specifically, decreased connectivity strength within the default mode network (DMN), between DMN and visual network (VN), ventral attention network (VAN), and between dorsal attention network (DAN) and VAN was observed in the lower frequency band (slow-5, slow-4), while decreased connectivity between limbic network (LN) and frontal-parietal network (FPN) was observed in the higher frequency band (slow-3). Furthermore, weaker connectivity within and between specific networks correlated with poorer communication and social interaction skills in the slow-5 band, uniquely. These results demonstrate intrinsic under-connectivity within and between multiple brain networks within predefined frequency bands in ASD, suggesting that frequency-related properties underlie abnormal brain network organization in the disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    SciTech Connect

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

    2015-08-01

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

  1. Standard Errors for National Trends in International Large-Scale Assessments in the Case of Cross-National Differential Item Functioning

    ERIC Educational Resources Information Center

    Sachse, Karoline A.; Haag, Nicole

    2017-01-01

    Standard errors computed according to the operational practices of international large-scale assessment studies such as the Programme for International Student Assessment's (PISA) or the Trends in International Mathematics and Science Study (TIMSS) may be biased when cross-national differential item functioning (DIF) and item parameter drift are…

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

    ERIC Educational Resources Information Center

    Pietarinen, Janne; Pyhältö, Kirsi; Soini, Tiina

    2017-01-01

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

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

    ERIC Educational Resources Information Center

    Pietarinen, Janne; Pyhältö, Kirsi; Soini, Tiina

    2017-01-01

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

  4. Large-scale structural optimization

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.

    1983-01-01

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

  5. Large Scale Dynamos in Stars

    NASA Astrophysics Data System (ADS)

    Vishniac, Ethan T.

    2015-01-01

    We show that a differentially rotating conducting fluid automatically creates a magnetic helicity flux with components along the rotation axis and in the direction of the local vorticity. This drives a rapid growth in the local density of current helicity, which in turn drives a large scale dynamo. The dynamo growth rate derived from this process is not constant, but depends inversely on the large scale magnetic field strength. This dynamo saturates when buoyant losses of magnetic flux compete with the large scale dynamo, providing a simple prediction for magnetic field strength as a function of Rossby number in stars. Increasing anisotropy in the turbulence produces a decreasing magnetic helicity flux, which explains the flattening of the B/Rossby number relation at low Rossby numbers. We also show that the kinetic helicity is always a subdominant effect. There is no kinematic dynamo in real stars.

  6. 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

  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. Large scale scientific computing

    SciTech Connect

    Deuflhard, P. ); Engquist, B. )

    1987-01-01

    This book presents papers on large scale scientific computing. It includes: Initial value problems of ODE's and parabolic PDE's; Boundary value problems of ODE's and elliptic PDE's; Hyperbolic PDE's; Inverse problems; Optimization and optimal control problems; and Algorithm adaptation on supercomputers.

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2017-01-20

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

  11. 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. © 2014 Wiley Periodicals, Inc.

  12. 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

  13. 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.

  14. Imitating intrinsic alignments: a bias to the CMB lensing-galaxy shape cross-correlation power spectrum induced by the large-scale structure bispectrum

    NASA Astrophysics Data System (ADS)

    Merkel, Philipp M.; Schäfer, Björn Malte

    2017-10-01

    Cross-correlating the lensing signals of galaxies and comic microwave background (CMB) fluctuations is expected to provide valuable cosmological information. In particular, it may help tighten constraints on parameters describing the properties of intrinsically aligned galaxies at high redshift. To access the information conveyed by the cross-correlation signal, its accurate theoretical description is required. We compute the bias to CMB lensing-galaxy shape cross-correlation measurements induced by non-linear structure growth. Using tree-level perturbation theory for the large-scale structure bispectrum, we find that the bias is negative on most angular scales, therefore mimicking the signal of intrinsic alignments. Combining Euclid-like galaxy lensing data with a CMB experiment comparable to the Planck satellite mission, the bias becomes significant only on smallest scales (ℓ ≳ 2500). For improved CMB observations, however, the corrections amount to 10-15 per cent of the CMB lensing-intrinsic alignment signal over a wide multipole range (10 ≲ ℓ ≲ 2000). Accordingly, the power spectrum bias, if uncorrected, translates into 2σ and 3σ errors in the determination of the intrinsic alignment amplitude in the case of CMB stage III and stage IV experiments, respectively.

  15. 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.

  16. Adaptively Compressed Exchange Operator for Large-Scale Hybrid Density Functional Calculations with Applications to the Adsorption of Water on Silicene.

    PubMed

    Hu, Wei; Lin, Lin; Banerjee, Amartya S; Vecharynski, Eugene; Yang, Chao

    2017-03-14

    Density functional theory (DFT) calculations using hybrid exchange-correlation functionals have been shown to provide an accurate description of the electronic structures of nanosystems. However, such calculations are often limited to small system sizes due to the high computational cost associated with the construction and application of the Hartree-Fock (HF) exchange operator. In this paper, we demonstrate that the recently developed adaptively compressed exchange (ACE) operator formulation [J. Chem. Theory Comput. 2016, 12, 2242-2249] can enable hybrid functional DFT calculations for nanosystems with thousands of atoms. The cost of constructing the ACE operator is the same as that of applying the exchange operator to the occupied orbitals once, while the cost of applying the Hamiltonian operator with a hybrid functional (after construction of the ACE operator) is only marginally higher than that associated with applying a Hamiltonian constructed from local and semilocal exchange-correlation functionals. Therefore, this new development significantly lowers the computational barrier for using hybrid functionals in large-scale DFT calculations. We demonstrate that a parallel planewave implementation of this method can be used to compute the ground-state electronic structure of a 1000-atom bulk silicon system in less than 30 wall clock minutes and that this method scales beyond 8000 computational cores for a bulk silicon system containing about 4000 atoms. The efficiency of the present methodology in treating large systems enables us to investigate adsorption properties of water molecules on Ag-supported two-dimensional silicene. Our computational results show that water monomer, dimer, and trimer configurations exhibit distinct adsorption behaviors on silicene. In particular, the presence of additional water molecules in the dimer and trimer configurations induces a transition from physisorption to chemisorption, followed by dissociation on Ag-supported silicene

  17. 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.

  18. 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.

  19. Performance based assessment of functional skills in severe mental illness: Results of a large-scale study in China

    PubMed Central

    McIntosh, Belinda J; Zhang, Xiang Yang; Kosten, Thomas; Tan, Shu Ping; Xiu, Mei Hong; Harvey, Philip D

    2011-01-01

    Performance-based assessments of everyday living skills have been shown to be highly correlated with cognitive functioning in schizophrenia and bipolar disorder, as well as being predictive of deficits in real-world outcomes such as independent living and employment. In this study, we expand our assessments of impairments in everyday living skills to China, evaluating people with schizophrenia, bipolar disorder, and major depression, and comparing their performance to that of healthy controls. Samples of people with schizophrenia (N=272), bipolar disorder (n=61), major depression (n=50), and healthy controls (n=284) were examined with the Chinese version of the UCSD performance-based assessment, brief version (UPSA-B). Performance was compared across the groups and the association between age, gender, educational attainment, marital status, and UPSA-B scores was evaluated. When the performance on the UPSA was compared across the groups, with education as a covariate, significant effects of both diagnosis (F=86.3, p<.001) and education were found (F=228.3, p<.001). Sex and age did not contribute significantly when age and education were considered. Post-hoc comparisons revealed that total UPSA-B scores were lowest in the schizophrenia patients, followed by the patients with major depression. Patients with bipolar disorder did not differ from the healthy comparison subjects on overall performance. Scores for all groups were lower than previously reported in western samples (e.g., HC mean = 64). While diagnostic differences in UPSA-B scores are similar to those previously seen in western samples, the education effect is considerably more substantial. These data suggest that in developing countries educational attainment may be strongly associated with levels of adaptive outcomes and the utilization and interpretation of functional capacity measures be adjusted accordingly. PMID:21300378

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

    PubMed

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

    2013-04-15

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

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

    DTIC Science & Technology

    2014-09-24

    which nature uses strong electron correlation for efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an...strong electron correlation for efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an innovative paradigm...efficient energy transfer, particularly in photosynthesis and bioluminescence, (ii) providing an innovative paradigm for energy transfer in photovoltaic

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

    PubMed

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

    2011-09-25

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

  3. 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

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

    PubMed

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

    2014-04-01

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

  5. 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

  6. Large-scale gene co-expression network as a source of functional annotation for cattle genes.

    PubMed

    Beiki, Hamid; Nejati-Javaremi, Ardeshir; Pakdel, Abbas; Masoudi-Nejad, Ali; Hu, Zhi-Liang; Reecy, James M

    2016-11-02

    Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress. The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using "guilt-by-association" principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles. We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments

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

    PubMed

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

    2013-01-01

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

  8. Large-Scale Variation in Combined Impacts of Canopy Loss and Disturbance on Community Structure and Ecosystem Functioning

    PubMed Central

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

    2013-01-01

    Ecosystems are under pressure from multiple human disturbances whose impact may vary depending on environmental context. We experimentally evaluated variation in the separate and combined effects of the loss of a key functional group (canopy algae) and physical disturbance on rocky shore ecosystems at nine locations across Europe. Multivariate community structure was initially affected (during the first three to six months) at six locations but after 18 months, effects were apparent at only three. Loss of canopy caused increases in cover of non-canopy algae in the three locations in southern Europe and decreases in some northern locations. Measures of ecosystem functioning (community respiration, gross primary productivity, net primary productivity) were affected by loss of canopy at five of the six locations for which data were available. Short-term effects on community respiration were widespread, but effects were rare after 18 months. Functional changes corresponded with changes in community structure and/or species richness at most locations and times sampled, but no single aspect of biodiversity was an effective predictor of longer-term functional changes. Most ecosystems studied were able to compensate in functional terms for impacts caused by indiscriminate physical disturbance. The only consistent effect of disturbance was to increase cover of non-canopy species. Loss of canopy algae temporarily reduced community resistance to disturbance at only two locations and at two locations actually increased resistance. Resistance to disturbance-induced changes in gross primary productivity was reduced by loss of canopy algae at four locations. Location-specific variation in the effects of the same stressors argues for flexible frameworks for the management of marine environments. These results also highlight the need to analyse how species loss and other stressors combine and interact in different environmental contexts. PMID:23799082

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

    PubMed

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

    2013-04-01

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

  10. 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…

  11. 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.

  12. 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.

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

    PubMed

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

    2001-11-01

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

  14. The Influence of Large-Scale Airborne Particle Decline and Traffic-Related Exposure on Children’s Lung Function

    PubMed Central

    Sugiri, Dorothea; Ranft, Ulrich; Schikowski, Tamara; Krämer, Ursula

    2006-01-01

    Between 1991 and 2000, ambient air pollution in East Germany changed to resemble West German pollution levels: The concentration of total suspended particles (TSPs) decreased on a broad scale while traffic increased. During that time, we analyzed total lung capacity (TLC) and airway resistance (Raw) of East and West German children. We tested children 5–7 years of age (n = 2,574) with cooperation-independent body plethysmography in repeated cross sections. We used random-effect models to determine the mutually adjusted association between lung function and short-term and chronic particle exposure and its interaction with living near a busy road. Annual averages of TSPs declined from 77 to 44 μg/m3; averages on the day of investigation declined from 133 to 30 μg/m3. Differences in lung function between East and West German children vanished during the investigation time. The association of TSPs with Raw and TLC was stronger in children living > 50 m away from busy roads. East German children from this group had an Raw 2.5% higher [95% confidence interval (CI), 0.0–5.1%] per 40-μg/m3 increase of daily TSP averages. TLC decreased by 6.2% (95% CI, 0.04–11.6%) per 40-μg/m3 increase in annual mean TSPs, and this effect was equally pronounced in East and West Germany. TSP exposure decreased on a broad scale between 1991 and 2000. Lower concentrations of TSPs were associated with better measures of lung function in 6-year-old children. For children living near busy roads, this effect was diminished. PMID:16451868

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

    PubMed

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

    2017-03-01

    Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium (nStage1: 111,666; nStage2: 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea (PPM1J, EDEM3, ACP1, SPEG, EYA4, CYP1A1, and ATXN2L; PStage1<3.7×10(-7)), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 (P=5.4×10(-8) by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2-knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation. Copyright © 2017 by the American Society of Nephrology.

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

    PubMed

    Falda, Marco; Toppo, Stefano; Pescarolo, Alessandro; Lavezzo, Enrico; Di Camillo, Barbara; Facchinetti, Andrea; Cilia, Elisa; Velasco, Riccardo; Fontana, Paolo

    2012-03-28

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

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

    PubMed Central

    2010-01-01

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

  18. Large-scale biochemical profiling of the Candida albicans biofilm matrix: new compositional, structural, and functional insights.

    PubMed

    Lopez-Ribot, Jose L

    2014-09-09

    Among pathogenic fungi, Candida albicans is most frequently associated with biofilm formation, a lifestyle that is entirely different from the planktonic state. One of the distinguishing features of these biofilms is the presence of extracellular material, commonly referred to as the "biofilm matrix." The fungal biofilm matrix embeds sessile cells within these communities and plays important structural and physiological functions, including antifungal drug resistance with important clinical repercussions. This matrix is mostly self-produced by the fungal cells themselves and is composed of different types of biopolymers. In C. albicans, the main components of the biofilm matrix are carbohydrates, proteins, lipids, and DNA, but many of them remain unidentified and/or poorly characterized. In their recent article, Zarnowski et al. [mBio 5(4):e01333-14, 2014, doi:10.1128/mBio.01333-14] used a variety of biochemical and state-of-the-art "omic" approaches (glycomics, proteomics, and lipidomics) to identify and characterize unique biopolymers present in the C. albicans biofilm matrix. Besides generating a true "encyclopedic" catalog of individual moieties from each of the different macromolecular categories, results also provide important insights into structural and functional aspects of the fungal biofilm matrix, particularly the interaction between different components and the contribution of multiple matrix constituents to biofilm antifungal drug resistance. Copyright © 2014 Lopez-Ribot.

  19. Life style in persons with functional gastrointestinal disorders--large-scale internet survey of lifestyle in Japan.

    PubMed

    Miwa, H

    2012-05-01

    Care of patients with functional gastrointestinal disorders (FGIDs) commonly includes offering guidance on diet, exercise, and other lifestyle factors, but there is little information available on the actual lifestyles of FGID sufferers. An internet questionnaire survey of 15,000 adult members of the general public in Japan who were screened for functional dyspepsia (FD) and irritable bowel syndrome (IBS) using the Rome III adult FGID questionnaire was conducted. The prevalence of FD and IBS was 6.5% and 14.0%, respectively, and 3.0% of the subjects met the criteria for both FD and IBS. The prevalence of both FD and IBS was higher in women than in men. The lifestyles of 2,547 subjects who met the Rome III criteria for FD, IBS, or both were compared with the lifestyles of 1,000 control subjects who did not meet the criteria for FD or the criteria for IBS. Compared to the control subjects, a significantly lower percentage of subjects with FD, IBS, or both exercised frequently, and a significantly higher percentage thought that their sleep was insufficient, ate meals irregularly, did not have an appetite, did not like meat, thought that their vegetable consumption was insufficient, felt stress in their daily lives, and regarded themselves as being highly susceptible to stress. Persons with FGIDs are affected by impairment of sleep, eating habits, diet, exercise and other lifestyle factors, and feel excessive stress. This suggests that offering lifestyle guidance to FGID patients may be useful. © 2012 Blackwell Publishing Ltd.

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

    PubMed

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

    2017-03-22

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

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

    PubMed

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

    2016-10-12

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

  2. The pole expansion and selected inversion technique for solving Kohn-Sham density functional theory at large scale

    NASA Astrophysics Data System (ADS)

    Lin, Lin; Chen, Mohan; E, Weinan; He, Lixin; Lu, Jianfeng; Yang, Chao; Ying, Lexing

    2013-03-01

    The standard diagonalization based method for solving Kohn-Sham density functional theory (KSDFT) requires N eigenvectors for an O(N) * O(N) Kohn-Sham Hamiltonian matrix, with N being the number of electrons in the system. The computational cost for such procedure is expensive and scales as O(N3). We have developed a novel pole expansion plus selected inversion (PEXSI) method, in which KSDFT is solved by evaluating the selected elements of the inverse of a series of sparse symmetric matrices, and the overall algorithm scales at most O(N2) for all materials including metallic and insulating systems without any truncation. The PEXSI method can be used with orthogonal or nonorthogonal basis set, and the electron density, total energy, Helmholtz free energy and atomic force are calculated simultaneously and accurately without using the eigenvalues and eigenvectors. Combined with atomic orbital basis functions, the PEXSI method can be applied to study the electronic structure of boron nitride nanotube and carbon nanotube with more than 10,000 atoms on a single processor. U.S. Department of Energy DE-AC02-05CH11231

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

    PubMed Central

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

    2013-01-01

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

  4. Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation.

    PubMed

    Wendelken, Carter; Ferrer, Emilio; Ghetti, Simona; Bailey, Stephen K; Cutting, Laurie; Bunge, Silvia A

    2017-08-30

    Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead-lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC-IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC-IPL SC at one time point positively predicted future changes in RLPFC-IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability.SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation

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

    PubMed

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

    2014-02-01

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

  6. 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

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

    PubMed

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

    2014-10-01

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

  8. Large-scale non-Gaussian mass function and halo bias: tests on N-body simulations

    NASA Astrophysics Data System (ADS)

    Grossi, M.; Verde, L.; Carbone, C.; Dolag, K.; Branchini, E.; Iannuzzi, F.; Matarrese, S.; Moscardini, L.

    2009-09-01

    The description of the abundance and clustering of haloes for non-Gaussian initial conditions has recently received renewed interest, motivated by the forthcoming large galaxy and cluster surveys, which can potentially yield constraints of the order of unity on the non-Gaussianity parameter fNL. We present tests on N-body simulations of analytical formulae describing the halo abundance and clustering for non-Gaussian initial conditions. We calibrate the analytic non-Gaussian mass function of Matarrese, Verde & Jimenez and LoVerde et al. and the analytic description of clustering of haloes for non-Gaussian initial conditions on N-body simulations. We find an excellent agreement between the simulations and the analytic predictions if we make the corrections and , where q ~= 0.75, in the density threshold for gravitational collapse and in the non-Gaussian fractional correction to the halo bias, respectively. We discuss the implications of this correction on present and forecasted primordial non-Gaussianity constraints. We confirm that the non-Gaussian halo bias offers a robust and highly competitive test of primordial non-Gaussianity.

  9. Large-scale randomized clinical study on functional dyspepsia treatment with mosapride or teprenone: Japan Mosapride Mega-Study (JMMS).

    PubMed

    Hongo, Michio; Harasawa, Shigeru; Mine, Tetsuya; Sasaki, Iwao; Matsueda, Kei; Kusano, Motoyasu; Hanyu, Nobuyoshi; Nakada, Koji; Shibata, Chikashi

    2012-01-01

    Functional dyspepsia (FD) is a common condition seen in primary gastroenterology practice. The present study was conducted to compare the clinical effectiveness of mosapride and teprenone in patients with FD. Prospective clinical comparative study with random allocation of open labeled medications was performed as a multicenter trial in Japan. 1042 patients presenting symptoms of FD, either with gastric stasis (GSS) and/or epigastric pain (EPS), were enrolled. After initial endoscopic evaluation, medication either with mosapride 5 mg tid or teprenone 50 mg tid was started. Severity and frequency of GSS and EPS, health-related quality of life (HR-QOL) by the SF-36 Japanese version, and patients' compliance to medication was evaluated. Organic lesions were found in 90 patients (9%) in the 1027 patients examined by endoscopy. Among those without any specific lesions detected by endoscopy, gastrointestinal symptoms were resolved within one week after the endoscopy in 264 (28%) patients before initiating medication. 618 patients who remained symptomatic were randomized to medication either with mosapride (n = 311) or teprenone (n = 307). Two-week treatment with mosapride significantly improved GSS and EPS, while teprenone tended to improve only GSS. Mosapride also improved HR-QOL. 91% of patients treated with mosapride favored their medication, while only 52% of patients treated with teprenone favored their medication. Endoscopic evaluation at patients' presentation was effective to find active lesions and to improve FD symptoms. Mosapride was more favorably accepted than teprenone by the patients with sufficient safety and efficacy. © 2011 Journal of Gastroenterology and Hepatology Foundation and Blackwell Publishing Asia Pty Ltd.

  10. Effects of a large scale nitrogen and phosphorous fertilization on the ecosystem functioning of a Mediterranean tree-grass ecosystem

    NASA Astrophysics Data System (ADS)

    Migliavacca, Mirco; El Madany, Tarek; Perez-Priego, Oscar; Carrara, Arnaud; Hammer, Tiana; Henkel, Kathin; Kolle, Olaf; Luo, Yunpeng; Moreno, Gerardo; Morris, Kendalynn; Nair, Richard; Schrumpf, Marion; Wutzler, Thomas; Reichstein, Markus

    2017-04-01

    Recent studies have shown how human induced N/P imbalances affect essential ecosystem processes, and might be particularly important in water-limited ecosystems. In this contribution we will present results from an ecosystem scale nutrient manipulation experiment on a Mediterranean tree-grass ecosystem (Majadas del Tietar, Spain). Specifically, we will show how ecosystem functioning (e.g. light use efficiency, water use efficiency - WUE, albedo) changes as consequence of N and NP fertilization. A cluster of eddy covariance (EC) flux towers has been set up beside a long-term EC site (Control site) to measured high temporal resolution C and water fluxes between the ecosystem and the atmosphere. The sites were selected in a way to have similar pre-treatment conditions. Two out of three EC footprint areas (18 Ha) were fertilized with N and NP at the beginning of 2015 and 2016. To interpret the variations in C and water fluxes measured with the EC systems we monitored spatial and temporal variations in phenology, plant traits, species richness, and tree transpiration by using sap-flow meters, digital repeat photography, as well as soil sampling. The results show a consistent increase ( 15% compared to the Control site) in net ecosystem production (NEP) observed both in the N and the NP treatments. An increase of evapotranspiration (ET) of about 15% and 10% is observed in the N and NP site, respectively, indicating an increase of WUE in the NP treatment. The partitioning of the NEP into its gross components, the gross primary production (GPP) and the total ecosystem respiration (TER), show that the fertilization stimulated more GPP rather than TER, increasing therefore the capability of the ecosystem to act as carbon sink. The effects of fertilization are pronounced in spring and autumn and negligible in summer. This indicates that grass reacted much more than trees to N and NP addition. An increase of greenness and also an earlier green-up of grass in the N and NP sites

  11. The CLASSgal code for relativistic cosmological large scale structure

    NASA Astrophysics Data System (ADS)

    Di Dio, Enea; Montanari, Francesco; Lesgourgues, Julien; Durrer, Ruth

    2013-11-01

    We present accurate and efficient computations of large scale structure observables, obtained with a modified version of the CLASS code which is made publicly available. This code includes all relativistic corrections and computes both the power spectrum Cl(z1,z2) and the corresponding correlation function ξ(θ,z1,z2) of the matter density and the galaxy number fluctuations in linear perturbation theory. For Gaussian initial perturbations, these quantities contain the full information encoded in the large scale matter distribution at the level of linear perturbation theory. We illustrate the usefulness of our code for cosmological parameter estimation through a few simple examples.

  12. Definition and functions of health unified command and emergency operations centers for large-scale bioevent disasters within the existing ICS.

    PubMed

    Burkle, Frederick M; Hsu, Edbert B; Loehr, Michael; Christian, Michael D; Markenson, David; Rubinson, Lewis; Archer, Frank L

    2007-11-01

    The incident command system provides an organizational structure at the agency, discipline, or jurisdiction level for effectively coordinating response and recovery efforts during most conventional disasters. This structure does not have the capacity or capability to manage the complexities of a large-scale health-related disaster, especially a pandemic, in which unprecedented decisions at every level (eg, surveillance, triage protocols, surge capacity, isolation, quarantine, health care staffing, deployment) are necessary to investigate, control, and prevent transmission of disease. Emerging concepts supporting a unified decision-making, coordination, and resource management system through a health-specific emergency operations center are addressed and the potential structure, function, roles, and responsibilities are described, including comparisons across countries with similar incident command systems.

  13. 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.

  14. Lagrangian space consistency relation for large scale structure

    SciTech Connect

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

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  16. Large scale GW calculations

    DOE PAGES

    Govoni, Marco; Galli, Giulia

    2015-01-12

    We present GW calculations of molecules, ordered and disordered solids and interfaces, which employ an efficient contour deformation technique for frequency integration and do not require the explicit evaluation of virtual electronic states nor the inversion of dielectric matrices. We also present a parallel implementation of the algorithm, which takes advantage of separable expressions of both the single particle Green’s function and the screened Coulomb interaction. The method can be used starting from density functional theory calculations performed with semilocal or hybrid functionals. The newly developed technique was applied to GW calculations of systems of unprecedented size, including water/semiconductor interfacesmore » with thousands of electrons.« less

  17. Large-scale cortical networks and cognition.

    PubMed

    Bressler, S L

    1995-03-01

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

  18. Large scale biomimetic membrane arrays.

    PubMed

    Hansen, Jesper S; Perry, Mark; Vogel, Jörg; Groth, Jesper S; Vissing, Thomas; Larsen, Marianne S; Geschke, Oliver; Emneús, Jenny; Bohr, Henrik; Nielsen, Claus H

    2009-10-01

    To establish planar biomimetic membranes across large scale partition aperture arrays, we created a disposable single-use horizontal chamber design that supports combined optical-electrical measurements. Functional lipid bilayers could easily and efficiently be established across CO(2) laser micro-structured 8 x 8 aperture partition arrays with average aperture diameters of 301 +/- 5 microm. We addressed the electro-physical properties of the lipid bilayers established across the micro-structured scaffold arrays by controllable reconstitution of biotechnological and physiological relevant membrane peptides and proteins. Next, we tested the scalability of the biomimetic membrane design by establishing lipid bilayers in rectangular 24 x 24 and hexagonal 24 x 27 aperture arrays, respectively. The results presented show that the design is suitable for further developments of sensitive biosensor assays, and furthermore demonstrate that the design can conveniently be scaled up to support planar lipid bilayers in large square-centimeter partition arrays.

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed Central

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

    2016-01-01

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

  3. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    1984-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2015-04-01

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

  7. Large-Scale Sequence Comparison.

    PubMed

    Lal, Devi; Verma, Mansi

    2017-01-01

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

  8. Large-scale PACS implementation.

    PubMed

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

    1998-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Motamarri, Phani; Gavini, Vikram

    2014-09-01

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

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

    PubMed

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

    2017-03-01

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

  11. Methane emissions on large scales

    NASA Astrophysics Data System (ADS)

    Beswick, K. M.; Simpson, T. W.; Fowler, D.; Choularton, T. W.; Gallagher, M. W.; Hargreaves, K. J.; Sutton, M. A.; Kaye, A.

    with previous results from the area, indicating that this method of data analysis provided good estimates of large scale methane emissions.

  12. Large-scale structure of randomly jammed spheres

    NASA Astrophysics Data System (ADS)

    Ikeda, Atsushi; Berthier, Ludovic; Parisi, Giorgio

    2017-05-01

    We numerically analyze the density field of three-dimensional randomly jammed packings of monodisperse soft frictionless spherical particles, paying special attention to fluctuations occurring at large length scales. We study in detail the two-point static structure factor at low wave vectors in Fourier space. We also analyze the nature of the density field in real space by studying the large-distance behavior of the two-point pair correlation function, of density fluctuations in subsystems of increasing sizes, and of the direct correlation function. We show that such real space analysis can be greatly improved by introducing a coarse-grained density field to disentangle genuine large-scale correlations from purely local effects. Our results confirm that both Fourier and real space signatures of vanishing density fluctuations at large scale are absent, indicating that randomly jammed packings are not hyperuniform. In addition, we establish that the pair correlation function displays a surprisingly complex structure at large distances, which is however not compatible with the long-range negative correlation of hyperuniform systems but fully compatible with an analytic form for the structure factor. This implies that the direct correlation function is short ranged, as we also demonstrate directly. Our results reveal that density fluctuations in jammed packings do not follow the behavior expected for random hyperuniform materials, but display instead a more complex behavior.

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

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Blum, Daniel Brian

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

  15. Large-scale circuit simulation

    NASA Astrophysics Data System (ADS)

    Wei, Y. P.

    1982-12-01

    The simulation of VLSI (Very Large Scale Integration) circuits falls beyond the capabilities of conventional circuit simulators like SPICE. On the other hand, conventional logic simulators can only give the results of logic levels 1 and 0 with the attendent loss of detail in the waveforms. The aim of developing large-scale circuit simulation is to bridge the gap between conventional circuit simulation and logic simulation. This research is to investigate new approaches for fast and relatively accurate time-domain simulation of MOS (Metal Oxide Semiconductors), LSI (Large Scale Integration) and VLSI circuits. New techniques and new algorithms are studied in the following areas: (1) analysis sequencing (2) nonlinear iteration (3) modified Gauss-Seidel method (4) latency criteria and timestep control scheme. The developed methods have been implemented into a simulation program PREMOS which could be used as a design verification tool for MOS circuits.

  16. 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.

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

    DTIC Science & Technology

    2013-08-01

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

  18. Weather is not significantly correlated with destination-specific transport-related physical activity among adults: A large-scale temporally matched analysis.

    PubMed

    Durand, Casey P; Zhang, Kai; Salvo, Deborah

    2017-08-01

    Weather is an element of the natural environment that could have a significant effect on physical activity. Existing research, however, indicates only modest correlations between measures of weather and physical activity. This prior work has been limited by a failure to use time-matched weather and physical activity data, or has not adequately examined the different domains of physical activity (transport, leisure, occupational, etc.). Our objective was to identify the correlation between weather variables and destination-specific transport-related physical activity in adults. Data were sourced from the California Household Travel Survey, collected in 2012-3. Weather variables included: relative humidity, temperature, wind speed, and precipitation. Transport-related physical activity (walking) was sourced from participant-recorded travel diaries. Three-part hurdle models were used to analyze the data. Results indicate statistically or substantively insignificant correlations between the weather variables and transport-related physical activity for all destination types. These results provide the strongest evidence to date that transport-related physical activity may occur relatively independently of weather conditions. The knowledge that weather conditions do not seem to be a significant barrier to this domain of activity may potentially expand the universe of geographic locations that are amenable to environmental and programmatic interventions to increase transport-related walking. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  20. 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…

  1. Large-scale nanophotonic phased array.

    PubMed

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

    2013-01-10

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

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  4. 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.

  5. 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.

  6. The CLASSgal code for relativistic cosmological large scale structure

    SciTech Connect

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

    2013-11-01

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

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

    PubMed

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

    2010-06-01

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

  8. Hexagonalization of correlation functions

    NASA Astrophysics Data System (ADS)

    Fleury, Thiago; Komatsu, Shota

    2017-01-01

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

  9. 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.

  10. Cosmology with Large Scale Structure

    NASA Astrophysics Data System (ADS)

    Ho, Shirley; Cuesta, A.; Ross, A.; Seo, H.; DePutter, R.; Padmanabhan, N.; White, M.; Myers, A.; Bovy, J.; Blanton, M.; Hernandez, C.; Mena, O.; Percival, W.; Prada, F.; Ross, N. P.; Saito, S.; Schneider, D.; Skibba, R.; Smith, K.; Slosar, A.; Strauss, M.; Verde, L.; Weinberg, D.; Bachall, N.; Brinkmann, J.; da Costa, L. A.

    2012-01-01

    The Sloan Digital Sky Survey I-III surveyed 14,000 square degrees, and delivered over a trillion pixels of imaging data. I present cosmological results from this unprecedented data set which contains over a million galaxies distributed between redshift of 0.45 to 0.70. With such a large volume of data set, high precision cosmological constraints can be obtained given a careful control and understanding of observational systematics. I present a novel treatment of observational systematics and its application to the clustering signals from the data set. I will present cosmological constraints on dark components of the Universe and tightest constraints of the non-gaussianity of early Universe to date utilizing Large Scale Structure.

  11. Large-scale instabilities of helical flows

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

    A, Quesada, C.; Lloyd, J.

    2009-04-01

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

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

    PubMed

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

    2009-07-01

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

  14. 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

  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. Large scale cluster computing workshop

    SciTech Connect

    Dane Skow; Alan Silverman

    2002-12-23

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

  17. 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

  18. Large Scale Magnetostrictive Valve Actuator

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  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. 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…

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

    NASA Technical Reports Server (NTRS)

    Kaiser, N.

    1986-01-01

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

  2. Effective theory of squeezed correlation functions

    SciTech Connect

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

    2016-03-01

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

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

    PubMed Central

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

    2011-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. Large scale study of tooth enamel

    SciTech Connect

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

    1981-04-01

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

  8. How much can we learn about the function of bacterial rRNA modification by mining large-scale experimental datasets?

    PubMed

    Sergiev, Petr V; Golovina, Anna Y; Sergeeva, Olga V; Osterman, Ilya A; Nesterchuk, Mikhail V; Bogdanov, Alexey A; Dontsova, Olga A

    2012-07-01

    Modification of ribosomal RNA is ubiquitous among living organisms. Its functional role is well established for only a limited number of modified nucleotides. There are examples of rRNA modification involvement in the gene expression regulation in the cell. There is a need for large data set analysis in the search for potential functional partners for rRNA modification. In this study, we extracted phylogenetic profile, genome neighbourhood, co-expression and phenotype profile and co-purification data regarding Escherichia coli rRNA modification enzymes from public databases. Results were visualized as graphs using Cytoscape and analysed. Majority linked genes/proteins belong to translation apparatus. Among co-purification partners of rRNA modification enzymes are several candidates for experimental validation. Phylogenetic profiling revealed links of pseudouridine synthetases with RF2, RsmH with translation factors IF2, RF1 and LepA and RlmM with RdgC. Genome neighbourhood connections revealed several putative functionally linked genes, e.g. rlmH with genes coding for cell wall biosynthetic proteins and others. Comparative analysis of expression profiles (Gene Expression Omnibus) revealed two main associations, a group of genes expressed during fast growth and association of rrmJ with heat shock genes. This study might be used as a roadmap for further experimental verification of predicted functional interactions.

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

    DTIC Science & Technology

    2014-03-01

    measured with EEG/ MEG . Computers in Biology and Medicine, 41(12), 1110–1117. doi:10.1016/j.compbiomed.2011.06.020 39 Shackman, A. J., Maxwell, J. S...Daffertshofer, A. (2007). Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum

  10. How much can we learn about the function of bacterial rRNA modification by mining large-scale experimental datasets?

    PubMed Central

    Sergiev, Petr V.; Golovina, Anna Y.; Sergeeva, Olga V.; Osterman, Ilya A.; Nesterchuk, Mikhail V.; Bogdanov, Alexey A.; Dontsova, Olga A.

    2012-01-01

    Modification of ribosomal RNA is ubiquitous among living organisms. Its functional role is well established for only a limited number of modified nucleotides. There are examples of rRNA modification involvement in the gene expression regulation in the cell. There is a need for large data set analysis in the search for potential functional partners for rRNA modification. In this study, we extracted phylogenetic profile, genome neighbourhood, co-expression and phenotype profile and co-purification data regarding Escherichia coli rRNA modification enzymes from public databases. Results were visualized as graphs using Cytoscape and analysed. Majority linked genes/proteins belong to translation apparatus. Among co-purification partners of rRNA modification enzymes are several candidates for experimental validation. Phylogenetic profiling revealed links of pseudouridine synthetases with RF2, RsmH with translation factors IF2, RF1 and LepA and RlmM with RdgC. Genome neighbourhood connections revealed several putative functionally linked genes, e.g. rlmH with genes coding for cell wall biosynthetic proteins and others. Comparative analysis of expression profiles (Gene Expression Omnibus) revealed two main associations, a group of genes expressed during fast growth and association of rrmJ with heat shock genes. This study might be used as a roadmap for further experimental verification of predicted functional interactions. PMID:22411911

  11. 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

  12. 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.

  13. Scaled density functional theory correlation functionals.

    PubMed

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

    2007-10-18

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

  14. 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

  15. Assessment of functioning and disability in patients with schizophrenia using the WHO Disability Assessment Schedule 2.0 in a large-scale database.

    PubMed

    Chen, Ruey; Liou, Tsan-Hon; Chang, Kwang-Hwa; Yen, Chia-Feng; Liao, Hua-Fang; Chi, Wen-Chou; Chou, Kuei-Ru

    2017-08-11

    Schizophrenia is a common mental disorder characterized by deficits in multiple domains of functioning. This study is arguably the first of its kind in Taiwan to examine, in a multifaceted and objective manner, the disability of patients with schizophrenia and the factors affecting it. A cross-sectional design was adopted to gather data from 24,299 patients with schizophrenia who were listed in the Taiwan Databank of Persons with Disabilities. The level of disability in these patients was measured using the World Health Organization Disability Assessment Schedule 2.0. Statistical analyses were conducted through the χ (2) statistic and Poisson regression. The highest level of disability was in participation and the lowest was in self-care. An analysis of disability in all six domains of functioning on the basis of sex, age, type of residence, and socioeconomic status (SES) showed significant differences (P < 0.05). Significant factors (P < 0.05) affecting disability in these domains were female gender, age, educational attainment, SES, type of residence, and employment status. The overall degree of disability in schizophrenia patients was moderate. Six domains were measured in this study. The degrees of disability in mobility and self-care were mild while cognition, getting along, life activities, and participation were moderate. Moreover, female gender, an age of 45 or older, low educational attainment, middle to low SES, staying at healthcare institutions, and unemployment were crucial factors affecting disability of the participants. Preventive and rehabilitation programs should be developed to delay disability and functional degeneration in schizophrenic patients with these characteristics.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  18. Subthreshold attention-deficit/hyperactivity disorder is associated with functional impairments across domains: a comprehensive analysis in a large-scale community study.

    PubMed

    Hong, Soon-Beom; Dwyer, Dominic; Kim, Jae-Won; Park, Eun-Jin; Shin, Min-Sup; Kim, Boong-Nyun; Yoo, Hee-Jeong; Cho, In-Hee; Bhang, Soo-Young; Hong, Yun-Chul; Pantelis, Christos; Cho, Soo-Churl

    2014-08-01

    This study compared children who experience attention-deficit/hyperactivity disorder (ADHD) symptoms but do not meet criteria (i.e., subthreshold ADHD) with those with the full syndrome and healthy controls. Presence of ADHD symptoms was determined in a nationwide community sample of 921 children, aged 8-11 years. The main outcome measures comprised attentional symptoms, comorbidity profiles, academic performance, and neurocognitive ability (i.e., ADHD Rating Scale, Child Behavior Checklist, Learning Disability Evaluation Scale, and Stroop Color-Word Test, respectively). Subthreshold ADHD was equally prevalent in boys and girls, and more prevalent in low-income families. Throughout all the outcome measurements, subthreshold ADHD was both a significantly milder condition than full syndrome ADHD and a significantly more severe condition than non-ADHD status. The findings were consistent across the total as well as the subtest scores, and after correction for multiple comparisons (p < 0.0017). Children with subthreshold ADHD were found to experience significant symptoms and functional impairments. The results of this study support the clinical relevance of subthreshold ADHD in a childhood population. Subthreshold diagnostic criteria for ADHD may be more sensitive in detecting ADHD symptoms in girls than the full syndrome criteria, and subthreshold clinical, cognitive, and behavioral symptoms of ADHD may occur in a subset of children who are possibly more sensitive to their environment. Further consideration about the diagnostic threshold for ADHD may particularly benefit girls and children in low-income families.

  19. 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. © 2016 Wiley Periodicals, Inc.

  20. The occurrence of earlier changes in family dynamics and friendship conflict predicting adolescent functional somatic symptoms: A large-scale prospective study.

    PubMed

    Marshall, Emma M; van Dulmen, Manfred H M; Stigall, Logan A

    2017-10-01

    To better understand the role earlier stressful environments have in predicting functional somatic symptoms (FSS) in late adolescence, this study explores the effect the occurrence of earlier changes in family dynamics and friendship conflict have on FSS. We used data from the Consortium for Longitudinal Studies on Child Abuse and Neglect (N = 1,314), a large, prospective study of children at risk for maltreatment and their parent/caregiver from approximately 4 to 18 years of age. We found a significant, small (Effect Size = .10), positive association between the frequency of family dynamic change during middle childhood (ages 6-12 years) and FSS at age 18 but not during middle adolescence (ages 14 and 16). Conflict with a same-sex best friend at age 16 moderated the association between the frequency of change and FSS. The frequency of family dynamic change in middle childhood and middle adolescence was associated with greater FSS among those who reported greater conflict but not for those who reported experiencing lower conflict. Overall, these effects were specific to friendship conflict and remained when other friendship processes (intimacy and companionship) were included, did not generalize to anxiety/depressive symptoms, and predicted FSS without comorbid anxiety/depressive symptoms. No gender differences were found. The change-conflict interaction differed according to type of family dynamic change (parental vs. residential). Findings emphasize how earlier exposure to frequent changes in family dynamics in middle childhood is particularly associated with late-adolescent health, especially in the context of greater friendship conflict. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  1. 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

  2. Jovian large-scale stratospheric circulation

    NASA Technical Reports Server (NTRS)

    West, R. A.; Friedson, A. J.; Appleby, J. F.

    1992-01-01

    An attempt is made to diagnose the annual-average mean meridional residual Jovian large-scale stratospheric circulation from observations of the temperature and reflected sunlight that reveal the morphology of the aerosol heating. The annual mean solar heating, total radiative flux divergence, mass stream function, and Eliassen-Palm flux divergence are shown. The stratospheric radiative flux divergence is dominated the high latitudes by aerosol absorption. Between the 270 and 100 mbar pressure levels, where there is no aerosol heating in the model, the structure of the circulation at low- to midlatitudes is governed by the meridional variation of infrared cooling in association with the variation of zonal mean temperatures observed by IRIS. The principal features of the vertical velocity profile found by Gierasch et al. (1986) are recovered in the present calculation.

  3. Organised convection embedded in a large-scale flow

    NASA Astrophysics Data System (ADS)

    Naumann, Ann Kristin; Stevens, Bjorn; Hohenegger, Cathy

    2017-04-01

    In idealised simulations of radiative convective equilibrium, convection aggregates spontaneously from randomly distributed convective cells into organized mesoscale convection despite homogeneous boundary conditions. Although these simulations apply very idealised setups, the process of self-aggregation is thought to be relevant for the development of tropical convective systems. One feature that idealised simulations usually neglect is the occurrence of a large-scale background flow. In the tropics, organised convection is embedded in a large-scale circulation system, which advects convection in along-wind direction and alters near surface convergence in the convective areas. A large-scale flow also modifies the surface fluxes, which are expected to be enhanced upwind of the convective area if a large-scale flow is applied. Convective clusters that are embedded in a large-scale flow therefore experience an asymmetric component of the surface fluxes, which influences the development and the pathway of a convective cluster. In this study, we use numerical simulations with explicit convection and add a large-scale flow to the established setup of radiative convective equilibrium. We then analyse how aggregated convection evolves when being exposed to wind forcing. The simulations suggest that convective line structures are more prevalent if a large-scale flow is present and that convective clusters move considerably slower than advection by the large-scale flow would suggest. We also study the asymmetric component of convective aggregation due to enhanced surface fluxes, and discuss the pathway and speed of convective clusters as a function of the large-scale wind speed.

  4. 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.

  5. 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

  6. Redshift distortions of galaxy correlation functions

    NASA Astrophysics Data System (ADS)

    Fry, J. N.; Gaztanaga, Enrique

    1994-04-01

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

  7. Redshift distortions of galaxy correlation functions

    NASA Astrophysics Data System (ADS)

    Fry, J. N.; Gaztanaga, E.

    1993-05-01

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

  8. Large-scale transport across narrow gaps in rod bundles

    SciTech Connect

    Guellouz, M.S.; Tavoularis, S.

    1995-09-01

    Flow visualization and how-wire anemometry were used to investigate the velocity field in a rectangular channel containing a single cylindrical rod, which could be traversed on the centreplane to form gaps of different widths with the plane wall. The presence of large-scale, quasi-periodic structures in the vicinity of the gap has been demonstrated through flow visualization, spectral analysis and space-time correlation measurements. These structures are seen to exist even for relatively large gaps, at least up to W/D=1.350 (W is the sum of the rod diameter, D, and the gap width). The above measurements appear to compatible with the field of a street of three-dimensional, counter-rotating vortices, whose detailed structure, however, remains to be determined. The convection speed and the streamwise spacing of these vortices have been determined as functions of the gap size.

  9. 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.

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

    PubMed

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

    2013-01-01

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

  11. 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.

  12. Correlation dynamics of Green functions

    NASA Astrophysics Data System (ADS)

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

    1994-06-01

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

  13. 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…

  14. Automating large-scale reactor systems

    SciTech Connect

    Kisner, R.A.

    1985-01-01

    This paper conveys a philosophy for developing automated large-scale control systems that behave in an integrated, intelligent, flexible manner. Methods for operating large-scale systems under varying degrees of equipment degradation are discussed, and a design approach that separates the effort into phases is suggested. 5 refs., 1 fig.

  15. Identifying large-scale brain networks in fragile X syndrome.

    PubMed

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

    2013-11-01

    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. 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. 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. Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression. 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. 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 insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging

  16. Voids in the Large-Scale Structure

    NASA Astrophysics Data System (ADS)

    El-Ad, Hagai; Piran, Tsvi

    1997-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Miralda-Escude, Jordi

    1991-01-01

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

  18. Large scale structure of the sun's corona

    NASA Astrophysics Data System (ADS)

    Kundu, Mukul R.

    Results concerning the large-scale structure of the solar corona obtained by observations at meter-decameter wavelengths are reviewed. Coronal holes observed on the disk at multiple frequencies show the radial and azimuthal geometry of the hole. At the base of the hole there is good correspondence to the chromospheric signature in He I 10,830 A, but at greater heights the hole may show departures from symmetry. Two-dimensional imaging of weak-type III bursts simultaneously with the HAO SMM coronagraph/polarimeter measurements indicate that these bursts occur along elongated features emanating from the quiet sun, corresponding in position angle to the bright coronal streamers. It is shown that the densest regions of streamers and the regions of maximum intensity of type II bursts coincide closely. Non-flare-associated type II/type IV bursts associated with coronal streamer disruption events are studied along with correlated type II burst emissions originating from distant centers on the sun.

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  20. 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.

  1. Large Scale Metal Additive Techniques Review

    SciTech Connect

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

    2016-01-01

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

  2. 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.

  3. The Large -scale Distribution of Galaxies

    NASA Astrophysics Data System (ADS)

    Flin, Piotr

    A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.

  4. 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

  5. The Influence of Large-scale Environments on Galaxy Properties

    NASA Astrophysics Data System (ADS)

    Wei, Yu-qing; Wang, Lei; Dai, Cai-ping

    2017-07-01

    The star formation properties of galaxies and their dependence on environments play an important role for understanding the formation and evolution of galaxies. Using the galaxy sample of the Sloan Digital Sky Survey (SDSS), different research groups have studied the physical properties of galaxies and their large-scale environments. Here, using the filament catalog from Tempel et al. and the galaxy catalog of large-scale structure classification from Wang et al., and taking the influence of the galaxy morphology, high/low local density environment, and central (satellite) galaxy into consideration, we have found that the properties of galaxies are correlated with their residential large-scale environments: the SSFR (specific star formation rate) and SFR (star formation rate) strongly depend on the large-scale environment for spiral galaxies and satellite galaxies, but this dependence is very weak for elliptical galaxies and central galaxies, and the influence of large-scale environments on galaxies in low density region is more sensitive than that in high density region. The above conclusions remain valid even for the galaxies with the same mass. In addition, the SSFR distributions derived from the catalogs of Tempel et al. and Wang et al. are not entirely consistent.

  6. 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.

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

    PubMed

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

    2015-03-01

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

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

    SciTech Connect

    Fujimura, R.K.

    1992-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  14. 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.

  15. 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…

  16. Newton Methods for Large Scale Problems in Machine Learning

    ERIC Educational Resources Information Center

    Hansen, Samantha Leigh

    2014-01-01

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

  17. Newton Methods for Large Scale Problems in Machine Learning

    ERIC Educational Resources Information Center

    Hansen, Samantha Leigh

    2014-01-01

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

  18. 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…

  19. 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

  20. 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.

  1. Large-scale multimedia modeling applications

    SciTech Connect

    Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

    1995-08-01

    Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications.

  2. 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…

  3. 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…

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

    SciTech Connect

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

    2013-10-20

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

  5. Large scale simulations of Brownian suspensions

    NASA Astrophysics Data System (ADS)

    Viera, Marc Nathaniel

    Particle suspensions occur in a wide variety of natural and engineering materials. Some examples are colloids, polymers, paints, and slurries. These materials exhibit complex behavior owing to the forces which act among the particles and are transmitted through the fluid medium. Depending on the application, particle sizes range from large macroscopic molecules of 100mum to smaller colloidal particles in the range of 10nm to 1mum. Particles of this size interact though interparticle forces such as electrostatic and van der Waals, as well as hydrodynamic forces transmitted through the fluid medium. Additionally, the particles are subjected to random thermal fluctuations in the fluid giving rise to Brownian motion. The central objective of our research is to develop efficient numerical algorithms for the large scale dynamic simulation of particle suspensions. While previous methods have incurred a computational cost of O(N3), where N is the number of particles, we have developed a novel algorithm capable of solving this problem in O(N ln N) operations. This has allowed us to perform dynamic simulations with up to 64,000 particles and Monte Carlo realizations of up to 1 million particles. Our algorithm follows a Stokesian dynamics formulation by evaluating many-body hydrodynamic interactions using a far-field multipole expansion combined with a near-field lubrication correction. The breakthrough O(N ln N) scaling is obtained by employing a Particle-Mesh-Ewald (PME) approach whereby near-field interactions are evaluated directly and far-field interactions are evaluated using a grid based velocity computed with FFT's. This approach is readily extended to include the effects of Brownian motion. For interacting particles, the fluctuation-dissipation theorem requires that the individual Brownian forces satisfy a correlation based on the N body resistance tensor R. The accurate modeling of these forces requires the computation of a matrix square root R 1/2 for matrices up

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

    NASA Astrophysics Data System (ADS)

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

    2002-08-01

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

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

    SciTech Connect

    Senatore, Leonardo

    2015-11-01

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

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

    DOE PAGES

    Senatore, Leonardo

    2015-11-05

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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Henderson, Nicholas C.

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

  11. Uplink channel estimation error for large scale MIMO system

    NASA Astrophysics Data System (ADS)

    Albdran, Saleh; Alshammari, Ahmad; Matin, Mohammad

    2016-09-01

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

  12. 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.

  13. 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.

  14. Large-scale Advanced Propfan (LAP) program

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  15. Large-scale fibre-array multiplexing

    SciTech Connect

    Cheremiskin, I V; Chekhlova, T K

    2001-05-31

    The possibility of creating a fibre multiplexer/demultiplexer with large-scale multiplexing without any basic restrictions on the number of channels and the spectral spacing between them is shown. The operating capacity of a fibre multiplexer based on a four-fibre array ensuring a spectral spacing of 0.7 pm ({approx} 10 GHz) between channels is demonstrated. (laser applications and other topics in quantum electronics)

  16. Modeling Human Behavior at a Large Scale

    DTIC Science & Technology

    2012-01-01

    Discerning intentions in dynamic human action. Trends in Cognitive Sciences , 5(4):171 – 178, 2001. Shirli Bar-David, Israel Bar-David, Paul C. Cross, Sadie...Limits of predictability in human mobility. Science , 327(5968):1018, 2010. S.A. Stouffer. Intervening opportunities: a theory relating mobility and...Modeling Human Behavior at a Large Scale by Adam Sadilek Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

  17. Large-Scale Aerosol Modeling and Analysis

    DTIC Science & Technology

    2008-09-30

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

  18. Economically viable large-scale hydrogen liquefaction

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  19. Large-Scale Visual Data Analysis

    NASA Astrophysics Data System (ADS)

    Johnson, Chris

    2014-04-01

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

  20. Large-scale neuromorphic computing systems

    NASA Astrophysics Data System (ADS)

    Furber, Steve

    2016-10-01

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

  1. 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…

  2. 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…

  3. 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.

  4. Elucidation of SESANS correlation functions through model

    SciTech Connect

    Shew, Chwen-Yang; Chen, Wei-Ren

    2012-01-01

    Several single-modal Debye correlation functions are closely examined to elucidate the behavior of their corresponding SESANS (Spin Echo Small Angle Neutron Scattering) correlation functions. We nd that the upper bound of a Debye correlation function and of its SESANS correlation func- tion is identical. For discrete Debye correlation functions, the peak of SESANS correlation function emerges at their rst discrete point, whereas for continuous Debye correlation functions with greater width, the peak position shifts to a greater value. In both cases, the intensity and shape of the peak of the SESANS correlation function are determined by the width of the normalized Debye correlation functions. In the application, we mimic the intramolecular and intermolecular Debye correlation functions of liquids composed of interacting particles by using the simple models to elucidate their competition in the SESANS correlation function. Our calculations show that the position of the rst minimum of SESANS correlation function shifts to a smaller value as inter- molecular attraction or correlation is enhanced. The minimum value can be positive or negative, and the positive values are observed for the cases equivalent to stronger intermolecular attraction, consistent with literature results based on more sophisticated liquid state theory and simulations.

  5. 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.

  6. Loops in inflationary correlation functions

    NASA Astrophysics Data System (ADS)

    Tanaka, Takahiro; Urakawa, Yuko

    2013-12-01

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

  7. On a Game of Large-Scale Projects Competition

    NASA Astrophysics Data System (ADS)

    Nikonov, Oleg I.; Medvedeva, Marina A.

    2009-09-01

    The paper is devoted to game-theoretical control problems motivated by economic decision making situations arising in realization of large-scale projects, such as designing and putting into operations the new gas or oil pipelines. A non-cooperative two player game is considered with payoff functions of special type for which standard existence theorems and algorithms for searching Nash equilibrium solutions are not applicable. The paper is based on and develops the results obtained in [1]-[5].

  8. 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.

  9. What is a large-scale dynamo?

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  10. Large-scale brightenings associated with flares

    NASA Technical Reports Server (NTRS)

    Mandrini, Cristina H.; Machado, Marcos E.

    1992-01-01

    It is shown that large-scale brightenings (LSBs) associated with solar flares, similar to the 'giant arches' discovered by Svestka et al. (1982) in images obtained by the SSM HXIS hours after the onset of two-ribbon flares, can also occur in association with confined flares in complex active regions. For these events, a clear link between the LSB and the underlying flare is clearly evident from the active-region magnetic field topology. The implications of these findings are discussed within the framework of the interacting loops of flares and the giant arch phenomenology.

  11. 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.

  12. 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.

  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. 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.

  15. Large-scale Heterogeneous Network Data Analysis

    DTIC Science & Technology

    2012-07-31

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

  16. Two-particle correlation function and dihadron correlation approach

    SciTech Connect

    Vechernin, V. V. Ivanov, K. O.; Neverov, D. I.

    2016-09-15

    It is shown that, in the case of asymmetric nuclear interactions, the application of the traditional dihadron correlation approach to determining a two-particle correlation function C may lead to a form distorted in relation to the canonical pair correlation function {sub C}{sup 2}. This result was obtained both by means of exact analytic calculations of correlation functions within a simple string model for proton–nucleus and deuteron–nucleus collisions and by means of Monte Carlo simulations based on employing the HIJING event generator. It is also shown that the method based on studying multiplicity correlations in two narrow observation windows separated in rapidity makes it possible to determine correctly the canonical pair correlation function C{sub 2} for all cases, including the case where the rapidity distribution of product particles is not uniform.

  17. Two-particle correlation function and dihadron correlation approach

    NASA Astrophysics Data System (ADS)

    Vechernin, V. V.; Ivanov, K. O.; Neverov, D. I.

    2016-09-01

    It is shown that, in the case of asymmetric nuclear interactions, the application of the traditional dihadron correlation approach to determining a two-particle correlation function C may lead to a form distorted in relation to the canonical pair correlation function C 2. This result was obtained both by means of exact analytic calculations of correlation functions within a simple string model for proton-nucleus and deuteron-nucleus collisions and by means of Monte Carlo simulations based on employing the HIJING event generator. It is also shown that the method based on studying multiplicity correlations in two narrow observation windows separated in rapidity makes it possible to determine correctly the canonical pair correlation function C 2 for all cases, including the case where the rapidity distribution of product particles is not uniform.

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

    NASA Astrophysics Data System (ADS)

    Aiola, Simone

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

  19. Developmental changes in large-scale network connectivity in autism.

    PubMed

    Nomi, Jason S; Uddin, Lucina Q

    2015-01-01

    Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD. The current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups. We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11-18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or

  20. 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.

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

    NASA Technical Reports Server (NTRS)

    Melott, Adrian L.

    1991-01-01

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

  2. Internationalization Measures in Large Scale Research Projects

    NASA Astrophysics Data System (ADS)

    Soeding, Emanuel; Smith, Nancy

    2017-04-01

    Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.

  3. 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.

  4. Large-scale Intelligent Transporation Systems simulation

    SciTech Connect

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

    1995-06-01

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

  5. 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.

  6. Large-scale Globally Propagating Coronal Waves.

    PubMed

    Warmuth, Alexander

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

  7. Channel capacity of next generation large scale MIMO systems

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

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

    PubMed Central

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

    2002-01-01

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

  9. Large-scale flow generation by inhomogeneous helicity.

    PubMed

    Yokoi, N; Brandenburg, A

    2016-03-01

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

  10. 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

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

    PubMed

    Tian, Yingjie; Ping, Yuan

    2014-02-01

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

  12. 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.

  13. 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.

  14. Efficient, large scale separation of coal macerals

    SciTech Connect

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

    1988-01-01

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

  15. Primer design for large scale sequencing.

    PubMed Central

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

    1998-01-01

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

  16. 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.

  17. 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.

  18. Large-scale optimization of neuron arbors

    NASA Astrophysics Data System (ADS)

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

    1999-05-01

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

  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. Large scale preparation of pure phycobiliproteins.

    PubMed

    Padgett, M P; Krogmann, D W

    1987-01-01

    This paper describes simple procedures for the purification of large amounts of phycocyanin and allophycocyanin from the cyanobacterium Microcystis aeruginosa. A homogeneous natural bloom of this organism provided hundreds of kilograms of cells. Large samples of cells were broken by freezing and thawing. Repeated extraction of the broken cells with distilled water released phycocyanin first, then allophycocyanin, and provides supporting evidence for the current models of phycobilisome structure. The very low ionic strength of the aqueous extracts allowed allophycocyanin release in a particulate form so that this protein could be easily concentrated by centrifugation. Other proteins in the extract were enriched and concentrated by large