A virtual pebble game to ensemble average graph rigidity.

PubMed

González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J

2015-01-01

The body-bar Pebble Game (PG) algorithm is commonly used to calculate network rigidity properties in proteins and polymeric materials. To account for fluctuating interactions such as hydrogen bonds, an ensemble of constraint topologies are sampled, and average network properties are obtained by averaging PG characterizations. At a simpler level of sophistication, Maxwell constraint counting (MCC) provides a rigorous lower bound for the number of internal degrees of freedom (DOF) within a body-bar network, and it is commonly employed to test if a molecular structure is globally under-constrained or over-constrained. MCC is a mean field approximation (MFA) that ignores spatial fluctuations of distance constraints by replacing the actual molecular structure by an effective medium that has distance constraints globally distributed with perfect uniform density. The Virtual Pebble Game (VPG) algorithm is a MFA that retains spatial inhomogeneity in the density of constraints on all length scales. Network fluctuations due to distance constraints that may be present or absent based on binary random dynamic variables are suppressed by replacing all possible constraint topology realizations with the probabilities that distance constraints are present. The VPG algorithm is isomorphic to the PG algorithm, where integers for counting "pebbles" placed on vertices or edges in the PG map to real numbers representing the probability to find a pebble. In the VPG, edges are assigned pebble capacities, and pebble movements become a continuous flow of probability within the network. Comparisons between the VPG and average PG results over a test set of proteins and disordered lattices demonstrate the VPG quantitatively estimates the ensemble average PG results well. The VPG performs about 20% faster than one PG, and it provides a pragmatic alternative to averaging PG rigidity characteristics over an ensemble of constraint topologies. The utility of the VPG falls in between the most accurate but slowest method of ensemble averaging over hundreds to thousands of independent PG runs, and the fastest but least accurate MCC.

Creation of the BMA ensemble for SST using a parallel processing technique

NASA Astrophysics Data System (ADS)

Kim, Kwangjin; Lee, Yang Won

2013-10-01

Despite the same purpose, each satellite product has different value because of its inescapable uncertainty. Also the satellite products have been calculated for a long time, and the kinds of the products are various and enormous. So the efforts for reducing the uncertainty and dealing with enormous data will be necessary. In this paper, we create an ensemble Sea Surface Temperature (SST) using MODIS Aqua, MODIS Terra and COMS (Communication Ocean and Meteorological Satellite). We used Bayesian Model Averaging (BMA) as ensemble method. The principle of the BMA is synthesizing the conditional probability density function (PDF) using posterior probability as weight. The posterior probability is estimated using EM algorithm. The BMA PDF is obtained by weighted average. As the result, the ensemble SST showed the lowest RMSE and MAE, which proves the applicability of BMA for satellite data ensemble. As future work, parallel processing techniques using Hadoop framework will be adopted for more efficient computation of very big satellite data.

Blending of Radial HF Radar Surface Current and Model Using ETKF Scheme For The Sunda Strait

NASA Astrophysics Data System (ADS)

Mujiasih, Subekti; Riyadi, Mochammad; Wandono, Dr; Wayan Suardana, I.; Nyoman Gede Wiryajaya, I.; Nyoman Suarsa, I.; Hartanto, Dwi; Barth, Alexander; Beckers, Jean-Marie

2017-04-01

Preliminary study of data blending of surface current for Sunda Strait-Indonesia has been done using the analysis scheme of the Ensemble Transform Kalman Filter (ETKF). The method is utilized to combine radial velocity from HF Radar and u and v component of velocity from Global Copernicus - Marine environment monitoring service (CMEMS) model. The initial ensemble is based on the time variability of the CMEMS model result. Data tested are from 2 CODAR Seasonde radar sites in Sunda Strait and 2 dates such as 09 September 2013 and 08 February 2016 at 12.00 UTC. The radial HF Radar data has a hourly temporal resolution, 20-60 km of spatial range, 3 km of range resolution, 5 degree of angular resolution and spatial resolution and 11.5-14 MHz of frequency range. The u and v component of the model velocity represents a daily mean with 1/12 degree spatial resolution. The radial data from one HF radar site is analyzed and the result compared to the equivalent radial velocity from CMEMS for the second HF radar site. Error checking is calculated by root mean squared error (RMSE). Calculation of ensemble analysis and ensemble mean is using Sangoma software package. The tested R which represents observation error covariance matrix, is a diagonal matrix with diagonal elements equal 0.05, 0.5 or 1.0 m2/s2. The initial ensemble members comes from a model simulation spanning a month (September 2013 or February 2016), one year (2013) or 4 years (2013-2016). The spatial distribution of the radial current are analyzed and the RMSE values obtained from independent HF radar station are optimized. It was verified that the analysis reproduces well the structure included in the analyzed HF radar data. More importantly, the analysis was also improved relative to the second independent HF radar site. RMSE of the improved analysis is better than first HF Radar site Analysis. The best result of the blending exercise was obtained for observation error variance equal to 0.05 m2/s2. This study is still preliminary step, but it gives promising result for bigger size of data, combining other model and further development. Keyword: HF Radar, Sunda Strait, ETKF, CMEMS

Experimental investigation of turbulent diffusion of slightly buoyant droplets in locally isotropic turbulence

NASA Astrophysics Data System (ADS)

Gopalan, Balaji; Malkiel, Edwin; Katz, Joseph

2008-09-01

High-speed inline digital holographic cinematography is used for studying turbulent diffusion of slightly buoyant 0.5-1.2 mm diameter diesel droplets and 50 μm diameter neutral density particles. Experiments are performed in a 50×50×70 mm3 sample volume in a controlled, nearly isotropic turbulence facility, which is characterized by two dimensional particle image velocimetry. An automated tracking program has been used for measuring velocity time history of more than 17 000 droplets and 15 000 particles. For most of the present conditions, rms values of horizontal droplet velocity exceed those of the fluid. The rms values of droplet vertical velocity are higher than those of the fluid only for the highest turbulence level. The turbulent diffusion coefficient is calculated by integration of the ensemble-averaged Lagrangian velocity autocovariance. Trends of the asymptotic droplet diffusion coefficient are examined by noting that it can be viewed as a product of a mean square velocity and a diffusion time scale. To compare the effects of turbulence and buoyancy, the turbulence intensity (ui') is scaled by the droplet quiescent rise velocity (Uq). The droplet diffusion coefficients in horizontal and vertical directions are lower than those of the fluid at low normalized turbulence intensity, but exceed it with increasing normalized turbulence intensity. For most of the present conditions the droplet horizontal diffusion coefficient is higher than the vertical diffusion coefficient, consistent with trends of the droplet velocity fluctuations and in contrast to the trends of the diffusion timescales. The droplet diffusion coefficients scaled by the product of turbulence intensity and an integral length scale are a monotonically increasing function of ui'/Uq.

Experimental Demonstration of Quantum Stationary Light Pulses in an Atomic Ensemble

NASA Astrophysics Data System (ADS)

Park, Kwang-Kyoon; Cho, Young-Wook; Chough, Young-Tak; Kim, Yoon-Ho

2018-04-01

We report an experimental demonstration of the nonclassical stationary light pulse (SLP) in a cold atomic ensemble. A single collective atomic excitation is created and heralded by detecting a Stokes photon in the spontaneous Raman scattering process. The heralded single atomic excitation is converted into a single stationary optical excitation or the single-photon SLP, whose effective group velocity is zero, effectively forming a trapped single-photon pulse within the cold atomic ensemble. The single-photon SLP is then released from the atomic ensemble as an anti-Stokes photon after a specified trapping time. The second-order correlation measurement between the Stokes and anti-Stokes photons reveals the nonclassical nature of the single-photon SLP. Our work paves the way toward quantum nonlinear optics without a cavity.

How well the Reliable Ensemble Averaging Method (REA) for 15 CMIP5 GCMs simulations works for Mexico?

NASA Astrophysics Data System (ADS)

Colorado, G.; Salinas, J. A.; Cavazos, T.; de Grau, P.

2013-05-01

15 CMIP5 GCMs precipitation simulations were combined in a weighted ensemble using the Reliable Ensemble Averaging (REA) method, obtaining the weight of each model. This was done for a historical period (1961-2000) and for the future emissions based on low (RCP4.5) and high (RCP8.5) radiating forcing for the period 2075-2099. The annual cycle of simple ensemble of the historical GCMs simulations, the historical REA average and the Climate Research Unit (CRU TS3.1) database was compared in four zones of México. In the case of precipitation we can see the improvements by using the REA method, especially in the two northern zones of México where the REA average is more close to the observations (CRU) that the simple average. However in the southern zones although there is an improvement it is not as good as it is in the north, particularly in the southeast where instead of the REA average is able to reproduce qualitatively good the annual cycle with the mid-summer drought it was greatly underestimated. The main reason is because the precipitation is underestimated for all the models and the mid-summer drought do not even exists in some models. In the REA average of the future scenarios, as we can expected, the most drastic decrease in precipitation was simulated using the RCP8.5 especially in the monsoon area and in the south of Mexico in summer and in winter. In the center and southern of Mexico however, the same scenario in autumn simulates an increase of precipitation.

Coaxial volumetric velocimetry

NASA Astrophysics Data System (ADS)

Schneiders, Jan F. G.; Scarano, Fulvio; Jux, Constantin; Sciacchitano, Andrea

2018-06-01

This study describes the working principles of the coaxial volumetric velocimeter (CVV) for wind tunnel measurements. The measurement system is derived from the concept of tomographic PIV in combination with recent developments of Lagrangian particle tracking. The main characteristic of the CVV is its small tomographic aperture and the coaxial arrangement between the illumination and imaging directions. The system consists of a multi-camera arrangement subtending only few degrees solid angle and a long focal depth. Contrary to established PIV practice, laser illumination is provided along the same direction as that of the camera views, reducing the optical access requirements to a single viewing direction. The laser light is expanded to illuminate the full field of view of the cameras. Such illumination and imaging conditions along a deep measurement volume dictate the use of tracer particles with a large scattering area. In the present work, helium-filled soap bubbles are used. The fundamental principles of the CVV in terms of dynamic velocity and spatial range are discussed. Maximum particle image density is shown to limit tracer particle seeding concentration and instantaneous spatial resolution. Time-averaged flow fields can be obtained at high spatial resolution by ensemble averaging. The use of the CVV for time-averaged measurements is demonstrated in two wind tunnel experiments. After comparing the CVV measurements with the potential flow in front of a sphere, the near-surface flow around a complex wind tunnel model of a cyclist is measured. The measurements yield the volumetric time-averaged velocity and vorticity field. The measurements of the streamlines in proximity of the surface give an indication of the skin-friction lines pattern, which is of use in the interpretation of the surface flow topology.

Quantifying nonergodicity in nonautonomous dissipative dynamical systems: An application to climate change

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Ensemble representations: effects of set size and item heterogeneity on average size perception.

PubMed

Marchant, Alexander P; Simons, Daniel J; de Fockert, Jan W

2013-02-01

Observers can accurately perceive and evaluate the statistical properties of a set of objects, forming what is now known as an ensemble representation. The accuracy and speed with which people can judge the mean size of a set of objects have led to the proposal that ensemble representations of average size can be computed in parallel when attention is distributed across the display. Consistent with this idea, judgments of mean size show little or no decrement in accuracy when the number of objects in the set increases. However, the lack of a set size effect might result from the regularity of the item sizes used in previous studies. Here, we replicate these previous findings, but show that judgments of mean set size become less accurate when set size increases and the heterogeneity of the item sizes increases. This pattern can be explained by assuming that average size judgments are computed using a limited capacity sampling strategy, and it does not necessitate an ensemble representation computed in parallel across all items in a display. Copyright © 2012 Elsevier B.V. All rights reserved.

Inertial measurement unit pre-processors and post-flight STS-1 comparisons

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Mcconnell, J. G.

1981-01-01

The flight results show that the relative tri-redundant Inertial Measurement Unit IMU performance throughout the entire entry flight was within the expected accuracy. Comparisons are presented which show differences in the accumulated sensed velocity changes as measured by the tri-redundant IMUs (in Mean Equator and Equinox of 1950.0), differences in the equivalent inertial Euler angles as measured with respect to the M50 system, and finally, preliminary instrument calibrations determined relative to the ensemble average measurement set. Also, differences in the derived body axes rates and accelerations are presented. Because of the excellent performance of the IMUs during the STS-1 entry, the selection as to which particular IMU would best serve as the dynamic data source for entry reconstruction is arbitrary.

Field Measurements to Characterize Turbulent Inflow for Marine Hydrokinetic Devices - Marrowstone Island, WA

NASA Astrophysics Data System (ADS)

Richmond, M. C.; Thomson, J. M.; Durgesh, V.; Polagye, B. L.

2011-12-01

Field measurements are essential for developing an improved understanding of turbulent inflow conditions that affect the design and operation of marine and hydrokinetic (MHK) devices. The Marrowstone Island site in Puget Sound, Washington State is a potential location for installing MHK devices, as it experiences strong tides and associated currents. Here, field measurements from Nodule Point on the eastern side of Marrowstone Island are used to characterize the turbulence in terms of velocity variance as a function of length and time scales. The field measurements were performed using Acoustic Doppler Velocimetry (ADV) and Acoustic Doppler Current Profiler (ADCP) instruments. Both were deployed on a bottom-mounted tripod at the site by the Applied Physics Lab at the University of Washington (APL-UW). The ADV acquired single point, temporally resolved velocity data from 17-21 Feb 2011, at a height of 4.6 m above the seabed at a sampling frequency of 32 Hz. The ADCP measured the velocity profile over the water column from a height of 2.6 m above the seabed up to the sea-surface in 36 bins, with each bin of 0.5 m size. The ADCP acquired data from 11-27 Feb 2011 at a sampling frequency of 2 Hz. Analysis of the ADV measurements shows distinct dynamic regions by scale: anisotropic eddies at large scales, an isotropic turbulent cascade (-5/3 slope in frequency spectra) at mesoscales, and contamination by Doppler noise at small scales. While Doppler noise is an order of magnitude greater for the ADCP measurements, the turbulence bulk statistics are consistent between the two instruments. There are significant variations in turbulence statistics with stage of the tidal currents (i.e., from slack to non-slack tidal conditions), however an average turbulent intensity of 10% is a robust, canonical value for this site. The ADCP velocity profiles are useful in quantifying the variability in velocity along the water column, and the ensemble averaged velocity profiles may be described by a power law, commonly used to characterize boundary layers.

Not a Copernican observer: biased peculiar velocity statistics in the local Universe

NASA Astrophysics Data System (ADS)

Hellwing, Wojciech A.; Nusser, Adi; Feix, Martin; Bilicki, Maciej

2017-05-01

We assess the effect of the local large-scale structure on the estimation of two-point statistics of the observed radial peculiar velocities of galaxies. A large N-body simulation is used to examine these statistics from the perspective of random observers as well as 'Local Group-like' observers conditioned to reside in an environment resembling the observed Universe within 20 Mpc. The local environment systematically distorts the shape and amplitude of velocity statistics with respect to ensemble-averaged measurements made by a Copernican (random) observer. The Virgo cluster has the most significant impact, introducing large systematic deviations in all the statistics. For a simple 'top-hat' selection function, an idealized survey extending to ˜160 h-1 Mpc or deeper is needed to completely mitigate the effects of the local environment. Using shallower catalogues leads to systematic deviations of the order of 50-200 per cent depending on the scale considered. For a flat redshift distribution similar to the one of the CosmicFlows-3 survey, the deviations are even more prominent in both the shape and amplitude at all separations considered (≲100 h-1 Mpc). Conclusions based on statistics calculated without taking into account the impact of the local environment should be revisited.

Experimental validation benchmark data for CFD of transient convection from forced to natural with flow reversal on a vertical flat plate

DOE PAGES

Lance, Blake W.; Smith, Barton L.

2016-06-23

Transient convection has been investigated experimentally for the purpose of providing Computational Fluid Dynamics (CFD) validation benchmark data. A specialized facility for validation benchmark experiments called the Rotatable Buoyancy Tunnel was used to acquire thermal and velocity measurements of flow over a smooth, vertical heated plate. The initial condition was forced convection downward with subsequent transition to mixed convection, ending with natural convection upward after a flow reversal. Data acquisition through the transient was repeated for ensemble-averaged results. With simple flow geometry, validation data were acquired at the benchmark level. All boundary conditions (BCs) were measured and their uncertainties quantified.more » Temperature profiles on all four walls and the inlet were measured, as well as as-built test section geometry. Inlet velocity profiles and turbulence levels were quantified using Particle Image Velocimetry. System Response Quantities (SRQs) were measured for comparison with CFD outputs and include velocity profiles, wall heat flux, and wall shear stress. Extra effort was invested in documenting and preserving the validation data. Details about the experimental facility, instrumentation, experimental procedure, materials, BCs, and SRQs are made available through this paper. As a result, the latter two are available for download and the other details are included in this work.« less

Application of Generalized Feynman-Hellmann Theorem in Quantization of LC Circuit in Thermo Bath

NASA Astrophysics Data System (ADS)

Fan, Hong-Yi; Tang, Xu-Bing

For the quantized LC electric circuit, when taking the Joule thermal effect into account, we think that physical observables should be evaluated in the context of ensemble average. We then use the generalized Feynman-Hellmann theorem for ensemble average to calculate them, which seems convenient. Fluctuation of observables in various LC electric circuits in the presence of thermo bath growing with temperature is exhibited.

Calculating ensemble averaged descriptions of protein rigidity without sampling.

PubMed

González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J

2012-01-01

Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.

Boltzmann equations for a binary one-dimensional ideal gas.

PubMed

Boozer, A D

2011-09-01

We consider a time-reversal invariant dynamical model of a binary ideal gas of N molecules in one spatial dimension. By making time-asymmetric assumptions about the behavior of the gas, we derive Boltzmann and anti-Boltzmann equations that describe the evolution of the single-molecule velocity distribution functions for an ensemble of such systems. We show that for a special class of initial states of the ensemble one can obtain an exact expression for the N-molecule velocity distribution function, and we use this expression to rigorously prove that the time-asymmetric assumptions needed to derive the Boltzmann and anti-Boltzmann equations hold in the limit of large N. Our results clarify some subtle issues regarding the origin of the time asymmetry of Boltzmann's H theorem.

Diurnal cross-shore thermal exchange on a tropical forereef

NASA Astrophysics Data System (ADS)

Molina, L.; Pawlak, G.; Wells, J. R.; Monismith, S. G.; Merrifield, M. A.

2014-09-01

Observations of the velocity structure at the Kilo Nalu Observatory on the south shore of Oahu, Hawaii show that thermally driven baroclinic exchange is a dominant mechanism for cross-shore transport for this tropical forereef environment. Estimates of the exchange and net volume fluxes are comparable and show that the average residence time for the zone shoreward of the 12 m isobath is generally much less than 1 day. Although cross-shore wind stress influences the diurnal cross-shore exchange, surface heat flux is identified as the primary forcing mechanism from the phase relationships and from analysis of momentum and buoyancy balances for the record-averaged diurnal structure. Dynamic flow regimes are characterized based on a two-dimensional theoretical framework and the observations of the thermal structure at Kilo Nalu are shown to be in the unsteady temperature regime. Diurnal phasing and the cross-shore momentum balance suggest that turbulent stress divergence is an important driver of the baroclinic exchange. While the thermally driven exchange has a robust diurnal profile in the long term, there is high temporal variability on shorter time scales. Ensemble-averaged diurnal profiles indicate that the exchange is strongly modulated by surface heat flux, wind speed/direction, and alongshore velocity direction. The latter highlights the role of alongshore variability in the thermally driven exchange. Analysis of the thermal balance in the nearshore region indicates that the cross-shore exchange accounts for roughly 38% of the advective heat transport on a daily basis. This article was corrected on 10 OCT 2014. See the end of the full text for details.

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

PubMed

Strecker, Claas; Meyer, Bernd

2018-05-29

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Toward canonical ensemble distribution from self-guided Langevin dynamics simulation

NASA Astrophysics Data System (ADS)

Wu, Xiongwu; Brooks, Bernard R.

2011-04-01

This work derives a quantitative description of the conformational distribution in self-guided Langevin dynamics (SGLD) simulations. SGLD simulations employ guiding forces calculated from local average momentums to enhance low-frequency motion. This enhancement in low-frequency motion dramatically accelerates conformational search efficiency, but also induces certain perturbations in conformational distribution. Through the local averaging, we separate properties of molecular systems into low-frequency and high-frequency portions. The guiding force effect on the conformational distribution is quantitatively described using these low-frequency and high-frequency properties. This quantitative relation provides a way to convert between a canonical ensemble and a self-guided ensemble. Using example systems, we demonstrated how to utilize the relation to obtain canonical ensemble properties and conformational distributions from SGLD simulations. This development makes SGLD not only an efficient approach for conformational searching, but also an accurate means for conformational sampling.

Causal network in a deafferented non-human primate brain.

PubMed

Balasubramanian, Karthikeyan; Takahashi, Kazutaka; Hatsopoulos, Nicholas G

2015-01-01

De-afferented/efferented neural ensembles can undergo causal changes when interfaced to neuroprosthetic devices. These changes occur via recruitment or isolation of neurons, alterations in functional connectivity within the ensemble and/or changes in the role of neurons, i.e., excitatory/inhibitory. In this work, emergence of a causal network and changes in the dynamics are demonstrated for a deafferented brain region exposed to BMI (brain-machine interface) learning. The BMI was controlling a robot for reach-and-grasp behavior. And, the motor cortical regions used for the BMI were deafferented due to chronic amputation, and ensembles of neurons were decoded for velocity control of the multi-DOF robot. A generalized linear model-framework based Granger causality (GLM-GC) technique was used in estimating the ensemble connectivity. Model selection was based on the AIC (Akaike Information Criterion).

TESTING THE ASTEROSEISMIC SCALING RELATIONS FOR RED GIANTS WITH ECLIPSING BINARIES OBSERVED BY KEPLER

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

Gaulme, P.; McKeever, J.; Jackiewicz, J.

2016-12-01

Given the potential of ensemble asteroseismology for understanding fundamental properties of large numbers of stars, it is critical to determine the accuracy of the scaling relations on which these measurements are based. From several powerful validation techniques, all indications so far show that stellar radius estimates from the asteroseismic scaling relations are accurate to within a few percent. Eclipsing binary systems hosting at least one star with detectable solar-like oscillations constitute the ideal test objects for validating asteroseismic radius and mass inferences. By combining radial velocity (RV) measurements and photometric time series of eclipses, it is possible to determine themore » masses and radii of each component of a double-lined spectroscopic binary. We report the results of a four-year RV survey performed with the échelle spectrometer of the Astrophysical Research Consortium’s 3.5 m telescope and the APOGEE spectrometer at Apache Point Observatory. We compare the masses and radii of 10 red giants (RGs) obtained by combining radial velocities and eclipse photometry with the estimates from the asteroseismic scaling relations. We find that the asteroseismic scaling relations overestimate RG radii by about 5% on average and masses by about 15% for stars at various stages of RG evolution. Systematic overestimation of mass leads to underestimation of stellar age, which can have important implications for ensemble asteroseismology used for Galactic studies. As part of a second objective, where asteroseismology is used for understanding binary systems, we confirm that oscillations of RGs in close binaries can be suppressed enough to be undetectable, a hypothesis that was proposed in a previous work.« less

On the v-representability of ensemble densities of electron systems

NASA Astrophysics Data System (ADS)

Gonis, A.; Däne, M.

2018-05-01

Analogously to the case at zero temperature, where the density of the ground state of an interacting many-particle system determines uniquely (within an arbitrary additive constant) the external potential acting on the system, the thermal average of the density over an ensemble defined by the Boltzmann distribution at the minimum of the thermodynamic potential, or the free energy, determines the external potential uniquely (and not just modulo a constant) acting on a system described by this thermodynamic potential or free energy. The paper describes a formal procedure that generates the domain of a constrained search over general ensembles (at zero or elevated temperatures) that lead to a given density, including as a special case a density thermally averaged at a given temperature, and in the case of a v-representable density determines the external potential leading to the ensemble density. As an immediate consequence of the general formalism, the concept of v-representability is extended beyond the hitherto discussed case of ground state densities to encompass excited states as well. Specific application to thermally averaged densities solves the v-representability problem in connection with the Mermin functional in a manner analogous to that in which this problem was recently settled with respect to the Hohenberg and Kohn functional. The main formalism is illustrated with numerical results for ensembles of one-dimensional, non-interacting systems of particles under a harmonic potential.

On the v-representability of ensemble densities of electron systems

DOE PAGES

Gonis, A.; Dane, M.

2017-12-30

Analogously to the case at zero temperature, where the density of the ground state of an interacting many-particle system determines uniquely (within an arbitrary additive constant) the external potential acting on the system, the thermal average of the density over an ensemble defined by the Boltzmann distribution at the minimum of the thermodynamic potential, or the free energy, determines the external potential uniquely (and not just modulo a constant) acting on a system described by this thermodynamic potential or free energy. The study describes a formal procedure that generates the domain of a constrained search over general ensembles (at zeromore » or elevated temperatures) that lead to a given density, including as a special case a density thermally averaged at a given temperature, and in the case of a v-representable density determines the external potential leading to the ensemble density. As an immediate consequence of the general formalism, the concept of v-representability is extended beyond the hitherto discussed case of ground state densities to encompass excited states as well. Specific application to thermally averaged densities solves the v-representability problem in connection with the Mermin functional in a manner analogous to that in which this problem was recently settled with respect to the Hohenberg and Kohn functional. Finally, the main formalism is illustrated with numerical results for ensembles of one-dimensional, non-interacting systems of particles under a harmonic potential.« less

Post-processing method for wind speed ensemble forecast using wind speed and direction

NASA Astrophysics Data System (ADS)

Sofie Eide, Siri; Bjørnar Bremnes, John; Steinsland, Ingelin

2017-04-01

Statistical methods are widely applied to enhance the quality of both deterministic and ensemble NWP forecasts. In many situations, like wind speed forecasting, most of the predictive information is contained in one variable in the NWP models. However, in statistical calibration of deterministic forecasts it is often seen that including more variables can further improve forecast skill. For ensembles this is rarely taken advantage of, mainly due to that it is generally not straightforward how to include multiple variables. In this study, it is demonstrated how multiple variables can be included in Bayesian model averaging (BMA) by using a flexible regression method for estimating the conditional means. The method is applied to wind speed forecasting at 204 Norwegian stations based on wind speed and direction forecasts from the ECMWF ensemble system. At about 85 % of the sites the ensemble forecasts were improved in terms of CRPS by adding wind direction as predictor compared to only using wind speed. On average the improvements were about 5 %, but mainly for moderate to strong wind situations. For weak wind speeds adding wind direction had more or less neutral impact.

Using Bayesian Model Averaging (BMA) to calibrate probabilistic surface temperature forecasts over Iran

NASA Astrophysics Data System (ADS)

Soltanzadeh, I.; Azadi, M.; Vakili, G. A.

2011-07-01

Using Bayesian Model Averaging (BMA), an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM), with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME) of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009) over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast.

Langevin equation with fluctuating diffusivity: A two-state model

NASA Astrophysics Data System (ADS)

Miyaguchi, Tomoshige; Akimoto, Takuma; Yamamoto, Eiji

2016-07-01

Recently, anomalous subdiffusion, aging, and scatter of the diffusion coefficient have been reported in many single-particle-tracking experiments, though the origins of these behaviors are still elusive. Here, as a model to describe such phenomena, we investigate a Langevin equation with diffusivity fluctuating between a fast and a slow state. Namely, the diffusivity follows a dichotomous stochastic process. We assume that the sojourn time distributions of these two states are given by power laws. It is shown that, for a nonequilibrium ensemble, the ensemble-averaged mean-square displacement (MSD) shows transient subdiffusion. In contrast, the time-averaged MSD shows normal diffusion, but an effective diffusion coefficient transiently shows aging behavior. The propagator is non-Gaussian for short time and converges to a Gaussian distribution in a long-time limit; this convergence to Gaussian is extremely slow for some parameter values. For equilibrium ensembles, both ensemble-averaged and time-averaged MSDs show only normal diffusion and thus we cannot detect any traces of the fluctuating diffusivity with these MSDs. Therefore, as an alternative approach to characterizing the fluctuating diffusivity, the relative standard deviation (RSD) of the time-averaged MSD is utilized and it is shown that the RSD exhibits slow relaxation as a signature of the long-time correlation in the fluctuating diffusivity. Furthermore, it is shown that the RSD is related to a non-Gaussian parameter of the propagator. To obtain these theoretical results, we develop a two-state renewal theory as an analytical tool.

Statistical properties of a cloud ensemble - A numerical study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Simpson, Joanne; Soong, Su-Tzai

1987-01-01

The statistical properties of cloud ensembles under a specified large-scale environment, such as mass flux by cloud drafts and vertical velocity as well as the condensation and evaporation associated with these cloud drafts, are examined using a three-dimensional numerical cloud ensemble model described by Soong and Ogura (1980) and Tao and Soong (1986). The cloud drafts are classified as active and inactive, and separate contributions to cloud statistics in areas of different cloud activity are then evaluated. The model results compare well with results obtained from aircraft measurements of a well-organized ITCZ rainband that occurred on August 12, 1974, during the Global Atmospheric Research Program's Atlantic Tropical Experiment.

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Direct shear mapping - a new weak lensing tool

NASA Astrophysics Data System (ADS)

de Burgh-Day, C. O.; Taylor, E. N.; Webster, R. L.; Hopkins, A. M.

2015-08-01

We have developed a new technique called direct shear mapping (DSM) to measure gravitational lensing shear directly from observations of a single background source. The technique assumes the velocity map of an unlensed, stably rotating galaxy will be rotationally symmetric. Lensing distorts the velocity map making it asymmetric. The degree of lensing can be inferred by determining the transformation required to restore axisymmetry. This technique is in contrast to traditional weak lensing methods, which require averaging an ensemble of background galaxy ellipticity measurements, to obtain a single shear measurement. We have tested the efficacy of our fitting algorithm with a suite of systematic tests on simulated data. We demonstrate that we are in principle able to measure shears as small as 0.01. In practice, we have fitted for the shear in very low redshift (and hence unlensed) velocity maps, and have obtained null result with an error of ±0.01. This high-sensitivity results from analysing spatially resolved spectroscopic images (i.e. 3D data cubes), including not just shape information (as in traditional weak lensing measurements) but velocity information as well. Spirals and rotating ellipticals are ideal targets for this new technique. Data from any large Integral Field Unit (IFU) or radio telescope is suitable, or indeed any instrument with spatially resolved spectroscopy such as the Sydney-Australian-Astronomical Observatory Multi-Object Integral Field Spectrograph (SAMI), the Atacama Large Millimeter/submillimeter Array (ALMA), the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) and the Square Kilometer Array (SKA).

Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

NASA Astrophysics Data System (ADS)

Pollard, David; Chang, Won; Haran, Murali; Applegate, Patrick; DeConto, Robert

2016-05-01

A 3-D hybrid ice-sheet model is applied to the last deglacial retreat of the West Antarctic Ice Sheet over the last ˜ 20 000 yr. A large ensemble of 625 model runs is used to calibrate the model to modern and geologic data, including reconstructed grounding lines, relative sea-level records, elevation-age data and uplift rates, with an aggregate score computed for each run that measures overall model-data misfit. Two types of statistical methods are used to analyze the large-ensemble results: simple averaging weighted by the aggregate score, and more advanced Bayesian techniques involving Gaussian process-based emulation and calibration, and Markov chain Monte Carlo. The analyses provide sea-level-rise envelopes with well-defined parametric uncertainty bounds, but the simple averaging method only provides robust results with full-factorial parameter sampling in the large ensemble. Results for best-fit parameter ranges and envelopes of equivalent sea-level rise with the simple averaging method agree well with the more advanced techniques. Best-fit parameter ranges confirm earlier values expected from prior model tuning, including large basal sliding coefficients on modern ocean beds.

Aerodynamic Surface Stress Intermittency and Conditionally Averaged Turbulence Statistics

NASA Astrophysics Data System (ADS)

Anderson, W.

2015-12-01

Aeolian erosion of dry, flat, semi-arid landscapes is induced (and sustained) by kinetic energy fluxes in the aloft atmospheric surface layer. During saltation -- the mechanism responsible for surface fluxes of dust and sediment -- briefly suspended sediment grains undergo a ballistic trajectory before impacting and `splashing' smaller-diameter (dust) particles vertically. Conceptual models typically indicate that sediment flux, q (via saltation or drift), scales with imposed aerodynamic (basal) stress raised to some exponent, n, where n > 1. Since basal stress (in fully rough, inertia-dominated flows) scales with the incoming velocity squared, u^2, it follows that q ~ u^2n (where u is some relevant component of the above flow field, u(x,t)). Thus, even small (turbulent) deviations of u from its time-averaged value may play an enormously important role in aeolian activity on flat, dry landscapes. The importance of this argument is further augmented given that turbulence in the atmospheric surface layer exhibits maximum Reynolds stresses in the fluid immediately above the landscape. In order to illustrate the importance of surface stress intermittency, we have used conditional averaging predicated on aerodynamic surface stress during large-eddy simulation of atmospheric boundary layer flow over a flat landscape with momentum roughness length appropriate for the Llano Estacado in west Texas (a flat agricultural region that is notorious for dust transport). By using data from a field campaign to measure diurnal variability of aeolian activity and prevailing winds on the Llano Estacado, we have retrieved the threshold friction velocity (which can be used to compute threshold surface stress under the geostrophic balance with the Monin-Obukhov similarity theory). This averaging procedure provides an ensemble-mean visualization of flow structures responsible for erosion `events'. Preliminary evidence indicates that surface stress peaks are associated with the passage of inclined, high-momentum regions flanked by adjacent low-momentum regions. We will characterize geometric attributes of such structures and explore streamwise and vertical vorticity distribution within the conditionally averaged flow field.

Training set extension for SVM ensemble in P300-speller with familiar face paradigm.

PubMed

Li, Qi; Shi, Kaiyang; Gao, Ning; Li, Jian; Bai, Ou

2018-03-27

P300-spellers are brain-computer interface (BCI)-based character input systems. Support vector machine (SVM) ensembles are trained with large-scale training sets and used as classifiers in these systems. However, the required large-scale training data necessitate a prolonged collection time for each subject, which results in data collected toward the end of the period being contaminated by the subject's fatigue. This study aimed to develop a method for acquiring more training data based on a collected small training set. A new method was developed in which two corresponding training datasets in two sequences are superposed and averaged to extend the training set. The proposed method was tested offline on a P300-speller with the familiar face paradigm. The SVM ensemble with extended training set achieved 85% classification accuracy for the averaged results of four sequences, and 100% for 11 sequences in the P300-speller. In contrast, the conventional SVM ensemble with non-extended training set achieved only 65% accuracy for four sequences, and 92% for 11 sequences. The SVM ensemble with extended training set achieves higher classification accuracies than the conventional SVM ensemble, which verifies that the proposed method effectively improves the classification performance of BCI P300-spellers, thus enhancing their practicality.

Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution

NASA Astrophysics Data System (ADS)

Oh, Seok-Geun; Suh, Myoung-Seok

2017-07-01

The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.

Self-averaging and weak ergodicity breaking of diffusion in heterogeneous media

NASA Astrophysics Data System (ADS)

Russian, Anna; Dentz, Marco; Gouze, Philippe

2017-08-01

Diffusion in natural and engineered media is quantified in terms of stochastic models for the heterogeneity-induced fluctuations of particle motion. However, fundamental properties such as ergodicity and self-averaging and their dependence on the disorder distribution are often not known. Here, we investigate these questions for diffusion in quenched disordered media characterized by spatially varying retardation properties, which account for particle retention due to physical or chemical interactions with the medium. We link self-averaging and ergodicity to the disorder sampling efficiency Rn, which quantifies the number of disorder realizations a noise ensemble may sample in a single disorder realization. Diffusion for disorder scenarios characterized by a finite mean transition time is ergodic and self-averaging for any dimension. The strength of the sample to sample fluctuations decreases with increasing spatial dimension. For an infinite mean transition time, particle motion is weakly ergodicity breaking in any dimension because single particles cannot sample the heterogeneity spectrum in finite time. However, even though the noise ensemble is not representative of the single-particle time statistics, subdiffusive motion in q ≥2 dimensions is self-averaging, which means that the noise ensemble in a single realization samples a representative part of the heterogeneity spectrum.

Boundary Layer Control of a Circular Cylinder Using a Synthetic Jet

DTIC Science & Technology

2005-06-01

Average Velocity at . 375 Hz .............................................................................65 Figure 54 Average Velocity at 0.45 Hz...Figure 53 Average Velocity at . 375 Hz Columns=0; Rows=0 Figure 54 Average Velocity at 0.45 Hz Columns=0; Rows=0 Figure 55 Average Velocity

Correlation Scales of the Turbulent Cascade at 1 au

NASA Astrophysics Data System (ADS)

Smith, Charles W.; Vasquez, Bernard J.; Coburn, Jesse T.; Forman, Miriam A.; Stawarz, Julia E.

2018-05-01

We examine correlation functions of the mixed, third-order expressions that, when ensemble-averaged, describe the cascade of energy in the inertial range of magnetohydrodynamic turbulence. Unlike the correlation function of primitive variables such as the magnetic field, solar wind velocity, temperature, and density, the third-order expressions decorrelate at a scale that is approximately 20% of the lag. This suggests the nonlinear dynamics decorrelate in less than one wavelength. Therefore, each scale can behave differently from one wavelength to the next. In the same manner, different scales within the inertial range can behave independently at any given time or location. With such a cascade that can be strongly patchy and highly variable, it is often possible to obtain negative cascade rates for short periods of time, as reported earlier for individual samples of data.

Ensemble Weight Enumerators for Protograph LDPC Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush

2006-01-01

Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

NASA Astrophysics Data System (ADS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

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

Ortoleva, Peter J.

Illustrative embodiments of systems and methods for the deductive multiscale simulation of macromolecules are disclosed. In one illustrative embodiment, a deductive multiscale simulation method may include (i) constructing a set of order parameters that model one or more structural characteristics of a macromolecule, (ii) simulating an ensemble of atomistic configurations for the macromolecule using instantaneous values of the set of order parameters, (iii) simulating thermal-average forces and diffusivities for the ensemble of atomistic configurations, and (iv) evolving the set of order parameters via Langevin dynamics using the thermal-average forces and diffusivities.

How Interplanetary Scintillation Data Can Improve Modeling of Coronal Mass Ejection Propagation

NASA Astrophysics Data System (ADS)

Taktakishvili, A.; Mays, M. L.; Manoharan, P. K.; Rastaetter, L.; Kuznetsova, M. M.

2017-12-01

Coronal mass ejections (CMEs) can have a significant impact on the Earth's magnetosphere-ionosphere system and cause widespread anomalies for satellites from geosynchronous to low-Earth orbit and produce effects such as geomagnetically induced currents. At the NASA/GSFC Community Coordinated Modeling Center we have been using ensemble modeling of CMEs since 2012. In this presnetation we demonstrate that using of interplanetary scintillation (IPS) observations from the Ooty Radio Telescope facility in India can help to track CME propagaion and improve ensemble forecasting of CMEs. The observations of the solar wind density and velocity using IPS from hundreds of distant sources in ensemble modeling of CMEs can be a game-changing improvement of the current state of the art in CME forecasting.

Optimal averaging of soil moisture predictions from ensemble land surface model simulations

USDA-ARS?s Scientific Manuscript database

The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an instrumental variabl...

Investigation of short-term effective radiative forcing of fire aerosols over North America using nudged hindcast ensembles

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

Liu, Yawen; Zhang, Kai; Qian, Yun

Aerosols from fire emissions can potentially have large impact on clouds and radiation. However, fire aerosol sources are often intermittent, and their effect on weather and climate is difficult to quantify. Here we investigated the short-term effective radiative forcing of fire aerosols using the global aerosol–climate model Community Atmosphere Model version 5 (CAM5). Different from previous studies, we used nudged hindcast ensembles to quantify the forcing uncertainty due to the chaotic response to small perturbations in the atmosphere state. Daily mean emissions from three fire inventories were used to consider the uncertainty in emission strength and injection heights. The simulated aerosolmore » optical depth (AOD) and mass concentrations were evaluated against in situ measurements and reanalysis data. Overall, the results show the model has reasonably good predicting skills. Short (10-day) nudged ensemble simulations were then performed with and without fire emissions to estimate the effective radiative forcing. Results show fire aerosols have large effects on both liquid and ice clouds over the two selected regions in April 2009. Ensemble mean results show strong negative shortwave cloud radiative effect (SCRE) over almost the entirety of southern Mexico, with a 10-day regional mean value of –3.0 W m –2. Over the central US, the SCRE is positive in the north but negative in the south, and the regional mean SCRE is small (–0.56 W m –2). For the 10-day average, we found a large ensemble spread of regional mean shortwave cloud radiative effect over southern Mexico (15.6 % of the corresponding ensemble mean) and the central US (64.3 %), despite the regional mean AOD time series being almost indistinguishable during the 10-day period. Moreover, the ensemble spread is much larger when using daily averages instead of 10-day averages. In conclusion, this demonstrates the importance of using a large ensemble of simulations to estimate the short-term aerosol effective radiative forcing.« less

Investigation of short-term effective radiative forcing of fire aerosols over North America using nudged hindcast ensembles

DOE PAGES

Liu, Yawen; Zhang, Kai; Qian, Yun; ...

2018-01-03

Aerosols from fire emissions can potentially have large impact on clouds and radiation. However, fire aerosol sources are often intermittent, and their effect on weather and climate is difficult to quantify. Here we investigated the short-term effective radiative forcing of fire aerosols using the global aerosol–climate model Community Atmosphere Model version 5 (CAM5). Different from previous studies, we used nudged hindcast ensembles to quantify the forcing uncertainty due to the chaotic response to small perturbations in the atmosphere state. Daily mean emissions from three fire inventories were used to consider the uncertainty in emission strength and injection heights. The simulated aerosolmore » optical depth (AOD) and mass concentrations were evaluated against in situ measurements and reanalysis data. Overall, the results show the model has reasonably good predicting skills. Short (10-day) nudged ensemble simulations were then performed with and without fire emissions to estimate the effective radiative forcing. Results show fire aerosols have large effects on both liquid and ice clouds over the two selected regions in April 2009. Ensemble mean results show strong negative shortwave cloud radiative effect (SCRE) over almost the entirety of southern Mexico, with a 10-day regional mean value of –3.0 W m –2. Over the central US, the SCRE is positive in the north but negative in the south, and the regional mean SCRE is small (–0.56 W m –2). For the 10-day average, we found a large ensemble spread of regional mean shortwave cloud radiative effect over southern Mexico (15.6 % of the corresponding ensemble mean) and the central US (64.3 %), despite the regional mean AOD time series being almost indistinguishable during the 10-day period. Moreover, the ensemble spread is much larger when using daily averages instead of 10-day averages. In conclusion, this demonstrates the importance of using a large ensemble of simulations to estimate the short-term aerosol effective radiative forcing.« less

Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

PubMed

Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

2014-01-01

The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

Real­-Time Ensemble Forecasting of Coronal Mass Ejections Using the Wsa-Enlil+Cone Model

NASA Astrophysics Data System (ADS)

Mays, M. L.; Taktakishvili, A.; Pulkkinen, A. A.; Odstrcil, D.; MacNeice, P. J.; Rastaetter, L.; LaSota, J. A.

2014-12-01

Ensemble forecasting of coronal mass ejections (CMEs) provides significant information in that it provides an estimation of the spread or uncertainty in CME arrival time predictions. Real-time ensemble modeling of CME propagation is performed by forecasters at the Space Weather Research Center (SWRC) using the WSA-ENLIL+cone model available at the Community Coordinated Modeling Center (CCMC). To estimate the effect of uncertainties in determining CME input parameters on arrival time predictions, a distribution of n (routinely n=48) CME input parameter sets are generated using the CCMC Stereo CME Analysis Tool (StereoCAT) which employs geometrical triangulation techniques. These input parameters are used to perform n different simulations yielding an ensemble of solar wind parameters at various locations of interest, including a probability distribution of CME arrival times (for hits), and geomagnetic storm strength (for Earth-directed hits). We present the results of ensemble simulations for a total of 38 CME events in 2013-2014. For 28 of the ensemble runs containing hits, the observed CME arrival was within the range of ensemble arrival time predictions for 14 runs (half). The average arrival time prediction was computed for each of the 28 ensembles predicting hits and using the actual arrival time, an average absolute error of 10.0 hours (RMSE=11.4 hours) was found for all 28 ensembles, which is comparable to current forecasting errors. Some considerations for the accuracy of ensemble CME arrival time predictions include the importance of the initial distribution of CME input parameters, particularly the mean and spread. When the observed arrivals are not within the predicted range, this still allows the ruling out of prediction errors caused by tested CME input parameters. Prediction errors can also arise from ambient model parameters such as the accuracy of the solar wind background, and other limitations. Additionally the ensemble modeling sysem was used to complete a parametric event case study of the sensitivity of the CME arrival time prediction to free parameters for ambient solar wind model and CME. The parameter sensitivity study suggests future directions for the system, such as running ensembles using various magnetogram inputs to the WSA model.

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: Scenario analysis

USGS Publications Warehouse

Huisman, J.A.; Breuer, L.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.; Willems, P.

2009-01-01

An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions. ?? 2008 Elsevier Ltd.

Scaling of peak flows with constant flow velocity in random self-similar networks

USGS Publications Warehouse

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2011-01-01

A methodology is presented to understand the role of the statistical self-similar topology of real river networks on scaling, or power law, in peak flows for rainfall-runoff events. We created Monte Carlo generated sets of ensembles of 1000 random self-similar networks (RSNs) with geometrically distributed interior and exterior generators having parameters pi and pe, respectively. The parameter values were chosen to replicate the observed topology of real river networks. We calculated flow hydrographs in each of these networks by numerically solving the link-based mass and momentum conservation equation under the assumption of constant flow velocity. From these simulated RSNs and hydrographs, the scaling exponents β and φ characterizing power laws with respect to drainage area, and corresponding to the width functions and flow hydrographs respectively, were estimated. We found that, in general, φ > β, which supports a similar finding first reported for simulations in the river network of the Walnut Gulch basin, Arizona. Theoretical estimation of β and φ in RSNs is a complex open problem. Therefore, using results for a simpler problem associated with the expected width function and expected hydrograph for an ensemble of RSNs, we give heuristic arguments for theoretical derivations of the scaling exponents β(E) and φ(E) that depend on the Horton ratios for stream lengths and areas. These ratios in turn have a known dependence on the parameters of the geometric distributions of RSN generators. Good agreement was found between the analytically conjectured values of β(E) and φ(E) and the values estimated by the simulated ensembles of RSNs and hydrographs. The independence of the scaling exponents φ(E) and φ with respect to the value of flow velocity and runoff intensity implies an interesting connection between unit hydrograph theory and flow dynamics. Our results provide a reference framework to study scaling exponents under more complex scenarios of flow dynamics and runoff generation processes using ensembles of RSNs.

Quantifying Nucleic Acid Ensembles with X-ray Scattering Interferometry.

PubMed

Shi, Xuesong; Bonilla, Steve; Herschlag, Daniel; Harbury, Pehr

2015-01-01

The conformational ensemble of a macromolecule is the complete description of the macromolecule's solution structures and can reveal important aspects of macromolecular folding, recognition, and function. However, most experimental approaches determine an average or predominant structure, or follow transitions between states that each can only be described by an average structure. Ensembles have been extremely difficult to experimentally characterize. We present the unique advantages and capabilities of a new biophysical technique, X-ray scattering interferometry (XSI), for probing and quantifying structural ensembles. XSI measures the interference of scattered waves from two heavy metal probes attached site specifically to a macromolecule. A Fourier transform of the interference pattern gives the fractional abundance of different probe separations directly representing the multiple conformation states populated by the macromolecule. These probe-probe distance distributions can then be used to define the structural ensemble of the macromolecule. XSI provides accurate, calibrated distance in a model-independent fashion with angstrom scale sensitivity in distances. XSI data can be compared in a straightforward manner to atomic coordinates determined experimentally or predicted by molecular dynamics simulations. We describe the conceptual framework for XSI and provide a detailed protocol for carrying out an XSI experiment. © 2015 Elsevier Inc. All rights reserved.

The mean and turbulent flow structure of a weak hydraulic jump

NASA Astrophysics Data System (ADS)

Misra, S. K.; Kirby, J. T.; Brocchini, M.; Veron, F.; Thomas, M.; Kambhamettu, C.

2008-03-01

The turbulent air-water interface and flow structure of a weak, turbulent hydraulic jump are analyzed in detail using particle image velocimetry measurements. The study is motivated by the need to understand the detailed dynamics of turbulence generated in steady spilling breakers and the relative importance of the reverse-flow and breaker shear layer regions with attention to their topology, mean flow, and turbulence structure. The intermittency factor derived from turbulent fluctuations of the air-water interface in the breaker region is found to fit theoretical distributions of turbulent interfaces well. A conditional averaging technique is used to calculate ensemble-averaged properties of the flow. The computed mean velocity field accurately satisfies mass conservation. A thin, curved shear layer oriented parallel to the surface is responsible for most of the turbulence production with the turbulence intensity decaying rapidly away from the toe of the breaker (location of largest surface curvature) with both increasing depth and downstream distance. The reverse-flow region, localized about the ensemble-averaged free surface, is characterized by a weak downslope mean flow and entrainment of water from below. The Reynolds shear stress is negative in the breaker shear layer, which shows that momentum diffuses upward into the shear layer from the flow underneath, and it is positive just below the mean surface indicating a downward flux of momentum from the reverse-flow region into the shear layer. The turbulence structure of the breaker shear layer resembles that of a mixing layer originating from the toe of the breaker, and the streamwise variations of the length scale and growth rate are found to be in good agreement with observed values in typical mixing layers. All evidence suggests that breaking is driven by a surface-parallel adverse pressure gradient and a streamwise flow deceleration at the toe of the breaker. Both effects force the shear layer to thicken rapidly, thereby inducing a sharp free surface curvature change at the toe.

Optimal averaging of soil moisture predictions from ensemble land surface model simulations

USDA-ARS?s Scientific Manuscript database

The correct interpretation of ensemble 3 soil moisture information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an inst...

Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms.

PubMed

Ozcift, Akin; Gulten, Arif

2011-12-01

Improving accuracies of machine learning algorithms is vital in designing high performance computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier performance might be enhanced by ensemble classification strategies. In this study, we construct rotation forest (RF) ensemble classifiers of 30 machine learning algorithms to evaluate their classification performances using Parkinson's, diabetes and heart diseases from literature. While making experiments, first the feature dimension of three datasets is reduced using correlation based feature selection (CFS) algorithm. Second, classification performances of 30 machine learning algorithms are calculated for three datasets. Third, 30 classifier ensembles are constructed based on RF algorithm to assess performances of respective classifiers with the same disease data. All the experiments are carried out with leave-one-out validation strategy and the performances of the 60 algorithms are evaluated using three metrics; classification accuracy (ACC), kappa error (KE) and area under the receiver operating characteristic (ROC) curve (AUC). Base classifiers succeeded 72.15%, 77.52% and 84.43% average accuracies for diabetes, heart and Parkinson's datasets, respectively. As for RF classifier ensembles, they produced average accuracies of 74.47%, 80.49% and 87.13% for respective diseases. RF, a newly proposed classifier ensemble algorithm, might be used to improve accuracy of miscellaneous machine learning algorithms to design advanced CADx systems. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Experiments on waves under impulsive wind forcing in view of the Phillips (1957) theory

NASA Astrophysics Data System (ADS)

Shemer, Lev; Zavadsky, Andrey

2016-11-01

Only limited information is currently available on the initial stages of wind-waves growth from rest under sudden wind forcing; the mechanisms leading to the appearance of waves are still not well understood. In the present work, waves emerging in a small-scale laboratory facility under the action of step-like turbulent wind forcing are studied using capacitance and laser slope gauges. Measurements are performed at a number of fetches and for a range of wind velocities. Taking advantage of the fully automated experimental procedure, at least 100 independent realizations are recorded for each wind velocity at every fetch. The accumulated data sets allow calculating ensemble-averaged values of the measured parameters as a function of time elapsed from the blower activation. The accumulated results on the temporal variation of wind-wave field initially at rest allow quantitative comparison with the theory of Phillips (1957). Following Phillips, appearance of the initial detectable ripples was considered first, while the growth of short gravity waves at later times was analyzed separately. Good qualitative and partial quantitative agreement between the Phillips predictions and the measurements was obtained for both those stages of the initial wind-wave field evolution.

Experimental study of temporal evolution of waves under transient wind conditions

NASA Astrophysics Data System (ADS)

Zavadsky, Andrey; Shemer, Lev

2016-11-01

Temporal variation of the waves excited by nearly sudden wind forcing over an initially still water surface is studied in a small wind-wave flume at Tel Aviv University for variety of fetches and wind velocities. Simultaneous measurements of the surface elevation using a conventional capacitance wave-gauge and of the surface slope in along-wind and cross-wind directions by a laser slope gauge were performed. Variation with time of two components of instantaneous surface velocity was measured by particle tracking velocimetry. The size of the experimental facility and thus relatively short characteristic time scales of the phenomena under investigation, as well as an automated experimental procedure controlling the experiments made it possible to record a large amount of independent realizations for each wind-fetch condition. Sufficient data were accumulated to compute reliable ensemble averaged temporal variation of governing wave parameters. The essentially three-dimensional structure of wind-waves at all stages of evolution is demonstrated. The results obtained at each wind-fetch condition allowed to characterize the major stages of the evolution of the wind-wave field and to suggest a plausible scenario for the initial growth of the wind-waves.

Rapid Geodetic Shortening Across the Eastern Cordillera of NW Argentina Observed by the Puna-Andes GPS Array

NASA Astrophysics Data System (ADS)

McFarland, Phillip K.; Bennett, Richard A.; Alvarado, Patricia; DeCelles, Peter G.

2017-10-01

We present crustal velocities for 29 continuously recording GPS stations from the southern central Andes across the Puna, Eastern Cordillera, and Santa Barbara system for the period between the 27 February 2010 Maule and 1 April 2014 Iquique earthquakes in a South American frame. The velocity field exhibits a systematic decrease in magnitude from 35 mm/yr near the trench to <1 mm/yr within the craton. We forward model loading on the Nazca-South America (NZ-SA) subduction interface using back slip on elastic dislocations to approximate a fully locked interface from 10 to 50 km depth. We generate an ensemble of models by iterating over the percentage of NZ-SA convergence accommodated at the subduction interface. Velocity residuals calculated for each model demonstrate that locking on the NZ-SA interface is insufficient to reproduce the observed velocities. We model deformation associated with a back-arc décollement using an edge dislocation, estimating model parameters from the velocity residuals for each forward model of the subduction interface ensemble using a Bayesian approach. We realize our best fit to the thrust-perpendicular velocity field with 70 ± 5% of NZ-SA convergence accommodated at the subduction interface and a slip rate of 9.1 ± 0.9 mm/yr on the fold-thrust belt décollement. We also estimate a locking depth of 14 ± 9 km, which places the downdip extent of the locked zone 135 ± 20 km from the thrust front. The thrust-parallel component of velocity is fit by a constant shear strain rate of -19 × 10-9 yr-1, equivalent to clockwise rigid block rotation of the back arc at a rate of 1.1°/Myr.

Comparison of different assimilation schemes in an operational assimilation system with Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Yan, Yajing; Barth, Alexander; Beckers, Jean-Marie; Candille, Guillem; Brankart, Jean-Michel; Brasseur, Pierre

2016-04-01

In this paper, four assimilation schemes, including an intermittent assimilation scheme (INT) and three incremental assimilation schemes (IAU 0, IAU 50 and IAU 100), are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The three IAU schemes differ from each other in the position of the increment update window that has the same size as the assimilation window. 0, 50 and 100 correspond to the degree of superposition of the increment update window on the current assimilation window. Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/observation difference, as well as by rank histogram before the assimilation experiments The relevance of each assimilation scheme is evaluated through analyses on thermohaline variables and the current velocities. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semi-independent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system.

Analyses and forecasts of a tornadic supercell outbreak using a 3DVAR system ensemble

NASA Astrophysics Data System (ADS)

Zhuang, Zhaorong; Yussouf, Nusrat; Gao, Jidong

2016-05-01

As part of NOAA's "Warn-On-Forecast" initiative, a convective-scale data assimilation and prediction system was developed using the WRF-ARW model and ARPS 3DVAR data assimilation technique. The system was then evaluated using retrospective short-range ensemble analyses and probabilistic forecasts of the tornadic supercell outbreak event that occurred on 24 May 2011 in Oklahoma, USA. A 36-member multi-physics ensemble system provided the initial and boundary conditions for a 3-km convective-scale ensemble system. Radial velocity and reflectivity observations from four WSR-88Ds were assimilated into the ensemble using the ARPS 3DVAR technique. Five data assimilation and forecast experiments were conducted to evaluate the sensitivity of the system to data assimilation frequencies, in-cloud temperature adjustment schemes, and fixed- and mixed-microphysics ensembles. The results indicated that the experiment with 5-min assimilation frequency quickly built up the storm and produced a more accurate analysis compared with the 10-min assimilation frequency experiment. The predicted vertical vorticity from the moist-adiabatic in-cloud temperature adjustment scheme was larger in magnitude than that from the latent heat scheme. Cycled data assimilation yielded good forecasts, where the ensemble probability of high vertical vorticity matched reasonably well with the observed tornado damage path. Overall, the results of the study suggest that the 3DVAR analysis and forecast system can provide reasonable forecasts of tornadic supercell storms.

Understanding the Central Equatorial African long-term drought using AMIP-type simulations

NASA Astrophysics Data System (ADS)

Hua, Wenjian; Zhou, Liming; Chen, Haishan; Nicholson, Sharon E.; Jiang, Yan; Raghavendra, Ajay

2018-02-01

Previous studies show that Indo-Pacific sea surface temperature (SST) variations may help to explain the observed long-term drought during April-May-June (AMJ) since the 1990s over Central equatorial Africa (CEA). However, the underlying physical mechanisms for this drought are still not clear due to observation limitations. Here we use the AMIP-type simulations with 24 ensemble members forced by observed SSTs from the ECHAM4.5 model to explore the likely physical processes that determine the rainfall variations over CEA. We not only examine the ensemble mean (EM), but also compare the "good" and "poor" ensemble members to understand the intra-ensemble variability. In general, EM and the "good" ensemble member can simulate the drought and associated reduced vertical velocity and anomalous anti-cyclonic circulation in the lower troposphere. However, the "poor" ensemble members cannot simulate the drought and associated circulation patterns. These contrasts indicate that the drought is tightly associated with the tropical Walker circulation and atmospheric teleconnection patterns. If the observational circulation patterns cannot be reproduced, the CEA drought will not be captured. Despite the large intra-ensemble spread, the model simulations indicate an essential role of SST forcing in causing the drought. These results suggest that the long-term drought may result from tropical Indo-Pacific SST variations associated with the enhanced and westward extended tropical Walker circulation.

Aerodynamic surface stress intermittency and conditionally averaged turbulence statistics

NASA Astrophysics Data System (ADS)

Anderson, William; Lanigan, David

2015-11-01

Aeolian erosion is induced by aerodynamic stress imposed by atmospheric winds. Erosion models prescribe that sediment flux, Q, scales with aerodynamic stress raised to exponent, n, where n > 1 . Since stress (in fully rough, inertia-dominated flows) scales with incoming velocity squared, u2, it follows that q ~u2n (where u is some relevant component of the flow). Thus, even small (turbulent) deviations of u from its time-mean may be important for aeolian activity. This rationale is augmented given that surface layer turbulence exhibits maximum Reynolds stresses in the fluid immediately above the landscape. To illustrate the importance of stress intermittency, we have used conditional averaging predicated on stress during large-eddy simulation of atmospheric boundary layer flow over an arid, bare landscape. Conditional averaging provides an ensemble-mean visualization of flow structures responsible for erosion `events'. Preliminary evidence indicates that surface stress peaks are associated with the passage of inclined, high-momentum regions flanked by adjacent low-momentum regions. We characterize geometric attributes of such structures and explore streamwise and vertical vorticity distribution within the conditionally averaged flow field. This work was supported by the National Sci. Foundation, Phys. and Dynamic Meteorology Program (PM: Drs. N. Anderson, C. Lu, and E. Bensman) under Grant # 1500224. Computational resources were provided by the Texas Adv. Comp. Center at the Univ. of Texas.

Ensemble Deep Learning for Biomedical Time Series Classification

PubMed Central

2016-01-01

Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost. PMID:27725828

On estimating attenuation from the amplitude of the spectrally whitened ambient seismic field

NASA Astrophysics Data System (ADS)

Weemstra, Cornelis; Westra, Willem; Snieder, Roel; Boschi, Lapo

2014-06-01

Measuring attenuation on the basis of interferometric, receiver-receiver surface waves is a non-trivial task: the amplitude, more than the phase, of ensemble-averaged cross-correlations is strongly affected by non-uniformities in the ambient wavefield. In addition, ambient noise data are typically pre-processed in ways that affect the amplitude itself. Some authors have recently attempted to measure attenuation in receiver-receiver cross-correlations obtained after the usual pre-processing of seismic ambient-noise records, including, most notably, spectral whitening. Spectral whitening replaces the cross-spectrum with a unit amplitude spectrum. It is generally assumed that cross-terms have cancelled each other prior to spectral whitening. Cross-terms are peaks in the cross-correlation due to simultaneously acting noise sources, that is, spurious traveltime delays due to constructive interference of signal coming from different sources. Cancellation of these cross-terms is a requirement for the successful retrieval of interferometric receiver-receiver signal and results from ensemble averaging. In practice, ensemble averaging is replaced by integrating over sufficiently long time or averaging over several cross-correlation windows. Contrary to the general assumption, we show in this study that cross-terms are not required to cancel each other prior to spectral whitening, but may also cancel each other after the whitening procedure. Specifically, we derive an analytic approximation for the amplitude difference associated with the reversed order of cancellation and normalization. Our approximation shows that an amplitude decrease results from the reversed order. This decrease is predominantly non-linear at small receiver-receiver distances: at distances smaller than approximately two wavelengths, whitening prior to ensemble averaging causes a significantly stronger decay of the cross-spectrum.

Equipartition terms in transition path ensemble: Insights from molecular dynamics simulations of alanine dipeptide.

PubMed

Li, Wenjin

2018-02-28

Transition path ensemble consists of reactive trajectories and possesses all the information necessary for the understanding of the mechanism and dynamics of important condensed phase processes. However, quantitative description of the properties of the transition path ensemble is far from being established. Here, with numerical calculations on a model system, the equipartition terms defined in thermal equilibrium were for the first time estimated in the transition path ensemble. It was not surprising to observe that the energy was not equally distributed among all the coordinates. However, the energies distributed on a pair of conjugated coordinates remained equal. Higher energies were observed to be distributed on several coordinates, which are highly coupled to the reaction coordinate, while the rest were almost equally distributed. In addition, the ensemble-averaged energy on each coordinate as a function of time was also quantified. These quantitative analyses on energy distributions provided new insights into the transition path ensemble.

Perception of ensemble statistics requires attention.

PubMed

Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A

2017-02-01

To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics. Copyright © 2016 Elsevier Inc. All rights reserved.

Genetic programming based ensemble system for microarray data classification.

PubMed

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

Genetic Programming Based Ensemble System for Microarray Data Classification

PubMed Central

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved. PMID:25810748

Some far-field acoustics characteristics of the XV-15 tilt-rotor aircraft

NASA Technical Reports Server (NTRS)

Golub, Robert A.; Conner, David A.; Becker, Lawrence E.; Rutledge, C. Kendall; Smith, Rita A.

1990-01-01

Far-field acoustics tests have been conducted on an instrumented XV-15 tilt-rotor aircraft. The purpose of these acoustic measurements was to create an encompassing, high confidence (90 percent), and accurate (-1.4/ +1/8 dB theoretical confidence interval) far-field acoustics data base to validate ROTONET and other current rotorcraft noise prediction computer codes. This paper describes the flight techniques used, with emphasis on the care taken to obtain high-quality far-field acoustic data. The quality and extensiveness of the data base collected are shown by presentation of ground acoustic contours for level flyovers for the airplane flight mode and for several forward velocities and nacelle tilts for the transition mode and helicopter flight mode. Acoustic pressure time-histories and fully analyzed ensemble averaged far-field data results (spectra) are shown for each of the ground contour cases.

The twin cell model and its excellence in determining the glass transition temperature of thin film metallic glass

NASA Astrophysics Data System (ADS)

Kanjilal, Baishali; Iram, Samreen; Das, Atreyee; Chakrabarti, Haimanti

2018-05-01

This work reports a novel two dimensional approach to the theoretical computation of the glass transition temperature in simple hypothetical icosahedral packed structures based on Thin Film metallic glasses using liquid state theories in the realm of transport properties. The model starts from Navier-Stokes equation and evaluates the statistical average velocity of each different species of atom under the condition of ensemble equality to compute diffusion lengths and the diffusion coefficients as a function of temperature. The additional correction brought in is that of the limited states due to tethering of one nodule vis -a-vis the others. The movement of the molecules use our Twin Cell Model a typical model pertinent for modeling chain motions. A temperature viscosity correction by Cohen and Grest is included through the temperature dependence of the relaxation times for glass formers.

Tube Visualization and Properties from Isoconfigurational Averaging

NASA Astrophysics Data System (ADS)

Qin, Jian; Bisbee, Windsor; Milner, Scott

2012-02-01

We introduce a simulation method to visualize the confining tube in polymer melts and measure its properties. We studied bead-spring ring polymers, which conveniently suppresses constraint release and contour length fluctuations. We allow molecules to cross and reach topologically equilibrated states by invoking various molecular rebridging moves in Monte Carlo simulations. To reveal the confining tube, we start with a well equilibrated configuration, turn off rebridging moves, and run molecular dynamics simulation multiple times, each with different initial velocities. The resulting set of ``movies'' of molecular trajectories defines an isoconfigurational ensemble, with the bead positions at different times and in different ``movies'' giving rise to a cloud. The cloud shows the shape, range and strength of the tube confinement, which enables us to study the statistical properties of tube. Using this approach, we studied the effects of free surface, and found that the tube diameter near the surface is greater than the bulk value by about 25%.

Drift-wave turbulence and zonal flow generation.

PubMed

Balescu, R

2003-10-01

Drift-wave turbulence in a plasma is analyzed on the basis of the wave Liouville equation, describing the evolution of the distribution function of wave packets (quasiparticles) characterized by position x and wave vector k. A closed kinetic equation is derived for the ensemble-averaged part of this function by the methods of nonequilibrium statistical mechanics. It has the form of a non-Markovian advection-diffusion equation describing coupled diffusion processes in x and k spaces. General forms of the diffusion coefficients are obtained in terms of Lagrangian velocity correlations. The latter are calculated in the decorrelation trajectory approximation, a method recently developed for an accurate measure of the important trapping phenomena of particles in the rugged electrostatic potential. The analysis of individual decorrelation trajectories provides an illustration of the fragmentation of drift-wave structures in the radial direction and the generation of long-wavelength structures in the poloidal direction that are identified as zonal flows.

Continuous centrifuge decelerator for polar molecules.

PubMed

Chervenkov, S; Wu, X; Bayerl, J; Rohlfes, A; Gantner, T; Zeppenfeld, M; Rempe, G

2014-01-10

Producing large samples of slow molecules from thermal-velocity ensembles is a formidable challenge. Here we employ a centrifugal force to produce a continuous molecular beam with a high flux at near-zero velocities. We demonstrate deceleration of three electrically guided molecular species, CH3F, CF3H, and CF3CCH, with input velocities of up to 200  m s(-1) to obtain beams with velocities below 15  m s(-1) and intensities of several 10(9)  mm(-2) s(-1). The centrifuge decelerator is easy to operate and can, in principle, slow down any guidable particle. It has the potential to become a standard technique for continuous deceleration of molecules.

Fidelity decay of the two-level bosonic embedded ensembles of random matrices

NASA Astrophysics Data System (ADS)

Benet, Luis; Hernández-Quiroz, Saúl; Seligman, Thomas H.

2010-12-01

We study the fidelity decay of the k-body embedded ensembles of random matrices for bosons distributed over two single-particle states. Fidelity is defined in terms of a reference Hamiltonian, which is a purely diagonal matrix consisting of a fixed one-body term and includes the diagonal of the perturbing k-body embedded ensemble matrix, and the perturbed Hamiltonian which includes the residual off-diagonal elements of the k-body interaction. This choice mimics the typical mean-field basis used in many calculations. We study separately the cases k = 2 and 3. We compute the ensemble-averaged fidelity decay as well as the fidelity of typical members with respect to an initial random state. Average fidelity displays a revival at the Heisenberg time, t = tH = 1, and a freeze in the fidelity decay, during which periodic revivals of period tH are observed. We obtain the relevant scaling properties with respect to the number of bosons and the strength of the perturbation. For certain members of the ensemble, we find that the period of the revivals during the freeze of fidelity occurs at fractional times of tH. These fractional periodic revivals are related to the dominance of specific k-body terms in the perturbation.

Canonical-ensemble state-averaged complete active space self-consistent field (SA-CASSCF) strategy for problems with more diabatic than adiabatic states: Charge-bond resonance in monomethine cyanines

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

Olsen, Seth, E-mail: seth.olsen@uq.edu.au

2015-01-28

This paper reviews basic results from a theory of the a priori classical probabilities (weights) in state-averaged complete active space self-consistent field (SA-CASSCF) models. It addresses how the classical probabilities limit the invariance of the self-consistency condition to transformations of the complete active space configuration interaction (CAS-CI) problem. Such transformations are of interest for choosing representations of the SA-CASSCF solution that are diabatic with respect to some interaction. I achieve the known result that a SA-CASSCF can be self-consistently transformed only within degenerate subspaces of the CAS-CI ensemble density matrix. For uniformly distributed (“microcanonical”) SA-CASSCF ensembles, self-consistency is invariant tomore » any unitary CAS-CI transformation that acts locally on the ensemble support. Most SA-CASSCF applications in current literature are microcanonical. A problem with microcanonical SA-CASSCF models for problems with “more diabatic than adiabatic” states is described. The problem is that not all diabatic energies and couplings are self-consistently resolvable. A canonical-ensemble SA-CASSCF strategy is proposed to solve the problem. For canonical-ensemble SA-CASSCF, the equilibrated ensemble is a Boltzmann density matrix parametrized by its own CAS-CI Hamiltonian and a Lagrange multiplier acting as an inverse “temperature,” unrelated to the physical temperature. Like the convergence criterion for microcanonical-ensemble SA-CASSCF, the equilibration condition for canonical-ensemble SA-CASSCF is invariant to transformations that act locally on the ensemble CAS-CI density matrix. The advantage of a canonical-ensemble description is that more adiabatic states can be included in the support of the ensemble without running into convergence problems. The constraint on the dimensionality of the problem is relieved by the introduction of an energy constraint. The method is illustrated with a complete active space valence-bond (CASVB) analysis of the charge/bond resonance electronic structure of a monomethine cyanine: Michler’s hydrol blue. The diabatic CASVB representation is shown to vary weakly for “temperatures” corresponding to visible photon energies. Canonical-ensemble SA-CASSCF enables the resolution of energies and couplings for all covalent and ionic CASVB structures contributing to the SA-CASSCF ensemble. The CASVB solution describes resonance of charge- and bond-localized electronic structures interacting via bridge resonance superexchange. The resonance couplings can be separated into channels associated with either covalent charge delocalization or chemical bonding interactions, with the latter significantly stronger than the former.« less

Canonical-ensemble state-averaged complete active space self-consistent field (SA-CASSCF) strategy for problems with more diabatic than adiabatic states: charge-bond resonance in monomethine cyanines.

PubMed

Olsen, Seth

2015-01-28

This paper reviews basic results from a theory of the a priori classical probabilities (weights) in state-averaged complete active space self-consistent field (SA-CASSCF) models. It addresses how the classical probabilities limit the invariance of the self-consistency condition to transformations of the complete active space configuration interaction (CAS-CI) problem. Such transformations are of interest for choosing representations of the SA-CASSCF solution that are diabatic with respect to some interaction. I achieve the known result that a SA-CASSCF can be self-consistently transformed only within degenerate subspaces of the CAS-CI ensemble density matrix. For uniformly distributed ("microcanonical") SA-CASSCF ensembles, self-consistency is invariant to any unitary CAS-CI transformation that acts locally on the ensemble support. Most SA-CASSCF applications in current literature are microcanonical. A problem with microcanonical SA-CASSCF models for problems with "more diabatic than adiabatic" states is described. The problem is that not all diabatic energies and couplings are self-consistently resolvable. A canonical-ensemble SA-CASSCF strategy is proposed to solve the problem. For canonical-ensemble SA-CASSCF, the equilibrated ensemble is a Boltzmann density matrix parametrized by its own CAS-CI Hamiltonian and a Lagrange multiplier acting as an inverse "temperature," unrelated to the physical temperature. Like the convergence criterion for microcanonical-ensemble SA-CASSCF, the equilibration condition for canonical-ensemble SA-CASSCF is invariant to transformations that act locally on the ensemble CAS-CI density matrix. The advantage of a canonical-ensemble description is that more adiabatic states can be included in the support of the ensemble without running into convergence problems. The constraint on the dimensionality of the problem is relieved by the introduction of an energy constraint. The method is illustrated with a complete active space valence-bond (CASVB) analysis of the charge/bond resonance electronic structure of a monomethine cyanine: Michler's hydrol blue. The diabatic CASVB representation is shown to vary weakly for "temperatures" corresponding to visible photon energies. Canonical-ensemble SA-CASSCF enables the resolution of energies and couplings for all covalent and ionic CASVB structures contributing to the SA-CASSCF ensemble. The CASVB solution describes resonance of charge- and bond-localized electronic structures interacting via bridge resonance superexchange. The resonance couplings can be separated into channels associated with either covalent charge delocalization or chemical bonding interactions, with the latter significantly stronger than the former.

Decadal climate predictions improved by ocean ensemble dispersion filtering

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

2017-06-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.