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.

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…

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.

Minimum important differences for the patient-specific functional scale, 4 region-specific outcome measures, and the numeric pain rating scale.

PubMed

Abbott, J Haxby; Schmitt, John

2014-08-01

Multicenter, prospective, longitudinal cohort study. To investigate the minimum important difference (MID) of the Patient-Specific Functional Scale (PSFS), 4 region-specific outcome measures, and the numeric pain rating scale (NPRS) across 3 levels of patient-perceived global rating of change in a clinical setting. The MID varies depending on the external anchor defining patient-perceived "importance." The MID for the PSFS has not been established across all body regions. One thousand seven hundred eight consecutive patients with musculoskeletal disorders were recruited from 5 physical therapy clinics. The PSFS, NPRS, and 4 region-specific outcome measures-the Oswestry Disability Index, Neck Disability Index, Upper Extremity Functional Index, and Lower Extremity Functional Scale-were assessed at the initial and final physical therapy visits. Global rating of change was assessed at the final visit. MID was calculated for the PSFS and NPRS (overall and for each body region), and for each region-specific outcome measure, across 3 levels of change defined by the global rating of change (small, medium, large change) using receiver operating characteristic curve methodology. The MID for the PSFS (on a scale from 0 to 10) ranged from 1.3 (small change) to 2.3 (medium change) to 2.7 (large change), and was relatively stable across body regions. MIDs for the NPRS (-1.5 to -3.5), Oswestry Disability Index (-12), Neck Disability Index (-14), Upper Extremity Functional Index (6 to 11), and Lower Extremity Functional Scale (9 to 16) are also reported. We reported the MID for small, medium, and large patient-perceived change on the PSFS, NPRS, Oswestry Disability Index, Neck Disability Index, Upper Extremity Functional Index, and Lower Extremity Functional Scale for use in clinical practice and research.

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.

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…

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Scale-space measures for graph topology link protein network architecture to function.

PubMed

Hulsman, Marc; Dimitrakopoulos, Christos; de Ridder, Jeroen

2014-06-15

The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale). In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions-genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture. Matlab(TM) code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA © The Author 2014. Published by Oxford University Press.

The up-scaling of ecosystem functions in a heterogeneous world

NASA Astrophysics Data System (ADS)

Lohrer, Andrew M.; Thrush, Simon F.; Hewitt, Judi E.; Kraan, Casper

2015-05-01

Earth is in the midst of a biodiversity crisis that is impacting the functioning of ecosystems and the delivery of valued goods and services. However, the implications of large scale species losses are often inferred from small scale ecosystem functioning experiments with little knowledge of how the dominant drivers of functioning shift across scales. Here, by integrating observational and manipulative experimental field data, we reveal scale-dependent influences on primary productivity in shallow marine habitats, thus demonstrating the scalability of complex ecological relationships contributing to coastal marine ecosystem functioning. Positive effects of key consumers (burrowing urchins, Echinocardium cordatum) on seafloor net primary productivity (NPP) elucidated by short-term, single-site experiments persisted across multiple sites and years. Additional experimentation illustrated how these effects amplified over time, resulting in greater primary producer biomass sediment chlorophyll a content (Chla) in the longer term, depending on climatic context and habitat factors affecting the strengths of mutually reinforcing feedbacks. The remarkable coherence of results from small and large scales is evidence of real-world ecosystem function scalability and ecological self-organisation. This discovery provides greater insights into the range of responses to broad-scale anthropogenic stressors in naturally heterogeneous environmental settings.

The up-scaling of ecosystem functions in a heterogeneous world

PubMed Central

Lohrer, Andrew M.; Thrush, Simon F.; Hewitt, Judi E.; Kraan, Casper

2015-01-01

Earth is in the midst of a biodiversity crisis that is impacting the functioning of ecosystems and the delivery of valued goods and services. However, the implications of large scale species losses are often inferred from small scale ecosystem functioning experiments with little knowledge of how the dominant drivers of functioning shift across scales. Here, by integrating observational and manipulative experimental field data, we reveal scale-dependent influences on primary productivity in shallow marine habitats, thus demonstrating the scalability of complex ecological relationships contributing to coastal marine ecosystem functioning. Positive effects of key consumers (burrowing urchins, Echinocardium cordatum) on seafloor net primary productivity (NPP) elucidated by short-term, single-site experiments persisted across multiple sites and years. Additional experimentation illustrated how these effects amplified over time, resulting in greater primary producer biomass sediment chlorophyll a content (Chla) in the longer term, depending on climatic context and habitat factors affecting the strengths of mutually reinforcing feedbacks. The remarkable coherence of results from small and large scales is evidence of real-world ecosystem function scalability and ecological self-organisation. This discovery provides greater insights into the range of responses to broad-scale anthropogenic stressors in naturally heterogeneous environmental settings. PMID:25993477

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. © 2015 Wiley Periodicals, Inc.

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…

Treatment effect of methylphenidate on intrinsic functional brain network in medication-naïve ADHD children: A multivariate analysis.

PubMed

Yoo, Jae Hyun; Kim, Dohyun; Choi, Jeewook; Jeong, Bumseok

2018-04-01

Methylphenidate is a first-line therapeutic option for treating attention-deficit/hyperactivity disorder (ADHD); however, elicited changes on resting-state functional networks (RSFNs) are not well understood. This study investigated the treatment effect of methylphenidate using a variety of RSFN analyses and explored the collaborative influences of treatment-relevant RSFN changes in children with ADHD. Resting-state functional magnetic resonance imaging was acquired from 20 medication-naïve ADHD children before methylphenidate treatment and twelve weeks later. Changes in large-scale functional connectivity were defined using independent component analysis with dual regression and graph theoretical analysis. The amplitude of low frequency fluctuation (ALFF) was measured to investigate local spontaneous activity alteration. Finally, significant findings were recruited to random forest regression to identify the feature subset that best explains symptom improvement. After twelve weeks of methylphenidate administration, large-scale connectivity was increased between the left fronto-parietal RSFN and the left insula cortex and the right fronto-parietal and the brainstem, while the clustering coefficient (CC) of the global network and nodes, the left fronto-parietal, cerebellum, and occipital pole-visual network, were decreased. ALFF was increased in the bilateral superior parietal cortex and decreased in the right inferior fronto-temporal area. The subset of the local and large-scale RSFN changes, including widespread ALFF changes, the CC of the global network and the cerebellum, could explain the 27.1% variance of the ADHD Rating Scale and 13.72% of the Conner's Parent Rating Scale. Our multivariate approach suggests that the neural mechanism of methylphenidate treatment could be associated with alteration of spontaneous activity in the superior parietal cortex or widespread brain regions as well as functional segregation of the large-scale intrinsic functional network.

Lagrangian space consistency relation for large scale structure

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

Horn, Bart; Hui, Lam; Xiao, Xiao

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

Lagrangian space consistency relation for large scale structure

DOE PAGES

Horn, Bart; Hui, Lam; Xiao, Xiao

2015-09-29

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

Relative importance of local- and large-scale drivers of alpine soil microarthropod communities.

PubMed

Mitchell, Ruth J; Urpeth, Hannah M; Britton, Andrea J; Black, Helaina; Taylor, Astrid R

2016-11-01

Nitrogen (N) deposition and climate are acknowledged drivers of change in biodiversity and ecosystem function at large scales. However, at a local scale, their impact on functions and community structure of organisms is filtered by drivers like habitat quality and food quality/availability. This study assesses the relative impact of large-scale factors, N deposition and climate (rainfall and temperature), versus local-scale factors of habitat quality and food quality/availability on soil fauna communities at 15 alpine moss-sedge heaths along an N deposition gradient in the UK. Habitat quality and food quality/availability were the primary drivers of microarthropod communities. No direct impacts of N deposition on the microarthropod community were observed, but induced changes in habitat quality (decline in moss cover and depth) and food quality (decreased vegetation C:N) associated with increased N deposition strongly suggest an indirect impact of N. Habitat quality and climate explained variation in the composition of the Oribatida, Mesostigmata, and Collembola communities, while only habitat quality significantly impacted the Prostigmata. Food quality and prey availability were important in explaining the composition of the oribatid and mesostigmatid mite communities, respectively. This study shows that, in alpine habitats, soil microarthropod community structure responds most strongly to local-scale variation in habitat quality and food availability rather than large-scale variation in climate and pollution. However, given the strong links between N deposition and the key habitat quality parameters, we conclude that N deposition indirectly drives changes in the soil microarthropod community, suggesting a mechanism by which large-scale drivers indirectly impacts these functionally important groups.

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.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

A behavioral-level HDL description of SFQ logic circuits for quantitative performance analysis of large-scale SFQ digital systems

NASA Astrophysics Data System (ADS)

Matsuzaki, F.; Yoshikawa, N.; Tanaka, M.; Fujimaki, A.; Takai, Y.

2003-10-01

Recently many single flux quantum (SFQ) logic circuits containing several thousands of Josephson junctions have been designed successfully by using digital domain simulation based on the hard ware description language (HDL). In the present HDL-based design of SFQ circuits, a structure-level HDL description has been used, where circuits are made up of basic gate cells. However, in order to analyze large-scale SFQ digital systems, such as a microprocessor, more higher-level circuit abstraction is necessary to reduce the circuit simulation time. In this paper we have investigated the way to describe functionality of the large-scale SFQ digital circuits by a behavior-level HDL description. In this method, the functionality and the timing of the circuit block is defined directly by describing their behavior by the HDL. Using this method, we can dramatically reduce the simulation time of large-scale SFQ digital circuits.

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

A large scale GIS geodatabase of soil parameters supporting the modeling of conservation practice alternatives in the United States

USDA-ARS?s Scientific Manuscript database

Water quality modeling requires across-scale support of combined digital soil elements and simulation parameters. This paper presents the unprecedented development of a large spatial scale (1:250,000) ArcGIS geodatabase coverage designed as a functional repository of soil-parameters for modeling an...

Backscattering from a Gaussian distributed, perfectly conducting, rough surface

NASA Technical Reports Server (NTRS)

Brown, G. S.

1977-01-01

The problem of scattering by random surfaces possessing many scales of roughness is analyzed. The approach is applicable to bistatic scattering from dielectric surfaces, however, this specific analysis is restricted to backscattering from a perfectly conducting surface in order to more clearly illustrate the method. The surface is assumed to be Gaussian distributed so that the surface height can be split into large and small scale components, relative to the electromagnetic wavelength. A first order perturbation approach is employed wherein the scattering solution for the large scale structure is perturbed by the small scale diffraction effects. The scattering from the large scale structure is treated via geometrical optics techniques. The effect of the large scale surface structure is shown to be equivalent to a convolution in k-space of the height spectrum with the following: the shadowing function, a polarization and surface slope dependent function, and a Gaussian factor resulting from the unperturbed geometrical optics solution. This solution provides a continuous transition between the near normal incidence geometrical optics and wide angle Bragg scattering results.

Lagrangian space consistency relation for large scale structure

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

Horn, Bart; Hui, Lam; Xiao, Xiao, E-mail: bh2478@columbia.edu, E-mail: lh399@columbia.edu, E-mail: xx2146@columbia.edu

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.more » 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.« less

Black holes from large N singlet models

NASA Astrophysics Data System (ADS)

Amado, Irene; Sundborg, Bo; Thorlacius, Larus; Wintergerst, Nico

2018-03-01

The emergent nature of spacetime geometry and black holes can be directly probed in simple holographic duals of higher spin gravity and tensionless string theory. To this end, we study time dependent thermal correlation functions of gauge invariant observables in suitably chosen free large N gauge theories. At low temperature and on short time scales the correlation functions encode propagation through an approximate AdS spacetime while interesting departures emerge at high temperature and on longer time scales. This includes the existence of evanescent modes and the exponential decay of time dependent boundary correlations, both of which are well known indicators of bulk black holes in AdS/CFT. In addition, a new time scale emerges after which the correlation functions return to a bulk thermal AdS form up to an overall temperature dependent normalization. A corresponding length scale was seen in equal time correlation functions in the same models in our earlier work.

Disappearance of Anisotropic Intermittency in Large-amplitude MHD Turbulence and Its Comparison with Small-amplitude MHD Turbulence

NASA Astrophysics Data System (ADS)

Yang, Liping; Zhang, Lei; He, Jiansen; Tu, Chuanyi; Li, Shengtai; Wang, Xin; Wang, Linghua

2018-03-01

Multi-order structure functions in the solar wind are reported to display a monofractal scaling when sampled parallel to the local magnetic field and a multifractal scaling when measured perpendicularly. Whether and to what extent will the scaling anisotropy be weakened by the enhancement of turbulence amplitude relative to the background magnetic strength? In this study, based on two runs of the magnetohydrodynamic (MHD) turbulence simulation with different relative levels of turbulence amplitude, we investigate and compare the scaling of multi-order magnetic structure functions and magnetic probability distribution functions (PDFs) as well as their dependence on the direction of the local field. The numerical results show that for the case of large-amplitude MHD turbulence, the multi-order structure functions display a multifractal scaling at all angles to the local magnetic field, with PDFs deviating significantly from the Gaussian distribution and a flatness larger than 3 at all angles. In contrast, for the case of small-amplitude MHD turbulence, the multi-order structure functions and PDFs have different features in the quasi-parallel and quasi-perpendicular directions: a monofractal scaling and Gaussian-like distribution in the former, and a conversion of a monofractal scaling and Gaussian-like distribution into a multifractal scaling and non-Gaussian tail distribution in the latter. These results hint that when intermittencies are abundant and intense, the multifractal scaling in the structure functions can appear even if it is in the quasi-parallel direction; otherwise, the monofractal scaling in the structure functions remains even if it is in the quasi-perpendicular direction.

Large-scale functional models of visual cortex for remote sensing

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

Brumby, Steven P; Kenyon, Garrett; Rasmussen, Craig E

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 simplemore » 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.« less

Effects of biasing on the galaxy power spectrum at large scales

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

Beltran Jimenez, Jose; Departamento de Fisica Teorica, Universidad Complutense de Madrid, 28040, Madrid; Durrer, Ruth

2011-05-15

In this paper we study the effect of biasing on the power spectrum at large scales. We show that even though nonlinear biasing does introduce a white noise contribution on large scales, the P(k){proportional_to}k{sup n} behavior of the matter power spectrum on large scales may still be visible and above the white noise for about one decade. We show, that the Kaiser biasing scheme which leads to linear bias of the correlation function on large scales, also generates a linear bias of the power spectrum on rather small scales. This is a consequence of the divergence on small scales ofmore » the pure Harrison-Zeldovich spectrum. However, biasing becomes k dependent if we damp the underlying power spectrum on small scales. We also discuss the effect of biasing on the baryon acoustic oscillations.« less

The luminosity function for the CfA redshift survey slices

NASA Technical Reports Server (NTRS)

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

1989-01-01

The luminosity function for two complete slices of the extension of the CfA redshift survey is calculated. The nonparametric technique of Lynden-Bell (1971) and Turner (1979) is used to determine the shape for the luminosity function of the 12 deg slice of the redshift survey. The amplitude of the luminosity function is determined, taking large-scale inhomogeneities into account. The effects of the Malmquist bias on a magnitude-limited redshift survey are examined, showing that the random errors in the magnitudes for the 12 deg slice affect both the determination of the luminosity function and the spatial density constrast of large scale structures.

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.

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package.

PubMed

Womack, James C; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-28

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package

NASA Astrophysics Data System (ADS)

Womack, James C.; Mardirossian, Narbe; Head-Gordon, Martin; Skylaris, Chris-Kriton

2016-11-01

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

Highly efficient model updating for structural condition assessment of large-scale bridges.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

PubMed Central

Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.

2014-01-01

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949

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

Performance of Grey Wolf Optimizer on large scale problems

NASA Astrophysics Data System (ADS)

Gupta, Shubham; Deep, Kusum

2017-01-01

For solving nonlinear continuous problems of optimization numerous nature inspired optimization techniques are being proposed in literature which can be implemented to solve real life problems wherein the conventional techniques cannot be applied. Grey Wolf Optimizer is one of such technique which is gaining popularity since the last two years. The objective of this paper is to investigate the performance of Grey Wolf Optimization Algorithm on large scale optimization problems. The Algorithm is implemented on 5 common scalable problems appearing in literature namely Sphere, Rosenbrock, Rastrigin, Ackley and Griewank Functions. The dimensions of these problems are varied from 50 to 1000. The results indicate that Grey Wolf Optimizer is a powerful nature inspired Optimization Algorithm for large scale problems, except Rosenbrock which is a unimodal function.

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…

Stability of large-scale systems with stable and unstable subsystems.

NASA Technical Reports Server (NTRS)

Grujic, Lj. T.; Siljak, D. D.

1972-01-01

The purpose of this paper is to develop new methods for constructing vector Liapunov functions and broaden the application of Liapunov'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. With minor technical adjustments, the same criterion can be used to determine connective asymptotic stability of large-scale systems subject to structural perturbations. By redefining the constraints imposed on the interconnections among the subsystems, the considered class of systems is broadened in an essential way to include composite systems with unstable subsystems. In this way, the theory is brought substantially closer to reality since stability of all subsystems is no longer a necessary assumption in establishing stability of the overall composite system.

Breaking of scale invariance in the time dependence of correlation functions in isotropic and homogeneous turbulence

NASA Astrophysics Data System (ADS)

Tarpin, Malo; Canet, Léonie; Wschebor, Nicolás

2018-05-01

In this paper, we present theoretical results on the statistical properties of stationary, homogeneous, and isotropic turbulence in incompressible flows in three dimensions. Within the framework of the non-perturbative renormalization group, we derive a closed renormalization flow equation for a generic n-point correlation (and response) function for large wave-numbers with respect to the inverse integral scale. The closure is obtained from a controlled expansion and relies on extended symmetries of the Navier-Stokes field theory. It yields the exact leading behavior of the flow equation at large wave-numbers |p→ i| and for arbitrary time differences ti in the stationary state. Furthermore, we obtain the form of the general solution of the corresponding fixed point equation, which yields the analytical form of the leading wave-number and time dependence of n-point correlation functions, for large wave-numbers and both for small ti and in the limit ti → ∞. At small ti, the leading contribution at large wave-numbers is logarithmically equivalent to -α (ɛL ) 2 /3|∑tip→ i|2, where α is a non-universal constant, L is the integral scale, and ɛ is the mean energy injection rate. For the 2-point function, the (tp)2 dependence is known to originate from the sweeping effect. The derived formula embodies the generalization of the effect of sweeping to n-point correlation functions. At large wave-numbers and large ti, we show that the ti2 dependence in the leading order contribution crosses over to a |ti| dependence. The expression of the correlation functions in this regime was not derived before, even for the 2-point function. Both predictions can be tested in direct numerical simulations and in experiments.

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

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

Blas, Diego; Garny, Mathias; Sibiryakov, Sergey

2016-07-01

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

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

A density spike on astrophysical scales from an N-field waterfall transition

NASA Astrophysics Data System (ADS)

Halpern, Illan F.; Hertzberg, Mark P.; Joss, Matthew A.; Sfakianakis, Evangelos I.

2015-09-01

Hybrid inflation models are especially interesting as they lead to a spike in the density power spectrum on small scales, compared to the CMB, while also satisfying current bounds on tensor modes. Here we study hybrid inflation with N waterfall fields sharing a global SO (N) symmetry. The inclusion of many waterfall fields has the obvious advantage of avoiding topologically stable defects for N > 3. We find that it also has another advantage: it is easier to engineer models that can simultaneously (i) be compatible with constraints on the primordial spectral index, which tends to otherwise disfavor hybrid models, and (ii) produce a spike on astrophysically large length scales. The latter may have significant consequences, possibly seeding the formation of astrophysically large black holes. We calculate correlation functions of the time-delay, a measure of density perturbations, produced by the waterfall fields, as a convergent power series in both 1 / N and the field's correlation function Δ (x). We show that for large N, the two-point function is < δt (x) δt (0) > ∝Δ2 (| x |) / N and the three-point function is < δt (x) δt (y) δt (0) > ∝ Δ (| x - y |) Δ (| x |) Δ (| y |) /N2. In accordance with the central limit theorem, the density perturbations on the scale of the spike are Gaussian for large N and non-Gaussian for small N.

Large-scale self-assembly of uniform submicron silver sulfide material driven by precise pressure control

NASA Astrophysics Data System (ADS)

Qi, Juanjuan; Chen, Ke; Zhang, Shuhao; Yang, Yun; Guo, Lin; Yang, Shihe

2017-03-01

The controllable self-assembly of nanosized building blocks into larger specific structures can provide an efficient method of synthesizing novel materials with excellent properties. The self-assembly of nanocrystals by assisted means is becoming an extremely active area of research, because it provides a method of producing large-scale advanced functional materials with potential applications in the areas of energy, electronics, optics, and biologics. In this study, we applied an efficient strategy, namely, the use of ‘pressure control’ to the assembly of silver sulfide (Ag2S) nanospheres with a diameter of approximately 33 nm into large-scale, uniform Ag2S sub-microspheres with a size of about 0.33 μm. More importantly, this strategy realizes the online control of the overall reaction system, including the pressure, reaction time, and temperature, and could also be used to easily fabricate other functional materials on an industrial scale. Moreover, the thermodynamics and kinetics parameters for the thermal decomposition of silver diethyldithiocarbamate (Ag(DDTC)) are also investigated to explore the formation mechanism of the Ag2S nanosized building blocks which can be assembled into uniform sub-micron scale architecture. As a method of producing sub-micron Ag2S particles by means of the pressure-controlled self-assembly of nanoparticles, we foresee this strategy being an efficient and universally applicable option for constructing other new building blocks and assembling novel and large functional micromaterials on an industrial scale.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Universal scaling function in discrete time asymmetric exclusion processes

NASA Astrophysics Data System (ADS)

Chia, Nicholas; Bundschuh, Ralf

2005-03-01

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.

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.

Large-Angular-Scale Clustering as a Clue to the Source of UHECRs

NASA Astrophysics Data System (ADS)

Berlind, Andreas A.; Farrar, Glennys R.

We explore what can be learned about the sources of UHECRs from their large-angular-scale clustering (referred to as their "bias" by the cosmology community). Exploiting the clustering on large scales has the advantage over small-scale correlations of being insensitive to uncertainties in source direction from magnetic smearing or measurement error. In a Cold Dark Matter cosmology, the amplitude of large-scale clustering depends on the mass of the system, with more massive systems such as galaxy clusters clustering more strongly than less massive systems such as ordinary galaxies or AGN. Therefore, studying the large-scale clustering of UHECRs can help determine a mass scale for their sources, given the assumption that their redshift depth is as expected from the GZK cutoff. We investigate the constraining power of a given UHECR sample as a function of its cutoff energy and number of events. We show that current and future samples should be able to distinguish between the cases of their sources being galaxy clusters, ordinary galaxies, or sources that are uncorrelated with the large-scale structure of the universe.

Effect of helicity on the correlation time of large scales in turbulent flows

NASA Astrophysics Data System (ADS)

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

2017-11-01

Solutions of the forced Navier-Stokes equation have been conjectured to thermalize at scales larger than the forcing scale, similar to an absolute equilibrium obtained for the spectrally truncated Euler equation. Using direct numeric simulations of Taylor-Green flows and general-periodic helical flows, we present results on the probability density function, energy spectrum, autocorrelation function, and correlation time that compare the two systems. In the case of highly helical flows, we derive an analytic expression describing the correlation time for the absolute equilibrium of helical flows that is different from the E-1 /2k-1 scaling law of weakly helical flows. This model predicts a new helicity-based scaling law for the correlation time as τ (k ) ˜H-1 /2k-1 /2 . This scaling law is verified in simulations of the truncated Euler equation. In simulations of the Navier-Stokes equations the large-scale modes of forced Taylor-Green symmetric flows (with zero total helicity and large separation of scales) follow the same properties as absolute equilibrium including a τ (k ) ˜E-1 /2k-1 scaling for the correlation time. General-periodic helical flows also show similarities between the two systems; however, the largest scales of the forced flows deviate from the absolute equilibrium solutions.

The dependence of PGA and PGV on distance and magnitude inferred from Northern California ShakeMap data

USGS Publications Warehouse

Boatwright, J.; Bundock, H.; Luetgert, J.; Seekins, L.; Gee, L.; Lombard, P.

2003-01-01

We analyze peak ground velocity (PGV) and peak ground acceleration (PGA) data from 95 moderate (3.5 ??? M 100 km, the peak motions attenuate more rapidly than a simple power law (that is, r-??) can fit. Instead, we use an attenuation function that combines a fixed power law (r-0.7) with a fitted exponential dependence on distance, which is estimated as expt(-0.0063r) and exp(-0.0073r) for PGV and PGA, respectively, for moderate earthquakes. We regress log(PGV) and log(PGA) as functions of distance and magnitude. We assume that the scaling of log(PGV) and log(PGA) with magnitude can differ for moderate and large earthquakes, but must be continuous. Because the frequencies that carry PGV and PGA can vary with earthquake size for large earthquakes, the regression for large earthquakes incorporates a magnitude dependence in the exponential attenuation function. We fix the scaling break between moderate and large earthquakes at M 5.5; log(PGV) and log(PGA) scale as 1.06M and 1.00M, respectively, for moderate earthquakes and 0.58M and 0.31M for large earthquakes.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Impact of large-scale tides on cosmological distortions via redshift-space power spectrum

NASA Astrophysics Data System (ADS)

Akitsu, Kazuyuki; Takada, Masahiro

2018-03-01

Although large-scale perturbations beyond a finite-volume survey region are not direct observables, these affect measurements of clustering statistics of small-scale (subsurvey) perturbations in large-scale structure, compared with the ensemble average, via the mode-coupling effect. In this paper we show that a large-scale tide induced by scalar perturbations causes apparent anisotropic distortions in the redshift-space power spectrum of galaxies in a way depending on an alignment between the tide, wave vector of small-scale modes and line-of-sight direction. Using the perturbation theory of structure formation, we derive a response function of the redshift-space power spectrum to large-scale tide. We then investigate the impact of large-scale tide on estimation of cosmological distances and the redshift-space distortion parameter via the measured redshift-space power spectrum for a hypothetical large-volume survey, based on the Fisher matrix formalism. To do this, we treat the large-scale tide as a signal, rather than an additional source of the statistical errors, and show that a degradation in the parameter is restored if we can employ the prior on the rms amplitude expected for the standard cold dark matter (CDM) model. We also discuss whether the large-scale tide can be constrained at an accuracy better than the CDM prediction, if the effects up to a larger wave number in the nonlinear regime can be included.

StePS: Stereographically Projected Cosmological Simulations

NASA Astrophysics Data System (ADS)

Rácz, Gábor; Szapudi, István; Csabai, István; Dobos, László

2018-05-01

StePS (Stereographically Projected Cosmological Simulations) compactifies the infinite spatial extent of the Universe into a finite sphere with isotropic boundary conditions to simulate the evolution of the large-scale structure. This eliminates the need for periodic boundary conditions, which are a numerical convenience unsupported by observation and which modifies the law of force on large scales in an unrealistic fashion. StePS uses stereographic projection for space compactification and naive O(N2) force calculation; this arrives at a correlation function of the same quality more quickly than standard (tree or P3M) algorithms with similar spatial and mass resolution. The N2 force calculation is easy to adapt to modern graphics cards, hence StePS can function as a high-speed prediction tool for modern large-scale surveys.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Male group size, female distribution and changes in sexual segregation by Roosevelt elk

PubMed Central

Peterson, Leah M.

2017-01-01

Sexual segregation, or the differential use of space by males and females, is hypothesized to be a function of body size dimorphism. Sexual segregation can also manifest at small (social segregation) and large (habitat segregation) spatial scales for a variety of reasons. Furthermore, the connection between small- and large-scale sexual segregation has rarely been addressed. We studied a population of Roosevelt elk (Cervus elaphus roosevelti) across 21 years in north coastal California, USA, to assess small- and large-scale sexual segregation in winter. We hypothesized that male group size would associate with small-scale segregation and that a change in female distribution would associate with large-scale segregation. Variation in forage biomass might also be coupled to small and large-scale sexual segregation. Our findings were consistent with male group size associating with small-scale segregation and a change in female distribution associating with large-scale segregation. Females appeared to avoid large groups comprised of socially dominant males. Males appeared to occupy a habitat vacated by females because of a wider forage niche, greater tolerance to lethal risks, and, perhaps, to reduce encounters with other elk. Sexual segregation at both spatial scales was a poor predictor of forage biomass. Size dimorphism was coupled to change in sexual segregation at small and large spatial scales. Small scale segregation can seemingly manifest when all forage habitat is occupied by females and large scale segregation might happen when some forage habitat is not occupied by females. PMID:29121076

Dual-wavelength hybrid optoacoustic-ultrasound biomicroscopy for functional imaging of large-scale cerebral vascular networks.

PubMed

Rebling, Johannes; Estrada, Héctor; Gottschalk, Sven; Sela, Gali; Zwack, Michael; Wissmeyer, Georg; Ntziachristos, Vasilis; Razansky, Daniel

2018-04-19

A critical link exists between pathological changes of cerebral vasculature and diseases affecting brain function. Microscopic techniques have played an indispensable role in the study of neurovascular anatomy and functions. Yet, investigations are often hindered by suboptimal trade-offs between the spatiotemporal resolution, field-of-view (FOV) and type of contrast offered by the existing optical microscopy techniques. We present a hybrid dual-wavelength optoacoustic (OA) biomicroscope capable of rapid transcranial visualization of large-scale cerebral vascular networks. The system offers 3-dimensional views of the morphology and oxygenation status of the cerebral vasculature with single capillary resolution and a FOV exceeding 6 × 8 mm 2 , thus covering the entire cortical vasculature in mice. The large-scale OA imaging capacity is complemented by simultaneously acquired pulse-echo ultrasound (US) biomicroscopy scans of the mouse skull. The new approach holds great potential to provide better insights into cerebrovascular function and facilitate efficient studies into neurological and vascular abnormalities of the brain. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

Root structural and functional dynamics in terrestrial biosphere models--evaluation and recommendations.

PubMed

Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D

2015-01-01

There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.

Large Eddy Simulation in the Computation of Jet Noise

NASA Technical Reports Server (NTRS)

Mankbadi, R. R.; Goldstein, M. E.; Povinelli, L. A.; Hayder, M. E.; Turkel, E.

1999-01-01

Noise can be predicted by solving Full (time-dependent) Compressible Navier-Stokes Equation (FCNSE) with computational domain. The fluctuating near field of the jet produces propagating pressure waves that produce far-field sound. The fluctuating flow field as a function of time is needed in order to calculate sound from first principles. Noise can be predicted by solving the full, time-dependent, compressible Navier-Stokes equations with the computational domain extended to far field - but this is not feasible as indicated above. At high Reynolds number of technological interest turbulence has large range of scales. Direct numerical simulations (DNS) can not capture the small scales of turbulence. The large scales are more efficient than the small scales in radiating sound. The emphasize is thus on calculating sound radiated by large scales.

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

Linear Scaling Density Functional Calculations with Gaussian Orbitals

NASA Technical Reports Server (NTRS)

Scuseria, Gustavo E.

1999-01-01

Recent advances in linear scaling algorithms that circumvent the computational bottlenecks of large-scale electronic structure simulations make it possible to carry out density functional calculations with Gaussian orbitals on molecules containing more than 1000 atoms and 15000 basis functions using current workstations and personal computers. This paper discusses the recent theoretical developments that have led to these advances and demonstrates in a series of benchmark calculations the present capabilities of state-of-the-art computational quantum chemistry programs for the prediction of molecular structure and properties.

Surgical Management of Large Periorbital Cutaneous Defects: Aesthetic Considerations and Technique Refinements.

PubMed

Zou, Yun; Hu, Li; Tremp, Mathias; Jin, Yunbo; Chen, Hui; Ma, Gang; Lin, Xiaoxi

2018-02-23

The aim of this study was to repair large periorbital cutaneous defects by an innovative technique called PEPSI (periorbital elevation and positioning with secret incisions) technique with functional and aesthetic outcomes. In this retrospective study, unilateral periorbital cutaneous defects in 15 patients were repaired by the PEPSI technique. The ages of patients ranged from 3 to 46 years (average, 19 years). The outcome evaluations included scars (Vancouver Scar Scale and visual analog scale score), function and aesthetic appearance of eyelids, and patient satisfaction. The repair size was measured by the maximum advancement distance of skin flap during operation. All patients achieved an effective repair with a mean follow-up of 18.3 months. Except one with a small (approximately 0.3 cm) necrosis, all patients healed with no complication. The mean Vancouver Scar Scale and visual analog scale scores were 2.1 ± 1.7 and 8.5 ± 1.2, respectively. Ideal cosmetic and functional outcomes were achieved in 14 patients (93.3%). All patients achieved complete satisfaction except 1 patient with partial satisfaction. The mean maximum advancement distance of skin flap was 20.2 mm (range, 8-50 mm). This study demonstrated that the PEPSI technique is an effective method to repair large periorbital cutaneous defects with acceptable functional and aesthetic outcomes.

Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162

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

PubMed Central

Formoso, Elena; Limongelli, Vittorio; Parrinello, Michele

2015-01-01

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. PMID:25672826

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.

Large-angle correlations in the cosmic microwave background

NASA Astrophysics Data System (ADS)

Efstathiou, George; Ma, Yin-Zhe; Hanson, Duncan

2010-10-01

It has been argued recently by Copi et al. 2009 that the lack of large angular correlations of the CMB temperature field provides strong evidence against the standard, statistically isotropic, inflationary Lambda cold dark matter (ΛCDM) cosmology. We compare various estimators of the temperature correlation function showing how they depend on assumptions of statistical isotropy and how they perform on the Wilkinson Microwave Anisotropy Probe (WMAP) 5-yr Internal Linear Combination (ILC) maps with and without a sky cut. We show that the low multipole harmonics that determine the large-scale features of the temperature correlation function can be reconstructed accurately from the data that lie outside the sky cuts. The reconstructions are only weakly dependent on the assumed statistical properties of the temperature field. The temperature correlation functions computed from these reconstructions are in good agreement with those computed from the ILC map over the whole sky. We conclude that the large-scale angular correlation function for our realization of the sky is well determined. A Bayesian analysis of the large-scale correlations is presented, which shows that the data cannot exclude the standard ΛCDM model. We discuss the differences between our results and those of Copi et al. Either there exists a violation of statistical isotropy as claimed by Copi et al., or these authors have overestimated the significance of the discrepancy because of a posteriori choices of estimator, statistic and sky cut.

Pollutant Transport and Fate: Relations Between Flow-paths and Downstream Impacts of Human Activities

NASA Astrophysics Data System (ADS)

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

2017-12-01

The quality of freshwater resources is increasingly impacted by human activities. Humans also extensively change the structure of landscapes, which may alter natural hydrological processes. To manage and maintain freshwater of good water quality, it is critical to understand how pollutants are released into, transported and transformed within the hydrological system. Some key scientific questions include: What are net downstream impacts of pollutants across different hydroclimatic and human disturbance conditions, and on different scales? What are the functions within and between components of the landscape, such as wetlands, on mitigating pollutant load delivery to downstream recipients? We explore these questions by synthesizing results from several relevant case study examples of intensely human-impacted hydrological systems. These case study sites have been specifically evaluated in terms of net impact of human activities on pollutant input to the aquatic system, as well as flow-path distributions trough wetlands as a potential ecosystem service of pollutant mitigation. Results shows that although individual wetlands have high retention capacity, efficient net retention effects were not always achieved at a larger landscape scale. Evidence suggests that the function of wetlands as mitigation solutions to pollutant loads is largely controlled by large-scale parallel and circular flow-paths, through which multiple wetlands are interconnected in the landscape. To achieve net mitigation effects at large scale, a large fraction of the polluted large-scale flows must be transported through multiple connected wetlands. Although such large-scale flow interactions are critical for assessing water pollution spreading and fate through the landscape, our synthesis shows a frequent lack of knowledge at such scales. We suggest ways forward for addressing the mismatch between the large scales at which key pollutant pressures and water quality changes take place and the relatively scale at which most studies and implementations are currently made. These suggestions can help bridge critical knowledge gaps, as needed for improving water quality predictions and mitigation solutions under human and environmental changes.

Methods for Evaluating the Temperature Structure-Function Parameter Using Unmanned Aerial Systems and Large-Eddy Simulation

NASA Astrophysics Data System (ADS)

Wainwright, Charlotte E.; Bonin, Timothy A.; Chilson, Phillip B.; Gibbs, Jeremy A.; Fedorovich, Evgeni; Palmer, Robert D.

2015-05-01

Small-scale turbulent fluctuations of temperature are known to affect the propagation of both electromagnetic and acoustic waves. Within the inertial-subrange scale, where the turbulence is locally homogeneous and isotropic, these temperature perturbations can be described, in a statistical sense, using the structure-function parameter for temperature, . Here we investigate different methods of evaluating , using data from a numerical large-eddy simulation together with atmospheric observations collected by an unmanned aerial system and a sodar. An example case using data from a late afternoon unmanned aerial system flight on April 24 2013 and corresponding large-eddy simulation data is presented and discussed.

Finite-time and finite-size scalings in the evaluation of large-deviation functions: Numerical approach in continuous time.

PubMed

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

2017-06-01

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provides a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to selection rules that favor the rare trajectories of interest. Such algorithms are plagued by finite simulation time and finite population size, effects that can render their use delicate. In this paper, we present a numerical approach which uses the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of rare trajectories. The method we propose allows one to extract the infinite-time and infinite-size limit of these estimators, which-as shown on the contact process-provides a significant improvement of the large deviation function estimators compared to the standard one.

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…

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

ERIC Educational Resources Information Center

Wendt, Heike; Bos, Wilfried; Goy, Martin

2011-01-01

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

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

NASA Technical Reports Server (NTRS)

Gould, J. M.

1978-01-01

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

Polychaete functional diversity in shallow habitats: Shelter from the storm

NASA Astrophysics Data System (ADS)

Wouters, Julia M.; Gusmao, Joao B.; Mattos, Gustavo; Lana, Paulo

2018-05-01

Innovative approaches are needed to help understanding how species diversity is related to the latitudinal gradient at large or small scales. We have applied a novel approach, by combining morphological and biological traits, to assess the relative importance of the large scale latitudinal gradient and regional morphodynamic drivers in shaping the functional diversity of polychaete assemblages in shallow water habitats, from exposed to estuarine sandy beaches. We used literature data on polychaetes from beaches along the southern and southeastern Brazilian coast together with data on beach types, slope, grain size, temperature, salinity, and chlorophyll a concentration. Generalized linear models on the FDis index for functional diversity calculated for each site and a combined RLQ and fourth-corner analysis were used to investigate relationships between functional traits and environmental variables. Functional diversity was not related to the latitudinal gradient but negatively correlated with grain size and beach slope. Functional diversity was highest in flat beaches with small grain size, little wave exposure and enhanced primary production, indicating that small scale morphodynamic conditions are the primary drivers of polychaete functional diversity.

Diagnostics of a large-scale irregularity in the electron density near the boundary of the radio transparency frequency range of the ionosphere

NASA Astrophysics Data System (ADS)

Afanasiev, N. T.; Markov, V. P.

2011-08-01

Approximate functional relationships for the calculation of a disturbed transionogram with a trace deformation caused by the influence of a large-scale irregularity in the electron density are obtained. Numerical and asymptotic modeling of disturbed transionograms at various positions of a spacecraft relative to a ground-based observation point is performed. A possibility of the determination of the intensity and dimensions of a single large-scale irregularity near the boundary of the radio transparency frequency range of the ionosphere is demonstrated.

Accelerating large scale Kohn-Sham density functional theory calculations with semi-local functionals and hybrid functionals

NASA Astrophysics Data System (ADS)

Lin, Lin

The computational cost of standard Kohn-Sham density functional theory (KSDFT) calculations scale cubically with respect to the system size, which limits its use in large scale applications. In recent years, we have developed an alternative procedure called the pole expansion and selected inversion (PEXSI) method. The PEXSI method solves KSDFT without solving any eigenvalue and eigenvector, and directly evaluates physical quantities including electron density, energy, atomic force, density of states, and local density of states. The overall algorithm scales as at most quadratically for all materials including insulators, semiconductors and the difficult metallic systems. The PEXSI method can be efficiently parallelized over 10,000 - 100,000 processors on high performance machines. The PEXSI method has been integrated into a number of community electronic structure software packages such as ATK, BigDFT, CP2K, DGDFT, FHI-aims and SIESTA, and has been used in a number of applications with 2D materials beyond 10,000 atoms. The PEXSI method works for LDA, GGA and meta-GGA functionals. The mathematical structure for hybrid functional KSDFT calculations is significantly different. I will also discuss recent progress on using adaptive compressed exchange method for accelerating hybrid functional calculations. DOE SciDAC Program, DOE CAMERA Program, LBNL LDRD, Sloan Fellowship.

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.

Finite-Time and -Size Scalings in the Evaluation of Large Deviation Functions. Numerical Analysis in Continuous Time

NASA Astrophysics Data System (ADS)

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provide a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to a selection rule that favors the rare trajectories of interest. However, such algorithms are plagued by finite simulation time- and finite population size- effects that can render their use delicate. Using the continuous-time cloning algorithm, we analyze the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of the rare trajectories. We use these scalings in order to propose a numerical approach which allows to extract the infinite-time and infinite-size limit of these estimators.

Large-Scale, Three–Dimensional, Free–Standing, and Mesoporous Metal Oxide Networks for High–Performance Photocatalysis

PubMed Central

Bai, Hua; Li, Xinshi; Hu, Chao; Zhang, Xuan; Li, Junfang; Yan, Yan; Xi, Guangcheng

2013-01-01

Mesoporous nanostructures represent a unique class of photocatalysts with many applications, including splitting of water, degradation of organic contaminants, and reduction of carbon dioxide. In this work, we report a general Lewis acid catalytic template route for the high–yield producing single– and multi–component large–scale three–dimensional (3D) mesoporous metal oxide networks. The large-scale 3D mesoporous metal oxide networks possess large macroscopic scale (millimeter–sized) and mesoporous nanostructure with huge pore volume and large surface exposure area. This method also can be used for the synthesis of large–scale 3D macro/mesoporous hierarchical porous materials and noble metal nanoparticles loaded 3D mesoporous networks. Photocatalytic degradation of Azo dyes demonstrated that the large–scale 3D mesoporous metal oxide networks enable high photocatalytic activity. The present synthetic method can serve as the new design concept for functional 3D mesoporous nanomaterials. PMID:23857595

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Development of large-scale functional brain networks in children.

PubMed

Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

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

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

Impact of incomplete metal coverage on the electrical properties of metal-CNT contacts: A large-scale ab initio study

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

Fediai, Artem, E-mail: artem.fediai@nano.tu-dresden.de; Ryndyk, Dmitry A.; Center for Advancing Electronics Dresden, TU Dresden, 01062 Dresden

2016-09-05

Using a dedicated combination of the non-equilibrium Green function formalism and large-scale density functional theory calculations, we investigated how incomplete metal coverage influences two of the most important electrical properties of carbon nanotube (CNT)-based transistors: contact resistance and its scaling with contact length, and maximum current. These quantities have been derived from parameter-free simulations of atomic systems that are as close as possible to experimental geometries. Physical mechanisms that govern these dependences have been identified for various metals, representing different CNT-metal interaction strengths from chemisorption to physisorption. Our results pave the way for an application-oriented design of CNT-metal contacts.

Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

PubMed

Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

2010-09-21

We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

Computational Thermochemistry: Scale Factor Databases and Scale Factors for Vibrational Frequencies Obtained from Electronic Model Chemistries.

PubMed

Alecu, I M; Zheng, Jingjing; Zhao, Yan; Truhlar, Donald G

2010-09-14

Optimized scale factors for calculating vibrational harmonic and fundamental frequencies and zero-point energies have been determined for 145 electronic model chemistries, including 119 based on approximate functionals depending on occupied orbitals, 19 based on single-level wave function theory, three based on the neglect-of-diatomic-differential-overlap, two based on doubly hybrid density functional theory, and two based on multicoefficient correlation methods. Forty of the scale factors are obtained from large databases, which are also used to derive two universal scale factor ratios that can be used to interconvert between scale factors optimized for various properties, enabling the derivation of three key scale factors at the effort of optimizing only one of them. A reduced scale factor optimization model is formulated in order to further reduce the cost of optimizing scale factors, and the reduced model is illustrated by using it to obtain 105 additional scale factors. Using root-mean-square errors from the values in the large databases, we find that scaling reduces errors in zero-point energies by a factor of 2.3 and errors in fundamental vibrational frequencies by a factor of 3.0, but it reduces errors in harmonic vibrational frequencies by only a factor of 1.3. It is shown that, upon scaling, the balanced multicoefficient correlation method based on coupled cluster theory with single and double excitations (BMC-CCSD) can lead to very accurate predictions of vibrational frequencies. With a polarized, minimally augmented basis set, the density functionals with zero-point energy scale factors closest to unity are MPWLYP1M (1.009), τHCTHhyb (0.989), BB95 (1.012), BLYP (1.013), BP86 (1.014), B3LYP (0.986), MPW3LYP (0.986), and VSXC (0.986).

Urban forest health monitoring: large-scale assessments in the United States

Treesearch

Anne Buckelew Cumming; Daniel B. Twardus; David J. Nowak

2008-01-01

The U.S. Department of Agriculture, Forest Service (USFS), together with state partners, developed methods to monitor urban forest structure, function, and health at a large statewide scale. Pilot studies have been established in five states using protocols based on USFS Forest Inventory and Analysis and Forest Health Monitoring program data collection standards....

Stability of large-scale systems.

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1972-01-01

The purpose of this paper is to present the results obtained in stability study of large-scale systems based upon the comparison principle and vector Liapunov functions. The exposition is essentially self-contained, with emphasis on recent innovations which utilize explicit information about the system structure. This provides a natural foundation for the stability theory of dynamic systems under structural perturbations.

Herbivory drives large-scale spatial variation in reef fish trophic interactions

PubMed Central

Longo, Guilherme O; Ferreira, Carlos Eduardo L; Floeter, Sergio R

2014-01-01

Trophic interactions play a critical role in the structure and function of ecosystems. Given the widespread loss of biodiversity due to anthropogenic activities, understanding how trophic interactions respond to natural gradients (e.g., abiotic conditions, species richness) through large-scale comparisons can provide a broader understanding of their importance in changing ecosystems and support informed conservation actions. We explored large-scale variation in reef fish trophic interactions, encompassing tropical and subtropical reefs with different abiotic conditions and trophic structure of reef fish community. Reef fish feeding pressure on the benthos was determined combining bite rates on the substrate and the individual biomass per unit of time and area, using video recordings in three sites between latitudes 17°S and 27°S on the Brazilian Coast. Total feeding pressure decreased 10-fold and the composition of functional groups and species shifted from the northern to the southernmost sites. Both patterns were driven by the decline in the feeding pressure of roving herbivores, particularly scrapers, while the feeding pressure of invertebrate feeders and omnivores remained similar. The differential contribution to the feeding pressure across trophic categories, with roving herbivores being more important in the northernmost and southeastern reefs, determined changes in the intensity and composition of fish feeding pressure on the benthos among sites. It also determined the distribution of trophic interactions across different trophic categories, altering the evenness of interactions. Feeding pressure was more evenly distributed at the southernmost than in the southeastern and northernmost sites, where it was dominated by few herbivores. Species and functional groups that performed higher feeding pressure than predicted by their biomass were identified as critical for their potential to remove benthic biomass. Fishing pressure unlikely drove the large-scale pattern; however, it affected the contribution of some groups on a local scale (e.g., large-bodied parrotfish) highlighting the need to incorporate critical functions into conservation strategies. PMID:25512851

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

Large-scale motions in the universe: Using clusters of galaxies as tracers

NASA Technical Reports Server (NTRS)

Gramann, Mirt; Bahcall, Neta A.; Cen, Renyue; Gott, J. Richard

1995-01-01

Can clusters of galaxies be used to trace the large-scale peculiar velocity field of the universe? We answer this question by using large-scale cosmological simulations to compare the motions of rich clusters of galaxies with the motion of the underlying matter distribution. Three models are investigated: Omega = 1 and Omega = 0.3 cold dark matter (CDM), and Omega = 0.3 primeval baryonic isocurvature (PBI) models, all normalized to the Cosmic Background Explorer (COBE) background fluctuations. We compare the cluster and mass distribution of peculiar velocities, bulk motions, velocity dispersions, and Mach numbers as a function of scale for R greater than or = 50/h Mpc. We also present the large-scale velocity and potential maps of clusters and of the matter. We find that clusters of galaxies trace well the large-scale velocity field and can serve as an efficient tool to constrain cosmological models. The recently reported bulk motion of clusters 689 +/- 178 km/s on approximately 150/h Mpc scale (Lauer & Postman 1994) is larger than expected in any of the models studied (less than or = 190 +/- 78 km/s).

Development of 5123 Intron-Length Polymorphic Markers for Large-Scale Genotyping Applications in Foxtail Millet

PubMed Central

Muthamilarasan, Mehanathan; Venkata Suresh, B.; Pandey, Garima; Kumari, Kajal; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

Generating genomic resources in terms of molecular markers is imperative in molecular breeding for crop improvement. Though development and application of microsatellite markers in large-scale was reported in the model crop foxtail millet, no such large-scale study was conducted for intron-length polymorphic (ILP) markers. Considering this, we developed 5123 ILP markers, of which 4049 were physically mapped onto 9 chromosomes of foxtail millet. BLAST analysis of 5123 expressed sequence tags (ESTs) suggested the function for ∼71.5% ESTs and grouped them into 5 different functional categories. About 440 selected primer pairs representing the foxtail millet genome and the different functional groups showed high-level of cross-genera amplification at an average of ∼85% in eight millets and five non-millet species. The efficacy of the ILP markers for distinguishing the foxtail millet is demonstrated by observed heterozygosity (0.20) and Nei's average gene diversity (0.22). In silico comparative mapping of physically mapped ILP markers demonstrated substantial percentage of sequence-based orthology and syntenic relationship between foxtail millet chromosomes and sorghum (∼50%), maize (∼46%), rice (∼21%) and Brachypodium (∼21%) chromosomes. Hence, for the first time, we developed large-scale ILP markers in foxtail millet and demonstrated their utility in germplasm characterization, transferability, phylogenetics and comparative mapping studies in millets and bioenergy grass species. PMID:24086082

Transport Coefficients from Large Deviation Functions

NASA Astrophysics Data System (ADS)

Gao, Chloe; Limmer, David

2017-10-01

We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.

Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi

2017-04-01

The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.

Density-dependent clustering: I. Pulling back the curtains on motions of the BAO peak

NASA Astrophysics Data System (ADS)

Neyrinck, Mark C.; Szapudi, István; McCullagh, Nuala; Szalay, Alexander S.; Falck, Bridget; Wang, Jie

2018-05-01

The most common statistic used to analyze large-scale structure surveys is the correlation function, or power spectrum. Here, we show how `slicing' the correlation function on local density brings sensitivity to interesting non-Gaussian features in the large-scale structure, such as the expansion or contraction of baryon acoustic oscillations (BAO) according to the local density. The sliced correlation function measures the large-scale flows that smear out the BAO, instead of just correcting them as reconstruction algorithms do. Thus, we expect the sliced correlation function to be useful in constraining the growth factor, and modified gravity theories that involve the local density. Out of the studied cases, we find that the run of the BAO peak location with density is best revealed when slicing on a ˜40 h-1 Mpc filtered density. But slicing on a ˜100 h-1 Mpc filtered density may be most useful in distinguishing between underdense and overdense regions, whose BAO peaks are separated by a substantial ˜5 h-1 Mpc at z = 0. We also introduce `curtain plots' showing how local densities drive particle motions toward or away from each other over the course of an N-body simulation.

Coagulation-Fragmentation Model for Animal Group-Size Statistics

NASA Astrophysics Data System (ADS)

Degond, Pierre; Liu, Jian-Guo; Pego, Robert L.

2017-04-01

We study coagulation-fragmentation equations inspired by a simple model proposed in fisheries science to explain data for the size distribution of schools of pelagic fish. Although the equations lack detailed balance and admit no H-theorem, we are able to develop a rather complete description of equilibrium profiles and large-time behavior, based on recent developments in complex function theory for Bernstein and Pick functions. In the large-population continuum limit, a scaling-invariant regime is reached in which all equilibria are determined by a single scaling profile. This universal profile exhibits power-law behavior crossing over from exponent -2/3 for small size to -3/2 for large size, with an exponential cutoff.

Analyzing the cosmic variance limit of remote dipole measurements of the cosmic microwave background using the large-scale kinetic Sunyaev Zel'dovich effect

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

Terrana, Alexandra; Johnson, Matthew C.; Harris, Mary-Jean, E-mail: aterrana@perimeterinstitute.ca, E-mail: mharris8@perimeterinstitute.ca, E-mail: mjohnson@perimeterinstitute.ca

Due to cosmic variance we cannot learn any more about large-scale inhomogeneities from the primary cosmic microwave background (CMB) alone. More information on large scales is essential for resolving large angular scale anomalies in the CMB. Here we consider cross correlating the large-scale kinetic Sunyaev Zel'dovich (kSZ) effect and probes of large-scale structure, a technique known as kSZ tomography. The statistically anisotropic component of the cross correlation encodes the CMB dipole as seen by free electrons throughout the observable Universe, providing information about long wavelength inhomogeneities. We compute the large angular scale power asymmetry, constructing the appropriate transfer functions, andmore » estimate the cosmic variance limited signal to noise for a variety of redshift bin configurations. The signal to noise is significant over a large range of power multipoles and numbers of bins. We present a simple mode counting argument indicating that kSZ tomography can be used to estimate more modes than the primary CMB on comparable scales. A basic forecast indicates that a first detection could be made with next-generation CMB experiments and galaxy surveys. This paper motivates a more systematic investigation of how close to the cosmic variance limit it will be possible to get with future observations.« less

Topological Properties of Some Integrated Circuits for Very Large Scale Integration Chip Designs

NASA Astrophysics Data System (ADS)

Swanson, S.; Lanzerotti, M.; Vernizzi, G.; Kujawski, J.; Weatherwax, A.

2015-03-01

This talk presents topological properties of integrated circuits for Very Large Scale Integration chip designs. These circuits can be implemented in very large scale integrated circuits, such as those in high performance microprocessors. Prior work considered basic combinational logic functions and produced a mathematical framework based on algebraic topology for integrated circuits composed of logic gates. Prior work also produced an historically-equivalent interpretation of Mr. E. F. Rent's work for today's complex circuitry in modern high performance microprocessors, where a heuristic linear relationship was observed between the number of connections and number of logic gates. This talk will examine topological properties and connectivity of more complex functionally-equivalent integrated circuits. The views expressed in this article are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense or the U.S. Government.

Divergence of perturbation theory in large scale structures

NASA Astrophysics Data System (ADS)

Pajer, Enrico; van der Woude, Drian

2018-05-01

We make progress towards an analytical understanding of the regime of validity of perturbation theory for large scale structures and the nature of some non-perturbative corrections. We restrict ourselves to 1D gravitational collapse, for which exact solutions before shell crossing are known. We review the convergence of perturbation theory for the power spectrum, recently proven by McQuinn and White [1], and extend it to non-Gaussian initial conditions and the bispectrum. In contrast, we prove that perturbation theory diverges for the real space two-point correlation function and for the probability density function (PDF) of the density averaged in cells and all the cumulants derived from it. We attribute these divergences to the statistical averaging intrinsic to cosmological observables, which, even on very large and "perturbative" scales, gives non-vanishing weight to all extreme fluctuations. Finally, we discuss some general properties of non-perturbative effects in real space and Fourier space.

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

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

RELIABILITY OF THE DETECTION OF THE BARYON ACOUSTIC PEAK

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

MartInez, Vicent J.; Arnalte-Mur, Pablo; De la Cruz, Pablo

2009-05-01

The correlation function of the distribution of matter in the universe shows, at large scales, baryon acoustic oscillations, which were imprinted prior to recombination. This feature was first detected in the correlation function of the luminous red galaxies of the Sloan Digital Sky Survey (SDSS). Recently, the final release (DR7) of the SDSS has been made available, and the useful volume is about two times bigger than in the old sample. We present here, for the first time, the redshift-space correlation function of this sample at large scales together with that for one shallower, but denser volume-limited subsample drawn frommore » the Two-Degree Field Redshift Survey. We test the reliability of the detection of the acoustic peak at about 100 h {sup -1} Mpc and the behavior of the correlation function at larger scales by means of careful estimation of errors. We confirm the presence of the peak in the latest data although broader than in previous detections.« less

Flexible Redistribution in Cognitive Networks.

PubMed

Hartwigsen, Gesa

2018-06-15

Previous work has emphasized that cognitive functions in the human brain are organized into large-scale networks. However, the mechanisms that allow these networks to compensate for focal disruptions remain elusive. I suggest a new perspective on the compensatory flexibility of cognitive networks. First, I demonstrate that cognitive networks can rapidly change the functional weight of the relative contribution of different regions. Second, I argue that there is an asymmetry in the compensatory potential of different kinds of networks. Specifically, recruitment of domain-general functions can partially compensate for focal disruptions of specialized cognitive functions, but not vice versa. Considering the compensatory potential within and across networks will increase our understanding of functional adaptation and reorganization after brain lesions and offers a new perspective on large-scale neural network (re-)organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Scaling A Moment-Rate Function For Small To Large Magnitude Events

NASA Astrophysics Data System (ADS)

Archuleta, Ralph; Ji, Chen

2017-04-01

Since the 1980's seismologists have recognized that peak ground acceleration (PGA) and peak ground velocity (PGV) scale differently with magnitude for large and moderate earthquakes. In a recent paper (Archuleta and Ji, GRL 2016) we introduced an apparent moment-rate function (aMRF) that accurately predicts the scaling with magnitude of PGA, PGV, PWA (Wood-Anderson Displacement) and the ratio PGA/2πPGV (dominant frequency) for earthquakes 3.3 ≤ M ≤ 5.3. This apparent moment-rate function is controlled by two temporal parameters, tp and td, which are related to the time for the moment-rate function to reach its peak amplitude and the total duration of the earthquake, respectively. These two temporal parameters lead to a Fourier amplitude spectrum (FAS) of displacement that has two corners in between which the spectral amplitudes decay as 1/f, f denotes frequency. At higher or lower frequencies, the FAS of the aMRF looks like a single-corner Aki-Brune omega squared spectrum. However, in the presence of attenuation the higher corner is almost certainly masked. Attempting to correct the spectrum to an Aki-Brune omega-squared spectrum will produce an "apparent" corner frequency that falls between the double corner frequency of the aMRF. We reason that the two corners of the aMRF are the reason that seismologists deduce a stress drop (e.g., Allmann and Shearer, JGR 2009) that is generally much smaller than the stress parameter used to produce ground motions from stochastic simulations (e.g., Boore, 2003 Pageoph.). The presence of two corners for the smaller magnitude earthquakes leads to several questions. Can deconvolution be successfully used to determine scaling from small to large earthquakes? Equivalently will large earthquakes have a double corner? If large earthquakes are the sum of many smaller magnitude earthquakes, what should the displacement FAS look like for a large magnitude earthquake? Can a combination of such a double-corner spectrum and random vibration theory explain the PGA, PGV scaling relationships for larger magnitude?

Scaling of muscle architecture and fiber types in the rat hindlimb.

PubMed

Eng, Carolyn M; Smallwood, Laura H; Rainiero, Maria Pia; Lahey, Michele; Ward, Samuel R; Lieber, Richard L

2008-07-01

The functional capacity of a muscle is determined by its architecture and metabolic properties. Although extensive analyses of muscle architecture and fiber type have been completed in a large number of muscles in numerous species, there have been few studies that have looked at the interrelationship of these functional parameters among muscles of a single species. Nor have the architectural properties of individual muscles been compared across species to understand scaling. This study examined muscle architecture and fiber type in the rat (Rattus norvegicus) hindlimb to examine each muscle's functional specialization. Discriminant analysis demonstrated that architectural properties are a greater predictor of muscle function (as defined by primary joint action and anti-gravity or non anti-gravity role) than fiber type. Architectural properties were not strictly aligned with fiber type, but when muscles were grouped according to anti-gravity versus non-anti-gravity function there was evidence of functional specialization. Specifically, anti-gravity muscles had a larger percentage of slow fiber type and increased muscle physiological cross-sectional area. Incongruities between a muscle's architecture and fiber type may reflect the variability of functional requirements on single muscles, especially those that cross multiple joints. Additionally, discriminant analysis and scaling of architectural variables in the hindlimb across several mammalian species was used to explore whether any functional patterns could be elucidated within single muscles or across muscle groups. Several muscles deviated from previously described muscle architecture scaling rules and there was large variability within functional groups in how muscles should be scaled with body size. This implies that functional demands placed on muscles across species should be examined on the single muscle level.

Monitoring Ephemeral Streams Using Airborne Very High Resolution Multispectral Remote Sensing in Arid Environments

NASA Astrophysics Data System (ADS)

Hamada, Y.; O'Connor, B. L.

2012-12-01

Development in arid environments often results in the loss and degradation of the ephemeral streams that provide habitat and critical ecosystem functions such as water delivery, sediment transport, and groundwater recharge. Quantification of these ecosystem functions is challenging because of the episodic nature of runoff events in desert landscapes and the large spatial scale of watersheds that potentially can be impacted by large-scale development. Low-impact development guidelines and regulatory protection of ephemeral streams are often lacking due to the difficulty of accurately mapping and quantifying the critical functions of ephemeral streams at scales larger than individual reaches. Renewable energy development in arid regions has the potential to disturb ephemeral streams at the watershed scale, and it is necessary to develop environmental monitoring applications for ephemeral streams to help inform land management and regulatory actions aimed at protecting and mitigating for impacts related to large-scale land disturbances. This study focuses on developing remote sensing methodologies to identify and monitor impacts on ephemeral streams resulting from the land disturbance associated with utility-scale solar energy development in the desert southwest of the United States. Airborne very high resolution (VHR) multispectral imagery is used to produce stereoscopic, three-dimensional landscape models that can be used to (1) identify and map ephemeral stream channel networks, and (2) support analyses and models of hydrologic and sediment transport processes that pertain to the critical functionality of ephemeral streams. Spectral and statistical analyses are being developed to extract information about ephemeral channel location and extent, micro-topography, riparian vegetation, and soil moisture characteristics. This presentation will demonstrate initial results and provide a framework for future work associated with this project, for developing the necessary field measurements necessary to verify remote sensing landscape models, and for generating hydrologic models and analyses.

A Comparison of Linking Methods for Estimating National Trends in International Comparative Large-Scale Assessments in the Presence of Cross-national DIF

ERIC Educational Resources Information Center

Sachse, Karoline A.; Roppelt, Alexander; Haag, Nicole

2016-01-01

Trend estimation in international comparative large-scale assessments relies on measurement invariance between countries. However, cross-national differential item functioning (DIF) has been repeatedly documented. We ran a simulation study using national item parameters, which required trends to be computed separately for each country, to compare…

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory

DOE PAGES

Tait, E. W.; Ratcliff, L. E.; Payne, M. C.; ...

2016-04-20

Experimental techniques for electron energy loss spectroscopy (EELS) combine high energy resolution with high spatial resolution. They are therefore powerful tools for investigating the local electronic structure of complex systems such as nanostructures, interfaces and even individual defects. Interpretation of experimental electron energy loss spectra is often challenging and can require theoretical modelling of candidate structures, which themselves may be large and complex, beyond the capabilities of traditional cubic-scaling density functional theory. In this work, we present functionality to compute electron energy loss spectra within the onetep linear-scaling density functional theory code. We first demonstrate that simulated spectra agree withmore » those computed using conventional plane wave pseudopotential methods to a high degree of precision. The ability of onetep to tackle large problems is then exploited to investigate convergence of spectra with respect to supercell size. As a result, we apply the novel functionality to a study of the electron energy loss spectra of defects on the (1 0 1) surface of an anatase slab and determine concentrations of defects which might be experimentally detectable.« less

Resources for Functional Genomics Studies in Drosophila melanogaster

PubMed Central

Mohr, Stephanie E.; Hu, Yanhui; Kim, Kevin; Housden, Benjamin E.; Perrimon, Norbert

2014-01-01

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, “meta” information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally. PMID:24653003

Continental-scale patterns of canopy tree composition and function across Amazonia.

PubMed

ter Steege, Hans; Pitman, Nigel C A; Phillips, Oliver L; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-28

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Continental-scale patterns of canopy tree composition and function across Amazonia

NASA Astrophysics Data System (ADS)

Ter Steege, Hans; Pitman, Nigel C. A.; Phillips, Oliver L.; Chave, Jerome; Sabatier, Daniel; Duque, Alvaro; Molino, Jean-François; Prévost, Marie-Françoise; Spichiger, Rodolphe; Castellanos, Hernán; von Hildebrand, Patricio; Vásquez, Rodolfo

2006-09-01

The world's greatest terrestrial stores of biodiversity and carbon are found in the forests of northern South America, where large-scale biogeographic patterns and processes have recently begun to be described. Seven of the nine countries with territory in the Amazon basin and the Guiana shield have carried out large-scale forest inventories, but such massive data sets have been little exploited by tropical plant ecologists. Although forest inventories often lack the species-level identifications favoured by tropical plant ecologists, their consistency of measurement and vast spatial coverage make them ideally suited for numerical analyses at large scales, and a valuable resource to describe the still poorly understood spatial variation of biomass, diversity, community composition and forest functioning across the South American tropics. Here we show, by using the seven forest inventories complemented with trait and inventory data collected elsewhere, two dominant gradients in tree composition and function across the Amazon, one paralleling a major gradient in soil fertility and the other paralleling a gradient in dry season length. The data set also indicates that the dominance of Fabaceae in the Guiana shield is not necessarily the result of root adaptations to poor soils (nodulation or ectomycorrhizal associations) but perhaps also the result of their remarkably high seed mass there as a potential adaptation to low rates of disturbance.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex.

PubMed

Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing

2016-11-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

PubMed Central

Mejias, Jorge F.; Murray, John D.; Kennedy, Henry; Wang, Xiao-Jing

2016-01-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions. PMID:28138530

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

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

Raccanelli, Alvise; Doré, Olivier; Bertacca, Daniele

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-scalemore » 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.« less

Reliability and Validity of a German Version of the "Questions about Behavioral Function" (QABF) Scale for Self-Injurious Behavior in Individuals with Intellectual Disabilities

ERIC Educational Resources Information Center

Bienstein, Pia; Nussbeck, Susanne

2009-01-01

The psychometric properties of a German version of the Questions About Behavioral Function Scale (QABF) (Matson & Vollmer, 1995) were examined in a sample of 522 individuals with intellectual disabilities residing in large facilities participated. The factor structure was first examined by exploratory factor analysis, yielding a…

The Large Local Hole in the Galaxy Distribution: The 2MASS Galaxy Angular Power Spectrum

NASA Astrophysics Data System (ADS)

Frith, W. J.; Outram, P. J.; Shanks, T.

2005-06-01

We present new evidence for a large deficiency in the local galaxy distribution situated in the ˜4000 deg2 APM survey area. We use models guided by the 2dF Galaxy Redshift Survey (2dFGRS) n(z) as a probe of the underlying large-scale structure. We first check the usefulness of this technique by comparing the 2dFGRS n(z) model prediction with the K-band and B-band number counts extracted from the 2MASS and 2dFGRS parent catalogues over the 2dFGRS Northern and Southern declination strips, before turning to a comparison with the APM counts. We find that the APM counts in both the B and K-bands indicate a deficiency in the local galaxy distribution of ˜30% to z ≈ 0.1 over the entire APM survey area. We examine the implied significance of such a large local hole, considering several possible forms for the real-space correlation function. We find that such a deficiency in the APM survey area indicates an excess of power at large scales over what is expected from the correlation function observed in 2dFGRS correlation function or predicted from ΛCDM Hubble Volume mock catalogues. In order to check further the clustering at large scales in the 2MASS data, we have calculated the angular power spectrum for 2MASS galaxies. Although in the linear regime (l<30), ΛCDM models can give a good fit to the 2MASS angular power spectrum, over a wider range (l<100) the power spectrum from Hubble Volume mock catalogues suggests that scale-dependent bias may be needed for ΛCDM to fit. However, the modest increase in large-scale power observed in the 2MASS angular power spectrum is still not enough to explain the local hole. If the APM survey area really is 25% deficient in galaxies out to z≈0.1, explanations for the disagreement with observed galaxy clustering statistics include the possibilities that the galaxy clustering is non-Gaussian on large scales or that the 2MASS volume is still too small to represent a `fair sample' of the Universe. Extending the 2dFGRS redshift survey over the whole APM area would resolve many of the remaining questions about the existence and interpretation of this local hole.

Combining paleo-data and modern exclosure experiments to assess the impact of megafauna extinctions on woody vegetation

PubMed Central

Bakker, Elisabeth S.; Gill, Jacquelyn L.; Johnson, Christopher N.; Vera, Frans W. M.; Sandom, Christopher J.; Asner, Gregory P.; Svenning, Jens-Christian

2016-01-01

Until recently in Earth history, very large herbivores (mammoths, ground sloths, diprotodons, and many others) occurred in most of the World’s terrestrial ecosystems, but the majority have gone extinct as part of the late-Quaternary extinctions. How has this large-scale removal of large herbivores affected landscape structure and ecosystem functioning? In this review, we combine paleo-data with information from modern exclosure experiments to assess the impact of large herbivores (and their disappearance) on woody species, landscape structure, and ecosystem functions. In modern landscapes characterized by intense herbivory, woody plants can persist by defending themselves or by association with defended species, can persist by growing in places that are physically inaccessible to herbivores, or can persist where high predator activity limits foraging by herbivores. At the landscape scale, different herbivore densities and assemblages may result in dynamic gradients in woody cover. The late-Quaternary extinctions were natural experiments in large-herbivore removal; the paleoecological record shows evidence of widespread changes in community composition and ecosystem structure and function, consistent with modern exclosure experiments. We propose a conceptual framework that describes the impact of large herbivores on woody plant abundance mediated by herbivore diversity and density, predicting that herbivore suppression of woody plants is strongest where herbivore diversity is high. We conclude that the decline of large herbivores induces major alterations in landscape structure and ecosystem functions. PMID:26504223

Combining paleo-data and modern exclosure experiments to assess the impact of megafauna extinctions on woody vegetation.

PubMed

Bakker, Elisabeth S; Gill, Jacquelyn L; Johnson, Christopher N; Vera, Frans W M; Sandom, Christopher J; Asner, Gregory P; Svenning, Jens-Christian

2016-01-26

Until recently in Earth history, very large herbivores (mammoths, ground sloths, diprotodons, and many others) occurred in most of the World's terrestrial ecosystems, but the majority have gone extinct as part of the late-Quaternary extinctions. How has this large-scale removal of large herbivores affected landscape structure and ecosystem functioning? In this review, we combine paleo-data with information from modern exclosure experiments to assess the impact of large herbivores (and their disappearance) on woody species, landscape structure, and ecosystem functions. In modern landscapes characterized by intense herbivory, woody plants can persist by defending themselves or by association with defended species, can persist by growing in places that are physically inaccessible to herbivores, or can persist where high predator activity limits foraging by herbivores. At the landscape scale, different herbivore densities and assemblages may result in dynamic gradients in woody cover. The late-Quaternary extinctions were natural experiments in large-herbivore removal; the paleoecological record shows evidence of widespread changes in community composition and ecosystem structure and function, consistent with modern exclosure experiments. We propose a conceptual framework that describes the impact of large herbivores on woody plant abundance mediated by herbivore diversity and density, predicting that herbivore suppression of woody plants is strongest where herbivore diversity is high. We conclude that the decline of large herbivores induces major alterations in landscape structure and ecosystem functions.

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.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Workflow management in large distributed systems

NASA Astrophysics Data System (ADS)

Legrand, I.; Newman, H.; Voicu, R.; Dobre, C.; Grigoras, C.

2011-12-01

The MonALISA (Monitoring Agents using a Large Integrated Services Architecture) framework provides a distributed service system capable of controlling and optimizing large-scale, data-intensive applications. An essential part of managing large-scale, distributed data-processing facilities is a monitoring system for computing facilities, storage, networks, and the very large number of applications running on these systems in near realtime. All this monitoring information gathered for all the subsystems is essential for developing the required higher-level services—the components that provide decision support and some degree of automated decisions—and for maintaining and optimizing workflow in large-scale distributed systems. These management and global optimization functions are performed by higher-level agent-based services. We present several applications of MonALISA's higher-level services including optimized dynamic routing, control, data-transfer scheduling, distributed job scheduling, dynamic allocation of storage resource to running jobs and automated management of remote services among a large set of grid facilities.

Large-Scale Phenomics Identifies Primary and Fine-Tuning Roles for CRKs in Responses Related to Oxidative Stress

PubMed Central

Rayapuram, Channabasavangowda; Idänheimo, Niina; Hunter, Kerri; Kimura, Sachie; Merilo, Ebe; Vaattovaara, Aleksia; Oracz, Krystyna; Kaufholdt, David; Pallon, Andres; Anggoro, Damar Tri; Glów, Dawid; Lowe, Jennifer; Zhou, Ji; Mohammadi, Omid; Puukko, Tuomas; Albert, Andreas; Lang, Hans; Ernst, Dieter; Kollist, Hannes; Brosché, Mikael; Durner, Jörg; Borst, Jan Willem; Collinge, David B.; Karpiński, Stanisław; Lyngkjær, Michael F.; Robatzek, Silke; Wrzaczek, Michael; Kangasjärvi, Jaakko

2015-01-01

Cysteine-rich receptor-like kinases (CRKs) are transmembrane proteins characterized by the presence of two domains of unknown function 26 (DUF26) in their ectodomain. The CRKs form one of the largest groups of receptor-like protein kinases in plants, but their biological functions have so far remained largely uncharacterized. We conducted a large-scale phenotyping approach of a nearly complete crk T-DNA insertion line collection showing that CRKs control important aspects of plant development and stress adaptation in response to biotic and abiotic stimuli in a non-redundant fashion. In particular, the analysis of reactive oxygen species (ROS)-related stress responses, such as regulation of the stomatal aperture, suggests that CRKs participate in ROS/redox signalling and sensing. CRKs play general and fine-tuning roles in the regulation of stomatal closure induced by microbial and abiotic cues. Despite their great number and high similarity, large-scale phenotyping identified specific functions in diverse processes for many CRKs and indicated that CRK2 and CRK5 play predominant roles in growth regulation and stress adaptation, respectively. As a whole, the CRKs contribute to specificity in ROS signalling. Individual CRKs control distinct responses in an antagonistic fashion suggesting future potential for using CRKs in genetic approaches to improve plant performance and stress tolerance. PMID:26197346

Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation.

PubMed

Jacquet, Claire; Mouillot, David; Kulbicki, Michel; Gravel, Dominique

2017-02-01

The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species-area relationship. We compare model predictions to the body-size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large-sized species than large and connected reefs. We also find that knowledge of species body-size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation. © 2016 John Wiley & Sons Ltd/CNRS.

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.

Systematic methods for defining coarse-grained maps in large biomolecules.

PubMed

Zhang, Zhiyong

2015-01-01

Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.

Large-Scale Corrections to the CMB Anisotropy from Asymptotic de Sitter Mode

NASA Astrophysics Data System (ADS)

Sojasi, A.

2018-01-01

In this study, large-scale effects from asymptotic de Sitter mode on the CMB anisotropy are investigated. Besides the slow variation of the Hubble parameter onset of the last stage of inflation, the recent observational constraints from Planck and WMAP on spectral index confirm that the geometry of the universe can not be pure de Sitter in this era. Motivated by these evidences, we use this mode to calculate the power spectrum of the CMB anisotropy on the large scale. It is found that the CMB spectrum is dependent on the index of Hankel function ν which in the de Sitter limit ν → 3/2, the power spectrum reduces to the scale invariant result. Also, the result shows that the spectrum of anisotropy is dependent on angular scale and slow-roll parameter and these additional corrections are swept away by a cutoff scale parameter H ≪ M ∗ < M P .

Tomato functional genomics database (TFGD): a comprehensive collection and analysis package for tomato functional genomics

USDA-ARS?s Scientific Manuscript database

Tomato Functional Genomics Database (TFGD; http://ted.bti.cornell.edu) provides a comprehensive systems biology resource to store, mine, analyze, visualize and integrate large-scale tomato functional genomics datasets. The database is expanded from the previously described Tomato Expression Database...

Classification and asymptotic scaling of the light-cone wave-function amplitudes of hadrons

DOE PAGES

Ji, Xiangdong; Ma, Jian-Ping; Yuan, Feng

2004-01-29

Here we classify the hadron light-cone wave-function amplitudes in terms of parton helicity, orbital angular momentum, and quark-flavor and color symmetries. We show in detail how this is done for the pion, ρ meson, nucleon, and delta resonance up to and including three partons. For the pion and nucleon, we also consider four-parton amplitudes. Using the scaling law derived previously, we show how these amplitudes scale in the limit that all parton transverse momenta become large.

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

The formation of cosmic structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Gooding, Andrew K.; Park, Changbom; Spergel, David N.; Turok, Neil; Gott, Richard, III

1992-01-01

The growth of density fluctuations induced by global texture in an Omega = 1 cold dark matter (CDM) cosmogony is calculated. The resulting power spectra are in good agreement with each other, with more power on large scales than in the standard inflation plus CDM model. Calculation of related statistics (two-point correlation functions, mass variances, cosmic Mach number) indicates that the texture plus CDM model compares more favorably than standard CDM with observations of large-scale structure. Texture produces coherent velocity fields on large scales, as observed. Excessive small-scale velocity dispersions, and voids less empty than those observed may be remedied by including baryonic physics. The topology of the cosmic structure agrees well with observation. The non-Gaussian texture induced density fluctuations lead to earlier nonlinear object formation than in Gaussian models and may also be more compatible with recent evidence that the galaxy density field is non-Gaussian on large scales. On smaller scales the density field is strongly non-Gaussian, but this appears to be primarily due to nonlinear gravitational clustering. The velocity field on smaller scales is surprisingly Gaussian.

The value of cows in reference populations for genomic selection of new functional traits.

PubMed

Buch, L H; Kargo, M; Berg, P; Lassen, J; Sørensen, A C

2012-06-01

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic prediction model to test the hypothesis that the value of cows in reference populations depends on the availability of phenotypic records. To test the hypothesis, we investigated different strategies of building a reference population for a new functional trait over a 10-year period. The trait was either recorded on a large scale (30 000 cows per year) or on a small scale (2000 cows per year). For large-scale recording, we compared four scenarios where the reference population consisted of 30 sires; 30 sires and 170 test bulls; 30 sires and 2000 cows; or 30 sires, 2000 cows and 170 test bulls in the first year with measurements of the new functional trait. In addition to varying the make-up of the reference population, we also varied the heritability of the trait (h2 = 0.05 v. 0.15). The results showed that a reference population of test bulls, cows and sires results in the highest accuracy of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new functional trait. The results showed that a reference population of cows results in the highest accuracy of the DGV whether the heritability is 0.05 or 0.15, because variation is lost when phenotypic data on cows are summarized in EBV of their sires. The main conclusions from this study are: (i) the fewer phenotypic records, the larger effect of including cows in the reference population; (ii) for small-scale recording, the accuracy of the DGV will continue to increase for several years, whereas the increases in the accuracy of the DGV quickly decrease with large-scale recording; (iii) it is possible to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls.

Large-scale production and study of a synthetic G protein-coupled receptor: Human olfactory receptor 17-4

PubMed Central

Cook, Brian L.; Steuerwald, Dirk; Kaiser, Liselotte; Graveland-Bikker, Johanna; Vanberghem, Melanie; Berke, Allison P.; Herlihy, Kara; Pick, Horst; Vogel, Horst; Zhang, Shuguang

2009-01-01

Although understanding of the olfactory system has progressed at the level of downstream receptor signaling and the wiring of olfactory neurons, the system remains poorly understood at the molecular level of the receptors and their interaction with and recognition of odorant ligands. The structure and functional mechanisms of these receptors still remain a tantalizing enigma, because numerous previous attempts at the large-scale production of functional olfactory receptors (ORs) have not been successful to date. To investigate the elusive biochemistry and molecular mechanisms of olfaction, we have developed a mammalian expression system for the large-scale production and purification of a functional OR protein in milligram quantities. Here, we report the study of human OR17-4 (hOR17-4) purified from a HEK293S tetracycline-inducible system. Scale-up of production yield was achieved through suspension culture in a bioreactor, which enabled the preparation of >10 mg of monomeric hOR17-4 receptor after immunoaffinity and size exclusion chromatography, with expression yields reaching 3 mg/L of culture medium. Several key post-translational modifications were identified using MS, and CD spectroscopy showed the receptor to be ≈50% α-helix, similar to other recently determined G protein-coupled receptor structures. Detergent-solubilized hOR17-4 specifically bound its known activating odorants lilial and floralozone in vitro, as measured by surface plasmon resonance. The hOR17-4 also recognized specific odorants in heterologous cells as determined by calcium ion mobilization. Our system is feasible for the production of large quantities of OR necessary for structural and functional analyses and research into OR biosensor devices. PMID:19581598

Large-scale production and study of a synthetic G protein-coupled receptor: human olfactory receptor 17-4.

PubMed

Cook, Brian L; Steuerwald, Dirk; Kaiser, Liselotte; Graveland-Bikker, Johanna; Vanberghem, Melanie; Berke, Allison P; Herlihy, Kara; Pick, Horst; Vogel, Horst; Zhang, Shuguang

2009-07-21

Although understanding of the olfactory system has progressed at the level of downstream receptor signaling and the wiring of olfactory neurons, the system remains poorly understood at the molecular level of the receptors and their interaction with and recognition of odorant ligands. The structure and functional mechanisms of these receptors still remain a tantalizing enigma, because numerous previous attempts at the large-scale production of functional olfactory receptors (ORs) have not been successful to date. To investigate the elusive biochemistry and molecular mechanisms of olfaction, we have developed a mammalian expression system for the large-scale production and purification of a functional OR protein in milligram quantities. Here, we report the study of human OR17-4 (hOR17-4) purified from a HEK293S tetracycline-inducible system. Scale-up of production yield was achieved through suspension culture in a bioreactor, which enabled the preparation of >10 mg of monomeric hOR17-4 receptor after immunoaffinity and size exclusion chromatography, with expression yields reaching 3 mg/L of culture medium. Several key post-translational modifications were identified using MS, and CD spectroscopy showed the receptor to be approximately 50% alpha-helix, similar to other recently determined G protein-coupled receptor structures. Detergent-solubilized hOR17-4 specifically bound its known activating odorants lilial and floralozone in vitro, as measured by surface plasmon resonance. The hOR17-4 also recognized specific odorants in heterologous cells as determined by calcium ion mobilization. Our system is feasible for the production of large quantities of OR necessary for structural and functional analyses and research into OR biosensor devices.

Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function.

PubMed

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

2014-05-01

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

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

NASA Astrophysics Data System (ADS)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that distinct strategies for coping with seasonality underlie phenological diversity. Observed drought responses highlight the importance of non-linear community responses to climate. Community phenology exhibits scale-specific patterns highlighting the need for multi-scale approaches to community dynamics.

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

Scaling analysis of cloud and rain water in marine stratocumulus and implications for scale-aware microphysical parameterizations

NASA Astrophysics Data System (ADS)

Witte, M.; Morrison, H.; Jensen, J. B.; Bansemer, A.; Gettelman, A.

2017-12-01

The spatial covariance of cloud and rain water (or in simpler terms, small and large drops, respectively) is an important quantity for accurate prediction of the accretion rate in bulk microphysical parameterizations that account for subgrid variability using assumed probability density functions (pdfs). Past diagnoses of this covariance from remote sensing, in situ measurements and large eddy simulation output have implicitly assumed that the magnitude of the covariance is insensitive to grain size (i.e. horizontal resolution) and averaging length, but this is not the case because both cloud and rain water exhibit scale invariance across a wide range of scales - from tens of centimeters to tens of kilometers in the case of cloud water, a range that we will show is primarily limited by instrumentation and sampling issues. Since the individual variances systematically vary as a function of spatial scale, it should be expected that the covariance follows a similar relationship. In this study, we quantify the scaling properties of cloud and rain water content and their covariability from high frequency in situ aircraft measurements of marine stratocumulus taken over the southeastern Pacific Ocean aboard the NSF/NCAR C-130 during the VOCALS-REx field experiment of October-November 2008. First we confirm that cloud and rain water scale in distinct manners, indicating that there is a statistically and potentially physically significant difference in the spatial structure of the two fields. Next, we demonstrate that the covariance is a strong function of spatial scale, which implies important caveats regarding the ability of limited-area models with domains smaller than a few tens of kilometers across to accurately reproduce the spatial organization of precipitation. Finally, we present preliminary work on the development of a scale-aware parameterization of cloud-rain water subgrid covariability based in multifractal analysis intended for application in large-scale model microphysics schemes.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

Techniques for Large-Scale Bacterial Genome Manipulation and Characterization of the Mutants with Respect to In Silico Metabolic Reconstructions.

PubMed

diCenzo, George C; Finan, Turlough M

2018-01-01

The rate at which all genes within a bacterial genome can be identified far exceeds the ability to characterize these genes. To assist in associating genes with cellular functions, a large-scale bacterial genome deletion approach can be employed to rapidly screen tens to thousands of genes for desired phenotypes. Here, we provide a detailed protocol for the generation of deletions of large segments of bacterial genomes that relies on the activity of a site-specific recombinase. In this procedure, two recombinase recognition target sequences are introduced into known positions of a bacterial genome through single cross-over plasmid integration. Subsequent expression of the site-specific recombinase mediates recombination between the two target sequences, resulting in the excision of the intervening region and its loss from the genome. We further illustrate how this deletion system can be readily adapted to function as a large-scale in vivo cloning procedure, in which the region excised from the genome is captured as a replicative plasmid. We next provide a procedure for the metabolic analysis of bacterial large-scale genome deletion mutants using the Biolog Phenotype MicroArray™ system. Finally, a pipeline is described, and a sample Matlab script is provided, for the integration of the obtained data with a draft metabolic reconstruction for the refinement of the reactions and gene-protein-reaction relationships in a metabolic reconstruction.

Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data.

PubMed

Ibrahim, Mohamed; Wickenhauser, Patrick; Rautek, Peter; Reina, Guido; Hadwiger, Markus

2018-01-01

Molecular dynamics (MD) simulations are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulations with 10 million particles or more, the visualization of large fields-of-view usually suffers from strong aliasing artifacts, because the mismatch between data size and output resolution leads to severe under-sampling of the geometry. Excessive super-sampling can alleviate this problem, but is prohibitively expensive. This paper presents a novel visualization method for large-scale particle data that addresses aliasing while enabling interactive high-quality rendering. We introduce the novel concept of screen-space normal distribution functions (S-NDFs) for particle data. S-NDFs represent the distribution of surface normals that map to a given pixel in screen space, which enables high-quality re-lighting without re-rendering particles. In order to facilitate interactive zooming, we cache S-NDFs in a screen-space mipmap (S-MIP). Together, these two concepts enable interactive, scale-consistent re-lighting and shading changes, as well as zooming, without having to re-sample the particle data. We show how our method facilitates the interactive exploration of real-world large-scale MD simulation data in different scenarios.

Ontogenetic functional diversity: size structure of a keystone predator drives functioning of a complex ecosystem.

PubMed

Rudolf, Volker H W; Rasmussen, Nick L

2013-05-01

A central challenge in community ecology is to understand the connection between biodiversity and the functioning of ecosystems. While traditional approaches have largely focused on species-level diversity, increasing evidence indicates that there exists substantial ecological diversity among individuals within species. By far, the largest source of this intraspecific diversity stems from variation among individuals in ontogenetic stage and size. Although such ontogenetic shifts are ubiquitous in natural communities, whether and how they scale up to influence the structure and functioning of complex ecosystems is largely unknown. Here we take an experimental approach to examine the consequences of ontogenetic niche shifts for the structure of communities and ecosystem processes. In particular we experimentally manipulated the stage structure in a keystone predator, larvae of the dragonfly Anax junius, in complex experimental pond communities to test whether changes in the population stage or size structure of a keystone species scale up to alter community structure and ecosystem processes, and how functional differences scale with relative differences in size among stages. We found that the functional role of A. junius was stage-specific. Altering what stages were present in a pond led to concurrent changes in community structure, primary producer biomass (periphyton and phytoplankton), and ultimately altered ecosystem processes (respiration and net primary productivity), indicating a strong, but stage-specific, trophic cascade. Interestingly, the stage-specific effects did not simply scale with size or biomass of the predator, but instead indicated clear ontogenetic niche shifts in ecological interactions. Thus, functional differences among stages within a keystone species scaled up to alter the functioning of entire ecosystems. Therefore, our results indicate that the classical approach of assuming an average functional role of a species can be misleading because functional roles are dynamic and will change with shifts in the stage structure of the species. In general this emphasizes the importance of accounting for functional diversity below the species level to predict how natural and anthropogenic changes alter the functioning of natural ecosystems.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

The influence of sub-grid scale motions on particle collision in homogeneous isotropic turbulence

NASA Astrophysics Data System (ADS)

Xiong, Yan; Li, Jing; Liu, Zhaohui; Zheng, Chuguang

2018-02-01

The absence of sub-grid scale (SGS) motions leads to severe errors in particle pair dynamics, which represents a great challenge to the large eddy simulation of particle-laden turbulent flow. In order to address this issue, data from direct numerical simulation (DNS) of homogenous isotropic turbulence coupled with Lagrangian particle tracking are used as a benchmark to evaluate the corresponding results of filtered DNS (FDNS). It is found that the filtering process in FDNS will lead to a non-monotonic variation of the particle collision statistics, including radial distribution function, radial relative velocity, and the collision kernel. The peak of radial distribution function shifts to the large-inertia region due to the lack of SGS motions, and the analysis of the local flowstructure characteristic variable at particle position indicates that the most effective interaction scale between particles and fluid eddies is increased in FDNS. Moreover, this scale shifting has an obvious effect on the odd-order moments of the probability density function of radial relative velocity, i.e. the skewness, which exhibits a strong correlation to the variance of radial distribution function in FDNS. As a whole, the radial distribution function, together with radial relative velocity, can compensate the SGS effects for the collision kernel in FDNS when the Stokes number based on the Kolmogorov time scale is greater than 3.0. However, it still leaves considerable errors for { St}_k <3.0.

An Automated Test of Rat Forelimb Supination Quantifies Motor Function Loss and Recovery After Corticospinal Injury.

PubMed

Sindhurakar, Anil; Butensky, Samuel D; Meyers, Eric; Santos, Joshua; Bethea, Thelma; Khalili, Ashley; Sloan, Andrew P; Rennaker, Robert L; Carmel, Jason B

2017-02-01

Rodents are the primary animal model of corticospinal injury and repair, yet current behavioral tests do not show the large deficits after injury observed in humans. Forearm supination is critical for hand function and is highly impaired by corticospinal injury in both humans and rats. Current tests of rodent forelimb function do not measure this movement. To determine if quantification of forelimb supination in rats reveals large-scale functional loss and partial recovery after corticospinal injury. We developed a knob supination device that quantifies supination using automated and objective methods. Rats in a reaching box have to grasp and turn a knob in supination in order to receive a food reward. Performance on this task and the single pellet reaching task were measured before and after 2 manipulations of the pyramidal tract: a cut lesion of 1 pyramid and inactivation of motor cortex using 2 different drug doses. A cut lesion of the corticospinal tract produced a large deficit in supination. In contrast, there was no change in pellet retrieval success. Supination function recovered partially over 6 weeks after injury, and a large deficit remained. Motor cortex inactivation produced a dose-dependent loss of knob supination; the effect on pellet reaching was more subtle. The knob supination task reveals in rodents 3 signature hand function changes observed in humans with corticospinal injury: (1) large-scale loss with injury, (2) partial recovery in the weeks after injury, and (3) loss proportional to degree of dysfunction.

A machine learning approach for efficient uncertainty quantification using multiscale methods

NASA Astrophysics Data System (ADS)

Chan, Shing; Elsheikh, Ahmed H.

2018-02-01

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions. Specifically, we employ a neural network predictor fitted using a set of solution samples from which it learns to generate subsequent basis functions at a lower computational cost than solving the local problems. The computational advantage of this approach is realized for uncertainty quantification tasks where a large number of realizations has to be evaluated. We attribute the ability to learn these basis functions to the modularity of the local problems and the redundancy of the permeability patches between samples. The proposed method is evaluated on elliptic problems yielding very promising results.

Tau, amyloid, and cascading network failure across the Alzheimer's disease spectrum.

PubMed

Jones, David T; Graff-Radford, Jonathan; Lowe, Val J; Wiste, Heather J; Gunter, Jeffrey L; Senjem, Matthew L; Botha, Hugo; Kantarci, Kejal; Boeve, Bradley F; Knopman, David S; Petersen, Ronald C; Jack, Clifford R

2017-12-01

Functionally related brain regions are selectively vulnerable to Alzheimer's disease pathophysiology. However, molecular markers of this pathophysiology (i.e., beta-amyloid and tau aggregates) have discrepant spatial and temporal patterns of progression within these selectively vulnerable brain regions. Existing reductionist pathophysiologic models cannot account for these large-scale spatiotemporal inconsistencies. Within the framework of the recently proposed cascading network failure model of Alzheimer's disease, however, these large-scale patterns are to be expected. This model postulates the following: 1) a tau-associated, circumscribed network disruption occurs in brain regions specific to a given phenotype in clinically normal individuals; 2) this disruption can trigger phenotype independent, stereotypic, and amyloid-associated compensatory brain network changes indexed by changes in the default mode network; 3) amyloid deposition marks a saturation of functional compensation and portends an acceleration of the inciting phenotype specific, and tau-associated, network failure. With the advent of in vivo molecular imaging of tau pathology, combined with amyloid and functional network imaging, it is now possible to investigate the relationship between functional brain networks, tau, and amyloid across the disease spectrum within these selectively vulnerable brain regions. In a large cohort (n = 218) spanning the Alzheimer's disease spectrum from young, amyloid negative, cognitively normal subjects to Alzheimer's disease dementia, we found several distinct spatial patterns of tau deposition, including 'Braak-like' and 'non-Braak-like', across functionally related brain regions. Rather than arising focally and spreading sequentially, elevated tau signal seems to occur system-wide based on inferences made from multiple cross-sectional analyses we conducted looking at regional patterns of tau signal. Younger age-of-disease-onset was associated with 'non-Braak-like' patterns of tau, suggesting an association with atypical clinical phenotypes. As predicted by the cascading network failure model of Alzheimer's disease, we found that amyloid is a partial mediator of the relationship between functional network failure and tau deposition in functionally connected brain regions. This study implicates large-scale brain networks in the pathophysiology of tau deposition and offers support to models incorporating large-scale network physiology into disease models linking tau and amyloid, such as the cascading network failure model of Alzheimer's disease. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Studies of land-cover, land-use, and biophysical properties of vegetation in the Large Scale Biosphere Atmosphere experiment in Amazonia.

Treesearch

Dar A. Robertsa; Michael Keller; Joao Vianei Soares

2003-01-01

We summarize early research on land-cover, land-use, and biophysical properties of vegetation from the Large Scale Biosphere Atmosphere (LBA) experiment in Amazoˆnia. LBA is an international research program developed to evaluate regional function and to determine how land-use and climate modify biological, chemical and physical processes there. Remote sensing has...

A new energy transfer model for turbulent free shear flow

NASA Technical Reports Server (NTRS)

Liou, William W.-W.

1992-01-01

A new model for the energy transfer mechanism in the large-scale turbulent kinetic energy equation is proposed. An estimate of the characteristic length scale of the energy containing large structures is obtained from the wavelength associated with the structures predicted by a weakly nonlinear analysis for turbulent free shear flows. With the inclusion of the proposed energy transfer model, the weakly nonlinear wave models for the turbulent large-scale structures are self-contained and are likely to be independent flow geometries. The model is tested against a plane mixing layer. Reasonably good agreement is achieved. Finally, it is shown by using the Liapunov function method, the balance between the production and the drainage of the kinetic energy of the turbulent large-scale structures is asymptotically stable as their amplitude saturates. The saturation of the wave amplitude provides an alternative indicator for flow self-similarity.

Derivation of large-scale cellular regulatory networks from biological time series data.

PubMed

de Bivort, Benjamin L

2010-01-01

Pharmacological agents and other perturbants of cellular homeostasis appear to nearly universally affect the activity of many genes, proteins, and signaling pathways. While this is due in part to nonspecificity of action of the drug or cellular stress, the large-scale self-regulatory behavior of the cell may also be responsible, as this typically means that when a cell switches states, dozens or hundreds of genes will respond in concert. If many genes act collectively in the cell during state transitions, rather than every gene acting independently, models of the cell can be created that are comprehensive of the action of all genes, using existing data, provided that the functional units in the model are collections of genes. Techniques to develop these large-scale cellular-level models are provided in detail, along with methods of analyzing them, and a brief summary of major conclusions about large-scale cellular networks to date.

Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

PubMed

Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

2016-09-26

In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

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

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

Direction of information flow in large-scale resting-state networks is frequency-dependent.

PubMed

Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

2016-04-05

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Intensive agriculture erodes β-diversity at large scales.

PubMed

Karp, Daniel S; Rominger, Andrew J; Zook, Jim; Ranganathan, Jai; Ehrlich, Paul R; Daily, Gretchen C

2012-09-01

Biodiversity is declining from unprecedented land conversions that replace diverse, low-intensity agriculture with vast expanses under homogeneous, intensive production. Despite documented losses of species richness, consequences for β-diversity, changes in community composition between sites, are largely unknown, especially in the tropics. Using a 10-year data set on Costa Rican birds, we find that low-intensity agriculture sustained β-diversity across large scales on a par with forest. In high-intensity agriculture, low local (α) diversity inflated β-diversity as a statistical artefact. Therefore, at small spatial scales, intensive agriculture appeared to retain β-diversity. Unlike in forest or low-intensity systems, however, high-intensity agriculture also homogenised vegetation structure over large distances, thereby decoupling the fundamental ecological pattern of bird communities changing with geographical distance. This ~40% decline in species turnover indicates a significant decline in β-diversity at large spatial scales. These findings point the way towards multi-functional agricultural systems that maintain agricultural productivity while simultaneously conserving biodiversity. © 2012 Blackwell Publishing Ltd/CNRS.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Functional Topography of Human Auditory Cortex

PubMed Central

Rauschecker, Josef P.

2016-01-01

Functional and anatomical studies have clearly demonstrated that auditory cortex is populated by multiple subfields. However, functional characterization of those fields has been largely the domain of animal electrophysiology, limiting the extent to which human and animal research can inform each other. In this study, we used high-resolution functional magnetic resonance imaging to characterize human auditory cortical subfields using a variety of low-level acoustic features in the spectral and temporal domains. Specifically, we show that topographic gradients of frequency preference, or tonotopy, extend along two axes in human auditory cortex, thus reconciling historical accounts of a tonotopic axis oriented medial to lateral along Heschl's gyrus and more recent findings emphasizing tonotopic organization along the anterior–posterior axis. Contradictory findings regarding topographic organization according to temporal modulation rate in acoustic stimuli, or “periodotopy,” are also addressed. Although isolated subregions show a preference for high rates of amplitude-modulated white noise (AMWN) in our data, large-scale “periodotopic” organization was not found. Organization by AM rate was correlated with dominant pitch percepts in AMWN in many regions. In short, our data expose early auditory cortex chiefly as a frequency analyzer, and spectral frequency, as imposed by the sensory receptor surface in the cochlea, seems to be the dominant feature governing large-scale topographic organization across human auditory cortex. SIGNIFICANCE STATEMENT In this study, we examine the nature of topographic organization in human auditory cortex with fMRI. Topographic organization by spectral frequency (tonotopy) extended in two directions: medial to lateral, consistent with early neuroimaging studies, and anterior to posterior, consistent with more recent reports. Large-scale organization by rates of temporal modulation (periodotopy) was correlated with confounding spectral content of amplitude-modulated white-noise stimuli. Together, our results suggest that the organization of human auditory cortex is driven primarily by its response to spectral acoustic features, and large-scale periodotopy spanning across multiple regions is not supported. This fundamental information regarding the functional organization of early auditory cortex will inform our growing understanding of speech perception and the processing of other complex sounds. PMID:26818527

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.

Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

NASA Technical Reports Server (NTRS)

Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

2005-01-01

Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

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.

An experimental study of large-scale vortices over a blunt-faced flat plate in pulsating flow

NASA Astrophysics Data System (ADS)

Hwang, K. S.; Sung, H. J.; Hyun, J. M.

Laboratory measurements are made of flow over a blunt flat plate of finite thickness, which is placed in a pulsating free stream, U=Uo(1+Aocos 2πfpt). Low turbulence-intensity wind tunnel experiments are conducted in the ranges of Stp<=1.23 and Ao<=0.118 at ReH=560. Pulsation is generated by means of a woofer speaker. Variations of the time-mean reattachment length xR as functions of Stp and Ao are scrutinized by using the forward-time fraction and surface pressure distributions (Cp). The shedding frequency of large-scale vortices due to pulsation is measured. Flow visualizations depict the behavior of large-scale vortices. The results for non-pulsating flows (Ao=0) are consistent with the published data. In the lower range of Ao, as Stp increases, xR attains a minimum value at a particular pulsation frequency. For large Ao, the results show complicated behaviors of xR. For Stp>=0.80, changes in xR are insignificant as Ao increases. The shedding frequency of large-scale vortices is locked-in to the pulsation frequency. A vortex-pairing process takes place between two neighboring large-scale vortices in the separated shear layer.

Statistical characterization of Earth’s heterogeneities from seismic scattering

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, R.

2009-12-01

The distortion of a teleseismic wavefront carries information about the heterogeneities through which the wave propagates and it is manifestited as logarithmic amplitude (logA) and phase fluctuations of the direct P wave recorded by a seismic network. By cross correlating the fluctuations (e.g., logA-logA or phase-phase), we obtain coherence functions, which depend on spatial lags between stations and incident angles between the incident waves. We have mathematically related the depth-dependent heterogeneity spectrum to the observable coherence functions using seismic scattering theory. We will show that our method has sharp depth resolution. Using the HiNet seismic network data in Japan, we have inverted power spectra for two depth ranges, ~0-120km and below ~120km depth. The coherence functions formed by different groups of stations or by different groups of earthquakes at different back azimuths are similar. This demonstrates that the method is statistically stable and the inhomogeneities are statistically stationary. In both depth intervals, the trend of the spectral amplitude decays from large scale to small scale in a power-law fashion with exceptions at ~50km for the logA data. Due to the spatial spacing of the seismometers, only information from length scale 15km to 200km is inverted. However our scattering method provides new information on small to intermediate scales that are comparable to scales of the recycled materials and thus is complimentary to the global seismic tomography which reveals mainly large-scale heterogeneities on the order of ~1000km. The small-scale heterogeneities revealed here are not likely of pure thermal origin. Therefore, the length scale and strength of heterogeneities as a function of depth may provide important constraints in mechanical mixing of various components in the mantle convection.

A practical overview and comparison of certain commercial forensic software tools for processing large-scale digital investigations

NASA Astrophysics Data System (ADS)

Kröger, Knut; Creutzburg, Reiner

2013-05-01

The aim of this paper is to show the usefulness of modern forensic software tools for processing large-scale digital investigations. In particular, we focus on the new version of Nuix 4.2 and compare it with AccessData FTK 4.2, X-Ways Forensics 16.9 and Guidance Encase Forensic 7 regarding its performance, functionality, usability and capability. We will show how these software tools work with large forensic images and how capable they are in examining complex and big data scenarios.

Large-Scale Brain Systems in ADHD: Beyond the Prefrontal-Striatal Model

PubMed Central

Castellanos, F. Xavier; Proal, Erika

2012-01-01

Attention-deficit/hyperactivity disorder (ADHD) has long been thought to reflect dysfunction of prefrontal-striatal circuitry, with involvement of other circuits largely ignored. Recent advances in systems neuroscience-based approaches to brain dysfunction enable the development of models of ADHD pathophysiology that encompass a number of different large-scale “resting state” networks. Here we review progress in delineating large-scale neural systems and illustrate their relevance to ADHD. We relate frontoparietal, dorsal attentional, motor, visual, and default networks to the ADHD functional and structural literature. Insights emerging from mapping intrinsic brain connectivity networks provide a potentially mechanistic framework for understanding aspects of ADHD, such as neuropsychological and behavioral inconsistency, and the possible role of primary visual cortex in attentional dysfunction in the disorder. PMID:22169776

The large-scale organization of metabolic networks

NASA Astrophysics Data System (ADS)

Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z. N.; Barabási, A.-L.

2000-10-01

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

Scale-dependent coupling of hysteretic capillary pressure, trapping, and fluid mobilities

NASA Astrophysics Data System (ADS)

Doster, F.; Celia, M. A.; Nordbotten, J. M.

2012-12-01

Many applications of multiphase flow in porous media, including CO2-storage and enhanced oil recovery, require mathematical models that span a large range of length scales. In the context of numerical simulations, practical grid sizes are often on the order of tens of meters, thereby de facto defining a coarse model scale. Under particular conditions, it is possible to approximate the sub-grid-scale distribution of the fluid saturation within a grid cell; that reconstructed saturation can then be used to compute effective properties at the coarse scale. If both the density difference between the fluids and the vertical extend of the grid cell are large, and buoyant segregation within the cell on a sufficiently shorte time scale, then the phase pressure distributions are essentially hydrostatic and the saturation profile can be reconstructed from the inferred capillary pressures. However, the saturation reconstruction may not be unique because the parameters and parameter functions of classical formulations of two-phase flow in porous media - the relative permeability functions, the capillary pressure -saturation relationship, and the residual saturations - show path dependence, i.e. their values depend not only on the state variables but also on their drainage and imbibition histories. In this study we focus on capillary pressure hysteresis and trapping and show that the contribution of hysteresis to effective quantities is dependent on the vertical length scale. By studying the transition from the two extreme cases - the homogeneous saturation distribution for small vertical extents and the completely segregated distribution for large extents - we identify how hysteretic capillary pressure at the local scale induces hysteresis in all coarse-scale quantities for medium vertical extents and finally vanishes for large vertical extents. Our results allow for more accurate vertically integrated modeling while improving our understanding of the coupling of capillary pressure and relative permeabilities over larger length scales.

Moditored unsaturated soil transport processes as a support for large scale soil and water management

NASA Astrophysics Data System (ADS)

Vanclooster, Marnik

2010-05-01

The current societal demand for sustainable soil and water management is very large. The drivers of global and climate change exert many pressures on the soil and water ecosystems, endangering appropriate ecosystem functioning. The unsaturated soil transport processes play a key role in soil-water system functioning as it controls the fluxes of water and nutrients from the soil to plants (the pedo-biosphere link), the infiltration flux of precipitated water to groundwater and the evaporative flux, and hence the feed back from the soil to the climate system. Yet, unsaturated soil transport processes are difficult to quantify since they are affected by huge variability of the governing properties at different space-time scales and the intrinsic non-linearity of the transport processes. The incompatibility of the scales between the scale at which processes reasonably can be characterized, the scale at which the theoretical process correctly can be described and the scale at which the soil and water system need to be managed, calls for further development of scaling procedures in unsaturated zone science. It also calls for a better integration of theoretical and modelling approaches to elucidate transport processes at the appropriate scales, compatible with the sustainable soil and water management objective. Moditoring science, i.e the interdisciplinary research domain where modelling and monitoring science are linked, is currently evolving significantly in the unsaturated zone hydrology area. In this presentation, a review of current moditoring strategies/techniques will be given and illustrated for solving large scale soil and water management problems. This will also allow identifying research needs in the interdisciplinary domain of modelling and monitoring and to improve the integration of unsaturated zone science in solving soil and water management issues. A focus will be given on examples of large scale soil and water management problems in Europe.

Upscaled soil-water retention using van Genuchten's function

USGS Publications Warehouse

Green, T.R.; Constantz, J.E.; Freyberg, D.L.

1996-01-01

Soils are often layered at scales smaller than the block size used in numerical and conceptual models of variably saturated flow. Consequently, the small-scale variability in water content within each block must be homogenized (upscaled). Laboratory results have shown that a linear volume average (LVA) of water content at a uniform suction is a good approximation to measured water contents in heterogeneous cores. Here, we upscale water contents using van Genuchten's function for both the local and upscaled soil-water-retention characteristics. The van Genuchten (vG) function compares favorably with LVA results, laboratory experiments under hydrostatic conditions in 3-cm cores, and numerical simulations of large-scale gravity drainage. Our method yields upscaled vG parameter values by fitting the vG curve to the LVA of water contents at various suction values. In practice, it is more efficient to compute direct averages of the local vG parameter values. Nonlinear power averages quantify a feasible range of values for each upscaled vG shape parameter; upscaled values of N are consistently less than the harmonic means, reflecting broad pore-size distributions of the upscaled soils. The vG function is useful for modeling soil-water retention at large scales, and these results provide guidance for its application.

Protein homology model refinement by large-scale energy optimization.

PubMed

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

A quenched study of the Schrödinger functional with chirally rotated boundary conditions: Applications

NASA Astrophysics Data System (ADS)

González López, J.; Jansen, K.; Renner, D. B.; Shindler, A.

2013-02-01

In a previous paper (González López, et al., 2013) [1], we have discussed the non-perturbative tuning of the chirally rotated Schrödinger functional (χSF). This tuning is required to eliminate bulk O(a) cutoff effects in physical correlation functions. Using our tuning results obtained in González López et al. (2013) [1] we perform scaling and universality tests analyzing the residual O(a) cutoff effects of several step-scaling functions and we compute renormalization factors at the matching scale. As an example of possible application of the χSF we compute the renormalized strange quark mass using large volume data obtained from Wilson twisted mass fermions at maximal twist.

On the linearity of tracer bias around voids

NASA Astrophysics Data System (ADS)

Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro

2017-07-01

The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.

Large-scale modeling of rain fields from a rain cell deterministic model

NASA Astrophysics Data System (ADS)

FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia

2006-04-01

A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

PubMed

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, p<0.001), with worse dystonia severity implying worse function. Secondary dystonias had worse dystonia and less function than primary dystonias (p<0.001). A longer proportion of life lived with dystonia is associated with more severe dystonia (rs =0.42, p<0.001). The BFM-M is strongly linked with the GMFCS, MACS, and CFCS, irrespective of aetiology. Each scale offers interrelated but complementary information and is applicable to all aetiologies. Movement disorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

A user-friendly tool to transform large scale administrative data into wide table format using a MapReduce program with a Pig Latin based script.

PubMed

Horiguchi, Hiromasa; Yasunaga, Hideo; Hashimoto, Hideki; Ohe, Kazuhiko

2012-12-22

Secondary use of large scale administrative data is increasingly popular in health services and clinical research, where a user-friendly tool for data management is in great demand. MapReduce technology such as Hadoop is a promising tool for this purpose, though its use has been limited by the lack of user-friendly functions for transforming large scale data into wide table format, where each subject is represented by one row, for use in health services and clinical research. Since the original specification of Pig provides very few functions for column field management, we have developed a novel system called GroupFilterFormat to handle the definition of field and data content based on a Pig Latin script. We have also developed, as an open-source project, several user-defined functions to transform the table format using GroupFilterFormat and to deal with processing that considers date conditions. Having prepared dummy discharge summary data for 2.3 million inpatients and medical activity log data for 950 million events, we used the Elastic Compute Cloud environment provided by Amazon Inc. to execute processing speed and scaling benchmarks. In the speed benchmark test, the response time was significantly reduced and a linear relationship was observed between the quantity of data and processing time in both a small and a very large dataset. The scaling benchmark test showed clear scalability. In our system, doubling the number of nodes resulted in a 47% decrease in processing time. Our newly developed system is widely accessible as an open resource. This system is very simple and easy to use for researchers who are accustomed to using declarative command syntax for commercial statistical software and Structured Query Language. Although our system needs further sophistication to allow more flexibility in scripts and to improve efficiency in data processing, it shows promise in facilitating the application of MapReduce technology to efficient data processing with large scale administrative data in health services and clinical research.

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies.

PubMed

Furnham, Nicholas; Dawson, Natalie L; Rahman, Syed A; Thornton, Janet M; Orengo, Christine A

2016-01-29

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Large-scale variation in subsurface stream biofilms: a cross-regional comparison of metabolic function and community similarity.

PubMed

Findlay, S; Sinsabaugh, R L

2006-10-01

We examined bacterial metabolic activity and community similarity in shallow subsurface stream sediments distributed across three regions of the eastern United States to assess whether there were parallel changes in functional and structural attributes at this large scale. Bacterial growth, oxygen consumption, and a suite of extracellular enzyme activities were assayed to describe functional variability. Community similarity was assessed using randomly amplified polymorphic DNA (RAPD) patterns. There were significant differences in streamwater chemistry, metabolic activity, and bacterial growth among regions with, for instance, twofold higher bacterial production in streams near Baltimore, MD, compared to Hubbard Brook, NH. Five of eight extracellular enzymes showed significant differences among regions. Cluster analyses of individual streams by metabolic variables showed clear groups with significant differences in representation of sites from different regions among groups. Clustering of sites based on randomly amplified polymorphic DNA banding resulted in groups with generally less internal similarity although there were still differences in distribution of regional sites. There was a marginally significant (p = 0.09) association between patterns based on functional and structural variables. There were statistically significant but weak (r2 approximately 30%) associations between landcover and measures of both structure and function. These patterns imply a large-scale organization of biofilm communities and this structure may be imposed by factor(s) such as landcover and covariates such as nutrient concentrations, which are known to also cause differences in macrobiota of stream ecosystems.

Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

PubMed

Astakhov, Vadim

2009-01-01

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

Abundance of common species, not species richness, drives delivery of a real-world ecosystem service.

PubMed

Winfree, Rachael; Fox, Jeremy W; Williams, Neal M; Reilly, James R; Cariveau, Daniel P

2015-07-01

Biodiversity-ecosystem functioning experiments have established that species richness and composition are both important determinants of ecosystem function in an experimental context. Determining whether this result holds for real-world ecosystem services has remained elusive, however, largely due to the lack of analytical methods appropriate for large-scale, associational data. Here, we use a novel analytical approach, the Price equation, to partition the contribution to ecosystem services made by species richness, composition and abundance in four large-scale data sets on crop pollination by native bees. We found that abundance fluctuations of dominant species drove ecosystem service delivery, whereas richness changes were relatively unimportant because they primarily involved rare species that contributed little to function. Thus, the mechanism behind our results was the skewed species-abundance distribution. Our finding that a few common species, not species richness, drive ecosystem service delivery could have broad generality given the ubiquity of skewed species-abundance distributions in nature. © 2015 John Wiley & Sons Ltd/CNRS.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

PubMed

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults.

PubMed

Shaw, Emily E; Schultz, Aaron P; Sperling, Reisa A; Hedden, Trey

2015-10-01

Intrinsic functional connectivity MRI has become a widely used tool for measuring integrity in large-scale cortical networks. This study examined multiple cortical networks using Template-Based Rotation (TBR), a method that applies a priori network and nuisance component templates defined from an independent dataset to test datasets of interest. A priori templates were applied to a test dataset of 276 older adults (ages 65-90) from the Harvard Aging Brain Study to examine the relationship between multiple large-scale cortical networks and cognition. Factor scores derived from neuropsychological tests represented processing speed, executive function, and episodic memory. Resting-state BOLD data were acquired in two 6-min acquisitions on a 3-Tesla scanner and processed with TBR to extract individual-level metrics of network connectivity in multiple cortical networks. All results controlled for data quality metrics, including motion. Connectivity in multiple large-scale cortical networks was positively related to all cognitive domains, with a composite measure of general connectivity positively associated with general cognitive performance. Controlling for the correlations between networks, the frontoparietal control network (FPCN) and executive function demonstrated the only significant association, suggesting specificity in this relationship. Further analyses found that the FPCN mediated the relationships of the other networks with cognition, suggesting that this network may play a central role in understanding individual variation in cognition during aging.

Gene regulatory networks and the underlying biology of developmental toxicity

EPA Science Inventory

Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

Reflections on conformal spectra

DOE PAGES

Kim, Hyungrok; Kravchuk, Petr; Ooguri, Hirosi

2016-04-29

Here, we use modular invariance and crossing symmetry of conformal field theory to reveal approximate reflection symmetries in the spectral decompositions of the partition function in two dimensions in the limit of large central charge and of the four-point function in any dimension in the limit of large scaling dimensions Δ 0 of external operators. We use these symmetries to motivate universal upper bounds on the spectrum and the operator product expansion coefficients, which we then derive by independent techniques. Some of the bounds for four-point functions are valid for finite Δ 0 as well as for large Δ 0.more » We discuss a similar symmetry in a large spacetime dimension limit. Finally, we comment on the analogue of the Cardy formula and sparse light spectrum condition for the four-point function.« less

Identification and Functional Prediction of Large Intergenic Noncoding RNAs (lincRNAs) in Rainbow Trout (Oncorhynchus mykiss)

USDA-ARS?s Scientific Manuscript database

Long noncoding RNAs (lncRNAs) have been recognized in recent years as key regulators of diverse cellular processes. Genome-wide large-scale projects have uncovered thousands of lncRNAs in many model organisms. Large intergenic noncoding RNAs (lincRNAs) are lncRNAs that are transcribed from intergeni...

Species richness and biomass explain spatial turnover in ecosystem functioning across tropical and temperate ecosystems.

PubMed

Barnes, Andrew D; Weigelt, Patrick; Jochum, Malte; Ott, David; Hodapp, Dorothee; Haneda, Noor Farikhah; Brose, Ulrich

2016-05-19

Predicting ecosystem functioning at large spatial scales rests on our ability to scale up from local plots to landscapes, but this is highly contingent on our understanding of how functioning varies through space. Such an understanding has been hampered by a strong experimental focus of biodiversity-ecosystem functioning research restricted to small spatial scales. To address this limitation, we investigate the drivers of spatial variation in multitrophic energy flux-a measure of ecosystem functioning in complex communities-at the landscape scale. We use a structural equation modelling framework based on distance matrices to test how spatial and environmental distances drive variation in community energy flux via four mechanisms: species composition, species richness, niche complementarity and biomass. We found that in both a tropical and a temperate study region, geographical and environmental distance indirectly influence species richness and biomass, with clear evidence that these are the dominant mechanisms explaining variability in community energy flux over spatial and environmental gradients. Our results reveal that species composition and trait variability may become redundant in predicting ecosystem functioning at the landscape scale. Instead, we demonstrate that species richness and total biomass may best predict rates of ecosystem functioning at larger spatial scales. © 2016 The Author(s).

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

PubMed Central

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

2014-01-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028

Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

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

Cree, Johnathan Vee; Delgado-Frias, Jose

Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configuremore » the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.« less

Large angular scale CMB anisotropy from an excited initial mode

NASA Astrophysics Data System (ADS)

Sojasi, A.; Mohsenzadeh, M.; Yusofi, E.

2016-07-01

According to inflationary cosmology, the CMB anisotropy gives an opportunity to test predictions of new physics hypotheses. The initial state of quantum fluctuations is one of the important options at high energy scale, as it can affect observables such as the CMB power spectrum. In this study a quasi-de Sitter inflationary background with approximate de Sitter mode function built over the Bunch-Davies mode is applied to investigate the scale-dependency of the CMB anisotropy. The recent Planck constraint on spectral index motivated us to examine the effect of a new excited mode function (instead of pure de Sitter mode) on the CMB anisotropy at large angular scales. In so doing, it is found that the angular scale-invariance in the CMB temperature fluctuations is broken and in the limit ℓ < 200 a tiny deviation appears. Also, it is shown that the power spectrum of CMB anisotropy is dependent on a free parameter with mass dimension H << M * < M p and on the slow-roll parameter ɛ. Supported by the Islamic Azad University, Rasht Branch, Rasht, Iran

Cluster-cluster clustering

NASA Technical Reports Server (NTRS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C. S.

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Molecular dynamics simulations of large macromolecular complexes.

PubMed

Perilla, Juan R; Goh, Boon Chong; Cassidy, C Keith; Liu, Bo; Bernardi, Rafael C; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of weak rotation on large-scale circulation cessations in turbulent convection.

PubMed

Assaf, Michael; Angheluta, Luiza; Goldenfeld, Nigel

2012-08-17

We investigate the effect of weak rotation on the large-scale circulation (LSC) of turbulent Rayleigh-Bénard convection, using the theory for cessations in a low-dimensional stochastic model of the flow previously studied. We determine the cessation frequency of the LSC as a function of rotation, and calculate the statistics of the amplitude and azimuthal velocity fluctuations of the LSC as a function of the rotation rate for different Rayleigh numbers. Furthermore, we show that the tails of the reorientation PDF remain unchanged for rotating systems, while the distribution of the LSC amplitude and correspondingly the cessation frequency are strongly affected by rotation. Our results are in close agreement with experimental observations.

Functional Independent Scaling Relation for ORR/OER Catalysts

DOE PAGES

Christensen, Rune; Hansen, Heine A.; Dickens, Colin F.; ...

2016-10-11

A widely used adsorption energy scaling relation between OH* and OOH* intermediates in the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), has previously been determined using density functional theory and shown to dictate a minimum thermodynamic overpotential for both reactions. Here, we show that the oxygen–oxygen bond in the OOH* intermediate is, however, not well described with the previously used class of exchange-correlation functionals. By quantifying and correcting the systematic error, an improved description of gaseous peroxide species versus experimental data and a reduction in calculational uncertainty is obtained. For adsorbates, we find that the systematic error largelymore » cancels the vdW interaction missing in the original determination of the scaling relation. An improved scaling relation, which is fully independent of the applied exchange–correlation functional, is obtained and found to differ by 0.1 eV from the original. Lastly, this largely confirms that, although obtained with a method suffering from systematic errors, the previously obtained scaling relation is applicable for predictions of catalytic activity.« less

From symptoms to social functioning: differential effects of antidepressant therapy.

PubMed

Kasper, S

1999-05-01

Significant impairments in social functioning frequently occur simultaneously with depressive symptoms. The implications of such impairments extend beyond the depressed individual to their family, friends and society at large. Classical rating scales such as the Hamilton rating scale for depression primarily assess the core symptoms of depression. A range of rating scales are available, both self-reporting and administered by clinician; however, many have been criticised for their unspecified conceptual background and for being complex and time-consuming. While antidepressants in general appear to improve social functioning, no clear advantage for any single class of agent has been reported. Recently, a new self-report rating scale, the Social Adaptation Self-evaluation Scale, has been developed and used to compare the novel selective noradrenaline reuptake inhibitor, reboxetine, with the selective serotonin re-uptake inhibitor, fluoxetine. The noradrenergic agent, reboxetine, was shown to be significantly more effective in improving social functioning than the serotonergic agent, fluoxetine. These findings are consistent with previous observations that noradrenaline may preferentially improve vigilance, motivation and self-perception.

Characterising large-scale structure with the REFLEX II cluster survey

NASA Astrophysics Data System (ADS)

Chon, Gayoung

2016-10-01

We study the large-scale structure with superclusters from the REFLEX X-ray cluster survey together with cosmological N-body simulations. It is important to construct superclusters with criteria such that they are homogeneous in their properties. We lay out our theoretical concept considering future evolution of superclusters in their definition, and show that the X-ray luminosity and halo mass functions of clusters in superclusters are found to be top-heavy, different from those of clusters in the field. We also show a promising aspect of using superclusters to study the local cluster bias and mass scaling relation with simulations.

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Observation of scaling violations in scaled momentum distributions at HERA

NASA Astrophysics Data System (ADS)

ZEUS Collaboration; Breitweg, J.; Derrick, M.; Krakauer, D.; Magill, S.; Mikunas, D.; Musgrave, B.; Repond, J.; Stanek, R.; Talaga, R. L.; Yoshida, R.; Zhang, H.; Mattingly, M. C. K.; Anselmo, F.; Antonioli, P.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Cara Romeo, G.; Castellini, G.; Cifarelli, L.; Cindolo, F.; Contin, A.; Corradi, M.; de Pasquale, S.; Gialas, I.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Margotti, A.; Massam, T.; Nania, R.; Palmonari, F.; Pesci, A.; Polini, A.; Ricci, F.; Sartorelli, G.; Zamora Garcia, Y.; Zichichi, A.; Amelung, C.; Bornheim, A.; Brock, I.; Coböken, K.; Crittenden, J.; Deffner, R.; Eckert, M.; Grothe, M.; Hartmann, H.; Heinloth, K.; Heinz, L.; Hilger, E.; Jakob, H.-P.; Katz, U. F.; Kerger, R.; Paul, E.; Pfeiffer, M.; Rembser, Ch.; Stamm, J.; Wedemeyer, R.; Wieber, H.; Bailey, D. S.; Campbell-Robson, S.; Cottingham, W. N.; Foster, B.; Hall-Wilton, R.; Hayes, M. E.; Heath, G. P.; Heath, H. F.; McFall, J. D.; Piccioni, D.; Roff, D. G.; Tapper, R. J.; Arneodo, M.; Ayad, R.; Capua, M.; Garfagnini, A.; Iannotti, L.; Schioppa, M.; Susinno, G.; Kim, J. Y.; Lee, J. H.; Lim, I. T.; Pac, M. Y.; Caldwell, A.; Cartiglia, N.; Jing, Z.; Liu, W.; Mellado, B.; Parsons, J. A.; Ritz, S.; Sampson, S.; Sciulli, F.; Straub, P. B.; Zhu, Q.; Borzemski, P.; Chwastowski, J.; Eskreys, A.; Figiel, J.; Klimek, K.; Przybycień , M. B.; Zawiejski, L.; Adamczyk, L.; Bednarek, B.; Bukowy, M.; Jeleń , K.; Kisielewska, D.; Kowalski, T.; Przybycień , M.; Rulikowska-Zarȩ Bska, E.; Suszycki, L.; Zaja C, J.; Duliń Ski, Z.; Kotań Ski, A.; Abbiendi, G.; Bauerdick, L. A. T.; Behrens, U.; Beier, H.; Bienlein, J. K.; Cases, G.; Deppe, O.; Desler, K.; Drews, G.; Fricke, U.; Gilkinson, D. J.; Glasman, C.; Göttlicher, P.; Haas, T.; Hain, W.; Hasell, D.; Johnson, K. F.; Kasemann, M.; Koch, W.; Kötz, U.; Kowalski, H.; Labs, J.; Lindemann, L.; Löhr, B.; Löwe, M.; Mań Czak, O.; Milewski, J.; Monteiro, T.; Ng, J. S. T.; Notz, D.; Ohrenberg, K.; Park, I. H.; Pellegrino, A.; Pelucchi, F.; Piotrzkowski, K.; Roco, M.; Rohde, M.; Roldán, J.; Ryan, J. J.; Savin, A. A.; Schneekloth, U.; Selonke, F.; Surrow, B.; Tassi, E.; Voß, T.; Westphal, D.; Wolf, G.; Wollmer, U.; Youngman, C.; Zsolararnecki, A. F.; Zeuner, W.; Burow, B. D.; Grabosch, H. J.; Meyer, A.; Schlenstedt, S.; Barbagli, G.; Gallo, E.; Pelfer, P.; Maccarrone, G.; Votano, L.; Bamberger, A.; Eisenhardt, S.; Markun, P.; Trefzger, T.; Wölfle, S.; Bromley, J. T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; MacDonald, N.; Saxon, D. H.; Sinclair, L. E.; Strickland, E.; Waugh, R.; Bohnet, I.; Gendner, N.; Holm, U.; Meyer-Larsen, A.; Salehi, H.; Wick, K.; Gladilin, L. K.; Horstmann, D.; Kçira, D.; Klanner, R.; Lohrmann, E.; Poelz, G.; Schott, W.; Zetsche, F.; Bacon, T. C.; Butterworth, I.; Cole, J. E.; Howell, G.; Hung, B. H. Y.; Lamberti, L.; Long, K. R.; Miller, D. B.; Pavel, N.; Prinias, A.; Sedgbeer, J. K.; Sideris, D.; Mallik, U.; Wang, S. M.; Wu, J. T.; Cloth, P.; Filges, D.; Fleck, J. I.; Ishii, T.; Kuze, M.; Suzuki, I.; Tokushuku, K.; Yamada, S.; Yamauchi, K.; Yamazaki, Y.; Hong, S. J.; Lee, S. B.; Nam, S. W.; Park, S. K.; Barreiro, F.; Fernández, J. P.; García, G.; Graciani, R.; Hernández, J. M.; Hervás, L.; Labarga, L.; Martínez, M.; del Peso, J.; Puga, J.; Terrón, J.; de Trocóniz, J. F.; Corriveau, F.; Hanna, D. S.; Hartmann, J.; Hung, L. W.; Murray, W. N.; Ochs, A.; Riveline, M.; Stairs, D. G.; St-Laurent, M.; Ullmann, R.; Tsurugai, T.; Bashkirov, V.; Dolgoshein, B. A.; Stifutkin, A.; Bashindzhagyan, G. L.; Ermolov, P. F.; Golubkov, Yu. A.; Khein, L. A.; Korotkova, N. A.; Korzhavina, I. A.; Kuzmin, V. A.; Lukina, O. Yu.; Proskuryakov, A. S.; Shcheglova, L. M.; Solomin, A. N.; Zotkin, S. A.; Bokel, C.; Botje, M.; Brümmer, N.; Chlebana, F.; Engelen, J.; Koffeman, E.; Kooijman, P.; van Sighem, A.; Tiecke, H.; Tuning, N.; Verkerke, W.; Vossebeld, J.; Vreeswijk, M.; Wiggers, L.; de Wolf, E.; Acosta, D.; Bylsma, B.; Durkin, L. S.; Gilmore, J.; Ginsburg, C. M.; Kim, C. L.; Ling, T. Y.; Nylander, P.; Romanowski, T. A.; Blaikley, H. E.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Edmonds, J. K.; Große-Knetter, J.; Harnew, N.; Lancaster, M.; Nath, C.; Noyes, V. A.; Quadt, A.; Ruske, O.; Tickner, J. R.; Uijterwaal, H.; Walczak, R.; Waters, D. S.; Bertolin, A.; Brugnera, R.; Carlin, R.; dal Corso, F.; Dosselli, U.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Bulmahn, J.; Oh, B. Y.; Okrasiń Ski, J. R.; Toothacker, W. S.; Whitmore, J. J.; Iga, Y.; D'Agostini, G.; Marini, G.; Nigro, A.; Raso, M.; Hart, J. C.; McCubbin, N. A.; Shah, T. P.; Epperson, D.; Heusch, C.; Rahn, J. T.; Sadrozinski, H. F.-W.; Seiden, A.; Wichmann, R.; Williams, D. C.; Schwarzer, O.; Walenta, A. H.; Abramowicz, H.; Briskin, G.; Dagan, S.; Kananov, S.; Levy, A.; Abe, T.; Fusayasu, T.; Inuzuka, M.; Nagano, K.; Umemori, K.; Yamashita, T.; Hamatsu, R.; Hirose, T.; Homma, K.; Kitamura, S.; Matsushita, T.; Cirio, R.; Costa, M.; Ferrero, M. I.; Maselli, S.; Monaco, V.; Peroni, C.; Petrucci, M. C.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Fagerstroem, C.-P.; Galea, R.; Hartner, G. F.; Joo, K. K.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Polenz, S.; Sabetfakhri, A.; Simmons, D.; Teuscher, R. J.; Butterworth, J. M.; Catterall, C. D.; Jones, T. W.; Lane, J. B.; Saunders, R. L.; Shulman, J.; Sutton, M. R.; Wing, M.; Ciborowski, J.; Grzelak, G.; Kasprzak, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Pawlak, R.; Tymieniecka, T.; Wróblewski, A. K.; Zakrzewski, J. A.; Adamus, M.; Coldewey, C.; Eisenberg, Y.; Hochman, D.; Karshon, U.; Badgett, W. F.; Chapin, D.; Cross, R.; Dasu, S.; Foudas, C.; Loveless, R. J.; Mattingly, S.; Reeder, D. D.; Smith, W. H.; Vaiciulis, A.; Wodarczyk, M.; Bhadra, S.; Frisken, W. R.; Khakzad, M.; Schmidke, W. B.

1997-11-01

Charged particle production has been measured in deep inelastic scattering (DIS) events over a large range of x and Q2 using the ZEUS detector. The evolution of the scaled momentum, xp, with Q2, in the range 10 to 1280 GeV2, has been investigated in the current fragmentation region of the Breit frame. The results show clear evidence, in a single experiment, for scaling violations in scaled momenta as a function of Q2.

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

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

Hong, Liang; Jain, Nitin; Cheng, Xiaolin

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

DOE PAGES

Hong, Liang; Jain, Nitin; Cheng, Xiaolin; ...

2016-10-14

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Spatial Covariability of Temperature and Hydroclimate as a Function of Timescale During the Common Era

NASA Astrophysics Data System (ADS)

McKay, N.

2017-12-01

As timescale increases from years to centuries, the spatial scale of covariability in the climate system is hypothesized to increase as well. Covarying spatial scales are larger for temperature than for hydroclimate, however, both aspects of the climate system show systematic changes on large-spatial scales on orbital to tectonic timescales. The extent to which this phenomenon is evident in temperature and hydroclimate at centennial timescales is largely unknown. Recent syntheses of multidecadal to century-scale variability in hydroclimate during the past 2k in the Arctic, North America, and Australasia show little spatial covariability in hydroclimate during the Common Era. To determine 1) the evidence for systematic relationships between the spatial scale of climate covariability as a function of timescale, and 2) whether century-scale hydroclimate variability deviates from the relationship between spatial covariability and timescale, we quantify this phenomenon during the Common Era by calculating the e-folding distance in large instrumental and paleoclimate datasets. We calculate this metric of spatial covariability, at different timescales (1, 10 and 100-yr), for a large network of temperature and precipitation observations from the Global Historical Climatology Network (n=2447), from v2.0.0 of the PAGES2k temperature database (n=692), and from moisture-sensitive paleoclimate records North America, the Arctic, and the Iso2k project (n = 328). Initial results support the hypothesis that the spatial scale of covariability is larger for temperature, than for precipitation or paleoclimate hydroclimate indicators. Spatially, e-folding distances for temperature are largest at low latitudes and over the ocean. Both instrumental and proxy temperature data show clear evidence for increasing spatial extent as a function of timescale, but this phenomenon is very weak in the hydroclimate data analyzed here. In the proxy hydroclimate data, which are predominantly indicators of effective moisture, e-folding distance increases from annual to decadal timescales, but does not continue to increase to centennial timescales. Future work includes examining additional instrumental and proxy datasets of moisture variability, and extending the analysis to millennial timescales of variability.

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].

Local loss and spatial homogenization of plant diversity reduce ecosystem multifunctionality.

PubMed

Hautier, Yann; Isbell, Forest; Borer, Elizabeth T; Seabloom, Eric W; Harpole, W Stanley; Lind, Eric M; MacDougall, Andrew S; Stevens, Carly J; Adler, Peter B; Alberti, Juan; Bakker, Jonathan D; Brudvig, Lars A; Buckley, Yvonne M; Cadotte, Marc; Caldeira, Maria C; Chaneton, Enrique J; Chu, Chengjin; Daleo, Pedro; Dickman, Christopher R; Dwyer, John M; Eskelinen, Anu; Fay, Philip A; Firn, Jennifer; Hagenah, Nicole; Hillebrand, Helmut; Iribarne, Oscar; Kirkman, Kevin P; Knops, Johannes M H; La Pierre, Kimberly J; McCulley, Rebecca L; Morgan, John W; Pärtel, Meelis; Pascual, Jesus; Price, Jodi N; Prober, Suzanne M; Risch, Anita C; Sankaran, Mahesh; Schuetz, Martin; Standish, Rachel J; Virtanen, Risto; Wardle, Glenda M; Yahdjian, Laura; Hector, Andy

2018-01-01

Biodiversity is declining in many local communities while also becoming increasingly homogenized across space. Experiments show that local plant species loss reduces ecosystem functioning and services, but the role of spatial homogenization of community composition and the potential interaction between diversity at different scales in maintaining ecosystem functioning remains unclear, especially when many functions are considered (ecosystem multifunctionality). We present an analysis of eight ecosystem functions measured in 65 grasslands worldwide. We find that more diverse grasslands-those with both species-rich local communities (α-diversity) and large compositional differences among localities (β-diversity)-had higher levels of multifunctionality. Moreover, α- and β-diversity synergistically affected multifunctionality, with higher levels of diversity at one scale amplifying the contribution to ecological functions at the other scale. The identity of species influencing ecosystem functioning differed among functions and across local communities, explaining why more diverse grasslands maintained greater functionality when more functions and localities were considered. These results were robust to variation in environmental drivers. Our findings reveal that plant diversity, at both local and landscape scales, contributes to the maintenance of multiple ecosystem services provided by grasslands. Preserving ecosystem functioning therefore requires conservation of biodiversity both within and among ecological communities.

RAID-2: Design and implementation of a large scale disk array controller

NASA Technical Reports Server (NTRS)

Katz, R. H.; Chen, P. M.; Drapeau, A. L.; Lee, E. K.; Lutz, K.; Miller, E. L.; Seshan, S.; Patterson, D. A.

1992-01-01

We describe the implementation of a large scale disk array controller and subsystem incorporating over 100 high performance 3.5 inch disk drives. It is designed to provide 40 MB/s sustained performance and 40 GB capacity in three 19 inch racks. The array controller forms an integral part of a file server that attaches to a Gb/s local area network. The controller implements a high bandwidth interconnect between an interleaved memory, an XOR calculation engine, the network interface (HIPPI), and the disk interfaces (SCSI). The system is now functionally operational, and we are tuning its performance. We review the design decisions, history, and lessons learned from this three year university implementation effort to construct a truly large scale system assembly.

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Examining Measurement Properties of an English Self-Efficacy Scale for English Language Learners in Korea

ERIC Educational Resources Information Center

Wang, Chuang; Kim, Do-Hong; Bong, Mimi; Ahn, Hyun Seon

2013-01-01

This study provides evidence for the validity of the Questionnaire of English Self-Efficacy in a sample of 167 college students in Korea. Results show that the scale measures largely satisfy the Rasch model for unidimensionality. The rating scale appeared to function effectively. The item hierarchy was consistent with the expected item order. The…

Quasielastic charged-current neutrino scattering in the scaling model with relativistic effective mass

NASA Astrophysics Data System (ADS)

Ruiz Simo, I.; Martinez-Consentino, V. L.; Amaro, J. E.; Ruiz Arriola, E.

2018-06-01

We use a recent scaling analysis of the quasielastic electron scattering data from C 12 to predict the quasielastic charge-changing neutrino scattering cross sections within an uncertainty band. We use a scaling function extracted from a selection of the (e ,e') cross section data, and an effective nucleon mass inspired by the relativistic mean-field model of nuclear matter. The corresponding superscaling analysis with relativistic effective mass (SuSAM*) describes a large amount of the electron data lying inside a phenomenological quasielastic band. The effective mass incorporates the enhancement of the transverse current produced by the relativistic mean field. The scaling function incorporates nuclear effects beyond the impulse approximation, in particular meson-exchange currents and short-range correlations producing tails in the scaling function. Besides its simplicity, this model describes the neutrino data as reasonably well as other more sophisticated nuclear models.

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

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

Tassev, Svetlin, E-mail: tassev@astro.princeton.edu

2014-06-01

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

A Continental-scale River Corridor Model to Synthesize Understanding and Prioritize Management of Water Purification Functions and Ecological Services in Large Basins

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.; Scott, D.; Boyer, E. W.; Schmadel, N. M.; Alexander, R. B.; Eng, K.; Golden, H. E.; Kettner, A.; Konrad, C. P.; Moore, R. B.; Pizzuto, J. E.; Schwarz, G. E.; Soulsby, C.

2017-12-01

The functional values of rivers depend on more than just wetted river channels. Instead, the river channel exchanges water and suspended materials with adjacent riparian, floodplain, hyporheic zones, and ponded waters such as lakes and reservoirs. Together these features comprise a larger functional unit known as the river corridor. The exchange of water, solutes, and sediments within the river corridor alters downstream water quality and ecological functions, but our understanding of the large-scale, cumulative impacts is inadequate and has limited advancements in sustainable management practices. A problem with traditional watershed, groundwater, and river water quality models is that none of them explicitly accounts for river corridor storage and processing, and the exchanges of water, solutes, and sediments that occur many times between the channel and off-channel environments during a river's transport to the sea. Our River Corridor Working Group at the John Wesley Powell Center is quantifying the key components of river corridor functions. Relying on foundational studies that identified floodplain, riparian, and hyporheic exchange flows and resulting enhancement of chemical reactions at river reach scales, we are assembling the datasets and building the models to upscale that understanding onto 2.6 million river reaches in the U.S. A principal goal of the River Corridor Working group is to develop a national-scale river corridor model for the conterminous U.S. that will reveal, perhaps for the first time, the relative influences of hyporheic, riparian, floodplain, and ponded waters at large spatial scales. The simple but physically-based models are predictive for changing conditions and therefore can directly address the consequences and effectiveness of management actions in sustaining valuable river corridor functions. This presentation features interpretation of useful river corridor connectivity metrics and ponded water influences on nutrient and sediment processing in river networks of the Mid-Atlantic and Northeastern U.S. This research is a product of the John Wesley Powell Center River Corridor Working Group https://powellcenter.usgs.gov/view-project

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.

Universality of local dissipation scales in buoyancy-driven turbulence.

PubMed

Zhou, Quan; Xia, Ke-Qing

2010-03-26

We report an experimental investigation of the local dissipation scale field eta in turbulent thermal convection. Our results reveal two types of universality of eta. The first one is that, for the same flow, the probability density functions (PDFs) of eta are insensitive to turbulent intensity and large-scale inhomogeneity and anisotropy of the system. The second is that the small-scale dissipation dynamics in buoyancy-driven turbulence can be described by the same models developed for homogeneous and isotropic turbulence. However, the exact functional form of the PDF of the local dissipation scale is not universal with respect to different types of flows, but depends on the integral-scale velocity boundary condition, which is found to have an exponential, rather than Gaussian, distribution in turbulent Rayleigh-Bénard convection.

Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success

PubMed Central

Sheppard, John Patrick; Wang, Ji-Ping; Wong, Patrick C. M.

2013-01-01

The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants’ future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults. PMID:22360625

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.

The ellipsoidal universe in the Planck satellite era

NASA Astrophysics Data System (ADS)

Cea, Paolo

2014-06-01

Recent Planck data confirm that the cosmic microwave background displays the quadrupole power suppression together with large-scale anomalies. Progressing from previous results, that focused on the quadrupole anomaly, we strengthen the proposal that the slightly anisotropic ellipsoidal universe may account for these anomalies. We solved at large scales the Boltzmann equation for the photon distribution functions by taking into account both the effects of the inflation produced primordial scalar perturbations and the anisotropy of the geometry in the ellipsoidal universe. We showed that the low quadrupole temperature correlations allowed us to fix the eccentricity at decoupling, edec = (0.86 ± 0.14) 10-2, and to constraint the direction of the symmetry axis. We found that the anisotropy of the geometry of the universe contributes only to the large-scale temperature anisotropies without affecting the higher multipoles of the angular power spectrum. Moreover, we showed that the ellipsoidal geometry of the universe induces sizeable polarization signal at large scales without invoking the reionization scenario. We explicitly evaluated the quadrupole TE and EE correlations. We found an average large-scale polarization ΔTpol = (1.20 ± 0.38) μK. We point out that great care is needed in the experimental determination of the large-scale polarization correlations since the average temperature polarization could be misinterpreted as foreground emission leading, thereby, to a considerable underestimate of the cosmic microwave background polarization signal.

Integration and segregation of large-scale brain networks during short-term task automatization

PubMed Central

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F.; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-01-01

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes. PMID:27808095

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

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

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

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

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 D V = 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 themore » 2-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%; 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

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.

Multi-scale comparison of source parameter estimation using empirical Green's function approach

NASA Astrophysics Data System (ADS)

Chen, X.; Cheng, Y.

2015-12-01

Analysis of earthquake source parameters requires correction of path effect, site response, and instrument responses. Empirical Green's function (EGF) method is one of the most effective methods in removing path effects and station responses by taking the spectral ratio between a larger and smaller event. Traditional EGF method requires identifying suitable event pairs, and analyze each event individually. This allows high quality estimations for strictly selected events, however, the quantity of resolvable source parameters is limited, which challenges the interpretation of spatial-temporal coherency. On the other hand, methods that exploit the redundancy of event-station pairs are proposed, which utilize the stacking technique to obtain systematic source parameter estimations for a large quantity of events at the same time. This allows us to examine large quantity of events systematically, facilitating analysis of spatial-temporal patterns, and scaling relationship. However, it is unclear how much resolution is scarified during this process. In addition to the empirical Green's function calculation, choice of model parameters and fitting methods also lead to biases. Here, using two regional focused arrays, the OBS array in the Mendocino region, and the borehole array in the Salton Sea geothermal field, I compare the results from the large scale stacking analysis, small-scale cluster analysis, and single event-pair analysis with different fitting methods to systematically compare the results within completely different tectonic environment, in order to quantify the consistency and inconsistency in source parameter estimations, and the associated problems.

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 D V = 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 themore » 2-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%; 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

Large-scale filament formation inhibits the activity of CTP synthetase

PubMed Central

Barry, Rachael M; Bitbol, Anne-Florence; Lorestani, Alexander; Charles, Emeric J; Habrian, Chris H; Hansen, Jesse M; Li, Hsin-Jung; Baldwin, Enoch P; Wingreen, Ned S; Kollman, Justin M; Gitai, Zemer

2014-01-01

CTP Synthetase (CtpS) is a universally conserved and essential metabolic enzyme. While many enzymes form small oligomers, CtpS forms large-scale filamentous structures of unknown function in prokaryotes and eukaryotes. By simultaneously monitoring CtpS polymerization and enzymatic activity, we show that polymerization inhibits activity, and CtpS's product, CTP, induces assembly. To understand how assembly inhibits activity, we used electron microscopy to define the structure of CtpS polymers. This structure suggests that polymerization sterically hinders a conformational change necessary for CtpS activity. Structure-guided mutagenesis and mathematical modeling further indicate that coupling activity to polymerization promotes cooperative catalytic regulation. This previously uncharacterized regulatory mechanism is important for cellular function since a mutant that disrupts CtpS polymerization disrupts E. coli growth and metabolic regulation without reducing CTP levels. We propose that regulation by large-scale polymerization enables ultrasensitive control of enzymatic activity while storing an enzyme subpopulation in a conformationally restricted form that is readily activatable. DOI: http://dx.doi.org/10.7554/eLife.03638.001 PMID:25030911

Large Spatial Scale Variability in Bathyal Macrobenthos Abundance, Biomass, α- and β-Diversity along the Mediterranean Continental Margin

PubMed Central

Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena

2014-01-01

The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project (“Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna”), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas. PMID:25225909

Large spatial scale variability in bathyal macrobenthos abundance, biomass, α- and β-diversity along the Mediterranean continental margin.

PubMed

Baldrighi, Elisa; Lavaleye, Marc; Aliani, Stefano; Conversi, Alessandra; Manini, Elena

2014-01-01

The large-scale deep-sea biodiversity distribution of the benthic fauna was explored in the Mediterranean Sea, which can be seen as a miniature model of the oceans of the world. Within the framework of the BIOFUN project ("Biodiversity and Ecosystem Functioning in Contrasting Southern European Deep-sea Environments: from viruses to megafauna"), we investigated the large spatial scale variability (over >1,000 km) of the bathyal macrofauna communities that inhabit the Mediterranean basin, and their relationships with the environmental variables. The macrofauna abundance, biomass, community structure and functional diversity were analysed and the α-diversity and β-diversity were estimated across six selected slope areas at different longitudes and along three main depths. The macrobenthic standing stock and α-diversity were lower in the deep-sea sediments of the eastern Mediterranean basin, compared to the western and central basins. The macrofaunal standing stock and diversity decreased significantly from the upper bathyal to the lower bathyal slope stations. The major changes in the community composition of the higher taxa and in the trophic (functional) structure occurred at different longitudes, rather than at increasing water depth. For the β-diversity, very high dissimilarities emerged at all levels: (i) between basins; (ii) between slopes within the same basin; and (iii) between stations at different depths; this therefore demonstrates the high macrofaunal diversity of the Mediterranean basins at large spatial scales. Overall, the food sources (i.e., quantity and quality) that characterised the west, central and eastern Mediterranean basins, as well as sediment grain size, appear to influence the macrobenthic standing stock and the biodiversity along the different slope areas.

Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2012-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

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

PubMed Central

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

2014-01-01

IMPORTANCE Interactions of large-scale brain networks may underlie cognitive dysfunctions in psychiatric and addictive disorders. OBJECTIVES To test the hypothesis that the strength of coupling among 3 large-scale brain networks–salience, executive control, and default mode–will reflect the state of nicotine withdrawal (vs smoking satiety) and will predict abstinence-induced craving and cognitive deficits and to develop a resource allocation index (RAI) that reflects the combined strength of interactions among the 3 large-scale networks. DESIGN, SETTING, AND PARTICIPANTS A within-subject functional magnetic resonance imaging study in an academic medical center compared resting-state functional connectivity coherence strength after 24 hours of abstinence and after smoking satiety. We examined the relationship of abstinence-induced changes in the RAI with alterations in subjective, behavioral, and neural functions. We included 37 healthy smoking volunteers, aged 19 to 61 years, for analyses. INTERVENTIONS Twenty-four hours of abstinence vs smoking satiety. MAIN OUTCOMES AND MEASURES Inter-network connectivity strength (primary) and the relationship with subjective, behavioral, and neural measures of nicotine withdrawal during abstinence vs smoking satiety states (secondary). RESULTS The RAI was significantly lower in the abstinent compared with the smoking satiety states (left RAI, P = .002; right RAI, P = .04), suggesting weaker inhibition between the default mode and salience networks. Weaker inter-network connectivity (reduced RAI) predicted abstinence-induced cravings to smoke (r = −0.59; P = .007) and less suppression of default mode activity during performance of a subsequent working memory task (ventromedial prefrontal cortex, r = −0.66, P = .003; posterior cingulate cortex, r = −0.65, P = .001). CONCLUSIONS AND RELEVANCE Alterations in coupling of the salience and default mode networks and the inability to disengage from the default mode network may be critical in cognitive/affective alterations that underlie nicotine dependence. PMID:24622915

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

PubMed

Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens; Shendure, Jay; Fowler, Douglas M

2018-01-24

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/). Copyright © 2017 Elsevier Inc. All rights reserved.

Large Scale Landslide Database System Established for the Reservoirs in Southern Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsai-Tsung; Tsai, Kuang-Jung; Shieh, Chjeng-Lun

2017-04-01

Typhoon Morakot seriously attack southern Taiwan awaken the public awareness of large scale landslide disasters. Large scale landslide disasters produce large quantity of sediment due to negative effects on the operating functions of reservoirs. In order to reduce the risk of these disasters within the study area, the establishment of a database for hazard mitigation / disaster prevention is necessary. Real time data and numerous archives of engineering data, environment information, photo, and video, will not only help people make appropriate decisions, but also bring the biggest concern for people to process and value added. The study tried to define some basic data formats / standards from collected various types of data about these reservoirs and then provide a management platform based on these formats / standards. Meanwhile, in order to satisfy the practicality and convenience, the large scale landslide disasters database system is built both provide and receive information abilities, which user can use this large scale landslide disasters database system on different type of devices. IT technology progressed extreme quick, the most modern system might be out of date anytime. In order to provide long term service, the system reserved the possibility of user define data format /standard and user define system structure. The system established by this study was based on HTML5 standard language, and use the responsive web design technology. This will make user can easily handle and develop this large scale landslide disasters database system.

Preface: Introductory Remarks: Linear Scaling Methods

NASA Astrophysics Data System (ADS)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up implementation questions relating to parallelization (particularly with multi-core processors starting to dominate the market) and inherent scaling and basis sets (in both normal and linear scaling codes). For now, the answer seems to lie between 100-1,000 atoms, though this depends on the type of simulation used among other factors. Basis sets are still a problematic question in the area of electronic structure calculations. The linear scaling community has largely split into two camps: those using relatively small basis sets based on local atomic-like functions (where systematic convergence to the full basis set limit is hard to achieve); and those that use necessarily larger basis sets which allow convergence systematically and therefore are the localised equivalent of plane waves. Related to basis sets is the study of Wannier functions, on which some linear scaling methods are based and which give a good point of contact with traditional techniques; they are particularly interesting for modelling unoccupied states with linear scaling methods. There are, of course, as many approaches to linear scaling solution for the density matrix as there are groups in the area, though there are various broad areas: McWeeny-based methods, fragment-based methods, recursion methods, and combinations of these. While many ideas have been in development for several years, there are still improvements emerging, as shown by the rich variety of the talks below. Applications using O(N) DFT methods are now starting to emerge, though they are still clearly not trivial. Once systems to be simulated cross the 10,000 atom barrier, only linear scaling methods can be applied, even with the most efficient standard techniques. One of the most challenging problems remaining, now that ab initio methods can be applied to large systems, is the long timescale problem. Although much of the work presented was concerned with improving the performance of the codes, and applying them to scientificallyimportant problems, there was another important theme: extending functionality. The search for greater accuracy has given an implementation of density functional designed to model van der Waals interactions accurately as well as local correlation, TDDFT and QMC and GW methods which, while not explicitly O(N), take advantage of localisation. All speakers at the workshop were invited to contribute to this issue, but not all were able to do this. Hence it is useful to give a complete list of the talks presented, with the names of the sessions; however, many talks fell within more than one area. This is an exciting time for linear scaling methods, which are already starting to contribute significantly to important scientific problems. Applications to nanostructures and biomolecules A DFT study on the structural stability of Ge 3D nanostructures on Si(001) using CONQUEST Tsuyoshi Miyazaki, D R Bowler, M J Gillan, T Otsuka and T Ohno Large scale electronic structure calculation theory and several applications Takeo Fujiwara and Takeo Hoshi ONETEP:Linear-scaling DFT with plane waves Chris-Kriton Skylaris, Peter D Haynes, Arash A Mostofi, Mike C Payne Maximally-localised Wannier functions as building blocks for large-scale electronic structure calculations Arash A Mostofi and Nicola Marzari A linear scaling three dimensional fragment method for ab initio calculations Lin-Wang Wang, Zhengji Zhao, Juan Meza Peta-scalable reactive Molecular dynamics simulation of mechanochemical processes Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, Fuyuki Shimojo and Priya Vashishta Recent developments and applications of the real-space multigrid (RMG) method Jerzy Bernholc, M Hodak, W Lu, and F Ribeiro Energy minimisation functionals and algorithms CONQUEST: A linear scaling DFT Code David R Bowler, Tsuyoshi Miyazaki, Antonio Torralba, Veronika Brazdova, Milica Todorovic, Takao Otsuka and Mike Gillan Kernel optimisation and the physical significance of optimised local orbitals in the ONETEP code Peter Haynes, Chris-Kriton Skylaris, Arash Mostofi and Mike Payne A miscellaneous overview of SIESTA algorithms Jose M Soler Wavelets as a basis set for electronic structure calculations and electrostatic problems Stefan Goedecker Wavelets as a basis set for linear scaling electronic structure calculationsMark Rayson O(N) Krylov subspace method for large-scale ab initio electronic structure calculations Taisuke Ozaki Linear scaling calculations with the divide-and-conquer approach and with non-orthogonal localized orbitals Weitao Yang Toward efficient wavefunction based linear scaling energy minimization Valery Weber Accurate O(N) first-principles DFT calculations using finite differences and confined orbitals Jean-Luc Fattebert Linear-scaling methods in dynamics simulations or beyond DFT and ground state properties An O(N) time-domain algorithm for TDDFT Guan Hua Chen Local correlation theory and electronic delocalization Joseph Subotnik Ab initio molecular dynamics with linear scaling: foundations and applications Eiji Tsuchida Towards a linear scaling Car-Parrinello-like approach to Born-Oppenheimer molecular dynamics Thomas Kühne, Michele Ceriotti, Matthias Krack and Michele Parrinello Partial linear scaling for quantum Monte Carlo calculations on condensed matter Mike Gillan Exact embedding of local defects in crystals using maximally localized Wannier functions Eric Cancès Faster GW calculations in larger model structures using ultralocalized nonorthogonal Wannier functions Paolo Umari Other approaches for linear-scaling, including methods formetals Partition-of-unity finite element method for large, accurate electronic-structure calculations of metals John E Pask and Natarajan Sukumar Semiclassical approach to density functional theory Kieron Burke Ab initio transport calculations in defected carbon nanotubes using O(N) techniques Blanca Biel, F J Garcia-Vidal, A Rubio and F Flores Large-scale calculations with the tight-binding (screened) KKR method Rudolf Zeller Acknowledgments We gratefully acknowledge funding for the workshop from the UK CCP9 network, CECAM and the ESF through the PsiK network. DRB, PDH and CKS are funded by the Royal Society. References [1] Car R and Parrinello M 1985 Phys. Rev. Lett. 55 2471 [2] Kühne T D, Krack M, Mohamed F R and Parrinello M 2007 Phys. Rev. Lett. 98 066401 [3] Goedecker S 1999 Rev. Mod. Phys. 71 1085

Connectome-Wide Phenotypical and Genotypical Associations in Focal Dystonia

PubMed Central

Fuertinger, Stefan

2017-01-01

Isolated focal dystonia is a debilitating movement disorder of unknown pathophysiology. Early studies in focal dystonias have pointed to segregated changes in brain activity and connectivity. Only recently has the notion that dystonia pathophysiology may lie in abnormalities of large-scale brain networks appeared in the literature. Here, we outline a novel concept of functional connectome-wide alterations that are linked to dystonia phenotype and genotype. Using a neural community detection strategy and graph theoretical analysis of functional MRI data in human patients with the laryngeal form of dystonia (LD) and healthy controls (both males and females), we identified an abnormally widespread hub formation in LD, which particularly affected the primary sensorimotor and parietal cortices and thalamus. Left thalamic regions formed a delineated functional community that highlighted differences in network topology between LD patients with and without family history of dystonia. Conversely, marked differences in the topological organization of parietal regions were found between phenotypically different forms of LD. The interface between sporadic genotype and adductor phenotype of LD yielded four functional communities that were primarily governed by intramodular hub regions. Conversely, the interface between familial genotype and abductor phenotype was associated with numerous long-range hub nodes and an abnormal integration of left thalamus and basal ganglia. Our findings provide the first comprehensive atlas of functional topology across different phenotypes and genotypes of focal dystonia. As such, this study constitutes an important step toward defining dystonia as a large-scale network disorder, understanding its causative pathophysiology, and identifying disorder-specific markers. SIGNIFICANCE STATEMENT The architecture of the functional connectome in focal dystonia was analyzed in a large population of patients with laryngeal dystonia. Breaking with the empirical concept of dystonia as a basal ganglia disorder, we discovered large-scale alterations of neural communities that are significantly influenced by the disorder's clinical phenotype and genotype. PMID:28674168

Annealed Scaling for a Charged Polymer

NASA Astrophysics Data System (ADS)

Caravenna, F.; den Hollander, F.; Pétrélis, N.; Poisat, J.

2016-03-01

This paper studies an undirected polymer chain living on the one-dimensional integer lattice and carrying i.i.d. random charges. Each self-intersection of the polymer chain contributes to the interaction Hamiltonian an energy that is equal to the product of the charges of the two monomers that meet. The joint probability distribution for the polymer chain and the charges is given by the Gibbs distribution associated with the interaction Hamiltonian. The focus is on the annealed free energy per monomer in the limit as the length of the polymer chain tends to infinity. We derive a spectral representation for the free energy and use this to prove that there is a critical curve in the parameter plane of charge bias versus inverse temperature separating a ballistic phase from a subballistic phase. We show that the phase transition is first order. We prove large deviation principles for the laws of the empirical speed and the empirical charge, and derive a spectral representation for the associated rate functions. Interestingly, in both phases both rate functions exhibit flat pieces, which correspond to an inhomogeneous strategy for the polymer to realise a large deviation. The large deviation principles in turn lead to laws of large numbers and central limit theorems. We identify the scaling behaviour of the critical curve for small and for large charge bias. In addition, we identify the scaling behaviour of the free energy for small charge bias and small inverse temperature. Both are linked to an associated Sturm-Liouville eigenvalue problem. A key tool in our analysis is the Ray-Knight formula for the local times of the one-dimensional simple random walk. This formula is exploited to derive a closed form expression for the generating function of the annealed partition function, and for several related quantities. This expression in turn serves as the starting point for the derivation of the spectral representation for the free energy, and for the scaling theorems. What happens for the quenched free energy per monomer remains open. We state two modest results and raise a few questions.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions.

PubMed

Delaforge, Elise; Milles, Sigrid; Huang, Jie-Rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

PubMed Central

Delaforge, Elise; Milles, Sigrid; Huang, Jie-rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J.; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. PMID:27679800

Large-scale fabrication of bioinspired fibers for directional water collection.

PubMed

Bai, Hao; Sun, Ruize; Ju, Jie; Yao, Xi; Zheng, Yongmei; Jiang, Lei

2011-12-16

Spider-silk inspired functional fibers with periodic spindle-knots and the ability to collect water in a directional manner are fabricated on a large scale using a fluid coating method. The fabrication process is investigated in detail, considering factors like the fiber-drawing velocity, solution viscosity, and surface tension. These bioinspired fibers are inexpensive and durable, which makes it possible to collect water from fog in a similar manner to a spider's web. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parameterizing atmosphere-land surface exchange for climate models with satellite data: A case study for the Southern Great Plains CART site

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

Gao, W.

High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, Sellers et al. and Wood and Lakshmi examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surfacemore » contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario, and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 {times} 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy`s Atmospheric Radiation Measurement (ARM) Program.« less

Large-Scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

PubMed Central

Xu, Jiansong; Potenza, Marc N.; Calhoun, Vince D.; Zhang, Rubin; Yip, Sarah W.; Wall, John T.; Pearlson, Godfrey D.; Worhunsky, Patrick D.; Garrison, Kathleen A.; Moran, Joseph M.

2016-01-01

Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain’s properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings. PMID:27592153

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.

Differences between child and adult large-scale functional brain networks for reading tasks.

PubMed

Liu, Xin; Gao, Yue; Di, Qiqi; Hu, Jiali; Lu, Chunming; Nan, Yun; Booth, James R; Liu, Li

2018-02-01

Reading is an important high-level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large-scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19-28 years old) and 16 children (11-13 years old), and graph theoretical analyses to investigate age-related changes in large-scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter-regional connectivity and nodal degree in occipital regions, while children had stronger inter-regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between-task differences in inter-regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults' reading network is more specialized. (3) Children showed greater inter-regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain-general while others may be specific to the reading domain. © 2017 Wiley Periodicals, Inc.

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

Song, Jong-Won; Hirao, Kimihiko

Long-range corrected density functional theory (LC-DFT) attracts many chemists’ attentions as a quantum chemical method to be applied to large molecular system and its property calculations. However, the expensive time cost to evaluate the long-range HF exchange is a big obstacle to be overcome to be applied to the large molecular systems and the solid state materials. Upon this problem, we propose a linear-scaling method of the HF exchange integration, in particular, for the LC-DFT hybrid functional.

Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements.

PubMed

Lan, Hui; Carson, Rachel; Provart, Nicholas J; Bonner, Anthony J

2007-09-21

Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these genes is currently unknown. The purpose of this study is to infer gene function in Arabidopsis using machine-learning algorithms applied to large-scale gene expression data sets, with the goal of identifying genes that are potentially involved in plant response to abiotic stress. Using in house and publicly available data, we assembled a large set of gene expression measurements for A. thaliana. Using those genes of known function, we first evaluated and compared the ability of basic machine-learning algorithms to predict which genes respond to stress. Predictive accuracy was measured using ROC50 and precision curves derived through cross validation. To improve accuracy, we developed a method for combining these classifiers using a weighted-voting scheme. The combined classifier was then trained on genes of known function and applied to genes of unknown function, identifying genes that potentially respond to stress. Visual evidence corroborating the predictions was obtained using electronic Northern analysis. Three of the predicted genes were chosen for biological validation. Gene knockout experiments confirmed that all three are involved in a variety of stress responses. The biological analysis of one of these genes (At1g16850) is presented here, where it is shown to be necessary for the normal response to temperature and NaCl. Supervised learning methods applied to large-scale gene expression measurements can be used to predict gene function. However, the ability of basic learning methods to predict stress response varies widely and depends heavily on how much dimensionality reduction is used. Our method of combining classifiers can improve the accuracy of such predictions - in this case, predictions of genes involved in stress response in plants - and it effectively chooses the appropriate amount of dimensionality reduction automatically. The method provides a useful means of identifying genes in A. thaliana that potentially respond to stress, and we expect it would be useful in other organisms and for other gene functions.

How Visual Is the Visual Cortex? Comparing Connectional and Functional Fingerprints between Congenitally Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; Peelen, Marius V; Han, Zaizhu; He, Chenxi; Caramazza, Alfonso; Bi, Yanchao

2015-09-09

Classical animal visual deprivation studies and human neuroimaging studies have shown that visual experience plays a critical role in shaping the functionality and connectivity of the visual cortex. Interestingly, recent studies have additionally reported circumscribed regions in the visual cortex in which functional selectivity was remarkably similar in individuals with and without visual experience. Here, by directly comparing resting-state and task-based fMRI data in congenitally blind and sighted human subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. We found a close agreement between connectional and functional maps, pointing to a strong interdependence of connectivity and function. Visual experience (or the absence thereof) had a pronounced effect on the resting-state connectivity and functional response profile of occipital cortex and the posterior lateral fusiform gyrus. By contrast, connectional and functional fingerprints in the anterior medial and posterior lateral parts of the ventral visual cortex were statistically indistinguishable between blind and sighted individuals. These results provide a large-scale mapping of the influence of visual experience on the development of both functional and connectivity properties of visual cortex, which serves as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions. Significance statement: How is the functionality and connectivity of the visual cortex shaped by visual experience? By directly comparing resting-state and task-based fMRI data in congenitally blind and sighted subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. In addition to revealing regions that are strongly dependent on visual experience (early visual cortex and posterior fusiform gyrus), our results showed regions in which connectional and functional patterns are highly similar in blind and sighted individuals (anterior medial and posterior lateral ventral occipital temporal cortex). These results serve as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions of the visual cortex. Copyright © 2015 the authors 0270-6474/15/3512545-15$15.00/0.

Avalanches and scaling collapse in the large-N Kuramoto model

NASA Astrophysics Data System (ADS)

Coleman, J. Patrick; Dahmen, Karin A.; Weaver, Richard L.

2018-04-01

We study avalanches in the Kuramoto model, defined as excursions of the order parameter due to ephemeral episodes of synchronization. We present scaling collapses of the avalanche sizes, durations, heights, and temporal profiles, extracting scaling exponents, exponent relations, and scaling functions that are shown to be consistent with the scaling behavior of the power spectrum, a quantity independent of our particular definition of an avalanche. A comprehensive scaling picture of the noise in the subcritical finite-N Kuramoto model is developed, linking this undriven system to a larger class of driven avalanching systems.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

Preparation of fosmid libraries and functional metagenomic analysis of microbial community DNA.

PubMed

Martínez, Asunción; Osburne, Marcia S

2013-01-01

One of the most important challenges in contemporary microbial ecology is to assign a functional role to the large number of novel genes discovered through large-scale sequencing of natural microbial communities that lack similarity to genes of known function. Functional screening of metagenomic libraries, that is, screening environmental DNA clones for the ability to confer an activity of interest to a heterologous bacterial host, is a promising approach for bridging the gap between metagenomic DNA sequencing and functional characterization. Here, we describe methods for isolating environmental DNA and constructing metagenomic fosmid libraries, as well as methods for designing and implementing successful functional screens of such libraries. © 2013 Elsevier Inc. All rights reserved.

Atomic orbital-based SOS-MP2 with tensor hypercontraction. II. Local tensor hypercontraction

NASA Astrophysics Data System (ADS)

Song, Chenchen; Martínez, Todd J.

2017-01-01

In the first paper of the series [Paper I, C. Song and T. J. Martinez, J. Chem. Phys. 144, 174111 (2016)], we showed how tensor-hypercontracted (THC) SOS-MP2 could be accelerated by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs). This reduced the formal scaling of the SOS-MP2 energy calculation to cubic with respect to system size. The computational bottleneck then becomes the THC metric matrix inversion, which scales cubically with a large prefactor. In this work, the local THC approximation is proposed to reduce the computational cost of inverting the THC metric matrix to linear scaling with respect to molecular size. By doing so, we have removed the primary bottleneck to THC-SOS-MP2 calculations on large molecules with O(1000) atoms. The errors introduced by the local THC approximation are less than 0.6 kcal/mol for molecules with up to 200 atoms and 3300 basis functions. Together with the graphical processing unit techniques and locality-exploiting approaches introduced in previous work, the scaled opposite spin MP2 (SOS-MP2) calculations exhibit O(N2.5) scaling in practice up to 10 000 basis functions. The new algorithms make it feasible to carry out SOS-MP2 calculations on small proteins like ubiquitin (1231 atoms/10 294 atomic basis functions) on a single node in less than a day.

Atomic orbital-based SOS-MP2 with tensor hypercontraction. II. Local tensor hypercontraction.

PubMed

Song, Chenchen; Martínez, Todd J

2017-01-21

In the first paper of the series [Paper I, C. Song and T. J. Martinez, J. Chem. Phys. 144, 174111 (2016)], we showed how tensor-hypercontracted (THC) SOS-MP2 could be accelerated by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs). This reduced the formal scaling of the SOS-MP2 energy calculation to cubic with respect to system size. The computational bottleneck then becomes the THC metric matrix inversion, which scales cubically with a large prefactor. In this work, the local THC approximation is proposed to reduce the computational cost of inverting the THC metric matrix to linear scaling with respect to molecular size. By doing so, we have removed the primary bottleneck to THC-SOS-MP2 calculations on large molecules with O(1000) atoms. The errors introduced by the local THC approximation are less than 0.6 kcal/mol for molecules with up to 200 atoms and 3300 basis functions. Together with the graphical processing unit techniques and locality-exploiting approaches introduced in previous work, the scaled opposite spin MP2 (SOS-MP2) calculations exhibit O(N 2.5 ) scaling in practice up to 10 000 basis functions. The new algorithms make it feasible to carry out SOS-MP2 calculations on small proteins like ubiquitin (1231 atoms/10 294 atomic basis functions) on a single node in less than a day.

Large-scale functional networks connect differently for processing words and symbol strings.

PubMed

Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

2018-01-01

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

Detection of the baryon acoustic peak in the large-scale correlation function of SDSS luminous red galaxies

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

Eisenstein, Daniel J.; Zehavi, Idit; Hogg, David W.

2005-01-01

We present the large-scale correlation function measured from a spectroscopic sample of 46,748 luminous red galaxies from the Sloan Digital Sky Survey. The survey region covers 0.72h{sup -3} Gpc{sup 3} over 3816 square degrees and 0.16 < z < 0.47, making it the best sample yet for the study of large-scale structure. We find a well-detected peak in the correlation function at 100h{sup -1} Mpc separation that is an excellent match to the predicted shape and location of the imprint of the recombination-epoch acoustic oscillations on the low-redshift clustering of matter. This detection demonstrates the linear growth of structure bymore » gravitational instability between z {approx} 1000 and the present and confirms a firm prediction of the standard cosmological theory. The acoustic peak provides a standard ruler by which we can measure the ratio of the distances to z = 0.35 and z = 1089 to 4% fractional accuracy and the absolute distance to z = 0.35 to 5% accuracy. From the overall shape of the correlation function, we measure the matter density {Omega}{sub m}h{sup 2} to 8% and find agreement with the value from cosmic microwave background (CMB) anisotropies. Independent of the constraints provided by the CMB acoustic scale, we find {Omega}{sub m} = 0.273 {+-} 0.025 + 0.123(1 + w{sub 0}) + 0.137{Omega}{sub K}. Including the CMB acoustic scale, we find that the spatial curvature is {Omega}{sub K} = -0.010 {+-} 0.009 if the dark energy is a cosmological constant. More generally, our results provide a measurement of cosmological distance, and hence an argument for dark energy, based on a geometric method with the same simple physics as the microwave background anisotropies. The standard cosmological model convincingly passes these new and robust tests of its fundamental properties.« less

Large-scale spatio-temporal monitoring highlights hotspots of demersal fish diversity in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Granger, Victoria; Fromentin, Jean-Marc; Bez, Nicolas; Relini, Giulio; Meynard, Christine N.; Gaertner, Jean-Claude; Maiorano, Porzia; Garcia Ruiz, Cristina; Follesa, Cristina; Gristina, Michele; Peristeraki, Panagiota; Brind'Amour, Anik; Carbonara, Pierluigi; Charilaou, Charis; Esteban, Antonio; Jadaud, Angélique; Joksimovic, Aleksandar; Kallianiotis, Argyris; Kolitari, Jerina; Manfredi, Chiara; Massuti, Enric; Mifsud, Roberta; Quetglas, Antoni; Refes, Wahid; Sbrana, Mario; Vrgoc, Nedo; Spedicato, Maria Teresa; Mérigot, Bastien

2015-01-01

Increasing human pressures and global environmental change may severely affect the diversity of species assemblages and associated ecosystem services. Despite the recent interest in phylogenetic and functional diversity, our knowledge on large spatio-temporal patterns of demersal fish diversity sampled by trawling remains still incomplete, notably in the Mediterranean Sea, one of the most threatened marine regions of the world. We investigated large spatio-temporal diversity patterns by analysing a dataset of 19,886 hauls from 10 to 800 m depth performed annually during the last two decades by standardised scientific bottom trawl field surveys across the Mediterranean Sea, within the MEDITS program. A multi-component (eight diversity indices) and multi-scale (local assemblages, biogeographic regions to basins) approach indicates that only the two most traditional components (species richness and evenness) were sufficient to reflect patterns in taxonomic, phylogenetic or functional richness and divergence. We also put into question the use of widely computed indices that allow comparing directly taxonomic, phylogenetic and functional diversity within a unique mathematical framework. In addition, demersal fish assemblages sampled by trawl do not follow a continuous decreasing longitudinal/latitudinal diversity gradients (spatial effects explained up to 70.6% of deviance in regression tree and generalised linear models), for any of the indices and spatial scales analysed. Indeed, at both local and regional scales species richness was relatively high in the Iberian region, Malta, the Eastern Ionian and Aegean seas, meanwhile the Adriatic Sea and Cyprus showed a relatively low level. In contrast, evenness as well as taxonomic, phylogenetic and functional divergences did not show regional hotspots. All studied diversity components remained stable over the last two decades. Overall, our results highlight the need to use complementary diversity indices through different spatial scales when developing conservation strategies and defining delimitations for protected areas.

Consultancy on Large-Scale Submerged Aerobic Cultivation Process Design - Final Technical Report: February 1, 2016 -- June 30, 2016

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

Crater, Jason; Galleher, Connor; Lievense, Jeff

NREL is developing an advanced aerobic bubble column model using Aspen Custom Modeler (ACM). The objective of this work is to integrate the new fermentor model with existing techno-economic models in Aspen Plus and Excel to establish a new methodology for guiding process design. To assist this effort, NREL has contracted Genomatica to critique and make recommendations for improving NREL's bioreactor model and large scale aerobic bioreactor design for biologically producing lipids at commercial scale. Genomatica has highlighted a few areas for improving the functionality and effectiveness of the model. Genomatica recommends using a compartment model approach with an integratedmore » black-box kinetic model of the production microbe. We also suggest including calculations for stirred tank reactors to extend the models functionality and adaptability for future process designs. Genomatica also suggests making several modifications to NREL's large-scale lipid production process design. The recommended process modifications are based on Genomatica's internal techno-economic assessment experience and are focused primarily on minimizing capital and operating costs. These recommendations include selecting/engineering a thermotolerant yeast strain with lipid excretion; using bubble column fermentors; increasing the size of production fermentors; reducing the number of vessels; employing semi-continuous operation; and recycling cell mass.« less

“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks

PubMed Central

Gillis, Jesse; Pavlidis, Paul

2012-01-01

Gene networks are commonly interpreted as encoding functional information in their connections. An extensively validated principle called guilt by association states that genes which are associated or interacting are more likely to share function. Guilt by association provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. In this work, we show that functional information within gene networks is typically concentrated in only a very few interactions whose properties cannot be reliably related to the rest of the network. In effect, the apparent encoding of function within networks has been largely driven by outliers whose behaviour cannot even be generalized to individual genes, let alone to the network at large. While experimentalist-driven analysis of interactions may use prior expert knowledge to focus on the small fraction of critically important data, large-scale computational analyses have typically assumed that high-performance cross-validation in a network is due to a generalizable encoding of function. Because we find that gene function is not systemically encoded in networks, but dependent on specific and critical interactions, we conclude it is necessary to focus on the details of how networks encode function and what information computational analyses use to extract functional meaning. We explore a number of consequences of this and find that network structure itself provides clues as to which connections are critical and that systemic properties, such as scale-free-like behaviour, do not map onto the functional connectivity within networks. PMID:22479173

Probing the statistics of primordial fluctuations and their evolution

NASA Technical Reports Server (NTRS)

Gaztanaga, Enrique; Yokoyama, Jun'ichi

1993-01-01

The statistical distribution of fluctuations on various scales is analyzed in terms of the counts in cells of smoothed density fields, using volume-limited samples of galaxy redshift catalogs. It is shown that the distribution on large scales, with volume average of the two-point correlation function of the smoothed field less than about 0.05, is consistent with Gaussian. Statistics are shown to agree remarkably well with the negative binomial distribution, which has hierarchial correlations and a Gaussian behavior at large scales. If these observed properties correspond to the matter distribution, they suggest that our universe started with Gaussian fluctuations and evolved keeping hierarchial form.

Theory of turbulent thermal convection

NASA Astrophysics Data System (ADS)

Lohse, Detlef

2002-03-01

We review our universal theory for the scaling of the Nusselt number and the Reynolds number as functions of the Rayleigh number and the Prandtl number in turbulent thermal convection (Siegfried Grossmann and Detlef Lohse, J. Fluid Mech. 407, 27 (2000); Phys. Rev. Lett. 86, 3316 (2001)). This theory is based on a decomposition of the energy dissipation and the thermal dissipation into a bulk and a boundary layer contribution. We will in particular focus on the behavior for large Prandtl numbers and on the scaling behavior of the Reynolds number for which new experimental results have been obtained recently. We will also address the chaotic switching of the large scale wind of turbulence.

Galaxy clusters and cold dark matter - A low-density unbiased universe?

NASA Technical Reports Server (NTRS)

Bahcall, Neta A.; Cen, Renyue

1992-01-01

Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.

The f ( R ) halo mass function in the cosmic web

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

Braun-Bates, F. von; Winther, H.A.; Alonso, D.

An important indicator of modified gravity is the effect of the local environment on halo properties. This paper examines the influence of the local tidal structure on the halo mass function, the halo orientation, spin and the concentration-mass relation. We use the excursion set formalism to produce a halo mass function conditional on large-scale structure. Our simple model agrees well with simulations on large scales at which the density field is linear or weakly non-linear. Beyond this, our principal result is that f ( R ) does affect halo abundances, the halo spin parameter and the concentration-mass relationship in anmore » environment-independent way, whereas we find no appreciable deviation from \\text(ΛCDM) for the mass function with fixed environment density, nor the alignment of the orientation and spin vectors of the halo to the eigenvectors of the local cosmic web. There is a general trend for greater deviation from \\text(ΛCDM) in underdense environments and for high-mass haloes, as expected from chameleon screening.« less

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints.

PubMed

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D

2015-02-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

PubMed Central

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D.

2015-01-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. PMID:25243991

Programmable gradational micropatterning of functional materials using maskless lithography controlling absorption.

PubMed

Jung, Yushin; Lee, Howon; Park, Tae-Joon; Kim, Sungsik; Kwon, Sunghoon

2015-10-22

The demand for patterning functional materials precisely on surfaces of stimuli-responsive devices has increased in many research fields. In situ polymerization technology is one of the most convenient ways to place the functional materials on a desired location with micron-scale accuracy. To fabricate stimuli-responsive surfaces, controlling concentration of the functional material is much as important as micropatterning them. However, patterning and controlling concentration of the functional materials simultaneously requires an additional process, such as preparing multiple co-flow microfluidic structures and numbers of solutions with various concentrations. Despite applying these processes, fabricating heterogeneous patterns in large scale (millimeter scale) is still impossible. In this study, we propose an advanced in situ polymerization technique to pattern the surface in micron scale in a concentration-controlled manner. Because the concentration of the functional materials is manipulated by self-assembly on the surface, a complex pattern could be easily fabricated without any additional procedure. The complex pattern is pre-designed with absorption amount of the functional material, which is pre-determined by the duration of UV exposure. We show that the resolution reaches up to 2.5 μm and demonstrate mm-scale objects, maintaining the same resolution. We also fabricated Multi-bit barcoded micro particles verify the flexibility of our system.

How global extinctions impact regional biodiversity in mammals.

PubMed

Huang, Shan; Davies, T Jonathan; Gittleman, John L

2012-04-23

Phylogenetic diversity (PD) represents the evolutionary history of a species assemblage and is a valuable measure of biodiversity because it captures not only species richness but potentially also genetic and functional diversity. Preserving PD could be critical for maintaining the functional integrity of the world's ecosystems, and species extinction will have a large impact on ecosystems in areas where the ecosystem cost per species extinction is high. Here, we show that impacts from global extinctions are linked to spatial location. Using a phylogeny of all mammals, we compare regional losses of PD against a model of random extinction. At regional scales, losses differ dramatically: several biodiversity hotspots in southern Asia and Amazonia will lose an unexpectedly large proportion of PD. Global analyses may therefore underestimate the impacts of extinction on ecosystem processes and function because they occur at finer spatial scales within the context of natural biogeography.

Transition from lognormal to χ2-superstatistics for financial time series

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2016-07-01

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.

Evaluation of the reliability and validity for X16 balance testing scale for the elderly.

PubMed

Ju, Jingjuan; Jiang, Yu; Zhou, Peng; Li, Lin; Ye, Xiaolei; Wu, Hongmei; Shen, Bin; Zhang, Jialei; He, Xiaoding; Niu, Chunjin; Xia, Qinghua

2018-05-10

Balance performance is considered as an indicator of functional status in the elderly, a large scale population screening and evaluation in the community context followed by proper interventions would be of great significance at public health level. However, there has been no suitable balance testing scale available for large scale studies in the unique community context of urban China. A balance scale named X16 balance testing scale was developed, which was composed of 3 domains and 16 items. A total of 1985 functionally independent and active community-dwelling elderly adults' balance abilities were tested using the X16 scale. The internal consistency, split-half reliability, content validity, construct validity, discriminant validity of X16 balance testing scale were evaluated. Factor analysis was performed to identify alternative factor structure. The Eigenvalues of factors 1, 2, and 3 were 8.53, 1.79, and 1.21, respectively, and their cumulative contribution to the total variance reached 72.0%. These 3 factors mainly represented domains static balance, postural stability, and dynamic balance. The Cronbach alpha coefficient for the scale was 0.933. The Spearman correlation coefficients between items and its corresponding domains were ranged from 0.538 to 0.964. The correlation coefficients between each item and its corresponding domain were higher than the coefficients between this item and other domains. With the increase of age, the scores of balance performance, domains static balance, postural stability, and dynamic balance in the elderly declined gradually (P < 0.001). With the increase of age, the proportion of the elderly with intact balance performance decreased gradually (P < 0.001). The reliability and validity of the X16 balance testing scale is both adequate and acceptable. Due to its simple and quick use features, it is practical to be used repeatedly and routinely especially in community setting and on large scale screening.

Time dependent turbulence modeling and analytical theories of turbulence

NASA Technical Reports Server (NTRS)

Rubinstein, R.

1993-01-01

By simplifying the direct interaction approximation (DIA) for turbulent shear flow, time dependent formulas are derived for the Reynolds stresses which can be included in two equation models. The Green's function is treated phenomenologically, however, following Smith and Yakhot, we insist on the short and long time limits required by DIA. For small strain rates, perturbative evaluation of the correlation function yields a time dependent theory which includes normal stress effects in simple shear flows. From this standpoint, the phenomenological Launder-Reece-Rodi model is obtained by replacing the Green's function by its long time limit. Eddy damping corrections to short time behavior initiate too quickly in this model; in contrast, the present theory exhibits strong suppression of eddy damping at short times. A time dependent theory for large strain rates is proposed in which large scales are governed by rapid distortion theory while small scales are governed by Kolmogorov inertial range dynamics. At short times and large strain rates, the theory closely matches rapid distortion theory, but at long times it relaxes to an eddy damping model.

Biotic homogenization can decrease landscape-scale forest multifunctionality.

PubMed

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coomes, David Anthony; Coppi, Andrea; Bastias, Cristina C; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Gessler, Arthur; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-Xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-03-29

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality.

Biotic homogenization can decrease landscape-scale forest multifunctionality

PubMed Central

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A.; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coppi, Andrea; Bastias, Cristina C.; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-01-01

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality. PMID:26979952

Constructing Optimal Coarse-Grained Sites of Huge Biomolecules by Fluctuation Maximization.

PubMed

Li, Min; Zhang, John Zenghui; Xia, Fei

2016-04-12

Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10,000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems.

Implementation of highly parallel and large scale GW calculations within the OpenAtom software

NASA Astrophysics Data System (ADS)

Ismail-Beigi, Sohrab

The need to describe electronic excitations with better accuracy than provided by band structures produced by Density Functional Theory (DFT) has been a long-term enterprise for the computational condensed matter and materials theory communities. In some cases, appropriate theoretical frameworks have existed for some time but have been difficult to apply widely due to computational cost. For example, the GW approximation incorporates a great deal of important non-local and dynamical electronic interaction effects but has been too computationally expensive for routine use in large materials simulations. OpenAtom is an open source massively parallel ab initiodensity functional software package based on plane waves and pseudopotentials (http://charm.cs.uiuc.edu/OpenAtom/) that takes advantage of the Charm + + parallel framework. At present, it is developed via a three-way collaboration, funded by an NSF SI2-SSI grant (ACI-1339804), between Yale (Ismail-Beigi), IBM T. J. Watson (Glenn Martyna) and the University of Illinois at Urbana Champaign (Laxmikant Kale). We will describe the project and our current approach towards implementing large scale GW calculations with OpenAtom. Potential applications of large scale parallel GW software for problems involving electronic excitations in semiconductor and/or metal oxide systems will be also be pointed out.

The large-scale gravitational bias from the quasi-linear regime.

NASA Astrophysics Data System (ADS)

Bernardeau, F.

1996-08-01

It is known that in gravitational instability scenarios the nonlinear dynamics induces non-Gaussian features in cosmological density fields that can be investigated with perturbation theory. Here, I derive the expression of the joint moments of cosmological density fields taken at two different locations. The results are valid when the density fields are filtered with a top-hat filter window function, and when the distance between the two cells is large compared to the smoothing length. In particular I show that it is possible to get the generating function of the coefficients C_p,q_ defined by <δ^p^({vec}(x)_1_)δ^q^({vec}(x)_2_)>_c_=C_p,q_ <δ^2^({vec}(x))>^p+q-2^ <δ({vec}(x)_1_)δ({vec}(x)_2_)> where δ({vec}(x)) is the local smoothed density field. It is then possible to reconstruct the joint density probability distribution function (PDF), generalizing for two points what has been obtained previously for the one-point density PDF. I discuss the validity of the large separation approximation in an explicit numerical Monte Carlo integration of the C_2,1_ parameter as a function of |{vec}(x)_1_-{vec}(x)_2_|. A straightforward application is the calculation of the large-scale ``bias'' properties of the over-dense (or under-dense) regions. The properties and the shape of the bias function are presented in details and successfully compared with numerical results obtained in an N-body simulation with CDM initial conditions.

Multi-scale Material Appearance

NASA Astrophysics Data System (ADS)

Wu, Hongzhi

Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.

The Impact of Large, Multi-Function/Multi-Site Competitions

DTIC Science & Technology

2003-08-01

this approach generates larger savings and improved service quality , and is less expensive to implement. Moreover, it is a way to meet the President s...of the study is to assess the degree to which large-scale competitions completed have resulted in increased savings and service quality and decreased

Lagrangian velocity and acceleration correlations of large inertial particles in a closed turbulent flow

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

Machicoane, Nathanaël; Volk, Romain

We investigate the response of large inertial particle to turbulent fluctuations in an inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters are comparable to the flow integral scale. Both velocity and acceleration correlation functions are analyzed to compute the Lagrangian integral time and the acceleration time scale of such particles. The knowledge of how size and density affect these time scales is crucial in understanding particle dynamics and may permit stochastic process modelization using two-time models (for instance, Sawford’s). As particles are tracked over long timesmore » in the quasi-totality of a closed flow, the mean flow influences their behaviour and also biases the velocity time statistics, in particular the velocity correlation functions. By using a method that allows for the computation of turbulent velocity trajectories, we can obtain unbiased Lagrangian integral time. This is particularly useful in accessing the scale separation for such particles and to comparing it to the case of fluid particles in a similar configuration.« less

Cold dark matter confronts the cosmic microwave background - Large-angular-scale anisotropies in Omega sub 0 + lambda 1 models

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Silk, Joseph; Vittorio, Nicola

1992-01-01

A new technique is used to compute the correlation function for large-angle cosmic microwave background anisotropies resulting from both the space and time variations in the gravitational potential in flat, vacuum-dominated, cold dark matter cosmological models. Such models with Omega sub 0 of about 0.2, fit the excess power, relative to the standard cold dark matter model, observed in the large-scale galaxy distribution and allow a high value for the Hubble constant. The low order multipoles and quadrupole anisotropy that are potentially observable by COBE and other ongoing experiments should definitively test these models.

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.

Dimers in Piecewise Temperleyan Domains

NASA Astrophysics Data System (ADS)

Russkikh, Marianna

2018-03-01

We study the large-scale behavior of the height function in the dimer model on the square lattice. Richard Kenyon has shown that the fluctuations of the height function on Temperleyan discretizations of a planar domain converge in the scaling limit (as the mesh size tends to zero) to the Gaussian Free Field with Dirichlet boundary conditions. We extend Kenyon's result to a more general class of discretizations. Moreover, we introduce a new factorization of the coupling function of the double-dimer model into two discrete holomorphic functions, which are similar to discrete fermions defined in Smirnov (Proceedings of the international congress of mathematicians (ICM), Madrid, Spain, 2006; Ann Math (2) 172:1435-1467, 2010). For Temperleyan discretizations with appropriate boundary modifications, the results of Kenyon imply that the expectation of the double-dimer height function converges to a harmonic function in the scaling limit. We use the above factorization to extend this result to the class of all polygonal discretizations, that are not necessarily Temperleyan. Furthermore, we show that, quite surprisingly, the expectation of the double-dimer height function in the Temperleyan case is exactly discrete harmonic (for an appropriate choice of Laplacian) even before taking the scaling limit.

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor Laboratory Press.

Reconstruction of halo power spectrum from redshift-space galaxy distribution: cylinder-grouping method and halo exclusion effect

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Takada, Masahiro; More, Surhud; Masaki, Shogo

2017-07-01

The peculiar velocity field measured by redshift-space distortions (RSD) in galaxy surveys provides a unique probe of the growth of large-scale structure. However, systematic effects arise when including satellite galaxies in the clustering analysis. Since satellite galaxies tend to reside in massive haloes with a greater halo bias, the inclusion boosts the clustering power. In addition, virial motions of the satellite galaxies cause a significant suppression of the clustering power due to non-linear RSD effects. We develop a novel method to recover the redshift-space power spectrum of haloes from the observed galaxy distribution by minimizing the contamination of satellite galaxies. The cylinder-grouping method (CGM) we study effectively excludes satellite galaxies from a galaxy sample. However, we find that this technique produces apparent anisotropies in the reconstructed halo distribution over all the scales which mimic RSD. On small scales, the apparent anisotropic clustering is caused by exclusion of haloes within the anisotropic cylinder used by the CGM. On large scales, the misidentification of different haloes in the large-scale structures, aligned along the line of sight, into the same CGM group causes the apparent anisotropic clustering via their cross-correlation with the CGM haloes. We construct an empirical model for the CGM halo power spectrum, which includes correction terms derived using the CGM window function at small scales as well as the linear matter power spectrum multiplied by a simple anisotropic function at large scales. We apply this model to a mock galaxy catalogue at z = 0.5, designed to resemble Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS) CMASS galaxies, and find that our model can predict both the monopole and quadrupole power spectra of the host haloes up to k < 0.5 {{h Mpc^{-1}}} to within 5 per cent.

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.

On the large eddy simulation of turbulent flows in complex geometry

NASA Technical Reports Server (NTRS)

Ghosal, Sandip

1993-01-01

Application of the method of Large Eddy Simulation (LES) to a turbulent flow consists of three separate steps. First, a filtering operation is performed on the Navier-Stokes equations to remove the small spatial scales. The resulting equations that describe the space time evolution of the 'large eddies' contain the subgrid-scale (sgs) stress tensor that describes the effect of the unresolved small scales on the resolved scales. The second step is the replacement of the sgs stress tensor by some expression involving the large scales - this is the problem of 'subgrid-scale modeling'. The final step is the numerical simulation of the resulting 'closed' equations for the large scale fields on a grid small enough to resolve the smallest of the large eddies, but still much larger than the fine scale structures at the Kolmogorov length. In dividing a turbulent flow field into 'large' and 'small' eddies, one presumes that a cut-off length delta can be sensibly chosen such that all fluctuations on a scale larger than delta are 'large eddies' and the remainder constitute the 'small scale' fluctuations. Typically, delta would be a length scale characterizing the smallest structures of interest in the flow. In an inhomogeneous flow, the 'sensible choice' for delta may vary significantly over the flow domain. For example, in a wall bounded turbulent flow, most statistical averages of interest vary much more rapidly with position near the wall than far away from it. Further, there are dynamically important organized structures near the wall on a scale much smaller than the boundary layer thickness. Therefore, the minimum size of eddies that need to be resolved is smaller near the wall. In general, for the LES of inhomogeneous flows, the width of the filtering kernel delta must be considered to be a function of position. If a filtering operation with a nonuniform filter width is performed on the Navier-Stokes equations, one does not in general get the standard large eddy equations. The complication is caused by the fact that a filtering operation with a nonuniform filter width in general does not commute with the operation of differentiation. This is one of the issues that we have looked at in detail as it is basic to any attempt at applying LES to complex geometry flows. Our principal findings are summarized.

The impact of land-surface wetness heterogeneity on mesoscale heat fluxes

NASA Technical Reports Server (NTRS)

Chen, Fei; Avissar, Roni

1994-01-01

Vertical heat fluxes associated with mesoscale circulations generated by land-surface wetness discontinuities are often stronger than turbulent fluxes, especially in the upper part of the atmospheric planetary boundary layer. As a result, they contribute significantly to the subgrid-scale fluxes in large-scale atmospheric models. Yet they are not considered in these models. To provide some insights into the possible parameterization of these fluxes in large-scale models, a state-of-the-art mesoscale numerical model was used to investigate the relationships between mesoscale heat fluxes and atmospheric and land-surface characteristics that play a key role in the generation of mesoscale circulations. The distribution of land-surface wetness, the wavenumber and the wavelength of the land-surface discontinuities, and the large-scale wind speed have a significant impact on the mesoscale heat fluxes. Empirical functions were derived to characterize the relationships between mesoscale heat fluxes and the spatial distribution of land-surface wetness. The strongest mesoscale heat fluxes were obtained for a wavelength of forcing corresponding approximately to the local Rossby deformation radius. The mesoscale heat fluxes are weakened by large-scale background winds but remain significant even with moderate winds.

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

PubMed

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

2014-12-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Large Scale Structure Studies: Final Results from a Rich Cluster Redshift Survey

NASA Astrophysics Data System (ADS)

Slinglend, K.; Batuski, D.; Haase, S.; Hill, J.

1995-12-01

The results from the COBE satellite show the existence of structure on scales on the order of 10% or more of the horizon scale of the universe. Rich clusters of galaxies from the Abell-ACO catalogs show evidence of structure on scales of 100 Mpc and hold the promise of confirming structure on the scale of the COBE result. Unfortunately, until now, redshift information has been unavailable for a large percentage of these clusters, so present knowledge of their three dimensional distribution has quite large uncertainties. Our approach in this effort has been to use the MX multifiber spectrometer on the Steward 2.3m to measure redshifts of at least ten galaxies in each of 88 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8 (estimated z<= 0.12) and zero or one measured redshifts. This work has resulted in a deeper, 95% complete and more reliable sample of 3-D positions of rich clusters. The primary intent of this survey has been to constrain theoretical models for the formation of the structure we see in the universe today through 2-pt. spatial correlation function and other analyses of the large scale structures traced by these clusters. In addition, we have obtained enough redshifts per cluster to greatly improve the quality and size of the sample of reliable cluster velocity dispersions available for use in other studies of cluster properties. This new data has also allowed the construction of an updated and more reliable supercluster candidate catalog. Our efforts have resulted in effectively doubling the volume traced by these clusters. Presented here is the resulting 2-pt. spatial correlation function, as well as density plots and several other figures quantifying the large scale structure from this much deeper and complete sample. Also, with 10 or more redshifts in most of our cluster fields, we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

PubMed

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large-scale datasets. Software and data sets are available at http://www.sfu.ca/~ester/software/DECOB.zip.

Scale dependence of the alignment between strain rate and rotation in turbulent shear flow

NASA Astrophysics Data System (ADS)

Fiscaletti, D.; Elsinga, G. E.; Attili, A.; Bisetti, F.; Buxton, O. R. H.

2016-10-01

The scale dependence of the statistical alignment tendencies of the eigenvectors of the strain-rate tensor ei, with the vorticity vector ω , is examined in the self-preserving region of a planar turbulent mixing layer. Data from a direct numerical simulation are filtered at various length scales and the probability density functions of the magnitude of the alignment cosines between the two unit vectors | ei.ω ̂| are examined. It is observed that the alignment tendencies are insensitive to the concurrent large-scale velocity fluctuations, but are quantitatively affected by the nature of the concurrent large-scale velocity-gradient fluctuations. It is confirmed that the small-scale (local) vorticity vector is preferentially aligned in parallel with the large-scale (background) extensive strain-rate eigenvector e1, in contrast to the global tendency for ω to be aligned in parallel with the intermediate strain-rate eigenvector [Hamlington et al., Phys. Fluids 20, 111703 (2008), 10.1063/1.3021055]. When only data from regions of the flow that exhibit strong swirling are included, the so-called high-enstrophy worms, the alignment tendencies are exaggerated with respect to the global picture. These findings support the notion that the production of enstrophy, responsible for a net cascade of turbulent kinetic energy from large scales to small scales, is driven by vorticity stretching due to the preferential parallel alignment between ω and nonlocal e1 and that the strongly swirling worms are kinematically significant to this process.

Scaling and self-organized criticality in proteins I

PubMed Central

Phillips, J. C.

2009-01-01

The complexity of proteins is substantially simplified by regarding them as archetypical examples of self-organized criticality (SOC). To test this idea and elaborate on it, this article applies the Moret–Zebende SOC hydrophobicity scale to the large-scale scaffold repeat protein of the HEAT superfamily, PR65/A. Hydrophobic plasticity is defined and used to identify docking platforms and hinges from repeat sequences alone. The difference between the MZ scale and conventional hydrophobicity scales reflects long-range conformational forces that are central to protein functionality. PMID:19218446

Effective model hierarchies for dynamic and static classical density functional theories

NASA Astrophysics Data System (ADS)

Majaniemi, S.; Provatas, N.; Nonomura, M.

2010-09-01

The origin and methodology of deriving effective model hierarchies are presented with applications to solidification of crystalline solids. In particular, it is discussed how the form of the equations of motion and the effective parameters on larger scales can be obtained from the more microscopic models. It will be shown that tying together the dynamic structure of the projection operator formalism with static classical density functional theories can lead to incomplete (mass) transport properties even though the linearized hydrodynamics on large scales is correctly reproduced. To facilitate a more natural way of binding together the dynamics of the macrovariables and classical density functional theory, a dynamic generalization of density functional theory based on the nonequilibrium generating functional is suggested.

Human Gut Microbiome: Function Matters.

PubMed

Heintz-Buschart, Anna; Wilmes, Paul

2017-11-22

The human gut microbiome represents a complex ecosystem contributing essential functions to its host. Recent large-scale metagenomic studies have provided insights into its structure and functional potential. However, the functional repertoire which is actually contributed to human physiology remains largely unexplored. Here, by leveraging recent omics datasets, we challenge current assumptions regarding key attributes of the functional gut microbiome, in particular with respect to its variability. We further argue that the closing of existing gaps in functional knowledge should be addressed by a most-wanted gene list, the development and application of molecular and cellular high-throughput measurements, the development and sensible use of experimental models, as well as the direct study of observable molecular effects in the human host. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018 Elsevier Inc. All rights reserved.

High cell density media for Escherichia coli are generally designed for aerobic cultivations – consequences for large-scale bioprocesses and shake flask cultures

PubMed Central

Soini, Jaakko; Ukkonen, Kaisa; Neubauer, Peter

2008-01-01

Background For the cultivation of Escherichia coli in bioreactors trace element solutions are generally designed for optimal growth under aerobic conditions. They do normally not contain selenium and nickel. Molybdenum is only contained in few of them. These elements are part of the formate hydrogen lyase (FHL) complex which is induced under anaerobic conditions. As it is generally known that oxygen limitation appears in shake flask cultures and locally in large-scale bioreactors, function of the FHL complex may influence the process behaviour. Formate has been described to accumulate in large-scale cultures and may have toxic effects on E. coli. Although the anaerobic metabolism of E. coli is well studied, reference data which estimate the impact of the FHL complex on bioprocesses of E. coli with oxygen limitation have so far not been published, but are important for a better process understanding. Results Two sets of fed-batch cultures with conditions triggering oxygen limitation and formate accumulation were performed. Permanent oxygen limitation which is typical for shake flask cultures was caused in a bioreactor by reduction of the agitation rate. Transient oxygen limitation, which has been described to eventually occur in the feed-zone of large-scale bioreactors, was mimicked in a two-compartment scale-down bioreactor consisting of a stirred tank reactor and a plug flow reactor (PFR) with continuous glucose feeding into the PFR. In both models formate accumulated up to about 20 mM in the culture medium without addition of selenium, molybdenum and nickel. By addition of these trace elements the formate accumulation decreased below the level observed in well-mixed laboratory-scale cultures. Interestingly, addition of the extra trace elements caused accumulation of large amounts of lactate and reduced biomass yield in the simulator with permanent oxygen limitation, but not in the scale-down two-compartment bioreactor. Conclusion The accumulation of formate in oxygen limited cultivations of E. coli can be fully prevented by addition of the trace elements selenium, nickel and molybdenum, necessary for the function of FHL complex. For large-scale cultivations, if glucose gradients are likely, the results from the two-compartment scale-down bioreactor indicate that the addition of the extra trace elements is beneficial. No negative effects on the biomass yield or on any other bioprocess parameters could be observed in cultures with the extra trace elements if the cells were repeatedly exposed to transient oxygen limitation. PMID:18687130

On the distribution of local dissipation scales in turbulent flows

NASA Astrophysics Data System (ADS)

May, Ian; Morshed, Khandakar; Venayagamoorthy, Karan; Dasi, Lakshmi

2014-11-01

Universality of dissipation scales in turbulence relies on self-similar scaling and large scale independence. We show that the probability density function of dissipation scales, Q (η) , is analytically defined by the two-point correlation function, and the Reynolds number (Re). We also present a new analytical form for the two-point correlation function for the dissipation scales through a generalized definition of a directional Taylor microscale. Comparison of Q (η) predicted within this framework and published DNS data shows excellent agreement. It is shown that for finite Re no single similarity law exists even for the case of homogeneous isotropic turbulence. Instead a family of scaling is presented, defined by Re and a dimensionless local inhomogeneity parameter based on the spatial gradient of the rms velocity. For moderate Re inhomogeneous flows, we note a strong directional dependence of Q (η) dictated by the principal Reynolds stresses. It is shown that the mode of the distribution Q (η) significantly shifts to sub-Kolmogorov scales along the inhomogeneous directions, as in wall bounded turbulence. This work extends the classical Kolmogorov's theory to finite Re homogeneous isotropic turbulence as well as the case of inhomogeneous anisotropic turbulence.

Probing features in the primordial perturbation spectrum with large-scale structure data

NASA Astrophysics Data System (ADS)

L'Huillier, Benjamin; Shafieloo, Arman; Hazra, Dhiraj Kumar; Smoot, George F.; Starobinsky, Alexei A.

2018-06-01

The form of the primordial power spectrum (PPS) of cosmological scalar (matter density) perturbations is not yet constrained satisfactorily in spite of the tremendous amount of information from the Cosmic Microwave Background (CMB) data. While a smooth power-law-like form of the PPS is consistent with the CMB data, some PPSs with small non-smooth features at large scales can also fit the CMB temperature and polarization data with similar statistical evidence. Future CMB surveys cannot help distinguish all such models due to the cosmic variance at large angular scales. In this paper, we study how well we can differentiate between such featured forms of the PPS not otherwise distinguishable using CMB data. We ran 15 N-body DESI-like simulations of these models to explore this approach. Showing that statistics such as the halo mass function and the two-point correlation function are not able to distinguish these models in a DESI-like survey, we advocate to avoid reducing the dimensionality of the problem by demonstrating that the use of a simple three-dimensional count-in-cell density field can be much more effective for the purpose of model distinction.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures.

PubMed

Lehnert, L W; Wesche, K; Trachte, K; Reudenbach, C; Bendix, J

2016-04-13

The Tibetan Plateau (TP) is a globally important "water tower" that provides water for nearly 40% of the world's population. This supply function is claimed to be threatened by pasture degradation on the TP and the associated loss of water regulation functions. However, neither potential large scale degradation changes nor their drivers are known. Here, we analyse trends in a high-resolution dataset of grassland cover to determine the interactions among vegetation dynamics, climate change and human impacts on the TP. The results reveal that vegetation changes have regionally different triggers: While the vegetation cover has increased since the year 2000 in the north-eastern part of the TP due to an increase in precipitation, it has declined in the central and western parts of the TP due to rising air temperature and declining precipitation. Increasing livestock numbers as a result of land use changes exacerbated the negative trends but were not their exclusive driver. Thus, we conclude that climate variability instead of overgrazing has been the primary cause for large scale vegetation cover changes on the TP since the new millennium. Since areas of positive and negative changes are almost equal in extent, pasture degradation is not generally proceeding.

Weighted and directed interactions in evolving large-scale epileptic brain networks

NASA Astrophysics Data System (ADS)

Dickten, Henning; Porz, Stephan; Elger, Christian E.; Lehnertz, Klaus

2016-10-01

Epilepsy can be regarded as a network phenomenon with functionally and/or structurally aberrant connections in the brain. Over the past years, concepts and methods from network theory substantially contributed to improve the characterization of structure and function of these epileptic networks and thus to advance understanding of the dynamical disease epilepsy. We extend this promising line of research and assess—with high spatial and temporal resolution and using complementary analysis approaches that capture different characteristics of the complex dynamics—both strength and direction of interactions in evolving large-scale epileptic brain networks of 35 patients that suffered from drug-resistant focal seizures with different anatomical onset locations. Despite this heterogeneity, we find that even during the seizure-free interval the seizure onset zone is a brain region that, when averaged over time, exerts strongest directed influences over other brain regions being part of a large-scale network. This crucial role, however, manifested by averaging on the population-sample level only - in more than one third of patients, strongest directed interactions can be observed between brain regions far off the seizure onset zone. This may guide new developments for individualized diagnosis, treatment and control.

Applications of species accumulation curves in large-scale biological data analysis.

PubMed

Deng, Chao; Daley, Timothy; Smith, Andrew D

2015-09-01

The species accumulation curve, or collector's curve, of a population gives the expected number of observed species or distinct classes as a function of sampling effort. Species accumulation curves allow researchers to assess and compare diversity across populations or to evaluate the benefits of additional sampling. Traditional applications have focused on ecological populations but emerging large-scale applications, for example in DNA sequencing, are orders of magnitude larger and present new challenges. We developed a method to estimate accumulation curves for predicting the complexity of DNA sequencing libraries. This method uses rational function approximations to a classical non-parametric empirical Bayes estimator due to Good and Toulmin [Biometrika, 1956, 43, 45-63]. Here we demonstrate how the same approach can be highly effective in other large-scale applications involving biological data sets. These include estimating microbial species richness, immune repertoire size, and k -mer diversity for genome assembly applications. We show how the method can be modified to address populations containing an effectively infinite number of species where saturation cannot practically be attained. We also introduce a flexible suite of tools implemented as an R package that make these methods broadly accessible.

Applications of species accumulation curves in large-scale biological data analysis

PubMed Central

Deng, Chao; Daley, Timothy; Smith, Andrew D

2016-01-01

The species accumulation curve, or collector’s curve, of a population gives the expected number of observed species or distinct classes as a function of sampling effort. Species accumulation curves allow researchers to assess and compare diversity across populations or to evaluate the benefits of additional sampling. Traditional applications have focused on ecological populations but emerging large-scale applications, for example in DNA sequencing, are orders of magnitude larger and present new challenges. We developed a method to estimate accumulation curves for predicting the complexity of DNA sequencing libraries. This method uses rational function approximations to a classical non-parametric empirical Bayes estimator due to Good and Toulmin [Biometrika, 1956, 43, 45–63]. Here we demonstrate how the same approach can be highly effective in other large-scale applications involving biological data sets. These include estimating microbial species richness, immune repertoire size, and k-mer diversity for genome assembly applications. We show how the method can be modified to address populations containing an effectively infinite number of species where saturation cannot practically be attained. We also introduce a flexible suite of tools implemented as an R package that make these methods broadly accessible. PMID:27252899

New Probe of Departures from General Relativity Using Minkowski Functionals.

PubMed

Fang, Wenjuan; Li, Baojiu; Zhao, Gong-Bo

2017-05-05

The morphological properties of the large scale structure of the Universe can be fully described by four Minkowski functionals (MFs), which provide important complementary information to other statistical observables such as the widely used 2-point statistics in configuration and Fourier spaces. In this work, for the first time, we present the differences in the morphology of the large scale structure caused by modifications to general relativity (to address the cosmic acceleration problem), by measuring the MFs from N-body simulations of modified gravity and general relativity. We find strong statistical power when using the MFs to constrain modified theories of gravity: with a galaxy survey that has survey volume ∼0.125(h^{-1}  Gpc)^{3} and galaxy number density ∼1/(h^{-1}  Mpc)^{3}, the two normal-branch Dvali-Gabadadze-Porrati models and the F5 f(R) model that we simulated can be discriminated from the ΛCDM model at a significance level ≳5σ with an individual MF measurement. Therefore, the MF of the large scale structure is potentially a powerful probe of gravity, and its application to real data deserves active exploration.

Suppression of phase mixing in drift-kinetic plasma turbulence

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

Parker, J. T., E-mail: joseph.parker@stfc.ac.uk; OCIAM, Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG; Brasenose College, Radcliffe Square, Oxford OX1 4AJ

2016-07-15

Transfer of free energy from large to small velocity-space scales by phase mixing leads to Landau damping in a linear plasma. In a turbulent drift-kinetic plasma, this transfer is statistically nearly canceled by an inverse transfer from small to large velocity-space scales due to “anti-phase-mixing” modes excited by a stochastic form of plasma echo. Fluid moments (density, velocity, and temperature) are thus approximately energetically isolated from the higher moments of the distribution function, so phase mixing is ineffective as a dissipation mechanism when the plasma collisionality is small.

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun

2015-01-01

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781

A guide to large-scale RNA sample preparation.

PubMed

Baronti, Lorenzo; Karlsson, Hampus; Marušič, Maja; Petzold, Katja

2018-05-01

RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods. Graphical abstract In this review we present different methods for large-scale production and purification of RNAs for structural and biophysical studies.

ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling | Office of Cancer Genomics

Cancer.gov

Functional genomics (FG) screens, using RNAi or CRISPR technology, have become a standard tool for systematic, genome-wide loss-of-function studies for therapeutic target discovery. As in many large-scale assays, however, off-target effects, variable reagents' potency and experimental noise must be accounted for appropriately control for false positives.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

Accurate density functional prediction of molecular electron affinity with the scaling corrected Kohn–Sham frontier orbital energies

NASA Astrophysics Data System (ADS)

Zhang, DaDi; Yang, Xiaolong; Zheng, Xiao; Yang, Weitao

2018-04-01

Electron affinity (EA) is the energy released when an additional electron is attached to an atom or a molecule. EA is a fundamental thermochemical property, and it is closely pertinent to other important properties such as electronegativity and hardness. However, accurate prediction of EA is difficult with density functional theory methods. The somewhat large error of the calculated EAs originates mainly from the intrinsic delocalisation error associated with the approximate exchange-correlation functional. In this work, we employ a previously developed non-empirical global scaling correction approach, which explicitly imposes the Perdew-Parr-Levy-Balduz condition to the approximate functional, and achieve a substantially improved accuracy for the calculated EAs. In our approach, the EA is given by the scaling corrected Kohn-Sham lowest unoccupied molecular orbital energy of the neutral molecule, without the need to carry out the self-consistent-field calculation for the anion.

The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2011-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks

PubMed Central

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory. PMID:28736535

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

PubMed

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study.

PubMed

Lix, Lisa M; Wu, Xiuyun; Hopman, Wilma; Mayo, Nancy; Sajobi, Tolulope T; Liu, Juxin; Prior, Jerilynn C; Papaioannou, Alexandra; Josse, Robert G; Towheed, Tanveer E; Davison, K Shawn; Sawatzky, Richard

2016-01-01

Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36), can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF), which arises when population sub-groups with the same underlying (i.e., latent) level of health have different measured item response probabilities, may compromise the comparability of these measures. The purpose of this study was to test for DIF on the SF-36 physical functioning (PF) and mental health (MH) sub-scale items in a Canadian population-based sample. Study data were from the prospective Canadian Multicentre Osteoporosis Study (CaMos), which collected baseline data in 1996-1997. DIF was tested using a multiple indicators multiple causes (MIMIC) method. Confirmatory factor analysis defined the latent variable measurement model for the item responses and latent variable regression with demographic and health status covariates (i.e., sex, age group, body weight, self-perceived general health) produced estimates of the magnitude of DIF effects. The CaMos cohort consisted of 9423 respondents; 69.4% were female and 51.7% were less than 65 years. Eight of 10 items on the PF sub-scale and four of five items on the MH sub-scale exhibited DIF. Large DIF effects were observed on PF sub-scale items about vigorous and moderate activities, lifting and carrying groceries, walking one block, and bathing or dressing. On the MH sub-scale items, all DIF effects were small or moderate in size. SF-36 PF and MH sub-scale scores were not comparable across population sub-groups defined by demographic and health status variables due to the effects of DIF, although the magnitude of this bias was not large for most items. We recommend testing and adjusting for DIF to ensure comparability of the SF-36 in population-based investigations.

Dark matter, long-range forces, and large-scale structure

NASA Technical Reports Server (NTRS)

Gradwohl, Ben-Ami; Frieman, Joshua A.

1992-01-01

If the dark matter in galaxies and clusters is nonbaryonic, it can interact with additional long-range fields that are invisible to experimental tests of the equivalence principle. We discuss the astrophysical and cosmological implications of a long-range force coupled only to the dark matter and find rather tight constraints on its strength. If the force is repulsive (attractive), the masses of galaxy groups and clusters (and the mean density of the universe inferred from them) have been systematically underestimated (overestimated). We explore the consequent effects on the two-point correlation function, large-scale velocity flows, and microwave background anisotropies, for models with initial scale-invariant adiabatic perturbations and cold dark matter.

Quality Function Deployment for Large Systems

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1992-01-01

Quality Function Deployment (QFD) is typically applied to small subsystems. This paper describes efforts to extend QFD to large scale systems. It links QFD to the system engineering process, the concurrent engineering process, the robust design process, and the costing process. The effect is to generate a tightly linked project management process of high dimensionality which flushes out issues early to provide a high quality, low cost, and, hence, competitive product. A pre-QFD matrix linking customers to customer desires is described.

Nonextensive Entropy Approach to Space Plasma Fluctuations and Turbulence

NASA Astrophysics Data System (ADS)

Leubner, M. P.; Vörös, Z.; Baumjohann, W.

Spatial intermittency in fully developed turbulence is an established feature of astrophysical plasma fluctuations and in particular apparent in the interplanetary medium by in situ observations. In this situation, the classical Boltzmann— Gibbs extensive thermo-statistics, applicable when microscopic interactions and memory are short ranged and the environment is a continuous and differentiable manifold, fails. Upon generalization of the entropy function to nonextensivity, accounting for long-range interactions and thus for correlations in the system, it is demonstrated that the corresponding probability distribution functions (PDFs) are members of a family of specific power-law distributions. In particular, the resulting theoretical bi-κ functional reproduces accurately the observed global leptokurtic, non-Gaussian shape of the increment PDFs of characteristic solar wind variables on all scales, where nonlocality in turbulence is controlled via a multiscale coupling parameter. Gradual decoupling is obtained by enhancing the spatial separation scale corresponding to increasing κ-values in case of slow solar wind conditions where a Gaussian is approached in the limit of large scales. Contrary, the scaling properties in the high speed solar wind are predominantly governed by the mean energy or variance of the distribution, appearing as second parameter in the theory. The PDFs of solar wind scalar field differences are computed from WIND and ACE data for different time-lags and bulk speeds and analyzed within the nonextensive theory, where also a particular nonlinear dependence of the coupling parameter and variance with scale arises for best fitting theoretical PDFs. Consequently, nonlocality in fluctuations, related to both, turbulence and its large scale driving, should be related to long-range interactions in the context of nonextensive entropy generalization, providing fundamentally the physical background of the observed scale dependence of fluctuations in intermittent space plasmas.

A Measurement Invariance Examination of the Revised Child Anxiety and Depression Scale in a Southern Sample: Differential Item Functioning between African American and Caucasian Youth

ERIC Educational Resources Information Center

Trent, Lindsay Rae; Buchanan, Erin; Ebesutani, Chad; Ale, Chelsea M.; Heiden, Laurie; Hight, Terry L.; Damon, John D.; Young, John

2013-01-01

This study examined the psychometric properties of the Revised Child Anxiety and Depression Scale in a large sample of youth from the Southern United States. The authors aimed to determine (a) if the established six-factor Revised Child Anxiety and Depression Scale structure could be replicated in this Southern sample and (b) if scores were…

Magnetic intermittency of solar wind turbulence in the dissipation range

NASA Astrophysics Data System (ADS)

Pei, Zhongtian; He, Jiansen; Tu, Chuanyi; Marsch, Eckart; Wang, Linghua

2016-04-01

The feature, nature, and fate of intermittency in the dissipation range are an interesting topic in the solar wind turbulence. We calculate the distribution of flatness for the magnetic field fluctuations as a functionof angle and scale. The flatness distribution shows a "butterfly" pattern, with two wings located at angles parallel/anti-parallel to local mean magnetic field direction and main body located at angles perpendicular to local B0. This "butterfly" pattern illustrates that the flatness profile in (anti-) parallel direction approaches to the maximum value at larger scale and drops faster than that in perpendicular direction. The contours for probability distribution functions at different scales illustrate a "vase" pattern, more clear in parallel direction, which confirms the scale-variation of flatness and indicates the intermittency generation and dissipation. The angular distribution of structure function in the dissipation range shows an anisotropic pattern. The quasi-mono-fractal scaling of structure function in the dissipation range is also illustrated and investigated with the mathematical model for inhomogeneous cascading (extended p-model). Different from the inertial range, the extended p-model for the dissipation range results in approximate uniform fragmentation measure. However, more complete mathematicaland physical model involving both non-uniform cascading and dissipation is needed. The nature of intermittency may be strong structures or large amplitude fluctuations, which may be tested with magnetic helicity. In one case study, we find the heating effect in terms of entropy for large amplitude fluctuations seems to be more obvious than strong structures.

Managing landscapes at multiple scales for sustainability of ecosystem functions (Preface)

Treesearch

R.A. Birdsey; R. Lucas; Y. Pan; G. Sun; E.J. Gustafson; A.H.  Perera

2010-01-01

The science of landscape ecology is a rapidly evolving academic field with an emphasis on studying large-scale spatial heterogeneity created by natural influences and human activities. These advances have important implications for managing and conserving natural resources. At a September 2008 IUFRO conference in Chengdu, Sichuan, P.R. China, we highlighted both the...

Changes in photosynthesis and soil moisture drive the seasonal soil respiration-temperature hysteresis relationship

USDA-ARS?s Scientific Manuscript database

In nearly all large-scale models, CO2 efflux from soil (i.e., soil respiration) is represented as a function of soil temperature. However, the relationship between soil respiration and soil temperature is highly variable at the local scale, and there is often a pronounced hysteresis in the soil resp...

Management of Protected Areas and Its Effect on an Ecosystem Function: Removal of Prosopis flexuosa Seeds by Mammals in Argentinian Drylands

PubMed Central

Campos, Valeria E.; Miguel, Florencia; Cona, Mónica I.

2016-01-01

The ecological function of animal seed dispersal depends on species interactions and can be affected by drivers such as the management interventions applied to protected areas. This study was conducted in two protected areas in the Monte Desert: a fenced reserve with grazing exclusion and absence of large native mammals (the Man and Biosphere Ñacuñán Reserve; FR) and an unfenced reserve with low densities of large native and domestic animals (Ischigualasto Park; UFR). The study focuses on Prosopis flexuosa seed removal by different functional mammal groups: “seed predators”, “scatter-hoarders”, and “opportunistic frugivores”. Under both interventions, the relative contribution to seed removal by different functional mammal groups was assessed, as well as how these groups respond to habitat heterogeneity (i.e. vegetation structure) at different spatial scales. Camera traps were used to identify mammal species removing P. flexuosa seeds and to quantify seed removal; remote sensing data helped analyze habitat heterogeneity. In the FR, the major fruit removers were a seed predator (Graomys griseoflavus) and a scatter-hoarder (Microcavia asutralis). In the UFR, the main seed removers were the opportunistic frugivores (Lycalopex griseus and Dolichotis patagonum), who removed more seeds than the seed predator in the FR. The FR shows higher habitat homogeneity than the UFR, and functional groups respond differently to habitat heterogeneity at different spatial scales. In the FR, because large herbivores are locally extinct (e.g. Lama guanicoe) and domestic herbivores are excluded, important functions of large herbivores are missing, such as the maintenance of habitat heterogeneity, which provides habitats for medium-sized opportunistic frugivores with consequent improvement of quality and quantity of seed dispersal services. In the UFR, with low densities of large herbivores, probably one important ecosystem function this group performs is to increase habitat heterogeneity, allowing for the activity of medium-sized mammals who, behaving as opportunistic frugivores, did the most significant seed removal. PMID:27655222

Management of Protected Areas and Its Effect on an Ecosystem Function: Removal of Prosopis flexuosa Seeds by Mammals in Argentinian Drylands.

PubMed

Campos, Claudia M; Campos, Valeria E; Miguel, Florencia; Cona, Mónica I

The ecological function of animal seed dispersal depends on species interactions and can be affected by drivers such as the management interventions applied to protected areas. This study was conducted in two protected areas in the Monte Desert: a fenced reserve with grazing exclusion and absence of large native mammals (the Man and Biosphere Ñacuñán Reserve; FR) and an unfenced reserve with low densities of large native and domestic animals (Ischigualasto Park; UFR). The study focuses on Prosopis flexuosa seed removal by different functional mammal groups: "seed predators", "scatter-hoarders", and "opportunistic frugivores". Under both interventions, the relative contribution to seed removal by different functional mammal groups was assessed, as well as how these groups respond to habitat heterogeneity (i.e. vegetation structure) at different spatial scales. Camera traps were used to identify mammal species removing P. flexuosa seeds and to quantify seed removal; remote sensing data helped analyze habitat heterogeneity. In the FR, the major fruit removers were a seed predator (Graomys griseoflavus) and a scatter-hoarder (Microcavia asutralis). In the UFR, the main seed removers were the opportunistic frugivores (Lycalopex griseus and Dolichotis patagonum), who removed more seeds than the seed predator in the FR. The FR shows higher habitat homogeneity than the UFR, and functional groups respond differently to habitat heterogeneity at different spatial scales. In the FR, because large herbivores are locally extinct (e.g. Lama guanicoe) and domestic herbivores are excluded, important functions of large herbivores are missing, such as the maintenance of habitat heterogeneity, which provides habitats for medium-sized opportunistic frugivores with consequent improvement of quality and quantity of seed dispersal services. In the UFR, with low densities of large herbivores, probably one important ecosystem function this group performs is to increase habitat heterogeneity, allowing for the activity of medium-sized mammals who, behaving as opportunistic frugivores, did the most significant seed removal.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

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.

Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library.

PubMed

Mohr, Stephan; Dawson, William; Wagner, Michael; Caliste, Damien; Nakajima, Takahito; Genovese, Luigi

2017-10-10

We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes.

SQDFT: Spectral Quadrature method for large-scale parallel O(N) Kohn-Sham calculations at high temperature

NASA Astrophysics Data System (ADS)

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; Pask, John E.

2018-03-01

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method for O(N) Kohn-Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw-Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw-Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. We further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect O(N) scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.

Environment and host as large-scale controls of ectomycorrhizal fungi.

PubMed

van der Linde, Sietse; Suz, Laura M; Orme, C David L; Cox, Filipa; Andreae, Henning; Asi, Endla; Atkinson, Bonnie; Benham, Sue; Carroll, Christopher; Cools, Nathalie; De Vos, Bruno; Dietrich, Hans-Peter; Eichhorn, Johannes; Gehrmann, Joachim; Grebenc, Tine; Gweon, Hyun S; Hansen, Karin; Jacob, Frank; Kristöfel, Ferdinand; Lech, Paweł; Manninger, Miklós; Martin, Jan; Meesenburg, Henning; Merilä, Päivi; Nicolas, Manuel; Pavlenda, Pavel; Rautio, Pasi; Schaub, Marcus; Schröck, Hans-Werner; Seidling, Walter; Šrámek, Vít; Thimonier, Anne; Thomsen, Iben Margrete; Titeux, Hugues; Vanguelova, Elena; Verstraeten, Arne; Vesterdal, Lars; Waldner, Peter; Wijk, Sture; Zhang, Yuxin; Žlindra, Daniel; Bidartondo, Martin I

2018-06-06

Explaining the large-scale diversity of soil organisms that drive biogeochemical processes-and their responses to environmental change-is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is-to our knowledge-unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.

Large-scale structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Park, Changbom; Spergel, David N.; Turok, Nail

1991-01-01

This paper studies the formation of large-scale structure by global texture in a flat universe dominated by cold dark matter. A code for evolution of the texture fields was combined with an N-body code for evolving the dark matter. The results indicate some promising aspects: with only one free parameter, the observed galaxy-galaxy correlation function is reproduced, clusters of galaxies are found to be significantly clustered on a scale of 20-50/h Mpc, and coherent structures of over 50/h Mpc in the galaxy distribution were found. The large-scale streaming motions observed are in good agreement with the observations: the average magnitude of the velocity field smoothed over 30/h Mpc is 430 km/sec. Global texture produces a cosmic Mach number that is compatible with observation. Also, significant evolution of clusters at low redshift was seen. Possible problems for the theory include too high velocity dispersions in clusters, and voids which are not as empty as those observed.

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 assessing gradual and abrupt changes in ecosystem functioning in Europe. Based on segmented trend analysis of water-use efficiency (WUE) time series, an Ecosystem Change Type (ECT) map was produced over Europe at 1km resolution for the period 1999 to 2013. An analysis of auxiliary data on land use/cover change, drought trends, and soil threats was performed over hotspot areas to better understand the observed changes in ecosystem functioning and their driving mechanisms. The ECT map was validated using the case study sites from the EU-funded RECARE project. Overall, the ECT map accurately highlighted areas characterized by a major change in pathways of ecosystem functioning as well as indicated the type and timing of changes. Allan, R. et al. (2007). Climate and land degradation. Verlag Berlin Heidelberg: Springer. de Jong, R et al. (2013). Remote Sensing, 5, 1117-1133 Horion, S. et al. (2016). Global Change Biology, 22, 2801-2817 Vogt, J. V et al. (2011). Land Degradation & Development, 22: 150-165.

Dispersion and Cluster Scales in the Ocean

NASA Astrophysics Data System (ADS)

Kirwan, A. D., Jr.; Chang, H.; Huntley, H.; Carlson, D. F.; Mensa, J. A.; Poje, A. C.; Fox-Kemper, B.

2017-12-01

Ocean flow space scales range from centimeters to thousands of kilometers. Because of their large Reynolds number these flows are considered turbulent. However, because of rotation and stratification constraints they do not conform to classical turbulence scaling theory. Mesoscale and large-scale motions are well described by geostrophic or "2D turbulence" theory, however extending this theory to submesoscales has proved to be problematic. One obvious reason is the difficulty in obtaining reliable data over many orders of magnitude of spatial scales in an ocean environment. The goal of this presentation is to provide a preliminary synopsis of two recent experiments that overcame these obstacles. The first experiment, the Grand LAgrangian Deployment (GLAD) was conducted during July 2012 in the eastern half of the Gulf of Mexico. Here approximately 300 GPS-tracked drifters were deployed with the primary goal to determine whether the relative dispersion of an initially densely clustered array was driven by processes acting at local pair separation scales or by straining imposed by mesoscale motions. The second experiment was a component of the LAgrangian Submesoscale Experiment (LASER) conducted during the winter of 2016. Here thousands of bamboo plates were tracked optically from an Aerostat. Together these two deployments provided an unprecedented data set on dispersion and clustering processes from 1 to 106 meter scales. Calculations of statistics such as two point separations, structure functions, and scale dependent relative diffusivities showed: inverse energy cascade as expected for scales above 10 km, a forward energy cascade at scales below 10 km with a possible energy input at Langmuir circulation scales. We also find evidence from structure function calculations for surface flow convergence at scales less than 10 km that account for material clustering at the ocean surface.

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.

Selectivity by host plants affects the distribution of arbuscular mycorrhizal fungi: evidence from ITS rDNA sequence metadata.

PubMed

Yang, Haishui; Zang, Yanyan; Yuan, Yongge; Tang, Jianjun; Chen, Xin

2012-04-12

Arbuscular mycorrhizal fungi (AMF) can form obligate symbioses with the vast majority of land plants, and AMF distribution patterns have received increasing attention from researchers. At the local scale, the distribution of AMF is well documented. Studies at large scales, however, are limited because intensive sampling is difficult. Here, we used ITS rDNA sequence metadata obtained from public databases to study the distribution of AMF at continental and global scales. We also used these sequence metadata to investigate whether host plant is the main factor that affects the distribution of AMF at large scales. We defined 305 ITS virtual taxa (ITS-VTs) among all sequences of the Glomeromycota by using a comprehensive maximum likelihood phylogenetic analysis. Each host taxonomic order averaged about 53% specific ITS-VTs, and approximately 60% of the ITS-VTs were host specific. Those ITS-VTs with wide host range showed wide geographic distribution. Most ITS-VTs occurred in only one type of host functional group. The distributions of most ITS-VTs were limited across ecosystem, across continent, across biogeographical realm, and across climatic zone. Non-metric multidimensional scaling analysis (NMDS) showed that AMF community composition differed among functional groups of hosts, and among ecosystem, continent, biogeographical realm, and climatic zone. The Mantel test showed that AMF community composition was significantly correlated with plant community composition among ecosystem, among continent, among biogeographical realm, and among climatic zone. The structural equation modeling (SEM) showed that the effects of ecosystem, continent, biogeographical realm, and climatic zone were mainly indirect on AMF distribution, but plant had strongly direct effects on AMF. The distribution of AMF as indicated by ITS rDNA sequences showed a pattern of high endemism at large scales. This pattern indicates high specificity of AMF for host at different scales (plant taxonomic order and functional group) and high selectivity from host plants for AMF. The effects of ecosystemic, biogeographical, continental and climatic factors on AMF distribution might be mediated by host plants.

Musical expertise is related to altered functional connectivity during audiovisual integration

PubMed Central

Paraskevopoulos, Evangelos; Kraneburg, Anja; Herholz, Sibylle Cornelia; Bamidis, Panagiotis D.; Pantev, Christo

2015-01-01

The present study investigated the cortical large-scale functional network underpinning audiovisual integration via magnetoencephalographic recordings. The reorganization of this network related to long-term musical training was investigated by comparing musicians to nonmusicians. Connectivity was calculated on the basis of the estimated mutual information of the sources’ activity, and the corresponding networks were statistically compared. Nonmusicians’ results indicated that the cortical network associated with audiovisual integration supports visuospatial processing and attentional shifting, whereas a sparser network, related to spatial awareness supports the identification of audiovisual incongruences. In contrast, musicians’ results showed enhanced connectivity in regions related to the identification of auditory pattern violations. Hence, nonmusicians rely on the processing of visual clues for the integration of audiovisual information, whereas musicians rely mostly on the corresponding auditory information. The large-scale cortical network underpinning multisensory integration is reorganized due to expertise in a cognitive domain that largely involves audiovisual integration, indicating long-term training-related neuroplasticity. PMID:26371305

Topology of Large-Scale Structure by Galaxy Type: Hydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Gott, J. Richard, III; Cen, Renyue; Ostriker, Jeremiah P.

1996-07-01

The topology of large-scale structure is studied as a function of galaxy type using the genus statistic. In hydrodynamical cosmological cold dark matter simulations, galaxies form on caustic surfaces (Zeldovich pancakes) and then slowly drain onto filaments and clusters. The earliest forming galaxies in the simulations (defined as "ellipticals") are thus seen at the present epoch preferentially in clusters (tending toward a meatball topology), while the latest forming galaxies (defined as "spirals") are seen currently in a spongelike topology. The topology is measured by the genus (number of "doughnut" holes minus number of isolated regions) of the smoothed density-contour surfaces. The measured genus curve for all galaxies as a function of density obeys approximately the theoretical curve expected for random- phase initial conditions, but the early-forming elliptical galaxies show a shift toward a meatball topology relative to the late-forming spirals. Simulations using standard biasing schemes fail to show such an effect. Large observational samples separated by galaxy type could be used to test for this effect.

The seesaw space, a vector space to identify and characterize large-scale structures at 1 AU

NASA Astrophysics Data System (ADS)

Lara, A.; Niembro, T.

2017-12-01

We introduce the seesaw space, an orthonormal space formed by the local and the global fluctuations of any of the four basic solar parameters: velocity, density, magnetic field and temperature at any heliospheric distance. The fluctuations compare the standard deviation of a moving average of three hours against the running average of the parameter in a month (consider as the local fluctuations) and in a year (global fluctuations) We created this new vectorial spaces to identify the arrival of transients to any spacecraft without the need of an observer. We applied our method to the one-minute resolution data of WIND spacecraft from 1996 to 2016. To study the behavior of the seesaw norms in terms of the solar cycle, we computed annual histograms and fixed piecewise functions formed by two log-normal distributions and observed that one of the distributions is due to large-scale structures while the other to the ambient solar wind. The norm values in which the piecewise functions change vary in terms of the solar cycle. We compared the seesaw norms of each of the basic parameters due to the arrival of coronal mass ejections, co-rotating interaction regions and sector boundaries reported in literature. High seesaw norms are due to large-scale structures. We found three critical values of the norms that can be used to determined the arrival of coronal mass ejections. We present as well general comparisons of the norms during the two maxima and the minimum solar cycle periods and the differences of the norms due to large-scale structures depending on each period.

Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

PubMed

Goya-Maldonado, Roberto; Brodmann, Katja; Keil, Maria; Trost, Sarah; Dechent, Peter; Gruber, Oliver

2016-02-01

Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

DOE PAGES

Banerjee, Amartya S.; Lin, Lin; Hu, Wei; ...

2016-10-21

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) canmore » be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.« less

Topology Trivialization and Large Deviations for the Minimum in the Simplest Random Optimization

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.; Le Doussal, Pierre

2014-01-01

Finding the global minimum of a cost function given by the sum of a quadratic and a linear form in N real variables over (N-1)-dimensional sphere is one of the simplest, yet paradigmatic problems in Optimization Theory known as the "trust region subproblem" or "constraint least square problem". When both terms in the cost function are random this amounts to studying the ground state energy of the simplest spherical spin glass in a random magnetic field. We first identify and study two distinct large-N scaling regimes in which the linear term (magnetic field) leads to a gradual topology trivialization, i.e. reduction in the total number {N}_{tot} of critical (stationary) points in the cost function landscape. In the first regime {N}_{tot} remains of the order N and the cost function (energy) has generically two almost degenerate minima with the Tracy-Widom (TW) statistics. In the second regime the number of critical points is of the order of unity with a finite probability for a single minimum. In that case the mean total number of extrema (minima and maxima) of the cost function is given by the Laplace transform of the TW density, and the distribution of the global minimum energy is expected to take a universal scaling form generalizing the TW law. Though the full form of that distribution is not yet known to us, one of its far tails can be inferred from the large deviation theory for the global minimum. In the rest of the paper we show how to use the replica method to obtain the probability density of the minimum energy in the large-deviation approximation by finding both the rate function and the leading pre-exponential factor.

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

PubMed

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Non-Gaussian shape discrimination with spectroscopic galaxy surveys

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

Byun, Joyce; Bean, Rachel, E-mail: byun@astro.cornell.edu, E-mail: rbean@astro.cornell.edu

2015-03-01

We consider how galaxy clustering data, from Mpc to Gpc scales, from upcoming large scale structure surveys, such as Euclid and DESI, can provide discriminating information about the bispectrum shape arising from a variety of inflationary scenarios. Through exploring in detail the weighting of shape properties in the calculation of the halo bias and halo mass function we show how they probe a broad range of configurations, beyond those in the squeezed limit, that can help distinguish between shapes with similar large scale bias behaviors. We assess the impact, on constraints for a diverse set of non-Gaussian shapes, of galaxymore » clustering information in the mildly non-linear regime, and surveys that span multiple redshifts and employ different galactic tracers of the dark matter distribution. Fisher forecasts are presented for a Euclid-like spectroscopic survey of Hα-selected emission line galaxies (ELGs), and a DESI-like survey, of luminous red galaxies (LRGs) and [O-II] doublet-selected ELGs, in combination with Planck-like CMB temperature and polarization data.While ELG samples provide better probes of shapes that are divergent in the squeezed limit, LRG constraints, centered below z<1, yield stronger constraints on shapes with scale-independent large-scale halo biases, such as the equilateral template. The ELG and LRG samples provide complementary degeneracy directions for distinguishing between different shapes. For Hα-selected galaxies, we note that recent revisions of the expected Hα luminosity function reduce the halo bias constraints on the local shape, relative to the CMB. For galaxy clustering constraints to be comparable to those from the CMB, additional information about the Gaussian galaxy bias is needed, such as can be determined from the galaxy clustering bispectrum or probing the halo power spectrum directly through weak lensing. If the Gaussian galaxy bias is constrained to better than a percent level then the LSS and CMB data could provide complementary constraints that will enable differentiation of bispectrum with distinct theoretical origins but with similar large scale, squeezed-limit properties.« less

Affordable and accurate large-scale hybrid-functional calculations on GPU-accelerated supercomputers

NASA Astrophysics Data System (ADS)

Ratcliff, Laura E.; Degomme, A.; Flores-Livas, José A.; Goedecker, Stefan; Genovese, Luigi

2018-03-01

Performing high accuracy hybrid functional calculations for condensed matter systems containing a large number of atoms is at present computationally very demanding or even out of reach if high quality basis sets are used. We present a highly optimized multiple graphics processing unit implementation of the exact exchange operator which allows one to perform fast hybrid functional density-functional theory (DFT) calculations with systematic basis sets without additional approximations for up to a thousand atoms. With this method hybrid DFT calculations of high quality become accessible on state-of-the-art supercomputers within a time-to-solution that is of the same order of magnitude as traditional semilocal-GGA functionals. The method is implemented in a portable open-source library.

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network1[OPEN

PubMed Central

Kim, Taehyong; Dreher, Kate; Nilo-Poyanco, Ricardo; Lee, Insuk; Fiehn, Oliver; Lange, Bernd Markus; Nikolau, Basil J.; Sumner, Lloyd; Welti, Ruth; Wurtele, Eve S.; Rhee, Seung Y.

2015-01-01

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes. PMID:25670818

Local Fitting of the Kohn-Sham Density in a Gaussian and Plane Waves Scheme for Large-Scale Density Functional Theory Simulations.

PubMed

Golze, Dorothea; Iannuzzi, Marcella; Hutter, Jürg

2017-05-09

A local resolution-of-the-identity (LRI) approach is introduced in combination with the Gaussian and plane waves (GPW) scheme to enable large-scale Kohn-Sham density functional theory calculations. In GPW, the computational bottleneck is typically the description of the total charge density on real-space grids. Introducing the LRI approximation, the linear scaling of the GPW approach with respect to system size is retained, while the prefactor for the grid operations is reduced. The density fitting is an O(N) scaling process implemented by approximating the atomic pair densities by an expansion in one-center fit functions. The computational cost for the grid-based operations becomes negligible in LRIGPW. The self-consistent field iteration is up to 30 times faster for periodic systems dependent on the symmetry of the simulation cell and on the density of grid points. However, due to the overhead introduced by the local density fitting, single point calculations and complete molecular dynamics steps, including the calculation of the forces, are effectively accelerated by up to a factor of ∼10. The accuracy of LRIGPW is assessed for different systems and properties, showing that total energies, reaction energies, intramolecular and intermolecular structure parameters are well reproduced. LRIGPW yields also high quality results for extended condensed phase systems such as liquid water, ice XV, and molecular crystals.

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

USDA-ARS?s Scientific Manuscript database

Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

COMPARABLE MEASURES OF COGNITIVE FUNCTION IN HUMAN INFANTS AND LABORATORY ANIMALS TO IDENTIFY ENVIRONMENTAL HEALTH RISKS TO CHILDREN

EPA Science Inventory

The importance of including neurodevelopmental end points in environmental studies is clear. A validated measure of cognitive function in human infants that also has a homologous or parallel test in laboratory animal studies will provide a valuable approach for large-scale studie...

Family and Human Development across Cultures: A View from the Other Side.

ERIC Educational Resources Information Center

Kagitcibasi, Cigdem

Using a contextual-developmental-functional approach, this book seeks to discover the functional links between family dynamics and socialization within varying sociocultural contexts to human development, and to integrate theory and application in large-scale interventions promoting human well-being and societal development in the Majority World.…

Analyzing Distributed Functions in an Integrated Hazard Analysis

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Massie, Michael J.

2010-01-01

Large scale integration of today's aerospace systems is achievable through the use of distributed systems. Validating the safety of distributed systems is significantly more difficult as compared to centralized systems because of the complexity of the interactions between simultaneously active components. Integrated hazard analysis (IHA), a process used to identify unacceptable risks and to provide a means of controlling them, can be applied to either centralized or distributed systems. IHA, though, must be tailored to fit the particular system being analyzed. Distributed systems, for instance, must be analyzed for hazards in terms of the functions that rely on them. This paper will describe systems-oriented IHA techniques (as opposed to traditional failure-event or reliability techniques) that should be employed for distributed systems in aerospace environments. Special considerations will be addressed when dealing with specific distributed systems such as active thermal control, electrical power, command and data handling, and software systems (including the interaction with fault management systems). Because of the significance of second-order effects in large scale distributed systems, the paper will also describe how to analyze secondary functions to secondary functions through the use of channelization.

Intrapixel measurement techniques on large focal plane arrays for astronomical applications: a comparative study

NASA Astrophysics Data System (ADS)

Ketchazo, C.; Viale, T.; Boulade, O.; de la Barrière, F.; Dubreuil, D.; Mugnier, L.; Moreau, V.; Guérineau, N.; Mulet, P.; Druart, G.; Delisle, C.

2017-09-01

The intrapixel response is the signal detected by a single pixel illuminated by a Dirac distribution as a function of the position of this Dirac inside this pixel. It is also known as the pixel response function (PRF). This function measures the sensitivity variation at the subpixel scale and gives a spatial map of the sensitivity across a pixel.

A Practical Computational Method for the Anisotropic Redshift-Space 3-Point Correlation Function

NASA Astrophysics Data System (ADS)

Slepian, Zachary; Eisenstein, Daniel J.

2018-04-01

We present an algorithm enabling computation of the anisotropic redshift-space galaxy 3-point correlation function (3PCF) scaling as N2, with N the number of galaxies. Our previous work showed how to compute the isotropic 3PCF with this scaling by expanding the radially-binned density field around each galaxy in the survey into spherical harmonics and combining these coefficients to form multipole moments. The N2 scaling occurred because this approach never explicitly required the relative angle between a galaxy pair about the primary galaxy. Here we generalize this work, demonstrating that in the presence of azimuthally-symmetric anisotropy produced by redshift-space distortions (RSD) the 3PCF can be described by two triangle side lengths, two independent total angular momenta, and a spin. This basis for the anisotropic 3PCF allows its computation with negligible additional work over the isotropic 3PCF. We also present the covariance matrix of the anisotropic 3PCF measured in this basis. Our algorithm tracks the full 5-D redshift-space 3PCF, uses an accurate line of sight to each triplet, is exact in angle, and easily handles edge correction. It will enable use of the anisotropic large-scale 3PCF as a probe of RSD in current and upcoming large-scale redshift surveys.

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.

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 different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Detectability of large-scale power suppression in the galaxy distribution

NASA Astrophysics Data System (ADS)

Gibelyou, Cameron; Huterer, Dragan; Fang, Wenjuan

2010-12-01

Suppression in primordial power on the Universe’s largest observable scales has been invoked as a possible explanation for large-angle observations in the cosmic microwave background, and is allowed or predicted by some inflationary models. Here we investigate the extent to which such a suppression could be confirmed by the upcoming large-volume redshift surveys. For definiteness, we study a simple parametric model of suppression that improves the fit of the vanilla ΛCDM model to the angular correlation function measured by WMAP in cut-sky maps, and at the same time improves the fit to the angular power spectrum inferred from the maximum likelihood analysis presented by the WMAP team. We find that the missing power at large scales, favored by WMAP observations within the context of this model, will be difficult but not impossible to rule out with a galaxy redshift survey with large-volume (˜100Gpc3). A key requirement for success in ruling out power suppression will be having redshifts of most galaxies detected in the imaging survey.

Single-user MIMO system, Painlevé transcendents, and double scaling

NASA Astrophysics Data System (ADS)

Chen, Hongmei; Chen, Min; Blower, Gordon; Chen, Yang

2017-12-01

In this paper, we study a particular Painlevé V (denoted PV) that arises from multi-input-multi-output wireless communication systems. Such PV appears through its intimate relation with the Hankel determinant that describes the moment generating function (MGF) of the Shannon capacity. This originates through the multiplication of the Laguerre weight or the gamma density xαe-x, x > 0, for α > -1 by (1 + x/t)λ with t > 0 a scaling parameter. Here the λ parameter "generates" the Shannon capacity; see Chen, Y. and McKay, M. R. [IEEE Trans. Inf. Theory 58, 4594-4634 (2012)]. It was found that the MGF has an integral representation as a functional of y(t) and y'(t), where y(t) satisfies the "classical form" of PV. In this paper, we consider the situation where n, the number of transmit antennas, (or the size of the random matrix), tends to infinity and the signal-to-noise ratio, P, tends to infinity such that s = 4n2/P is finite. Under such double scaling, the MGF, effectively an infinite determinant, has an integral representation in terms of a "lesser" PIII. We also consider the situations where α =k +1 /2 ,k ∈N , and α ∈ {0, 1, 2, …}, λ ∈ {1, 2, …}, linking the relevant quantity to a solution of the two-dimensional sine-Gordon equation in radial coordinates and a certain discrete Painlevé-II. From the large n asymptotic of the orthogonal polynomials, which appears naturally, we obtain the double scaled MGF for small and large s, together with the constant term in the large s expansion. With the aid of these, we derive a number of cumulants and find that the capacity distribution function is non-Gaussian.

Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits.

PubMed

Kefford, Ben J; Schäfer, Ralf B; Metzeling, Leon

2012-01-15

Ecological risk assessments mostly consider measures of community composition (structure) across large spatial scales. These assessments, using species sensitivity distributions (SSDs) or the relative species retention (RSR), may not be protective of ecosystem functions and services at smaller spatial scales. Here we examine how changes in biological traits, as proxy for ecosystem functions/services, at a fine spatial scale relate to larger scale assessment of structure. We use functional traits of stream insect species in south-east Australia in two habitats (riffle and edge/pool). We find that the protection of community structure in terms of 95% of species over multiple sites against adverse effects of salinity (as electrical conductivity) and turbidity will mostly, but not always, protect traits at smaller scales. Considering different combinations of trait modalities, contaminants and habitat, a mean of 17.5% (range 0%-36.8) of cases would result in under-protection of trait modalities despite protecting species composition (in terms of Jaccard's Index). This under-protection of trait modalities is only because of the different spatial scales that community structure and the traits were considered. We recommend that where the protection of biological traits, ecosystem functions or ecosystem services from stressors is a management goal, protective targets should not be solely set using measures of community structure such as SSDs or RSR. To protect both structural and functional attributes separate risk assessments should be done. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Consciousness, cognition and brain networks: New perspectives.

PubMed

Aldana, E M; Valverde, J L; Fábregas, N

2016-10-01

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

A Study of Transport in the Near-Earth Plasma Sheet During A Substorm Using Time-Dependent Large Scale Kinetics

NASA Technical Reports Server (NTRS)

El-Alaoui, M.; Ashour-Abdalla, M.; Raeder, J.; Frank, L. A.; Paterson, W. R.

1998-01-01

In this study we investigate the transport of H+ ions that made up the complex ion distribution function observed by the Geotail spacecraft at 0740 UT on November 24, 1996. This ion distribution function, observed by Geotail at approximately 20 R(sub E) downtail, was used to initialize a time-dependent large-scale kinetic (LSK) calculation of the trajectories of 75,000 ions forward in time. Time-dependent magnetic and electric fields were obtained from a global magnetohydrodynamic (MHD) simulation of the magnetosphere and its interaction with the solar wind and the interplanetary magnetic field (IMF) as observed during the interval of the observation of the distribution function. Our calculations indicate that the particles observed by Geotail were scattered across the equatorial plane by the multiple interactions with the current sheet and then convected sunward. They were energized by the dawn-dusk electric field during their transport from Geotail location and ultimately were lost at the ionospheric boundary or into the magnetopause.

Propagation of electromagnetic waves in a turbulent medium

NASA Technical Reports Server (NTRS)

Canuto, V. M.; Hartke, G. J.

1986-01-01

Theoretical modeling of the wealth of experimental data on propagation of electromagnetic radiation through turbulent media has centered on the use of the Heisenberg-Kolmogorov (HK) model, which is, however, valid only for medium to small sized eddies. Ad hoc modifications of the HK model to encompass the large-scale region of the eddy spectrum have been widely used, but a sound physical basis has been lacking. A model for large-scale turbulence that was recently proposed is applied to the above problem. The spectral density of the temperature field is derived and used to calculate the structure function of the index of refraction N. The result is compared with available data, yielding a reasonably good fit. The variance of N is also in accord with the data. The model is also applied to propagation effects. The phase structure function, covariance of the log amplitude, and variance of the log intensity are calculated. The calculated phase structure function is in excellent agreement with available data.

Gram-scale synthesis of single-crystalline graphene quantum dots with superior optical properties.

PubMed

Wang, Liang; Wang, Yanli; Xu, Tao; Liao, Haobo; Yao, Chenjie; Liu, Yuan; Li, Zhen; Chen, Zhiwen; Pan, Dengyu; Sun, Litao; Wu, Minghong

2014-10-28

Graphene quantum dots (GQDs) have various alluring properties and potential applications, but their large-scale applications are limited by current synthetic methods that commonly produce GQDs in small amounts. Moreover, GQDs usually exhibit polycrystalline or highly defective structures and thus poor optical properties. Here we report the gram-scale synthesis of single-crystalline GQDs by a facile molecular fusion route under mild and green hydrothermal conditions. The synthesis involves the nitration of pyrene followed by hydrothermal treatment in alkaline aqueous solutions, where alkaline species play a crucial role in tuning their size, functionalization and optical properties. The single-crystalline GQDs are bestowed with excellent optical properties such as bright excitonic fluorescence, strong excitonic absorption bands extending to the visible region, large molar extinction coefficients and long-term photostability. These high-quality GQDs can find a large array of novel applications in bioimaging, biosensing, light emitting diodes, solar cells, hydrogen production, fuel cells and supercapacitors.

A unifying framework for systems modeling, control systems design, and system operation

NASA Technical Reports Server (NTRS)

Dvorak, Daniel L.; Indictor, Mark B.; Ingham, Michel D.; Rasmussen, Robert D.; Stringfellow, Margaret V.

2005-01-01

Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition- whether functional or physical or discipline-based-that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework based on a state-, model-, and goal-based architecture for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASA's proposed Array-based Deep Space Network.

Constraints on the Origin of Cosmic Rays above 1018 eV from Large-scale Anisotropy Searches in Data of the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Pierre Auger Collaboration; Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antiči'c, T.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Caballero-Mora, K. S.; Caccianiga, B.; Caramete, L.; Caruso, R.; Castellina, A.; Catalano, O.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos Diaz, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; De Donato, C.; de Jong, S. J.; De La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; del Río, M.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gouffon, P.; Grashorn, E.; Grebe, S.; Griffith, N.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; LaHurd, D.; Latronico, L.; Lauer, R.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Messina, S.; Meurer, C.; Meyhandan, R.; Mi'canovi'c, S.; Micheletti, M. I.; Minaya, I. A.; Miramonti, L.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Cabo, I.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Silva Lopez, H. H.; Sima, O.; 'Smiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

2013-01-01

A thorough search for large-scale anisotropies in the distribution of arrival directions of cosmic rays detected above 1018 eV at the Pierre Auger Observatory is reported. For the first time, these large-scale anisotropy searches are performed as a function of both the right ascension and the declination and expressed in terms of dipole and quadrupole moments. Within the systematic uncertainties, no significant deviation from isotropy is revealed. Upper limits on dipole and quadrupole amplitudes are derived under the hypothesis that any cosmic ray anisotropy is dominated by such moments in this energy range. These upper limits provide constraints on the production of cosmic rays above 1018 eV, since they allow us to challenge an origin from stationary galactic sources densely distributed in the galactic disk and emitting predominantly light particles in all directions.

Auroral zone electric fields from DE 1 and 2 at magnetic conjunctions

NASA Technical Reports Server (NTRS)

Weimer, D. R.; Goertz, C. K.; Gurnett, D. A.; Maynard, N. C.; Burch, J. L.

1985-01-01

Nearly simultaneous measurements of auroral zone electric fields are obtained by the Dynamics Explorer spacecraft at altitudes below 900 km and above 4,500 km during magnetic conjunctions. The measured electric fields are usually perpendicular to the magnetic field lines. The north-south meridional electric fields are projected to a common altitude by a mapping function which accounts for the convergence of the magnetic field lines. When plotted as a function of invariant latitude, graphs of the projected electric fields measured by both DE-1 and DE-2 show that the large-scale electric field is the same at both altitudes, as expected. Superimposed on the large-scale fields, however, are small-scale features with wavelengths less than 100 km which are larger in magnitude at the higher altitude. Fourier transforms of the electric fields show that the magnitudes depend on wavelength. Outside of the auroral zone the electric field spectrums are nearly identical. But within the auroral zone the high and low altitude electric fields have a ratio which increases with the reciprocal of the wavelength. The small-scale electric field variations are associated with field-aligned currents. These currents are measured with both a plasma instrument and magnetometer on DE-1.

To the horizon and beyond: Weak lensing of the CMB and binary inspirals into horizonless objects

NASA Astrophysics Data System (ADS)

Kesden, Michael

This thesis examines two predictions of general relativity: weak lensing and gravitational waves. The cosmic microwave background (CMB) is gravitationally lensed by the large-scale structure between the observer and the last- scattering surface. This weak lensing induces non-Gaussian correlations that can be used to construct estimators for the deflection field. The error and bias of these estimators are derived and used to analyze the viability of lensing reconstruction for future CMB experiments. Weak lensing also affects the one-point probability distribution function of the CMB. The skewness and kurtosis induced by lensing and the Sunayev- Zel'dovich (SZ) effect are calculated as functions of the angular smoothing scale of the map. While these functions offer the advantage of easy computability, only the skewness from lensing-SZ correlations can potentially be detected, even in the limit of the largest amplitude fluctuations allowed by observation. Lensing estimators are also essential to constrain inflation, the favored explanation for large-scale isotropy and the origin of primordial perturbations. B-mode polarization is considered to be a "smoking-gun" signature of inflation, and lensing estimators can be used to recover primordial B-modes from lensing-induced contamination. The ability of future CMB experiments to constrain inflation is assessed as functions of survey size and instrumental sensitivity. A final application of lensing estimators is to constrain a possible cutoff in primordial density perturbations on near-horizon scales. The paucity of independent modes on such scales limits the statistical certainty of such a constraint. Measurements of the deflection field can be used to constrain at the 3s level the existence of a cutoff large enough to account for current CMB observations. A final chapter of this thesis considers an independent topic: the gravitational-wave (GW) signature of a binary inspiral into a horizonless object. If the supermassive objects at galactic centers lack the horizons of traditional black holes, inspiraling objects could emit GWs after passing within their surfaces. The GWs produced by such an inspiral are calculated, revealing distinctive features potentially observable by future GW observatories.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

Plasmonic resonances of nanoparticles from large-scale quantum mechanical simulations

NASA Astrophysics Data System (ADS)

Zhang, Xu; Xiang, Hongping; Zhang, Mingliang; Lu, Gang

2017-09-01

Plasmonic resonance of metallic nanoparticles results from coherent motion of its conduction electrons, driven by incident light. For the nanoparticles less than 10 nm in diameter, localized surface plasmonic resonances become sensitive to the quantum nature of the conduction electrons. Unfortunately, quantum mechanical simulations based on time-dependent Kohn-Sham density functional theory are computationally too expensive to tackle metal particles larger than 2 nm. Herein, we introduce the recently developed time-dependent orbital-free density functional theory (TD-OFDFT) approach which enables large-scale quantum mechanical simulations of plasmonic responses of metallic nanostructures. Using TD-OFDFT, we have performed quantum mechanical simulations to understand size-dependent plasmonic response of Na nanoparticles and plasmonic responses in Na nanoparticle dimers and trimers. An outlook of future development of the TD-OFDFT method is also presented.

A Magnetic Bead-Integrated Chip for the Large Scale Manufacture of Normalized esiRNAs

PubMed Central

Wang, Zhao; Huang, Huang; Zhang, Hanshuo; Sun, Changhong; Hao, Yang; Yang, Junyu; Fan, Yu; Xi, Jianzhong Jeff

2012-01-01

The chemically-synthesized siRNA duplex has become a powerful and widely used tool for RNAi loss-of-function studies, but suffers from a high off-target effect problem. Recently, endoribonulease-prepared siRNA (esiRNA) has been shown to be an attractive alternative due to its lower off-target effect and cost effectiveness. However, the current manufacturing method for esiRNA is complicated, mainly in regards to purification and normalization on a large-scale level. In this study, we present a magnetic bead-integrated chip that can immobilize amplification or transcription products on beads and accomplish transcription, digestion, normalization and purification in a robust and convenient manner. This chip is equipped to manufacture ready-to-use esiRNAs on a large-scale level. Silencing specificity and efficiency of these esiRNAs were validated at the transcriptional, translational and functional levels. Manufacture of several normalized esiRNAs in a single well, including those silencing PARP1 and BRCA1, was successfully achieved, and the esiRNAs were subsequently utilized to effectively investigate their synergistic effect on cell viability. A small esiRNA library targeting 68 tyrosine kinase genes was constructed for a loss-of-function study, and four genes were identified in regulating the migration capability of Hela cells. We believe that this approach provides a more robust and cost-effective choice for manufacturing esiRNAs than current approaches, and therefore these heterogeneous RNA strands may have utility in most intensive and extensive applications. PMID:22761791

An Overview of Nitrogen Cycling in a Semiarid Savanna: Some Implications for Management and Conservation in a Large African Park

NASA Astrophysics Data System (ADS)

Coetsee, Corli; Jacobs, Shayne; Govender, Navashni

2012-02-01

Nitrogen (N) is a major control on primary productivity and hence on the productivity and diversity of secondary producers and consumers. As such, ecosystem structure and function cannot be understood without a comprehensive understanding of N cycling and dynamics. This overview describes the factors that govern N distribution and dynamics and the consequences that variable N dynamics have for structure, function and thresholds of potential concern (TPCs) for management of a semiarid southern African savanna. We focus on the Kruger National Park (KNP), a relatively intact savanna, noted for its wide array of animal and plant species and a prized tourist destination. KNP's large size ensures integrity of most ecosystem processes and much can be learned about drivers of ecosystem structure and function using this park as a baseline. Our overview shows that large scale variability in substrates exists, but do not necessarily have predictable consequences for N cycling. The impact of major drivers such as fire is complex; at a landscape scale little differences in stocks and cycling were found, though at a smaller scale changes in woody cover can lead to concomitant changes in total N. Contrasting impacts of browsers and grazers on N turnover has been recorded. Due to the complexity of this ecosystem, we conclude that it will be complicated to draw up TPCs for most transformations and pools involved with the N cycle. However, we highlight in which cases the development of TPCs will be possible.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

PubMed

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

PubMed

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

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Leaf optical properties shed light on foliar trait variability at individual to global scales

NASA Astrophysics Data System (ADS)

Shiklomanov, A. N.; Serbin, S.; Dietze, M.

2016-12-01

Recent syntheses of large trait databases have contributed immensely to our understanding of drivers of plant function at the global scale. However, the global trade-offs revealed by such syntheses, such as the trade-off between leaf productivity and resilience (i.e. "leaf economics spectrum"), are often absent at smaller scales and fail to correlate with actual functional limitations. An improved understanding of how traits vary within communities, species, and individuals is critical to accurate representations of vegetation ecophysiology and ecological dynamics in ecosystem models. Spectral data from both field observations and remote sensing platforms present a potentially rich and widely available source of information on plant traits. In particular, the inversion of physically-based radiative transfer models (RTMs) is an effective and general method for estimating plant traits from spectral measurements. Here, we apply Bayesian inversion of the PROSPECT leaf RTM to a large database of field spectra and plant traits spanning tropical, temperate, and boreal forests, agricultural plots, arid shrublands, and tundra to identify dominant sources of variability and characterize trade-offs in plant functional traits. By leveraging such a large and diverse dataset, we re-calibrate the empirical absorption coefficients underlying the PROSPECT model and expand its scope to include additional leaf biochemical components, namely leaf nitrogen content. Our work provides a key methodological contribution as a physically-based retrieval of leaf nitrogen from remote sensing observations, and provides substantial insights about trait trade-offs related to plant acclimation, adaptation, and community assembly.

The influence of super-horizon scales on cosmological observables generated during inflation

NASA Astrophysics Data System (ADS)

Matarrese, Sabino; Musso, Marcello A.; Riotto, Antonio

2004-05-01

Using the techniques of out-of-equilibrium field theory, we study the influence on properties of cosmological perturbations generated during inflation on observable scales coming from fluctuations corresponding today to scales much bigger than the present Hubble radius. We write the effective action for the coarse grained inflaton perturbations, integrating out the sub-horizon modes, which manifest themselves as a coloured noise and lead to memory effects. Using the simple model of a scalar field with cubic self-interactions evolving in a fixed de Sitter background, we evaluate the two- and three-point correlation function on observable scales. Our basic procedure shows that perturbations do preserve some memory of the super-horizon scale dynamics, in the form of scale dependent imprints in the statistical moments. In particular, we find a blue tilt of the power spectrum on large scales, in agreement with the recent results of the WMAP collaboration which show a suppression of the lower multipoles in the cosmic microwave background anisotropies, and a substantial enhancement of the intrinsic non-Gaussianity on large scales.

Patterns and Variation in Benthic Biodiversity in a Large Marine Ecosystem.

PubMed

Piacenza, Susan E; Barner, Allison K; Benkwitt, Cassandra E; Boersma, Kate S; Cerny-Chipman, Elizabeth B; Ingeman, Kurt E; Kindinger, Tye L; Lee, Jonathan D; Lindsley, Amy J; Reimer, Jessica N; Rowe, Jennifer C; Shen, Chenchen; Thompson, Kevin A; Thurman, Lindsey L; Heppell, Selina S

2015-01-01

While there is a persistent inverse relationship between latitude and species diversity across many taxa and ecosystems, deviations from this norm offer an opportunity to understand the conditions that contribute to large-scale diversity patterns. Marine systems, in particular, provide such an opportunity, as marine diversity does not always follow a strict latitudinal gradient, perhaps because several hypothesized drivers of the latitudinal diversity gradient are uncorrelated in marine systems. We used a large scale public monitoring dataset collected over an eight year period to examine benthic marine faunal biodiversity patterns for the continental shelf (55-183 m depth) and slope habitats (184-1280 m depth) off the US West Coast (47°20'N-32°40'N). We specifically asked whether marine biodiversity followed a strict latitudinal gradient, and if these latitudinal patterns varied across depth, in different benthic substrates, and over ecological time scales. Further, we subdivided our study area into three smaller regions to test whether coast-wide patterns of biodiversity held at regional scales, where local oceanographic processes tend to influence community structure and function. Overall, we found complex patterns of biodiversity on both the coast-wide and regional scales that differed by taxonomic group. Importantly, marine biodiversity was not always highest at low latitudes. We found that latitude, depth, substrate, and year were all important descriptors of fish and invertebrate diversity. Invertebrate richness and taxonomic diversity were highest at high latitudes and in deeper waters. Fish richness also increased with latitude, but exhibited a hump-shaped relationship with depth, increasing with depth up to the continental shelf break, ~200 m depth, and then decreasing in deeper waters. We found relationships between fish taxonomic and functional diversity and latitude, depth, substrate, and time at the regional scale, but not at the coast-wide scale, suggesting that coast-wide patterns can obscure important correlates at smaller scales. Our study provides insight into complex diversity patterns of the deep water soft substrate benthic ecosystems off the US West Coast.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms

PubMed Central

Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as “avolition and anhedonia,” specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes. PMID:29410933

Large scale in vivo recordings to study neuronal biophysics.

PubMed

Giocomo, Lisa M

2015-06-01

Over the last several years, technological advances have enabled researchers to more readily observe single-cell membrane biophysics in awake, behaving animals. Studies utilizing these technologies have provided important insights into the mechanisms generating functional neural codes in both sensory and non-sensory cortical circuits. Crucial for a deeper understanding of how membrane biophysics control circuit dynamics however, is a continued effort to move toward large scale studies of membrane biophysics, in terms of the numbers of neurons and ion channels examined. Future work faces a number of theoretical and technical challenges on this front but recent technological developments hold great promise for a larger scale understanding of how membrane biophysics contribute to circuit coding and computation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Scaling up digital circuit computation with DNA strand displacement cascades.

PubMed

Qian, Lulu; Winfree, Erik

2011-06-03

To construct sophisticated biochemical circuits from scratch, one needs to understand how simple the building blocks can be and how robustly such circuits can scale up. Using a simple DNA reaction mechanism based on a reversible strand displacement process, we experimentally demonstrated several digital logic circuits, culminating in a four-bit square-root circuit that comprises 130 DNA strands. These multilayer circuits include thresholding and catalysis within every logical operation to perform digital signal restoration, which enables fast and reliable function in large circuits with roughly constant switching time and linear signal propagation delays. The design naturally incorporates other crucial elements for large-scale circuitry, such as general debugging tools, parallel circuit preparation, and an abstraction hierarchy supported by an automated circuit compiler.

Linking Dense Gas from the Milky Way to External Galaxies

NASA Astrophysics Data System (ADS)

Stephens, Ian W.; Jackson, James M.; Whitaker, J. Scott; Contreras, Yanett; Guzmán, Andrés E.; Sanhueza, Patricio; Foster, Jonathan B.; Rathborne, Jill M.

2016-06-01

In a survey of 65 galaxies, Gao & Solomon found a tight linear relation between the infrared luminosity (L IR, a proxy for the star formation rate) and the HCN(1-0) luminosity ({L}{{HCN}}). Wu et al. found that this relation extends from these galaxies to the much less luminous Galactic molecular high-mass star-forming clumps (˜1 pc scales), and posited that there exists a characteristic ratio L IR/{L}{{HCN}} for high-mass star-forming clumps. The Gao-Solomon relation for galaxies could then be explained as a summation of large numbers of high-mass star-forming clumps, resulting in the same L IR/{L}{{HCN}} ratio for galaxies. We test this explanation and other possible origins of the Gao-Solomon relation using high-density tracers (including HCN(1-0), N2H+(1-0), HCO+(1-0), HNC(1-0), HC3N(10-9), and C2H(1-0)) for ˜300 Galactic clumps from the Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey. The MALT90 data show that the Gao-Solomon relation in galaxies cannot be satisfactorily explained by the blending of large numbers of high-mass clumps in the telescope beam. Not only do the clumps have a large scatter in the L IR/{L}{{HCN}} ratio, but also far too many high-mass clumps are required to account for the Galactic IR and HCN luminosities. We suggest that the scatter in the L IR/{L}{{HCN}} ratio converges to the scatter of the Gao-Solomon relation at some size-scale ≳1 kpc. We suggest that the Gao-Solomon relation could instead result from of a universal large-scale star formation efficiency, initial mass function, core mass function, and clump mass function.

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

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

Scherrer, Robert J.; Berlind, Andreas A.; Mao, Qingqing

2010-01-01

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

Combined heat and power supply using Carnot engines

NASA Astrophysics Data System (ADS)

Horlock, J. H.

The Marshall Report on the thermodynamic and economic feasibility of introducing large scale combined heat and electrical power generation (CHP) into the United Kingdom is summarized. Combinations of reversible power plant (Carnot engines) to meet a given demand of power and heat production are analyzed. The Marshall Report states that fairly large scale CHP plants are an attractive energy saving option for areas of high heat load densities. Analysis shows that for given requirements, the total heat supply and utilization factor are functions of heat output, reservoir supply temperature, temperature of heat rejected to the reservoir, and an intermediate temperature for district heating.

On the Large Scale Thermo-Hydrodynamical Processes in a Baroclinic Atmosphere -- USSR --

DTIC Science & Technology

1960-08-03

factors ’^ ’" / ■ J ’ It is immediately clear, that t’ha influence function A,/ ’/>// serves as z function of height and therefore characterizes...a study the climatic value of the west-east velocity ot üK at / / P latitude 30"% figure 1) „ In figure 2 the influence function /_ / i v...level in the atmosphere, will be characterised Just by the influence function /, (£,() . The form of the influence function /_$ shows, that the

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.

Edge reconstruction in armchair phosphorene nanoribbons revealed by discontinuous Galerkin density functional theory.

PubMed

Hu, Wei; Lin, Lin; Yang, Chao

2015-12-21

With the help of our recently developed massively parallel DGDFT (Discontinuous Galerkin Density Functional Theory) methodology, we perform large-scale Kohn-Sham density functional theory calculations on phosphorene nanoribbons with armchair edges (ACPNRs) containing a few thousands to ten thousand atoms. The use of DGDFT allows us to systematically achieve a conventional plane wave basis set type of accuracy, but with a much smaller number (about 15) of adaptive local basis (ALB) functions per atom for this system. The relatively small number of degrees of freedom required to represent the Kohn-Sham Hamiltonian, together with the use of the pole expansion the selected inversion (PEXSI) technique that circumvents the need to diagonalize the Hamiltonian, results in a highly efficient and scalable computational scheme for analyzing the electronic structures of ACPNRs as well as their dynamics. The total wall clock time for calculating the electronic structures of large-scale ACPNRs containing 1080-10,800 atoms is only 10-25 s per self-consistent field (SCF) iteration, with accuracy fully comparable to that obtained from conventional planewave DFT calculations. For the ACPNR system, we observe that the DGDFT methodology can scale to 5000-50,000 processors. We use DGDFT based ab initio molecular dynamics (AIMD) calculations to study the thermodynamic stability of ACPNRs. Our calculations reveal that a 2 × 1 edge reconstruction appears in ACPNRs at room temperature.

Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM.

PubMed

Tuncbag, Nurcan; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2011-08-11

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.

Large-scale correlations in gas traced by Mg II absorbers around low-mass galaxies

NASA Astrophysics Data System (ADS)

Kauffmann, Guinevere

2018-03-01

The physical origin of the large-scale conformity in the colours and specific star formation rates of isolated low-mass central galaxies and their neighbours on scales in excess of 1 Mpc is still under debate. One possible scenario is that gas is heated over large scales by feedback from active galactic nuclei (AGNs), leading to coherent modulation of cooling and star formation between well-separated galaxies. In this Letter, the metal line absorption catalogue of Zhu & Ménard is used to probe gas out to large projected radii around a sample of a million galaxies with stellar masses ˜1010M⊙ and photometric redshifts in the range 0.4 < z < 0.8 selected from Sloan Digital Sky Survey imaging data. This galaxy sample covers an effective volume of 2.2 Gpc3. A statistically significant excess of Mg II absorbers is present around the red-low-mass galaxies compared to their blue counterparts out to projected radii of 10 Mpc. In addition, the equivalent width distribution function of Mg II absorbers around low-mass galaxies is shown to be strongly affected by the presence of a nearby (Rp < 2 Mpc) radio-loud AGNs out to projected radii of 5 Mpc.

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

PubMed

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

2016-07-12

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

Large scale rigidity-based flexibility analysis of biomolecules

PubMed Central

Streinu, Ileana

2016-01-01

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

A fast time-difference inverse solver for 3D EIT with application to lung imaging.

PubMed

Javaherian, Ashkan; Soleimani, Manuchehr; Moeller, Knut

2016-08-01

A class of sparse optimization techniques that require solely matrix-vector products, rather than an explicit access to the forward matrix and its transpose, has been paid much attention in the recent decade for dealing with large-scale inverse problems. This study tailors application of the so-called Gradient Projection for Sparse Reconstruction (GPSR) to large-scale time-difference three-dimensional electrical impedance tomography (3D EIT). 3D EIT typically suffers from the need for a large number of voxels to cover the whole domain, so its application to real-time imaging, for example monitoring of lung function, remains scarce since the large number of degrees of freedom of the problem extremely increases storage space and reconstruction time. This study shows the great potential of the GPSR for large-size time-difference 3D EIT. Further studies are needed to improve its accuracy for imaging small-size anomalies.

LSD: Large Survey Database framework

NASA Astrophysics Data System (ADS)

Juric, Mario

2012-09-01

The Large Survey Database (LSD) is a Python framework and DBMS for distributed storage, cross-matching and querying of large survey catalogs (>10^9 rows, >1 TB). The primary driver behind its development is the analysis of Pan-STARRS PS1 data. It is specifically optimized for fast queries and parallel sweeps of positionally and temporally indexed datasets. It transparently scales to more than >10^2 nodes, and can be made to function in "shared nothing" architectures.

A spatially homogeneous and isotropic Einstein-Dirac cosmology

NASA Astrophysics Data System (ADS)

Finster, Felix; Hainzl, Christian

2011-04-01

We consider a spatially homogeneous and isotropic cosmological model where Dirac spinors are coupled to classical gravity. For the Dirac spinors we choose a Hartree-Fock ansatz where all one-particle wave functions are coherent and have the same momentum. If the scale function is large, the universe behaves like the classical Friedmann dust solution. If however the scale function is small, quantum effects lead to oscillations of the energy-momentum tensor. It is shown numerically and proven analytically that these quantum oscillations can prevent the formation of a big bang or big crunch singularity. The energy conditions are analyzed. We prove the existence of time-periodic solutions which go through an infinite number of expansion and contraction cycles.

Screening for depression in arthritis populations: an assessment of differential item functioning in three self-reported questionnaires.

PubMed

Hu, Jinxiang; Ward, Michael M

2017-09-01

To determine if persons with arthritis differ systematically from persons without arthritis in how they respond to questions on three depression questionnaires, which include somatic items such as fatigue and sleep disturbance. We extracted data on the Centers for Epidemiological Studies Depression (CES-D) scale, the Patient Health Questionnaire-9 (PHQ-9), and the Kessler-6 (K-6) scale from three large population-based national surveys. We assessed items on these questionnaires for differential item functioning (DIF) between persons with and without self-reported physician-diagnosed arthritis using multiple indicator multiple cause models, which controlled for the underlying level of depression and important confounders. We also examined if DIF by arthritis status was similar between women and men. Although five items of the CES-D, one item of the PHQ-9, and five items of the K-6 scale had evidence of DIF based on statistical comparisons, the magnitude of each difference was less than the threshold of a small effect. The statistical differences were a function of the very large sample sizes in the surveys. Effect sizes for DIF were similar between women and men except for two items on the Patient Health Questionnaire-9. For each questionnaire, DIF accounted for 8% or less of the arthritis-depression association, and excluding items with DIF did not reduce the difference in depression scores between those with and without arthritis. Persons with arthritis respond to items on the CES-D, PHQ-9, and K-6 depression scales similarly to persons without arthritis, despite the inclusion of somatic items in these scales.

Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures

PubMed Central

Lehnert, L. W.; Wesche, K.; Trachte, K.; Reudenbach, C.; Bendix, J.

2016-01-01

The Tibetan Plateau (TP) is a globally important “water tower” that provides water for nearly 40% of the world’s population. This supply function is claimed to be threatened by pasture degradation on the TP and the associated loss of water regulation functions. However, neither potential large scale degradation changes nor their drivers are known. Here, we analyse trends in a high-resolution dataset of grassland cover to determine the interactions among vegetation dynamics, climate change and human impacts on the TP. The results reveal that vegetation changes have regionally different triggers: While the vegetation cover has increased since the year 2000 in the north-eastern part of the TP due to an increase in precipitation, it has declined in the central and western parts of the TP due to rising air temperature and declining precipitation. Increasing livestock numbers as a result of land use changes exacerbated the negative trends but were not their exclusive driver. Thus, we conclude that climate variability instead of overgrazing has been the primary cause for large scale vegetation cover changes on the TP since the new millennium. Since areas of positive and negative changes are almost equal in extent, pasture degradation is not generally proceeding. PMID:27073126

Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures

NASA Astrophysics Data System (ADS)

Lehnert, L. W.; Wesche, K.; Trachte, K.; Reudenbach, C.; Bendix, J.

2016-04-01

The Tibetan Plateau (TP) is a globally important “water tower” that provides water for nearly 40% of the world’s population. This supply function is claimed to be threatened by pasture degradation on the TP and the associated loss of water regulation functions. However, neither potential large scale degradation changes nor their drivers are known. Here, we analyse trends in a high-resolution dataset of grassland cover to determine the interactions among vegetation dynamics, climate change and human impacts on the TP. The results reveal that vegetation changes have regionally different triggers: While the vegetation cover has increased since the year 2000 in the north-eastern part of the TP due to an increase in precipitation, it has declined in the central and western parts of the TP due to rising air temperature and declining precipitation. Increasing livestock numbers as a result of land use changes exacerbated the negative trends but were not their exclusive driver. Thus, we conclude that climate variability instead of overgrazing has been the primary cause for large scale vegetation cover changes on the TP since the new millennium. Since areas of positive and negative changes are almost equal in extent, pasture degradation is not generally proceeding.

One-step synthesis of large-scale graphene film doped with gold nanoparticles at liquid-air interface for electrochemistry and Raman detection applications.

PubMed

Zhang, Panpan; Huang, Ying; Lu, Xin; Zhang, Siyu; Li, Jingfeng; Wei, Gang; Su, Zhiqiang

2014-07-29

We demonstrated a facile one-step synthesis strategy for the preparation of a large-scale reduced graphene oxide multilayered film doped with gold nanoparticles (RGO/AuNP film) and applied this film as functional nanomaterials for electrochemistry and Raman detection applications. The related applications of the fabricated RGO/AuNP film in electrochemical nonenzymatic H2O2 biosensor, electrochemical oxygen reduction reaction (ORR), and surface-enhanced Raman scattering (SERS) detection were investigated. Electrochemical data indicate that the H2O2 biosensor fabricated by RGO/AuNP film shows a wide linear range, low limitation of detection, high selectivity, and long-term stability. In addition, it was proved that the created RGO/AuNP film also exhibits excellent ORR electrochemical catalysis performance. The created RGO/AuNP film, when serving as SERS biodetection platform, presents outstanding performances in detecting 4-aminothiophenol with an enhancement factor of approximately 5.6 × 10(5) as well as 2-thiouracil sensing with a low concentration to 1 μM. It is expected that this facile strategy for fabricating large-scale graphene film doped with metallic nanoparticles will spark inspirations in preparing functional nanomaterials and further extend their applications in drug delivery, wastewater purification, and bioenergy.

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

PubMed Central

Azad, Ariful; Ouzounis, Christos A; Kyrpides, Nikos C; Buluç, Aydin

2018-01-01

Abstract Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. Here, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ∼70 million nodes with ∼68 billion edges in ∼2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license. PMID:29315405

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

DOE PAGES

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.; ...

2018-01-05

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

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

Azad, Ariful; Pavlopoulos, Georgios A.; Ouzounis, Christos A.

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times andmore » memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.« less

Graphene/MoS2 hybrid technology for large-scale two-dimensional electronics.

PubMed

Yu, Lili; Lee, Yi-Hsien; Ling, Xi; Santos, Elton J G; Shin, Yong Cheol; Lin, Yuxuan; Dubey, Madan; Kaxiras, Efthimios; Kong, Jing; Wang, Han; Palacios, Tomás

2014-06-11

Two-dimensional (2D) materials have generated great interest in the past few years as a new toolbox for electronics. This family of materials includes, among others, metallic graphene, semiconducting transition metal dichalcogenides (such as MoS2), and insulating boron nitride. These materials and their heterostructures offer excellent mechanical flexibility, optical transparency, and favorable transport properties for realizing electronic, sensing, and optical systems on arbitrary surfaces. In this paper, we demonstrate a novel technology for constructing large-scale electronic systems based on graphene/molybdenum disulfide (MoS2) heterostructures grown by chemical vapor deposition. We have fabricated high-performance devices and circuits based on this heterostructure, where MoS2 is used as the transistor channel and graphene as contact electrodes and circuit interconnects. We provide a systematic comparison of the graphene/MoS2 heterojunction contact to more traditional MoS2-metal junctions, as well as a theoretical investigation, using density functional theory, of the origin of the Schottky barrier height. The tunability of the graphene work function with electrostatic doping significantly improves the ohmic contact to MoS2. These high-performance large-scale devices and circuits based on this 2D heterostructure pave the way for practical flexible transparent electronics.

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.

Large-Scale Computation of Nuclear Magnetic Resonance Shifts for Paramagnetic Solids Using CP2K.

PubMed

Mondal, Arobendo; Gaultois, Michael W; Pell, Andrew J; Iannuzzi, Marcella; Grey, Clare P; Hutter, Jürg; Kaupp, Martin

2018-01-09

Large-scale computations of nuclear magnetic resonance (NMR) shifts for extended paramagnetic solids (pNMR) are reported using the highly efficient Gaussian-augmented plane-wave implementation of the CP2K code. Combining hyperfine couplings obtained with hybrid functionals with g-tensors and orbital shieldings computed using gradient-corrected functionals, contact, pseudocontact, and orbital-shift contributions to pNMR shifts are accessible. Due to the efficient and highly parallel performance of CP2K, a wide variety of materials with large unit cells can be studied with extended Gaussian basis sets. Validation of various approaches for the different contributions to pNMR shifts is done first for molecules in a large supercell in comparison with typical quantum-chemical codes. This is then extended to a detailed study of g-tensors for extended solid transition-metal fluorides and for a series of complex lithium vanadium phosphates. Finally, lithium pNMR shifts are computed for Li 3 V 2 (PO 4 ) 3 , for which detailed experimental data are available. This has allowed an in-depth study of different approaches (e.g., full periodic versus incremental cluster computations of g-tensors and different functionals and basis sets for hyperfine computations) as well as a thorough analysis of the different contributions to the pNMR shifts. This study paves the way for a more-widespread computational treatment of NMR shifts for paramagnetic materials.

Highly efficient SERS substrate for direct detection of explosive TNT using popcorn-shaped gold nanoparticle-functionalized SWCNT hybrid.

PubMed

Demeritte, Teresa; Kanchanapally, Rajashekhar; Fan, Zhen; Singh, Anant Kumar; Senapati, Dulal; Dubey, Madan; Zakar, Eugene; Ray, Paresh Chandra

2012-11-07

This paper reports for the first time the development of a large-scale SERS substrate from a popcorn-shaped gold nanoparticle-functionalized single walled carbon nanotubes hybrid thin film for the selective and highly sensitive detection of explosive TNT material at a 100 femtomolar (fM) level.

Employment Activities and Experiences of Adults with High-Functioning Autism and Asperger's Disorder

ERIC Educational Resources Information Center

Baldwin, Susanna; Costley, Debra; Warren, Anthony

2014-01-01

There is limited large-scale empirical research into the working lives of adults who have an autism spectrum disorder with no co-occurring intellectual disability. Drawing on data from a national survey, this report describes the employment activities and experiences of 130 adults with Asperger's Disorder (AD) and high functioning autism (HFA) in…

The Observations of Redshift Evolution in Large Scale Environments (ORELSE) Survey

NASA Astrophysics Data System (ADS)

Squires, Gordon K.; Lubin, L. M.; Gal, R. R.

2007-05-01

We present the motivation, design, and latest results from the Observations of Redshift Evolution in Large Scale Environments (ORELSE) Survey, a systematic search for structure on scales greater than 10 Mpc around 20 known galaxy clusters at z > 0.6. When complete, the survey will cover nearly 5 square degrees, all targeted at high-density regions, making it complementary and comparable to field surveys such as DEEP2, GOODS, and COSMOS. For the survey, we are using the Large Format Camera on the Palomar 5-m and SuPRIME-Cam on the Subaru 8-m to obtain optical/near-infrared imaging of an approximately 30 arcmin region around previously studied high-redshift clusters. Colors are used to identify likely member galaxies which are targeted for follow-up spectroscopy with the DEep Imaging Multi-Object Spectrograph on the Keck 10-m. This technique has been used to identify successfully the Cl 1604 supercluster at z = 0.9, a large scale structure containing at least eight clusters (Gal & Lubin 2004; Gal, Lubin & Squires 2005). We present the most recent structures to be photometrically and spectroscopically confirmed through this program, discuss the properties of the member galaxies as a function of environment, and describe our planned multi-wavelength (radio, mid-IR, and X-ray) observations of these systems. The goal of this survey is to identify and examine a statistical sample of large scale structures during an active period in the assembly history of the most massive clusters. With such a sample, we can begin to constrain large scale cluster dynamics and determine the effect of the larger environment on galaxy evolution.

Regional modeling of groundwater flow and arsenic transport in the Bengal Basin: challenges of scale and complexity (Invited)

NASA Astrophysics Data System (ADS)

Michael, H. A.; Voss, C. I.

2009-12-01

Widespread arsenic poisoning is occurring in large areas of Bangladesh and West Bengal, India due to high arsenic levels in shallow groundwater, which is the primary source of irrigation and drinking water in the region. The high-arsenic groundwater exists in aquifers of the Bengal Basin, a huge sedimentary system approximately 500km x 500km wide and greater than 15km deep in places. Deeper groundwater (>150m) is nearly universally low in arsenic and a potential source of safe drinking water, but evaluation of its sustainability requires understanding of the entire, interconnected regional aquifer system. Numerical modeling of flow and arsenic transport in the basin introduces problems of scale: challenges in representing the system in enough detail to produce meaningful simulations and answer relevant questions while maintaining enough simplicity to understand controls on processes and operating within computational constraints. A regional groundwater flow and transport model of the Bengal Basin was constructed to assess the large-scale functioning of the deep groundwater flow system, the vulnerability of deep groundwater to pumping-induced migration from above, and the effect of chemical properties of sediments (sorption) on sustainability. The primary challenges include the very large spatial scale of the system, dynamic monsoonal hydrology (small temporal scale fluctuations), complex sedimentary architecture (small spatial scale heterogeneity), and a lack of reliable hydrologic and geologic data. The approach was simple. Detailed inputs were reduced to only those that affect the functioning of the deep flow system. Available data were used to estimate upscaled parameter values. Nested small-scale simulations were performed to determine the effects of the simplifications, which include treatment of the top boundary condition and transience, effects of small-scale heterogeneity, and effects of individual pumping wells. Simulation of arsenic transport at the large scale adds another element of complexity. Minimization of numerical oscillation and mass balance errors required experimentation with solvers and discretization. In the face of relatively few data in a very large-scale model, sensitivity analyses were essential. The scale of the system limits evaluation of localized behavior, but results clearly identified the primary controls on the system and effects of various pumping scenarios and sorptive properties. It was shown that limiting deep pumping to domestic supply may result in sustainable arsenic-safe water for 90% of the arsenic-affected region over a 1000 year timescale, and that sorption of arsenic onto deep, oxidized Pleistocene sediments may increase the breakthrough time in unsustainable zones by more than an order of magnitude. Thus, both hydraulic and chemical defenses indicate the potential for sustainable, managed use of deep, safe groundwater resources in the Bengal Basin.

Large Eddy Simulation of Gravitational Effects on Transitional and Turbulent Gas-Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Givi, Peyman; Jaberi, Farhad A.

2001-01-01

The basic objective of this work is to assess the influence of gravity on "the compositional and the spatial structures" of transitional and turbulent diffusion flames via large eddy simulation (LES), and direct numerical simulation (DNS). The DNS is conducted for appraisal of the various closures employed in LES, and to study the effect of buoyancy on the small scale flow features. The LES is based on our "filtered mass density function"' (FMDF) model. The novelty of the methodology is that it allows for reliable simulations with inclusion of "realistic physics." It also allows for detailed analysis of the unsteady large scale flow evolution and compositional flame structure which is not usually possible via Reynolds averaged simulations.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

Evolution of wealth in a non-conservative economy driven by local Nash equilibria.

PubMed

Degond, Pierre; Liu, Jian-Guo; Ringhofer, Christian

2014-11-13

We develop a model for the evolution of wealth in a non-conservative economic environment, extending a theory developed in Degond et al. (2014 J. Stat. Phys. 154, 751-780 (doi:10.1007/s10955-013-0888-4)). The model considers a system of rational agents interacting in a game-theoretical framework. This evolution drives the dynamics of the agents in both wealth and economic configuration variables. The cost function is chosen to represent a risk-averse strategy of each agent. That is, the agent is more likely to interact with the market, the more predictable the market, and therefore the smaller its individual risk. This yields a kinetic equation for an effective single particle agent density with a Nash equilibrium serving as the local thermodynamic equilibrium. We consider a regime of scale separation where the large-scale dynamics is given by a hydrodynamic closure with this local equilibrium. A class of generalized collision invariants is developed to overcome the difficulty of the non-conservative property in the hydrodynamic closure derivation of the large-scale dynamics for the evolution of wealth distribution. The result is a system of gas dynamics-type equations for the density and average wealth of the agents on large scales. We recover the inverse Gamma distribution, which has been previously considered in the literature, as a local equilibrium for particular choices of the cost function. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Planetesimal Formation through the Streaming Instability

NASA Astrophysics Data System (ADS)

Yang, Chao-Chin; Johansen, Anders; Schäfer, Urs

2015-12-01

The streaming instability is a promising mechanism to circumvent the barriers in direct dust growth and lead to the formation of planetesimals, as demonstrated by many previous studies. In order to resolve the thin layer of solids, however, most of these studies were focused on a local region of a protoplanetary disk with a limited simulation domain. It remains uncertain how the streaming instability is affected by the disk gas on large scales, and models that have sufficient dynamical range to capture both the thin particle layer and the large-scale disk dynamics are required.We hereby systematically push the limits of the computational domain up to more than the gas scale height, and study the particle-gas interaction on large scales in the saturated state of the streaming instability and the initial mass function of the resulting planetesimals. To overcome the numerical challenges posed by this kind of models, we have developed a new technique to simultaneously relieve the stringent time step constraints due to small-sized particles and strong local solid concentrations. Using these models, we demonstrate that the streaming instability can drive multiple radial, filamentary concentrations of solids, implying that planetesimals are born in well separated belt-like structures. We also find that the initial mass function of planetesimals via the streaming instability has a characteristic exponential form, which is robust against computational domain as well as resolution. These findings will help us further constrain the cosmochemical history of the Solar system as well as the planet formation theory in general.

Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo

2016-01-01

Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.

Revision of the Rawls et al. (1982) pedotransfer functions for their applicability to US croplands

USDA-ARS?s Scientific Manuscript database

Large scale environmental impact studies typically involve the use of simulation models and require a variety of inputs, some of which may need to be estimated in absence of adequate measured data. As an example, soil water retention needs to be estimated for a large number of soils that are to be u...

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

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

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

SQDFT: Spectral Quadrature method for large-scale parallel O ( N ) Kohn–Sham calculations at high temperature

DOE PAGES

Suryanarayana, Phanish; Pratapa, Phanisri P.; Sharma, Abhiraj; ...

2017-12-07

We present SQDFT: a large-scale parallel implementation of the Spectral Quadrature (SQ) method formore » $$\\mathscr{O}(N)$$ Kohn–Sham Density Functional Theory (DFT) calculations at high temperature. Specifically, we develop an efficient and scalable finite-difference implementation of the infinite-cell Clenshaw–Curtis SQ approach, in which results for the infinite crystal are obtained by expressing quantities of interest as bilinear forms or sums of bilinear forms, that are then approximated by spatially localized Clenshaw–Curtis quadrature rules. We demonstrate the accuracy of SQDFT by showing systematic convergence of energies and atomic forces with respect to SQ parameters to reference diagonalization results, and convergence with discretization to established planewave results, for both metallic and insulating systems. Here, we further demonstrate that SQDFT achieves excellent strong and weak parallel scaling on computer systems consisting of tens of thousands of processors, with near perfect $$\\mathscr{O}(N)$$ scaling with system size and wall times as low as a few seconds per self-consistent field iteration. Finally, we verify the accuracy of SQDFT in large-scale quantum molecular dynamics simulations of aluminum at high temperature.« less

Super Clausius-Clapeyron scaling of extreme hourly precipitation and its relation to large-scale atmospheric conditions

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Barbero, Renaud; Loriaux, Jessica; Fowler, Hayley

2017-04-01

Present-day precipitation-temperature scaling relations indicate that hourly precipitation extremes may have a response to warming exceeding the Clausius-Clapeyron (CC) relation; for The Netherlands the dependency on surface dew point temperature follows two times the CC relation corresponding to 14 % per degree. Our hypothesis - as supported by a simple physical argument presented here - is that this 2CC behaviour arises from the physics of convective clouds. So, we think that this response is due to local feedbacks related to the convective activity, while other large scale atmospheric forcing conditions remain similar except for the higher temperature (approximately uniform warming with height) and absolute humidity (corresponding to the assumption of unchanged relative humidity). To test this hypothesis, we analysed the large-scale atmospheric conditions accompanying summertime afternoon precipitation events using surface observations combined with a regional re-analysis for the data in The Netherlands. Events are precipitation measurements clustered in time and space derived from approximately 30 automatic weather stations. The hourly peak intensities of these events again reveal a 2CC scaling with the surface dew point temperature. The temperature excess of moist updrafts initialized at the surface and the maximum cloud depth are clear functions of surface dew point temperature, confirming the key role of surface humidity on convective activity. Almost no differences in relative humidity and the dry temperature lapse rate were found across the dew point temperature range, supporting our theory that 2CC scaling is mainly due to the response of convection to increases in near surface humidity, while other atmospheric conditions remain similar. Additionally, hourly precipitation extremes are on average accompanied by substantial large-scale upward motions and therefore large-scale moisture convergence, which appears to accelerate with surface dew point. This increase in large-scale moisture convergence appears to be consequence of latent heat release due to the convective activity as estimated from the quasi-geostrophic omega equation. Consequently, most hourly extremes occur in precipitation events with considerable spatial extent. Importantly, this event size appears to increase rapidly at the highest dew point temperature range, suggesting potentially strong impacts of climatic warming.

Scaling and memory in volatility return intervals in financial markets

NASA Astrophysics Data System (ADS)

Yamasaki, Kazuko; Muchnik, Lev; Havlin, Shlomo; Bunde, Armin; Stanley, H. Eugene

2005-06-01

For both stock and currency markets, we study the return intervals τ between the daily volatilities of the price changes that are above a certain threshold q. We find that the distribution function Pq(τ) scales with the mean return interval [Formula] as [Formula]. The scaling function f(x) is similar in form for all seven stocks and for all seven currency databases analyzed, and f(x) is consistent with a power-law form, f(x) ˜ x-γ with γ ≈ 2. We also quantify how the conditional distribution Pq(τ|τ0) depends on the previous return interval τ0 and find that small (or large) return intervals are more likely to be followed by small (or large) return intervals. This “clustering” of the volatility return intervals is a previously unrecognized phenomenon that we relate to the long-term correlations known to be present in the volatility. Author contributions: S.H. and H.E.S. designed research; K.Y., L.M., S.H., and H.E.S. performed research; A.B. contributed new reagents/analytic tools; A.B. analyzed data; and S.H. wrote the paper.Abbreviations: pdf, probability density function; S&P 500, Standard and Poor's 500 Index; USD, U.S. dollar; JPY, Japanese yen; SEK, Swedish krona.

Planck 2015 results. XVI. Isotropy and statistics of the CMB

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Akrami, Y.; Aluri, P. K.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Casaponsa, B.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Contreras, D.; Couchot, F.; Coulais, A.; Crill, B. P.; Cruz, M.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fantaye, Y.; Fergusson, J.; Fernandez-Cobos, R.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Frolov, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kim, J.; Kisner, T. S.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Liu, H.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Marinucci, D.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mikkelsen, K.; Mitra, S.; Miville-Deschênes, M.-A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Pant, N.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Rotti, A.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Souradeep, T.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Trombetti, T.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zibin, J. P.; Zonca, A.

2016-09-01

We test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect our studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The "Cold Spot" is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.

Calculations of High-Temperature Jet Flow Using Hybrid Reynolds-Average Navier-Stokes Formulations

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Elmiligui, Alaa; Giriamaji, Sharath S.

2008-01-01

Two multiscale-type turbulence models are implemented in the PAB3D solver. The models are based on modifying the Reynolds-averaged Navier Stokes equations. The first scheme is a hybrid Reynolds-averaged- Navier Stokes/large-eddy-simulation model using the two-equation k(epsilon) model with a Reynolds-averaged-Navier Stokes/large-eddy-simulation transition function dependent on grid spacing and the computed turbulence length scale. The second scheme is a modified version of the partially averaged Navier Stokes model in which the unresolved kinetic energy parameter f(sub k) is allowed to vary as a function of grid spacing and the turbulence length scale. This parameter is estimated based on a novel two-stage procedure to efficiently estimate the level of scale resolution possible for a given flow on a given grid for partially averaged Navier Stokes. It has been found that the prescribed scale resolution can play a major role in obtaining accurate flow solutions. The parameter f(sub k) varies between zero and one and is equal to one in the viscous sublayer and when the Reynolds-averaged Navier Stokes turbulent viscosity becomes smaller than the large-eddy-simulation viscosity. The formulation, usage methodology, and validation examples are presented to demonstrate the enhancement of PAB3D's time-accurate turbulence modeling capabilities. The accurate simulations of flow and turbulent quantities will provide a valuable tool for accurate jet noise predictions. Solutions from these models are compared with Reynolds-averaged Navier Stokes results and experimental data for high-temperature jet flows. The current results show promise for the capability of hybrid Reynolds-averaged Navier Stokes and large eddy simulation and partially averaged Navier Stokes in simulating such flow phenomena.

Planck 2015 results: XVI. Isotropy and statistics of the CMB

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Akrami, Y.; ...

2016-09-20

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect ourmore » studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.« less

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

Ade, P. A. R.; Aghanim, N.; Akrami, Y.

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect ourmore » studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.« less

Intrauterine Exposure to Methylmercury and Neurocognitive Functions: Minamata Disease.

PubMed

Yorifuji, Takashi; Kato, Tsuguhiko; Kado, Yoko; Tokinobu, Akiko; Yamakawa, Michiyo; Tsuda, Toshihide; Sanada, Satoshi

2015-01-01

A large-scale food poisoning caused by methylmercury was identified in Minamata, Japan, in the 1950s. The severe intrauterine exposure cases are well known, although the possible impact of low-to-moderate methylmercury exposure in utero are rarely investigated. We examined neurocognitive functions among 22 participants in Minamata, mainly using an intelligence quotient test (Wechsler Adults Intelligent Scale III), in 2012/2013. The participants tended to score low on the Index score of processing speed (PS) relative to full-scale IQ, and discrepancies between PS and other scores within each participant were observed. The lower score on PS was due to deficits in digit symbol-coding and symbol search and was associated with methylmercury concentration in umbilical cords. The residents who experienced low-to-moderate methylmercury exposure including prenatal one in Minamata manifested deficits in their cognitive functions, processing speed in particular.

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of premorbid adjustment, neurocognition, and depression on social and role functioning in patients in an early psychosis treatment program.

PubMed

Minor, Kyle S; Friedman-Yakoobian, Michelle; Leung, Y Jude; Meyer, Eric C; Zimmet, Suzanna V; Caplan, Brina; Monteleone, Thomas; Bryant, Caitlin; Guyer, Margaret; Keshavan, Matcheri S; Seidman, Larry J

2015-05-01

Functional impairments are debilitating concomitants of psychotic disorders and are present early in the illness course and, commonly, prior to psychosis onset. The factors affecting social and role functioning in early psychosis (EP) following treatment are unclear. We evaluated whether six months of participation in the PREP(R), Boston, EP treatment program, part of a public-academic community mental health center, was related to improvements in social and role functioning and whether premorbid adjustment in adolescence, baseline neurocognition, and depression symptoms predicted functional improvement. The Global Functioning Social and Role scales, MATRICS neurocognitive battery, and Calgary Depression Scale were assessed at baseline and six months during naturalistic treatment, while premorbid adjustment was measured at baseline. All participants were psychotic disorder patients in PREP(R) (n = 46 with social functioning and 47 with role functioning measures at both time points). Large improvements were observed in role functioning (d = 0.84) and medium to large improvements were observed in social functioning (d = 0.70). Models consisting of adolescent premorbid adjustment and change in depression symptoms predicted social and role functioning change, whereas neuropsychological functioning did not. Substantial improvements in social and role functioning were observed among this sample participating in a recovery-based EP program. The impact of clinical factors on social and role functioning was highlighted. Further studies of premorbid adjustment in adolescence and the treatment of depression in EP programs in controlled treatment trials are needed to confirm these findings. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Comparative Effectiveness Research and Children With Cerebral Palsy: Identifying a Conceptual Framework and Specifying Measures.

PubMed

Gannotti, Mary E; Law, Mary; Bailes, Amy F; OʼNeil, Margaret E; Williams, Uzma; DiRezze, Briano

2016-01-01

A step toward advancing research about rehabilitation service associated with positive outcomes for children with cerebral palsy is consensus about a conceptual framework and measures. A Delphi process was used to establish consensus among clinicians and researchers in North America. Directors of large pediatric rehabilitation centers, clinicians from large hospitals, and researchers with expertise in outcomes participated (N = 18). Andersen's model of health care utilization framed outcomes: consumer satisfaction, activity, participation, quality of life, and pain. Measures agreed upon included Participation and Environment Measure for Children and Youth, Measure of Processes of Care, PEDI-CAT, KIDSCREEN-10, PROMIS Pediatric Pain Interference Scale, Visual Analog Scale for pain intensity, PROMIS Global Health Short Form, Family Environment Scale, Family Support Scale, and functional classification levels for gross motor, manual ability, and communication. Universal forms for documenting service use are needed. Findings inform clinicians and researchers concerned with outcome assessment.

Molecular Precision at Micrometer Length Scales: Hierarchical Assembly of DNA-Protein Nanostructures.

PubMed

Schiffels, Daniel; Szalai, Veronika A; Liddle, J Alexander

2017-07-25

Robust self-assembly across length scales is a ubiquitous feature of biological systems but remains challenging for synthetic structures. Taking a cue from biology-where disparate molecules work together to produce large, functional assemblies-we demonstrate how to engineer microscale structures with nanoscale features: Our self-assembly approach begins by using DNA polymerase to controllably create double-stranded DNA (dsDNA) sections on a single-stranded template. The single-stranded DNA (ssDNA) sections are then folded into a mechanically flexible skeleton by the origami method. This process simultaneously shapes the structure at the nanoscale and directs the large-scale geometry. The DNA skeleton guides the assembly of RecA protein filaments, which provides rigidity at the micrometer scale. We use our modular design strategy to assemble tetrahedral, rectangular, and linear shapes of defined dimensions. This method enables the robust construction of complex assemblies, greatly extending the range of DNA-based self-assembly methods.

Anisotropic evolution of 5D Friedmann-Robertson-Walker spacetime

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

Middleton, Chad A.; Stanley, Ethan

2011-10-15

We examine the time evolution of the five-dimensional Einstein field equations subjected to a flat, anisotropic Robertson-Walker metric, where the 3D and higher-dimensional scale factors are allowed to dynamically evolve at different rates. By adopting equations of state relating the 3D and higher-dimensional pressures to the density, we obtain an exact expression relating the higher-dimensional scale factor to a function of the 3D scale factor. This relation allows us to write the Friedmann-Robertson-Walker field equations exclusively in terms of the 3D scale factor, thus yielding a set of 4D effective Friedmann-Robertson-Walker field equations. We examine the effective field equations inmore » the general case and obtain an exact expression relating a function of the 3D scale factor to the time. This expression involves a hypergeometric function and cannot, in general, be inverted to yield an analytical expression for the 3D scale factor as a function of time. When the hypergeometric function is expanded for small and large arguments, we obtain a generalized treatment of the dynamical compactification scenario of Mohammedi [Phys. Rev. D 65, 104018 (2002)] and the 5D vacuum solution of Chodos and Detweiler [Phys. Rev. D 21, 2167 (1980)], respectively. By expanding the hypergeometric function near a branch point, we obtain the perturbative solution for the 3D scale factor in the small time regime. This solution exhibits accelerated expansion, which, remarkably, is independent of the value of the 4D equation of state parameter w. This early-time epoch of accelerated expansion arises naturally out of the anisotropic evolution of 5D spacetime when the pressure in the extra dimension is negative and offers a possible alternative to scalar field inflationary theory.« less

Large-Scale Gene Relocations following an Ancient Genome Triplication Associated with the Diversification of Core Eudicots.

PubMed

Wang, Yupeng; Ficklin, Stephen P; Wang, Xiyin; Feltus, F Alex; Paterson, Andrew H

2016-01-01

Different modes of gene duplication including whole-genome duplication (WGD), and tandem, proximal and dispersed duplications are widespread in angiosperm genomes. Small-scale, stochastic gene relocations and transposed gene duplications are widely accepted to be the primary mechanisms for the creation of dispersed duplicates. However, here we show that most surviving ancient dispersed duplicates in core eudicots originated from large-scale gene relocations within a narrow window of time following a genome triplication (γ) event that occurred in the stem lineage of core eudicots. We name these surviving ancient dispersed duplicates as relocated γ duplicates. In Arabidopsis thaliana, relocated γ, WGD and single-gene duplicates have distinct features with regard to gene functions, essentiality, and protein interactions. Relative to γ duplicates, relocated γ duplicates have higher non-synonymous substitution rates, but comparable levels of expression and regulation divergence. Thus, relocated γ duplicates should be distinguished from WGD and single-gene duplicates for evolutionary investigations. Our results suggest large-scale gene relocations following the γ event were associated with the diversification of core eudicots.

Large-Scale Gene Relocations following an Ancient Genome Triplication Associated with the Diversification of Core Eudicots

PubMed Central

Wang, Yupeng; Ficklin, Stephen P.; Wang, Xiyin; Feltus, F. Alex; Paterson, Andrew H.

2016-01-01

Different modes of gene duplication including whole-genome duplication (WGD), and tandem, proximal and dispersed duplications are widespread in angiosperm genomes. Small-scale, stochastic gene relocations and transposed gene duplications are widely accepted to be the primary mechanisms for the creation of dispersed duplicates. However, here we show that most surviving ancient dispersed duplicates in core eudicots originated from large-scale gene relocations within a narrow window of time following a genome triplication (γ) event that occurred in the stem lineage of core eudicots. We name these surviving ancient dispersed duplicates as relocated γ duplicates. In Arabidopsis thaliana, relocated γ, WGD and single-gene duplicates have distinct features with regard to gene functions, essentiality, and protein interactions. Relative to γ duplicates, relocated γ duplicates have higher non-synonymous substitution rates, but comparable levels of expression and regulation divergence. Thus, relocated γ duplicates should be distinguished from WGD and single-gene duplicates for evolutionary investigations. Our results suggest large-scale gene relocations following the γ event were associated with the diversification of core eudicots. PMID:27195960

Non-linear scaling of oxygen consumption and heart rate in a very large cockroach species (Gromphadorhina portentosa): correlated changes with body size and temperature.

PubMed

Streicher, Jeffrey W; Cox, Christian L; Birchard, Geoffrey F

2012-04-01

Although well documented in vertebrates, correlated changes between metabolic rate and cardiovascular function of insects have rarely been described. Using the very large cockroach species Gromphadorhina portentosa, we examined oxygen consumption and heart rate across a range of body sizes and temperatures. Metabolic rate scaled positively and heart rate negatively with body size, but neither scaled linearly. The response of these two variables to temperature was similar. This correlated response to endogenous (body mass) and exogenous (temperature) variables is likely explained by a mutual dependence on similar metabolic substrate use and/or coupled regulatory pathways. The intraspecific scaling for oxygen consumption rate showed an apparent plateauing at body masses greater than about 3 g. An examination of cuticle mass across all instars revealed isometric scaling with no evidence of an ontogenetic shift towards proportionally larger cuticles. Published oxygen consumption rates of other Blattodea species were also examined and, as in our intraspecific examination of G. portentosa, the scaling relationship was found to be non-linear with a decreasing slope at larger body masses. The decreasing slope at very large body masses in both intraspecific and interspecific comparisons may have important implications for future investigations of the relationship between oxygen transport and maximum body size in insects.

Direct and inverse energy cascades in a forced rotating turbulence experiment

NASA Astrophysics Data System (ADS)

Campagne, Antoine; Gallet, Basile; Moisy, Frédéric; Cortet, Pierre-Philippe

2014-12-01

We present experimental evidence for a double cascade of kinetic energy in a statistically stationary rotating turbulence experiment. Turbulence is generated by a set of vertical flaps, which continuously injects velocity fluctuations towards the center of a rotating water tank. The energy transfers are evaluated from two-point third-order three-component velocity structure functions, which we measure using stereoscopic particle image velocimetry in the rotating frame. Without global rotation, the energy is transferred from large to small scales, as in classical three-dimensional turbulence. For nonzero rotation rates, the horizontal kinetic energy presents a double cascade: a direct cascade at small horizontal scales and an inverse cascade at large horizontal scales. By contrast, the vertical kinetic energy is always transferred from large to small horizontal scales, a behavior reminiscent of the dynamics of a passive scalar in two-dimensional turbulence. At the largest rotation rate, the flow is nearly two-dimensional, and a pure inverse energy cascade is found for the horizontal energy. To describe the scale-by-scale energy budget, we consider a generalization of the Kármán-Howarth-Monin equation to inhomogeneous turbulent flows, in which the energy input is explicitly described as the advection of turbulent energy from the flaps through the surface of the control volume where the measurements are performed.

Nicholas Metropolis Award for Outstanding Doctoral Thesis Work in Computational Physics Talk: Understanding Nano-scale Electronic Systems via Large-scale Computation

NASA Astrophysics Data System (ADS)

Cao, Chao

2009-03-01

Nano-scale physical phenomena and processes, especially those in electronics, have drawn great attention in the past decade. Experiments have shown that electronic and transport properties of functionalized carbon nanotubes are sensitive to adsorption of gas molecules such as H2, NO2, and NH3. Similar measurements have also been performed to study adsorption of proteins on other semiconductor nano-wires. These experiments suggest that nano-scale systems can be useful for making future chemical and biological sensors. Aiming to understand the physical mechanisms underlying and governing property changes at nano-scale, we start off by investigating, via first-principles method, the electronic structure of Pd-CNT before and after hydrogen adsorption, and continue with coherent electronic transport using non-equilibrium Green’s function techniques combined with density functional theory. Once our results are fully analyzed they can be used to interpret and understand experimental data, with a few difficult issues to be addressed. Finally, we discuss a newly developed multi-scale computing architecture, OPAL, that coordinates simultaneous execution of multiple codes. Inspired by the capabilities of this computing framework, we present a scenario of future modeling and simulation of multi-scale, multi-physical processes.

New convergence results for the scaled gradient projection method

NASA Astrophysics Data System (ADS)

Bonettini, S.; Prato, M.

2015-09-01

The aim of this paper is to deepen the convergence analysis of the scaled gradient projection (SGP) method, proposed by Bonettini et al in a recent paper for constrained smooth optimization. The main feature of SGP is the presence of a variable scaling matrix multiplying the gradient, which may change at each iteration. In the last few years, extensive numerical experimentation showed that SGP equipped with a suitable choice of the scaling matrix is a very effective tool for solving large scale variational problems arising in image and signal processing. In spite of the very reliable numerical results observed, only a weak convergence theorem is provided establishing that any limit point of the sequence generated by SGP is stationary. Here, under the only assumption that the objective function is convex and that a solution exists, we prove that the sequence generated by SGP converges to a minimum point, if the scaling matrices sequence satisfies a simple and implementable condition. Moreover, assuming that the gradient of the objective function is Lipschitz continuous, we are also able to prove the {O}(1/k) convergence rate with respect to the objective function values. Finally, we present the results of a numerical experience on some relevant image restoration problems, showing that the proposed scaling matrix selection rule performs well also from the computational point of view.

Isolating relativistic effects in large-scale structure

NASA Astrophysics Data System (ADS)

Bonvin, Camille

2014-12-01

We present a fully relativistic calculation of the observed galaxy number counts in the linear regime. We show that besides the density fluctuations and redshift-space distortions, various relativistic effects contribute to observations at large scales. These effects all have the same physical origin: they result from the fact that our coordinate system, namely the galaxy redshift and the incoming photons’ direction, is distorted by inhomogeneities in our Universe. We then discuss the impact of the relativistic effects on the angular power spectrum and on the two-point correlation function in configuration space. We show that the latter is very well adapted to isolate the relativistic effects since it naturally makes use of the symmetries of the different contributions. In particular, we discuss how the Doppler effect and the gravitational redshift distortions can be isolated by looking for a dipole in the cross-correlation function between a bright and a faint population of galaxies.

Large-Scale First-Principles Molecular Dynamics Simulations with Electrostatic Embedding: Application to Acetylcholinesterase Catalysis

DOE PAGES

Fattebert, Jean-Luc; Lau, Edmond Y.; Bennion, Brian J.; ...

2015-10-22

Enzymes are complicated solvated systems that typically require many atoms to simulate their function with any degree of accuracy. We have recently developed numerical techniques for large scale First-Principles molecular dynamics simulations and applied them to study the enzymatic reaction catalyzed by acetylcholinesterase. We carried out Density functional theory calculations for a quantum mechanical (QM) sub- system consisting of 612 atoms with an O(N) complexity finite-difference approach. The QM sub-system is embedded inside an external potential field representing the electrostatic effect due to the environment. We obtained finite temperature sampling by First-Principles molecular dynamics for the acylation reaction of acetylcholinemore » catalyzed by acetylcholinesterase. Our calculations shows two energies barriers along the reaction coordinate for the enzyme catalyzed acylation of acetylcholine. In conclusion, the second barrier (8.5 kcal/mole) is rate-limiting for the acylation reaction and in good agreement with experiment.« less

The biology and polymer physics underlying large-scale chromosome organization.

PubMed

Sazer, Shelley; Schiessel, Helmut

2018-02-01

Chromosome large-scale organization is a beautiful example of the interplay between physics and biology. DNA molecules are polymers and thus belong to the class of molecules for which physicists have developed models and formulated testable hypotheses to understand their arrangement and dynamic properties in solution, based on the principles of polymer physics. Biologists documented and discovered the biochemical basis for the structure, function and dynamic spatial organization of chromosomes in cells. The underlying principles of chromosome organization have recently been revealed in unprecedented detail using high-resolution chromosome capture technology that can simultaneously detect chromosome contact sites throughout the genome. These independent lines of investigation have now converged on a model in which DNA loops, generated by the loop extrusion mechanism, are the basic organizational and functional units of the chromosome. © 2017 The Authors. Traffic published by John Wiley & Sons Ltd.

ProMotE: an efficient algorithm for counting independent motifs in uncertain network topologies.

PubMed

Ren, Yuanfang; Sarkar, Aisharjya; Kahveci, Tamer

2018-06-26

Identifying motifs in biological networks is essential in uncovering key functions served by these networks. Finding non-overlapping motif instances is however a computationally challenging task. The fact that biological interactions are uncertain events further complicates the problem, as it makes the existence of an embedding of a given motif an uncertain event as well. In this paper, we develop a novel method, ProMotE (Probabilistic Motif Embedding), to count non-overlapping embeddings of a given motif in probabilistic networks. We utilize a polynomial model to capture the uncertainty. We develop three strategies to scale our algorithm to large networks. Our experiments demonstrate that our method scales to large networks in practical time with high accuracy where existing methods fail. Moreover, our experiments on cancer and degenerative disease networks show that our method helps in uncovering key functional characteristics of biological networks.

A high-throughput assay for quantifying appetite and digestive dynamics.

PubMed

Jordi, Josua; Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-08-15

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. Copyright © 2015 the American Physiological Society.

A high-throughput assay for quantifying appetite and digestive dynamics

PubMed Central

Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-01-01

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. PMID:26108871

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

PubMed Central

Berényi, Antal; Somogyvári, Zoltán; Nagy, Anett J.; Roux, Lisa; Long, John D.; Fujisawa, Shigeyoshi; Stark, Eran; Leonardo, Anthony; Harris, Timothy D.

2013-01-01

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function. PMID:24353300

Large Scale Synthesis and Light Emitting Fibers of Tailor-Made Graphene Quantum Dots

PubMed Central

Park, Hun; Hyun Noh, Sung; Hye Lee, Ji; Jun Lee, Won; Yun Jaung, Jae; Geol Lee, Seung; Hee Han, Tae

2015-01-01

Graphene oxide (GO), which is an oxidized form of graphene, has a mixed structure consisting of graphitic crystallites of sp2 hybridized carbon and amorphous regions. In this work, we present a straightforward route for preparing graphene-based quantum dots (GQDs) by extraction of the crystallites from the amorphous matrix of the GO sheets. GQDs with controlled functionality are readily prepared by varying the reaction temperature, which results in precise tunability of their optical properties. Here, it was concluded that the tunable optical properties of GQDs are a result of the different fraction of chemical functionalities present. The synthesis approach presented in this paper provides an efficient strategy for achieving large-scale production and long-time optical stability of the GQDs, and the hybrid assembly of GQD and polymer has potential applications as photoluminescent fibers or films. PMID:26383257

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Preconditioning strategies for nonlinear conjugate gradient methods, based on quasi-Newton updates

NASA Astrophysics Data System (ADS)

Andrea, Caliciotti; Giovanni, Fasano; Massimo, Roma

2016-10-01

This paper reports two proposals of possible preconditioners for the Nonlinear Conjugate Gradient (NCG) method, in large scale unconstrained optimization. On one hand, the common idea of our preconditioners is inspired to L-BFGS quasi-Newton updates, on the other hand we aim at explicitly approximating in some sense the inverse of the Hessian matrix. Since we deal with large scale optimization problems, we propose matrix-free approaches where the preconditioners are built using symmetric low-rank updating formulae. Our distinctive new contributions rely on using information on the objective function collected as by-product of the NCG, at previous iterations. Broadly speaking, our first approach exploits the secant equation, in order to impose interpolation conditions on the objective function. In the second proposal we adopt and ad hoc modified-secant approach, in order to possibly guarantee some additional theoretical properties.

Feasibility analysis of large length-scale thermocapillary flow experiment for the International Space Station

NASA Astrophysics Data System (ADS)

Alberts, Samantha J.

The investigation of microgravity fluid dynamics emerged out of necessity with the advent of space exploration. In particular, capillary research took a leap forward in the 1960s with regards to liquid settling and interfacial dynamics. Due to inherent temperature variations in large spacecraft liquid systems, such as fuel tanks, forces develop on gas-liquid interfaces which induce thermocapillary flows. To date, thermocapillary flows have been studied in small, idealized research geometries usually under terrestrial conditions. The 1 to 3m lengths in current and future large tanks and hardware are designed based on hardware rather than research, which leaves spaceflight systems designers without the technological tools to effectively create safe and efficient designs. This thesis focused on the design and feasibility of a large length-scale thermocapillary flow experiment, which utilizes temperature variations to drive a flow. The design of a helical channel geometry ranging from 1 to 2.5m in length permits a large length-scale thermocapillary flow experiment to fit in a seemingly small International Space Station (ISS) facility such as the Fluids Integrated Rack (FIR). An initial investigation determined the proposed experiment produced measurable data while adhering to the FIR facility limitations. The computational portion of this thesis focused on the investigation of functional geometries of fuel tanks and depots using Surface Evolver. This work outlines the design of a large length-scale thermocapillary flow experiment for the ISS FIR. The results from this work improve the understanding thermocapillary flows and thus improve technological tools for predicting heat and mass transfer in large length-scale thermocapillary flows. Without the tools to understand the thermocapillary flows in these systems, engineers are forced to design larger, heavier vehicles to assure safety and mission success.

Initial eccentricity and constituent quark number scaling of elliptic flow in ideal and viscous dynamics

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

Chaudhuri, A. K.

2010-04-15

In the Israel-Stewart theory of dissipative hydrodynamics, the scaling properties of elliptic flow in Au+Au collisions are studied. The initial energy density of the fluid was fixed to reproduce STAR data on phi-meson multiplicity in 0-5% Au+Au collisions such that, irrespective of fluid viscosity, entropy at the freeze-out is similar in ideal or in viscous evolution. The initial eccentricity or constituent quark number scaling is only approximate in ideal or minimally viscous (eta/s=1/4pi) fluid. Eccentricity scaling becomes nearly exact in more viscous fluid (eta/s>=0.12). However, in more viscous fluid, constituent quark number scaled elliptic flow for mesons and baryons splitsmore » into separate scaling functions. Simulated flows also do not exhibit 'universal scaling'; that is, elliptic flow scaled by the constituent quark number and charged particles v{sub 2} is not a single function of transverse kinetic energy scaled by the quark number. From a study of the violation of universal scaling, we obtain an estimate of quark-gluon plasma viscosity, eta/s=0.12+-0.03. The error is statistical only. The systematic error in eta/s could be as large.« less

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

PubMed

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes.

Examination of the Positive and Negative Syndrome Scale factor structure and longitudinal relationships with functioning in early psychosis.

PubMed

Best, Michael W; Grossman, Michael; Oyewumi, L Kola; Bowie, Christopher R

2016-04-01

We examined the factor structure of the Positive and Negative Syndrome Scale (PANSS) in early-episode psychosis and its relationships with functioning at baseline and follow-up. A total of 240 consecutive admissions to an early intervention in psychosis clinic were assessed at intake to the program with the PANSS, Global Assessment of Functioning (GAF) and Social and Occupational Functioning Assessment Scale (SOFAS). Seventy individuals were reassessed at follow-up. A maximum likelihood factor analysis was conducted on baseline PANSS scores and the ability of each factor to predict baseline and follow-up GAF and SOFAS was examined. A five-factor model with varimax rotation was the best fit to our data and was largely congruent with factors found previously. The negative symptom factor was the best predictor of GAF and SOFAS at baseline and follow-up. Negative symptoms are the best symptomatic predictor of functioning in individuals with early psychosis and are an important treatment target to improve recovery. © 2014 Wiley Publishing Asia Pty Ltd.

Scale and modeling issues in water resources planning

USGS Publications Warehouse

Lins, H.F.; Wolock, D.M.; McCabe, G.J.

1997-01-01

Resource planners and managers interested in utilizing climate model output as part of their operational activities immediately confront the dilemma of scale discordance. Their functional responsibilities cover relatively small geographical areas and necessarily require data of relatively high spatial resolution. Climate models cover a large geographical, i.e. global, domain and produce data at comparatively low spatial resolution. Although the scale differences between model output and planning input are large, several techniques have been developed for disaggregating climate model output to a scale appropriate for use in water resource planning and management applications. With techniques in hand to reduce the limitations imposed by scale discordance, water resource professionals must now confront a more fundamental constraint on the use of climate models-the inability to produce accurate representations and forecasts of regional climate. Given the current capabilities of climate models, and the likelihood that the uncertainty associated with long-term climate model forecasts will remain high for some years to come, the water resources planning community may find it impractical to utilize such forecasts operationally.

Magnetic pattern at supergranulation scale: the void size distribution

NASA Astrophysics Data System (ADS)

Berrilli, F.; Scardigli, S.; Del Moro, D.

2014-08-01

The large-scale magnetic pattern observed in the photosphere of the quiet Sun is dominated by the magnetic network. This network, created by photospheric magnetic fields swept into convective downflows, delineates the boundaries of large-scale cells of overturning plasma and exhibits "voids" in magnetic organization. These voids include internetwork fields, which are mixed-polarity sparse magnetic fields that populate the inner part of network cells. To single out voids and to quantify their intrinsic pattern we applied a fast circle-packing-based algorithm to 511 SOHO/MDI high-resolution magnetograms acquired during the unusually long solar activity minimum between cycles 23 and 24. The computed void distribution function shows a quasi-exponential decay behavior in the range 10-60 Mm. The lack of distinct flow scales in this range corroborates the hypothesis of multi-scale motion flows at the solar surface. In addition to the quasi-exponential decay, we have found that the voids depart from a simple exponential decay at about 35 Mm.

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules.

PubMed

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I; de Boer, Pascal; Hagen, Kees C W; Hoogenboom, Jacob P; Giepmans, Ben N G

2017-04-07

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale 'color-EM' as a promising tool to unravel molecular (de)regulation in biomedicine.

Multi-color electron microscopy by element-guided identification of cells, organelles and molecules

PubMed Central

Scotuzzi, Marijke; Kuipers, Jeroen; Wensveen, Dasha I.; de Boer, Pascal; Hagen, Kees (C.) W.; Hoogenboom, Jacob P.; Giepmans, Ben N. G.

2017-01-01

Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale ‘color-EM’ as a promising tool to unravel molecular (de)regulation in biomedicine. PMID:28387351

Anisotropic storage medium development in a full-scale, sodium alanate-based, hydrogen storage system

DOE PAGES

Jorgensen, Scott W.; Johnson, Terry A.; Payzant, E. Andrew; ...

2016-06-11

Deuterium desorption in an automotive-scale hydrogen storage tube was studied in-situ using neutron diffraction. Gradients in the concentration of the various alanate phases were observed along the length of the tube but no significant radial anisotropy was present. In addition, neutron radiography and computed tomography showed large scale cracks and density fluctuations, confirming the presence of these structures in an undisturbed storage system. These results demonstrate that large scale storage structures are not uniform even after many absorption/desorption cycles and that movement of gaseous hydrogen cannot be properly modeled by a simple porous bed model. In addition, the evidence indicatesmore » that there is slow transformation of species at one end of the tube indicating loss of catalyst functionality. These observations explain the unusually fast movement of hydrogen in a full scale system and shows that loss of capacity is not occurring uniformly in this type of hydrogen-storage system.« less

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

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

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

Parameterized post-Newtonian cosmology

NASA Astrophysics Data System (ADS)

Sanghai, Viraj A. A.; Clifton, Timothy

2017-03-01

Einstein’s theory of gravity has been extensively tested on solar system scales, and for isolated astrophysical systems, using the perturbative framework known as the parameterized post-Newtonian (PPN) formalism. This framework is designed for use in the weak-field and slow-motion limit of gravity, and can be used to constrain a large class of metric theories of gravity with data collected from the aforementioned systems. Given the potential of future surveys to probe cosmological scales to high precision, it is a topic of much contemporary interest to construct a similar framework to link Einstein’s theory of gravity and its alternatives to observations on cosmological scales. Our approach to this problem is to adapt and extend the existing PPN formalism for use in cosmology. We derive a set of equations that use the same parameters to consistently model both weak fields and cosmology. This allows us to parameterize a large class of modified theories of gravity and dark energy models on cosmological scales, using just four functions of time. These four functions can be directly linked to the background expansion of the universe, first-order cosmological perturbations, and the weak-field limit of the theory. They also reduce to the standard PPN parameters on solar system scales. We illustrate how dark energy models and scalar-tensor and vector-tensor theories of gravity fit into this framework, which we refer to as ‘parameterized post-Newtonian cosmology’ (PPNC).

Anthropogenic disturbance and environmental associations with fish assemblage structure in two nonwadeable rivers

USGS Publications Warehouse

Parks, T. P.; Quist, Michael C.; Pierce, C.L.

2016-01-01

Nonwadeable rivers are unique ecosystems that support high levels of aquatic biodiversity, yet they have been greatly altered by human activities. Although riverine fish assemblages have been studied in the past, we still have an incomplete understanding of how fish assemblages respond to both natural and anthropogenic influences in large rivers. The purpose of this study was to evaluate associations between fish assemblage structure and reach-scale habitat, dam, and watershed land use characteristics. In the summers of 2011 and 2012, comprehensive fish and environmental data were collected from 33 reaches in the Iowa and Cedar rivers of eastern-central Iowa. Canonical correspondence analysis (CCA) was used to evaluate environmental relationships with species relative abundance, functional trait abundance (e.g. catch rate of tolerant species), and functional trait composition (e.g. percentage of tolerant species). On the basis of partial CCAs, reach-scale habitat, dam characteristics, and watershed land use features explained 25.0–81.1%, 6.2–25.1%, and 5.8–47.2% of fish assemblage variation, respectively. Although reach-scale, dam, and land use factors contributed to overall assemblage structure, the majority of fish assemblage variation was constrained by reach-scale habitat factors. Specifically, mean annual discharge was consistently selected in nine of the 11 CCA models and accounted for the majority of explained fish assemblage variance by reach-scale habitat. This study provides important insight on the influence of anthropogenic disturbances across multiple spatial scales on fish assemblages in large river systems.

Functional and phylogenetic relatedness in temporary wetland invertebrates: current macroecological patterns and implications for future climatic change scenarios.

PubMed

Ruhí, Albert; Boix, Dani; Gascón, Stéphanie; Sala, Jordi; Batzer, Darold P

2013-01-01

In freshwater ecosystems, species compositions are known to be determined hierarchically by large to small‑scale environmental factors, based on the biological traits of the organisms. However, in ephemeral habitats this heuristic framework remains largely untested. Although temporary wetland faunas are constrained by a local filter (i.e., desiccation), we propose its magnitude may still depend on large-scale climate characteristics. If this is true, climate should be related to the degree of functional and taxonomic relatedness of invertebrate communities inhabiting seasonal wetlands. We tested this hypothesis in two ways. First, based on 52 biological traits for invertebrates, we conducted a case study to explore functional trends among temperate seasonal wetlands differing in the harshness (i.e., dryness) of their dry season. After finding evidence of trait filtering, we addressed whether it could be generalized across a broader climatic scale. To this end, a meta-analysis (225 seasonal wetlands spread across broad climatic categories: Arid, Temperate, and Cold) allowed us to identify whether an equivalent climate-dependent pattern of trait richness was consistent between the Nearctic and the Western Palearctic. Functional overlap of invertebrates increased from mild (i.e., Temperate) to harsher climates (i.e., Arid and Cold), and phylogenetic clustering (using taxonomy as a surrogate) was highest in Arid and lowest in Temperate wetlands. We show that, (i) as has been described in streams, higher relatedness than would be expected by chance is generally observed in seasonal wetland invertebrate communities; and (ii) this relatedness is not constant but climate-dependent, with the climate under which a given seasonal wetland is located determining the functional overlap and the phylogenetic clustering of the community. Finally, using a space-for-time substitution approach we suggest our results may anticipate how the invertebrate biodiversity embedded in these vulnerable and often overlooked ecosystems will be affected by long-term climate change.

Functional and Phylogenetic Relatedness in Temporary Wetland Invertebrates: Current Macroecological Patterns and Implications for Future Climatic Change Scenarios

PubMed Central

Ruhí, Albert; Boix, Dani; Gascón, Stéphanie; Sala, Jordi; Batzer, Darold P.

2013-01-01

In freshwater ecosystems, species compositions are known to be determined hierarchically by large to small‑scale environmental factors, based on the biological traits of the organisms. However, in ephemeral habitats this heuristic framework remains largely untested. Although temporary wetland faunas are constrained by a local filter (i.e., desiccation), we propose its magnitude may still depend on large-scale climate characteristics. If this is true, climate should be related to the degree of functional and taxonomic relatedness of invertebrate communities inhabiting seasonal wetlands. We tested this hypothesis in two ways. First, based on 52 biological traits for invertebrates, we conducted a case study to explore functional trends among temperate seasonal wetlands differing in the harshness (i.e., dryness) of their dry season. After finding evidence of trait filtering, we addressed whether it could be generalized across a broader climatic scale. To this end, a meta-analysis (225 seasonal wetlands spread across broad climatic categories: Arid, Temperate, and Cold) allowed us to identify whether an equivalent climate-dependent pattern of trait richness was consistent between the Nearctic and the Western Palearctic. Functional overlap of invertebrates increased from mild (i.e., Temperate) to harsher climates (i.e., Arid and Cold), and phylogenetic clustering (using taxonomy as a surrogate) was highest in Arid and lowest in Temperate wetlands. We show that, (i) as has been described in streams, higher relatedness than would be expected by chance is generally observed in seasonal wetland invertebrate communities; and (ii) this relatedness is not constant but climate-dependent, with the climate under which a given seasonal wetland is located determining the functional overlap and the phylogenetic clustering of the community. Finally, using a space-for-time substitution approach we suggest our results may anticipate how the invertebrate biodiversity embedded in these vulnerable and often overlooked ecosystems will be affected by long-term climate change. PMID:24312347

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Neurite, a Finite Difference Large Scale Parallel Program for the Simulation of Electrical Signal Propagation in Neurites under Mechanical Loading

PubMed Central

García-Grajales, Julián A.; Rucabado, Gabriel; García-Dopico, Antonio; Peña, José-María; Jérusalem, Antoine

2015-01-01

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite—explicit and implicit—were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted. PMID:25680098

Examining the Construct Validity of the MMPI-2-RF Interpersonal Functioning Scales Using the Computerized Adaptive Test of Personality Disorder as a Comparative Framework.

PubMed

Franz, Annabel O; Harrop, Tiffany M; McCord, David M

2017-01-01

This study aimed to examine the construct validity of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) interpersonal functioning scales (Ben-Porath & Tellegen, 2008/2011 ) using as a criterion measure the Computerized Adaptive Test of Personality Disorder-Static Form (CAT-PD-SF; Simms et al., 2011 ). Participants were college students (n = 98) recruited through the university subject pool. A series of a priori hypotheses were developed for each of the 6 interpersonal functioning scales of the MMPI-2-RF, expressed as predicted correlations with construct-relevant CAT-PD-SF scales. Of the 27 specific predictions, 21 were supported by substantial (≥ |.30|) correlations. The MMPI-2-RF Family Problems scale (FML) demonstrated the strongest correlations with CAT-PD-SF scales Anhedonia and Mistrust; Cynicism (RC3) was most highly correlated with Mistrust and Norm Violation; Interpersonal Passivity (IPP) was most highly correlated with Domineering and Rudeness; Social Avoidance (SAV) was most highly correlated with Social Withdrawal and Anhedonia; Shyness (SHY) was most highly correlated with Social Withdrawal and Anxioiusness; and Disaffiliativeness (DSF) was most highly correlated with Emotional Detachment and Mistrust. Results are largely consistent with hypotheses suggesting support for both models of constructs relevant to interpersonal functioning. Future research designed to more precisely differentiate Social Avoidance (SAV) and Shyness (SHY) is suggested.

On strong homogeneity of a class of global optimization algorithms working with infinite and infinitesimal scales

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.

2018-06-01

The necessity to find the global optimum of multiextremal functions arises in many applied problems where finding local solutions is insufficient. One of the desirable properties of global optimization methods is strong homogeneity meaning that a method produces the same sequences of points where the objective function is evaluated independently both of multiplication of the function by a scaling constant and of adding a shifting constant. In this paper, several aspects of global optimization using strongly homogeneous methods are considered. First, it is shown that even if a method possesses this property theoretically, numerically very small and large scaling constants can lead to ill-conditioning of the scaled problem. Second, a new class of global optimization problems where the objective function can have not only finite but also infinite or infinitesimal Lipschitz constants is introduced. Third, the strong homogeneity of several Lipschitz global optimization algorithms is studied in the framework of the Infinity Computing paradigm allowing one to work numerically with a variety of infinities and infinitesimals. Fourth, it is proved that a class of efficient univariate methods enjoys this property for finite, infinite and infinitesimal scaling and shifting constants. Finally, it is shown that in certain cases the usage of numerical infinities and infinitesimals can avoid ill-conditioning produced by scaling. Numerical experiments illustrating theoretical results are described.

Large-scale studies of ion acceleration in laser-generated plasma at intensities from 1010 W/cm2 to 1019 W/cm2

NASA Astrophysics Data System (ADS)

Torrisi, L.

2018-02-01

A large-scale study of ion acceleration in laser-generated plasma, extended to intensities from 1010 W/cm2 up to 1019 W/cm2, is presented. Aluminium thick and thin foils were irradiated in high vacuum using different infrared lasers and pulse durations from ns up to fs scale. Plasma was monitored mainly using SiC detectors employed in time-of-flight configuration. Protons and aluminium ions, at different energies and yields, were measured as a function of the laser intensity. The discontinuity region between particle acceleration from both the backward plasma (BPA) in thick targets and the forward plasma in thin foils in the target normal sheath acceleration (TNSA) regimes were investigated.

Engineering of Baeyer-Villiger monooxygenase-based Escherichia coli biocatalyst for large scale biotransformation of ricinoleic acid into (Z)-11-(heptanoyloxy)undec-9-enoic acid

PubMed Central

Seo, Joo-Hyun; Kim, Hwan-Hee; Jeon, Eun-Yeong; Song, Young-Ha; Shin, Chul-Soo; Park, Jin-Byung

2016-01-01

Baeyer-Villiger monooxygenases (BVMOs) are able to catalyze regiospecific Baeyer-Villiger oxygenation of a variety of cyclic and linear ketones to generate the corresponding lactones and esters, respectively. However, the enzymes are usually difficult to express in a functional form in microbial cells and are rather unstable under process conditions hindering their large-scale applications. Thereby, we investigated engineering of the BVMO from Pseudomonas putida KT2440 and the gene expression system to improve its activity and stability for large-scale biotransformation of ricinoleic acid (1) into the ester (i.e., (Z)-11-(heptanoyloxy)undec-9-enoic acid) (3), which can be hydrolyzed into 11-hydroxyundec-9-enoic acid (5) (i.e., a precursor of polyamide-11) and n-heptanoic acid (4). The polyionic tag-based fusion engineering of the BVMO and the use of a synthetic promoter for constitutive enzyme expression allowed the recombinant Escherichia coli expressing the BVMO and the secondary alcohol dehydrogenase of Micrococcus luteus to produce the ester (3) to 85 mM (26.6 g/L) within 5 h. The 5 L scale biotransformation process was then successfully scaled up to a 70 L bioreactor; 3 was produced to over 70 mM (21.9 g/L) in the culture medium 6 h after biotransformation. This study demonstrated that the BVMO-based whole-cell reactions can be applied for large-scale biotransformations. PMID:27311560

Decomposing Multifractal Crossovers

PubMed Central

Nagy, Zoltan; Mukli, Peter; Herman, Peter; Eke, Andras

2017-01-01

Physiological processes—such as, the brain's resting-state electrical activity or hemodynamic fluctuations—exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for the topology of multifractal metrics free of the masking effect of the underlying random noise. PMID:28798694

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale

PubMed Central

Groarke, Jenny M.; Hogan, Michael J.

2018-01-01

Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML) and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants (N = 1,191, 17–66 years, M = 22.04, SD = 6.23, 326 males). Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML) scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity, and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML—the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross-sectional studies. PMID:29706916

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale.

PubMed

Groarke, Jenny M; Hogan, Michael J

2018-01-01

Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML) and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants ( N = 1,191, 17-66 years, M = 22.04, SD = 6.23, 326 males). Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML) scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity , and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML-the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross-sectional studies.

Diversification dynamics, species sorting, and changes in the functional diversity of marine benthic gastropods during the Pliocene-Quaternary at temperate western South America.

PubMed

Rivadeneira, Marcelo M; Nielsen, Sven N

2017-01-01

Functional diversity based on species traits is a powerful tool to investigate how changes in species richness and composition affect ecosystem functioning. However, studies aimed at understanding changes in functional diversity over large temporal and spatial scales are still scant. Here we evaluate the combined effect of diversification and species sorting on functional diversity of fossil marine gastropods during the Pliocene-Quaternary transition in the Pacific coast of South America. We analyzed a total of 172 species in 29 Pliocene and 97 Quaternary sites. Each species was characterized according to six functional traits: body size, feeding type, mobility, attachment, life-habit, and larval mode. Functional diversity was estimated according to four indexes (functional richness, evenness, divergence and dispersion) based on functional traits measured. Extrapolated species richness showed a slight yet not significant decrease from the Pliocene to the Quaternary despite the fact that a large faunal turnover took place; furthermore, a large extinction of Pliocene species (61-76%) was followed by a high pulse of appearances (49-56%) during the Quaternary. Three out of four indices of functional diversity (evenness, divergence and dispersion) increased significantly towards the Quaternary which is more than expected under a random turnover of species. The increase in functional diversity is associated with a loss of large-sized carnivore forms, which tended to be replaced by small-sized grazers. Hence, this trait-selective species turnover, even in the absence of significant changes in species richness, likely had a large effect and has shaped the functional diversity of present-day assemblages.

Large-scale protein/antibody patterning with limiting unspecific adsorption

NASA Astrophysics Data System (ADS)

Fedorenko, Viktoriia; Bechelany, Mikhael; Janot, Jean-Marc; Smyntyna, Valentyn; Balme, Sebastien

2017-10-01

A simple synthetic route based on nanosphere lithography has been developed in order to design a large-scale nanoarray for specific control of protein anchoring. This technique based on two-dimensional (2D) colloidal crystals composed of polystyrene spheres allows the easy and inexpensive fabrication of large arrays (up to several centimeters) by reducing the cost. A silicon wafer coated with a thin adhesion layer of chromium (15 nm) and a layer of gold (50 nm) is used as a substrate. PS spheres are deposited on the gold surface using the floating-transferring technique. The PS spheres were then functionalized with PEG-biotin and the defects by self-assembly monolayer (SAM) PEG to prevent unspecific adsorption. Using epifluorescence microscopy, we show that after immersion of sample on target protein (avidin and anti-avidin) solution, the latter are specifically located on polystyrene spheres. Thus, these results are meaningful for exploration of devices based on a large-scale nanoarray of PS spheres and can be used for detection of target proteins or simply to pattern a surface with specific proteins.

Effectively-truncated large-scale shell-model calculations and nuclei around 100Sn

NASA Astrophysics Data System (ADS)

Gargano, A.; Coraggio, L.; Itaco, N.

2017-09-01

This paper presents a short overview of a procedure we have recently introduced, dubbed the double-step truncation method, which is aimed to reduce the computational complexity of large-scale shell-model calculations. Within this procedure, one starts with a realistic shell-model Hamiltonian defined in a large model space, and then, by analyzing the effective single particle energies of this Hamiltonian as a function of the number of valence protons and/or neutrons, reduced model spaces are identified containing only the single-particle orbitals relevant to the description of the spectroscopic properties of a certain class of nuclei. As a final step, new effective shell-model Hamiltonians defined within the reduced model spaces are derived by way of a unitary transformation of the original large-scale Hamiltonian. A detailed account of this transformation is given and the merit of the double-step truncation method is illustrated by discussing few selected results for 96Mo, described as four protons and four neutrons outside 88Sr. Some new preliminary results for light odd-tin isotopes from A = 101 to 107 are also reported.

THE DEPENDENCE OF STELLAR MASS AND ANGULAR MOMENTUM LOSSES ON LATITUDE AND THE INTERACTION OF ACTIVE REGION AND DIPOLAR MAGNETIC FIELDS

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

Garraffo, Cecilia; Drake, Jeremy J.; Cohen, Ofer

Rotation evolution of late-type stars is dominated by magnetic braking and the underlying factors that control this angular momentum loss are important for the study of stellar spin-down. In this work, we study angular momentum loss as a function of two different aspects of magnetic activity using a calibrated Alfvén wave-driven magnetohydrodynamic wind model: the strengths of magnetic spots and their distribution in latitude. By driving the model using solar and modified solar surface magnetograms, we show that the topology of the field arising from the net interaction of both small-scale and large-scale field is important for spin-down rates andmore » that angular momentum loss is not a simple function of large scale magnetic field strength. We find that changing the latitude of magnetic spots can modify mass and angular momentum loss rates by a factor of two. The general effect that causes these differences is the closing down of large-scale open field at mid- and high-latitudes by the addition of the small-scale field. These effects might give rise to modulation of mass and angular momentum loss through stellar cycles, and present a problem for ab initio attempts to predict stellar spin-down based on wind models. For all the magnetogram cases considered here, from dipoles to various spotted distributions, we find that angular momentum loss is dominated by the mass loss at mid-latitudes. The spin-down torque applied by magnetized winds therefore acts at specific latitudes and is not evenly distributed over the stellar surface, though this aspect is unlikely to be important for understanding spin-down and surface flows on stars.« less

Size and structure of Chlorella zofingiensis /FeCl 3 flocs in a shear flow: Algae Floc Structure

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

Wyatt, Nicholas B.; O'Hern, Timothy J.; Shelden, Bion

Flocculation is a promising method to overcome the economic hurdle to separation of algae from its growth medium in large scale operations. But, understanding of the floc structure and the effects of shear on the floc structure are crucial to the large scale implementation of this technique. The floc structure is important because it determines, in large part, the density and settling behavior of the algae. Freshwater algae floc size distributions and fractal dimensions are presented as a function of applied shear rate in a Couette cell using ferric chloride as a flocculant. Comparisons are made with measurements made formore » a polystyrene microparticle model system taken here as well as reported literature results. The algae floc size distributions are found to be self-preserving with respect to shear rate, consistent with literature data for polystyrene. Moreover, three fractal dimensions are calculated which quantitatively characterize the complexity of the floc structure. Low shear rates result in large, relatively dense packed flocs which elongate and fracture as the shear rate is increased. Our results presented here provide crucial information for economically implementing flocculation as a large scale algae harvesting strategy.« less

The 'cube' meta-model for the information system of large health sector organizations--a (platform neutral) mapping tool to integrate information system development with changing business functions and organizational development.

PubMed

Balkányi, László

2002-01-01

To develop information systems (IS) in the changing environment of the health sector, a simple but throughout model, avoiding the techno-jargon of informatics, might be useful for the top management. A platform neutral, extensible, transparent conceptual model should be established. Limitations of current methods lead to a simple, but comprehensive mapping, in the form of a three-dimensional cube. The three 'orthogonal' views are (a) organization functionality, (b) organizational structures and (c) information technology. Each of the cube-sides is described according to its nature. This approach enables to define any kind of an IS component as a certain point/layer/domain of the cube and enables also the management to label all IS components independently form any supplier(s) and/or any specific platform. The model handles changes in organization structure, business functionality and the serving info-system independently form each other. Practical application extends to (a) planning complex, new ISs, (b) guiding development of multi-vendor, multi-site ISs, (c) supporting large-scale public procurement procedures and the contracting, implementation phase by establishing a platform neutral reference, (d) keeping an exhaustive inventory of an existing large-scale system, that handles non-tangible aspects of the IS.

Instanton dominance over αs at low momenta from lattice QCD simulations at Nf = 0, Nf = 2 + 1 and Nf = 2 + 1 + 1

NASA Astrophysics Data System (ADS)

Athenodorou, Andreas; Boucaud, Philippe; de Soto, Feliciano; Rodríguez-Quintero, José; Zafeiropoulos, Savvas

2018-03-01

We report on an instanton-based analysis of the gluon Green functions in the Landau gauge for low momenta; in particular we use lattice results for αs in the symmetric momentum subtraction scheme (MOM) for large-volume lattice simulations. We have exploited quenched gauge field configurations, Nf = 0, with both Wilson and tree-level Symanzik improved actions, and unquenched ones with Nf = 2 + 1 and Nf = 2 + 1 + 1 dynamical flavors (domain wall and twisted-mass fermions, respectively). We show that the dominance of instanton correlations on the low-momenta gluon Green functions can be applied to the determination of phenomenological parameters of the instanton liquid and, eventually, to a determination of the lattice spacing. We furthermore apply the Gradient Flow to remove short-distance fluctuations. The Gradient Flow gets rid of the QCD scale, ΛQCD, and reveals that the instanton prediction extents to large momenta. For those gauge field configurations free of quantum fluctuations, the direct study of topological charge density shows the appearance of large-scale lumps that can be identified as instantons, giving access to a direct study of the instanton density and size distribution that is compatible with those extracted from the analysis of the Green functions.

Predicting Hydrologic Function With Aquatic Gene Fragments

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Differential Item Functioning for Accommodated Students with Disabilities: Effect of Differences in Proficiency Distributions

ERIC Educational Resources Information Center

Quesen, Sarah

2016-01-01

When studying differential item functioning (DIF) with students with disabilities (SWD) focal groups typically suffer from small sample size, whereas the reference group population is usually large. This makes it possible for a researcher to select a sample from the reference population to be similar to the focal group on the ability scale. Doing…

Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

2016-01-01

In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

The Experiences and Needs of Female Adults with High-Functioning Autism Spectrum Disorder

ERIC Educational Resources Information Center

Baldwin, Susanna; Costley, Debra

2016-01-01

There is limited large-scale research into the lived experiences of female adults who have an autism spectrum disorder with no co-occurring intellectual disability. Drawing on the findings of an Australia-wide survey, this report presents self-report data from n = 82 women with high-functioning autism spectrum disorder in the areas of health,…

Minimum entropy deconvolution and blind equalisation

NASA Technical Reports Server (NTRS)

Satorius, E. H.; Mulligan, J. J.

1992-01-01

Relationships between minimum entropy deconvolution, developed primarily for geophysics applications, and blind equalization are pointed out. It is seen that a large class of existing blind equalization algorithms are directly related to the scale-invariant cost functions used in minimum entropy deconvolution. Thus the extensive analyses of these cost functions can be directly applied to blind equalization, including the important asymptotic results of Donoho.

Using a Mixture IRT Model to Understand English Learner Performance on Large-Scale Assessments

ERIC Educational Resources Information Center

Shea, Christine A.

2013-01-01

The purpose of this study was to determine whether an eighth grade state-level math assessment contained items that function differentially (DIF) for English Learner students (EL) as compared to English Only students (EO) and if so, what factors might have caused DIF. To determine this, Differential Item Functioning (DIF) analysis was employed.…

Exploring the Alaskan black spruce ecosystem: variability in species composition, ecosystem function, and fire history

Treesearch

T.N. Hollingsworth

2008-01-01

In this overview, I present extensive studies looking at the structure and function of the black spruce (Picea mariana) ecosystem of the boreal region of interior Alaska. One of the studies provides a classification of black spruce communities, the most abundant forest type in the region. Other studies examine large-scale processes that drive this...

A Numerical Comparison of Barrier and Modified Barrier Methods for Large-Scale Bound-Constrained Optimization

NASA Technical Reports Server (NTRS)

Nash, Stephen G.; Polyak, R.; Sofer, Ariela

1994-01-01

When a classical barrier method is applied to the solution of a nonlinear programming problem with inequality constraints, the Hessian matrix of the barrier function becomes increasingly ill-conditioned as the solution is approached. As a result, it may be desirable to consider alternative numerical algorithms. We compare the performance of two methods motivated by barrier functions. The first is a stabilized form of the classical barrier method, where a numerically stable approximation to the Newton direction is used when the barrier parameter is small. The second is a modified barrier method where a barrier function is applied to a shifted form of the problem, and the resulting barrier terms are scaled by estimates of the optimal Lagrange multipliers. The condition number of the Hessian matrix of the resulting modified barrier function remains bounded as the solution to the constrained optimization problem is approached. Both of these techniques can be used in the context of a truncated-Newton method, and hence can be applied to large problems, as well as on parallel computers. In this paper, both techniques are applied to problems with bound constraints and we compare their practical behavior.

Versatile Gene-Specific Sequence Tags for Arabidopsis Functional Genomics: Transcript Profiling and Reverse Genetics Applications

PubMed Central

Hilson, Pierre; Allemeersch, Joke; Altmann, Thomas; Aubourg, Sébastien; Avon, Alexandra; Beynon, Jim; Bhalerao, Rishikesh P.; Bitton, Frédérique; Caboche, Michel; Cannoot, Bernard; Chardakov, Vasil; Cognet-Holliger, Cécile; Colot, Vincent; Crowe, Mark; Darimont, Caroline; Durinck, Steffen; Eickhoff, Holger; de Longevialle, Andéol Falcon; Farmer, Edward E.; Grant, Murray; Kuiper, Martin T.R.; Lehrach, Hans; Léon, Céline; Leyva, Antonio; Lundeberg, Joakim; Lurin, Claire; Moreau, Yves; Nietfeld, Wilfried; Paz-Ares, Javier; Reymond, Philippe; Rouzé, Pierre; Sandberg, Goran; Segura, Maria Dolores; Serizet, Carine; Tabrett, Alexandra; Taconnat, Ludivine; Thareau, Vincent; Van Hummelen, Paul; Vercruysse, Steven; Vuylsteke, Marnik; Weingartner, Magdalena; Weisbeek, Peter J.; Wirta, Valtteri; Wittink, Floyd R.A.; Zabeau, Marc; Small, Ian

2004-01-01

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics. PMID:15489341

Covariation in Plant Functional Traits and Soil Fertility within Two Species-Rich Forests

PubMed Central

Liu, Xiaojuan; Swenson, Nathan G.; Wright, S. Joseph; Zhang, Liwen; Song, Kai; Du, Yanjun; Zhang, Jinlong; Mi, Xiangcheng; Ren, Haibao; Ma, Keping

2012-01-01

The distribution of plant species along environmental gradients is expected to be predictable based on organismal function. Plant functional trait research has shown that trait values generally vary predictably along broad-scale climatic and soil gradients. This work has also demonstrated that at any one point along these gradients there is a large amount of interspecific trait variation. The present research proposes that this variation may be explained by the local-scale sorting of traits along soil fertility and acidity axes. Specifically, we predicted that trait values associated with high resource acquisition and growth rates would be found on soils that are more fertile and less acidic. We tested the expected relationships at the species-level and quadrat-level (20×20 m) using two large forest plots in Panama and China that contain over 450 species combined. Predicted relationships between leaf area and wood density and soil fertility were supported in some instances, but the majority of the predicted relationships were rejected. Alternative resource axes, such as light gradients, therefore likely play a larger role in determining the interspecific variability in plant functional traits in the two forests studied. PMID:22509355

Altered contralateral sensorimotor system organization after experimental hemispherectomy: a structural and functional connectivity study.

PubMed

Otte, Willem M; van der Marel, Kajo; van Meer, Maurits P A; van Rijen, Peter C; Gosselaar, Peter H; Braun, Kees P J; Dijkhuizen, Rick M

2015-08-01

Hemispherectomy is often followed by remarkable recovery of cognitive and motor functions. This reflects plastic capacities of the remaining hemisphere, involving large-scale structural and functional adaptations. Better understanding of these adaptations may (1) provide new insights in the neuronal configuration and rewiring that underlies sensorimotor outcome restoration, and (2) guide development of rehabilitation strategies to enhance recovery after hemispheric lesioning. We assessed brain structure and function in a hemispherectomy model. With MRI we mapped changes in white matter structural integrity and gray matter functional connectivity in eight hemispherectomized rats, compared with 12 controls. Behavioral testing involved sensorimotor performance scoring. Diffusion tensor imaging and resting-state functional magnetic resonance imaging were acquired 7 and 49 days post surgery. Hemispherectomy caused significant sensorimotor deficits that largely recovered within 2 weeks. During the recovery period, fractional anisotropy was maintained and white matter volume and axial diffusivity increased in the contralateral cerebral peduncle, suggestive of preserved or improved white matter integrity despite overall reduced white matter volume. This was accompanied by functional adaptations in the contralateral sensorimotor network. The observed white matter modifications and reorganization of functional network regions may provide handles for rehabilitation strategies improving functional recovery following large lesions.

The Angular Correlation Function of Galaxies from Early Sloan Digital Sky Survey Data

NASA Astrophysics Data System (ADS)

Connolly, Andrew J.; Scranton, Ryan; Johnston, David; Dodelson, Scott; Eisenstein, Daniel J.; Frieman, Joshua A.; Gunn, James E.; Hui, Lam; Jain, Bhuvnesh; Kent, Stephen; Loveday, Jon; Nichol, Robert C.; O'Connell, Liam; Postman, Marc; Scoccimarro, Roman; Sheth, Ravi K.; Stebbins, Albert; Strauss, Michael A.; Szalay, Alexander S.; Szapudi, István; Tegmark, Max; Vogeley, Michael S.; Zehavi, Idit; Annis, James; Bahcall, Neta; Brinkmann, J.; Csabai, István; Doi, Mamoru; Fukugita, Masataka; Hennessy, G. S.; Hindsley, Robert; Ichikawa, Takashi; Ivezić, Željko; Kim, Rita S. J.; Knapp, Gillian R.; Kunszt, Peter; Lamb, D. Q.; Lee, Brian C.; Lupton, Robert H.; McKay, Timothy A.; Munn, Jeff; Peoples, John; Pier, Jeff; Rockosi, Constance; Schlegel, David; Stoughton, Christopher; Tucker, Douglas L.; Yanny, Brian; York, Donald G.

2002-11-01

The Sloan Digital Sky Survey is one of the first multicolor photometric and spectroscopic surveys designed to measure the statistical properties of galaxies within the local universe. In this paper we present some of the initial results on the angular two-point correlation function measured from the early SDSS galaxy data. The form of the correlation function, over the magnitude interval 18

Activity-based protein profiling for biochemical pathway discovery in cancer

PubMed Central

Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.

2011-01-01

Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252

Managing large-scale workflow execution from resource provisioning to provenance tracking: The CyberShake example

USGS Publications Warehouse

Deelman, E.; Callaghan, S.; Field, E.; Francoeur, H.; Graves, R.; Gupta, N.; Gupta, V.; Jordan, T.H.; Kesselman, C.; Maechling, P.; Mehringer, J.; Mehta, G.; Okaya, D.; Vahi, K.; Zhao, L.

2006-01-01

This paper discusses the process of building an environment where large-scale, complex, scientific analysis can be scheduled onto a heterogeneous collection of computational and storage resources. The example application is the Southern California Earthquake Center (SCEC) CyberShake project, an analysis designed to compute probabilistic seismic hazard curves for sites in the Los Angeles area. We explain which software tools were used to build to the system, describe their functionality and interactions. We show the results of running the CyberShake analysis that included over 250,000 jobs using resources available through SCEC and the TeraGrid. ?? 2006 IEEE.

DIALOG: An executive computer program for linking independent programs

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Watson, D. A.

1973-01-01

A very large scale computer programming procedure called the DIALOG executive system was developed for the CDC 6000 series computers. The executive computer program, DIALOG, controls the sequence of execution and data management function for a library of independent computer programs. Communication of common information is accomplished by DIALOG through a dynamically constructed and maintained data base of common information. Each computer program maintains its individual identity and is unaware of its contribution to the large scale program. This feature makes any computer program a candidate for use with the DIALOG executive system. The installation and uses of the DIALOG executive system are described.

Photometry of icy satellites: How important is multiple scattering in diluting shadows?

NASA Technical Reports Server (NTRS)

Buratti, B.; Veverka, J.

1984-01-01

Voyager observations have shown that the photometric properties of icy satellites are influenced significantly by large-scale roughness elements on the surfaces. While recent progress was made in treating the photometric effects of macroscopic roughness, it is still the case that even the most complete models do not account for the effects of multiple scattering fully. Multiple scattering dilutes shadows caused by large-scale features, yet for any specific model it is difficult to calculate the amount of dilution as a function of albedo. Accordingly, laboratory measurements were undertaken using the Cornell Goniometer to evaluate the magnitude of the effect.

HRLSim: a high performance spiking neural network simulator for GPGPU clusters.

PubMed

Minkovich, Kirill; Thibeault, Corey M; O'Brien, Michael John; Nogin, Aleksey; Cho, Youngkwan; Srinivasa, Narayan

2014-02-01

Modeling of large-scale spiking neural models is an important tool in the quest to understand brain function and subsequently create real-world applications. This paper describes a spiking neural network simulator environment called HRL Spiking Simulator (HRLSim). This simulator is suitable for implementation on a cluster of general purpose graphical processing units (GPGPUs). Novel aspects of HRLSim are described and an analysis of its performance is provided for various configurations of the cluster. With the advent of inexpensive GPGPU cards and compute power, HRLSim offers an affordable and scalable tool for design, real-time simulation, and analysis of large-scale spiking neural networks.

Distributed intrusion detection system based on grid security model

NASA Astrophysics Data System (ADS)

Su, Jie; Liu, Yahui

2008-03-01

Grid computing has developed rapidly with the development of network technology and it can solve the problem of large-scale complex computing by sharing large-scale computing resource. In grid environment, we can realize a distributed and load balance intrusion detection system. This paper first discusses the security mechanism in grid computing and the function of PKI/CA in the grid security system, then gives the application of grid computing character in the distributed intrusion detection system (IDS) based on Artificial Immune System. Finally, it gives a distributed intrusion detection system based on grid security system that can reduce the processing delay and assure the detection rates.