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At least 73 records · Page 4

Long-range anticorrelations and non-Gaussian behavior of the heartbeat

We find that the successive increments in the cardiac beat-to-beat intervals of healthy subjects display scale-invariant, long-range anticorrelations (up to 10 exp 4 heart beats). Furthermore, we find that the histogram for the heartbeat intervals increments is well described by a Levy (1991) stable distribution. For a group of subjects with severe heart disease, we find that the distribution is unchanged, but the long-range correlations vanish. Therefore, the different scaling behavior in health and disease must relate to the underlying dynamics of the heartbeat.

Peng, C.-K.↗

The Kepler Light Curves of AGN: A Detailed Analysis

We present a comprehensive analysis of 21 light curves of Type 1 active galactic nuclei (AGN) from the Kepler spacecraft. First, we describe the necessity and development of a customized pipeline for treating Kepler data of stochastically variable sources like AGN. We then present the light curves, power spectral density functions (PSDs), and flux histograms. The light curves display an astonishing variety of behaviors, many of which would not be detected in ground-based studies, including switching between distinct flux levels. Six objects exhibit PSD flattening at characteristic timescales that roughly correlate with black hole mass. These timescales are consistent with orbital timescales or free-fall accretion timescales. We check for correlations of variability and high-frequency PSD slope with accretion rate, black hole mass, redshift, and luminosity. We find that bolometric luminosity is anticorrelated with both variability and steepness of the PSD slope. We do not find evidence of the linear rms-flux relationships or lognormal flux distributions found in X-ray AGN light curves, indicating that reprocessing is not a significant contributor to optical variability at the 0.1%-10% level.

power spectral density functions(PSDs)↗

MemGaze: Rapid and Effective Load-Level Memory Trace Analysis

A major challenge of memory analysis tools is combining high-resolution analysis and low overhead measurement. Currently, hardware/software-based analysis of load-level sequences incurs time slowdowns of O(100×). We present MemGaze, a tool for low-overhead, high-resolution memory analysis. MemGaze uses Intel’s Processor Tracing (PT) instruction ptwrite to collect sampled and compressed memory address traces for load-level, sequence-aware analysis of data reuse. We describe multi-resolution analysis for locations vs. operations, accesses vs. spatio-temporal reuse, and reuse (distance, rate, volume) vs. access patterns. Both trace size and resolution are controllable. We use MemGaze to elucidate the memory effects of different data structures and algorithms. For sampled traces that are ˜1% of a full one, analysis metrics have 1-25% MAPE for histograms of varying dynamic sequence lengths. With current suboptimal kernel support (PT runs continuously), MemGaze’s time overhead is typically 10–95%; 7× at worst. However, when PT runs only during samples, overhead is 10–35% on memory intensive regions and correlates with executed ptwrites.

Kilic, Ozgur O.↗

Regime-Based Evaluation of Cloudiness in CMIP5 Models

The concept of Cloud Regimes (CRs) is used to develop a framework for evaluating the cloudiness of 12 fifth Coupled Model Intercomparison Project (CMIP5) models. Reference CRs come from existing global International Satellite Cloud Climatology Project (ISCCP) weather states. The evaluation is made possible by the implementation in several CMIP5 models of the ISCCP simulator generating for each gridcell daily joint histograms of cloud optical thickness and cloud top pressure. Model performance is assessed with several metrics such as CR global cloud fraction (CF), CR relative frequency of occurrence (RFO), their product (long-term average total cloud amount [TCA]), cross-correlations of CR RFO maps, and a metric of resemblance between model and ISCCP CRs. In terms of CR global RFO, arguably the most fundamental metric, the models perform unsatisfactorily overall, except for CRs representing thick storm clouds. Because model CR CF is internally constrained by our method, RFO discrepancies yield also substantial TCA errors. Our findings support previous studies showing that CMIP5 models underestimate cloudiness. The multi-model mean performs well in matching observed RFO maps for many CRs, but is not the best for this or other metrics. When overall performance across all CRs is assessed, some models, despite their shortcomings, apparently outperform Moderate Resolution Imaging Spectroradiometer (MODIS) cloud observations evaluated against ISCCP as if they were another model output. Lastly, cloud simulation performance is contrasted with each model's equilibrium climate sensitivity (ECS) in order to gain insight on whether good cloud simulation pairs with particular values of this parameter.

cloud climatology↗

The surface albedo of the earth in the near ultraviolet /330-340 nm/

Satellite-borne measurements of solar radiation backscattered by the earth and atmosphere allow a determination of the surface albedo in the near ultraviolet. The data yielded albedos at tropical latitudes during a 15-month period in 1979-1980. The wavelengths studied are 331.2 and 339.8 nm. Sixty-nine percent of the measurements imply albedos less than 0.3. Higher values include a contribution due to reflection from clouds and are consistent with previous estimates of the fractional cloudover in the tropics. An albedo histogram based on a bin width of 0.1 shows results in the range 0.1-0.2 to be the most frequent, appearing in 29% of the cases, although values which span the entire range 0.0-1.0 are present. The derived albedos show no correlation with solar zenith angle. This result is consistent with the fact that, at the wavelengths considered, the diffuse integrated intensity is larger than the attenuated direct solar beam near the ground.

Frederick, J. E.↗

Effects of satellite data resolution on measuring the space/time variations of surfaces and clouds

The correlated distributions of satellite-measured visible and infrared radiances, caused by spatial and temporal variations in clouds and surfaces, have been found to be characteristic of the major climate regimes and can be described by the attributes of bidimensional and monodimensional histograms and time-composite images. Most of the variability of both the surfaces and clouds is found to occur at scales larger than the minimum resolved by satellite imagery. Since satellite imaging data sets are difficult to analyze because of their large volumes, many studies reduce the volume by various sampling or averaging schemes. The effects of data resolution and sampling on the radiance histogram statistics and on the time-composite image characteristics are examined. In particular, the sampling strategy used by the International Satellite Cloud Climatology Project is tested. This sampling strategy is found to preserve the statistics of smaller cloud variations for most regions, with the exception of very rare events, if they are accumulated over large enough areas (at least 500 km in dimension) and long enough time periods (at least one month).

Seze, Genevieve↗

Calculation of area-averaged vertical profiles of the horizontal wind velocity from volume-imaging lidar data

Area-averaged horizontal wind measurements are derived from the motion of spatial inhomogeneities in aerosol backscattering observed with a volume-imaging lidar. Spatial averaging provides high precision, reducing sample variations of wind measurements well below the level of turbulent fluctuations, even under conditions of very light mean winds and strong convection or under the difficult conditions represented by roll convection. Wind velocities are measured using the two-dimensional spatial cross correlation computed between successive horizontal plane maps of aerosol backscattering, assembled from three-dimensional lidar scans. Prior to calculation of the correlation function, three crucial steps are performed: (1) the scans are corrected for image distortion by the wind during a finite scan time; (2) a temporal high pass median filtering is applied to eliminate structures that do not move with the wind; and (3) a histogram equalization is employed to reduce biases to the brightest features.

Schols, J. L.↗

Carbon Nanostructure Examined by Lattice Fringe Analysis of High Resolution Transmission Electron Microscopy Images

The dimensions of graphitic layer planes directly affect the reactivity of soot towards oxidation and growth. Quantification of graphitic structure could be used to develop and test correlations between the soot nanostructure and its reactivity. Based upon transmission electron microscopy images, this paper provides a demonstration of the robustness of a fringe image analysis code for determining the level of graphitic structure within nanoscale carbon, i.e. soot. Results, in the form of histograms of graphitic layer plane lengths, are compared to their determination through Raman analysis.

VanderWal, Randy L.↗

Carbon Nanostructure Examined by Lattice Fringe Analysis of High Resolution Transmission Electron Microscopy Images

The dimensions of graphitic layer planes directly affect the reactivity of soot towards oxidation and growth. Quantification of graphitic structure could be used to develop and test correlations between the soot nanostructure and its reactivity. Based upon transmission electron microscopy images, this paper provides a demonstration of the robustness of a fringe image analysis code for determining the level of graphitic structure within nanoscale carbon, i.e., soot. Results, in the form of histograms of graphitic layer plane lengths, are compared to their determination through Raman analysis.

VanderWal, Randy L.↗

Macromolecular Topography Leaps into the Digital Age

A low-cost, real-time digital topography system is under development which will replace x-ray film and nuclear emulsion plates. The imaging system is based on an inexpensive surveillance camera that offers a 1000x1000 array of 8 im square pixels, anti-blooming circuitry, and very quick read out. Currently, the system directly converts x-rays to an image with no phosphor. The system is small and light and can be easily adapted to work with other crystallographic equipment. Preliminary images have been acquired of cubic insulin at the NSLS x26c beam line. NSLS x26c was configured for unfocused monochromatic radiation. Six reflections were collected with stills spaced from 0.002 to 0.001 degrees apart across the entire oscillation range that the reflections were in diffracting condition. All of the reflections were rotated to the vertical to reduce Lorentz and beam related effects. This particular CCD is designed for short exposure applications (much less than 1 sec) and so has a relatively high dark current leading to noisy raw images. The images are processed to remove background and other system noise with a multi-step approach including the use of wavelets, histogram, and mean window filtering. After processing, animations were constructed with the corresponding reflection profile to show the diffraction of the crystal volume vs. the oscillation angle as well as composite images showing the parts of the crystal with the strongest diffraction for each reflection. The final goal is to correlate features seen in reflection profiles captured with fine phi slicing to those seen in the topography images. With this development macromolecular topography finally comes into the digital age.

Lovelace, J.↗

Prospects of the ICESat-2 Laser Altimetry Mission for Savanna Ecosystem Structural Studies Based on Airborne Simulation Data

The next planned spaceborne lidar mission is the Ice, Cloud and land Elevation Satellite 2 (ICESat-2), which will use the Advanced Topographic Laser Altimeter System (ATLAS) sensor, a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in an oak savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA's Goddard Space Flight Center. ATLAS-like data was generated using the MATLAS simulator, which adjusts MABEL data's detected number of signal and noise photons to that expected from the ATLAS instrument. Transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we chose to use data from the near infrared channel that had the highest number of photons. We segmented each transect into 50 m, 25 m and 14 m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an automated algorithm to identify cut off points where the cumulative density of photons from the highest elevation indicates the presence of the canopy top and likewise where such cumulative density from the lowest elevation indicates the mean terrain elevation. MABEL derived height metrics were moderately correlated to discrete return lidar (DRL) derived height metrics r(sub 2) and RMSE values ranging from 0.60 to 0.73 and 2.9 m to 4.4 m respectively) but MATLAS simulation resulted in more modest correlations with DRL indices r(sub 2) ranging from 0.5 to 0.64 and RMSE from 3.6 m to 4.6 m). Simulations also indicated that the expected number of signal photons from ATLAS will be substantially lower, a situation that reduces canopy height estimation precision especially in areas of low density vegetation cover. On the basis of the simulated data, there is reason to believe that the ability of ICESat-2 to estimate height in savannas will be comparable to the original ICESat mission although the respective sensors have different measurement principles.

Gwenzi, David↗

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Preliminary results of the analysis of CaII K spectroheliograms

The preliminary results of the photometry of CaII K spectroheliograms are presented. From the spectrograms for 1992, plages, the magnetic network, intranetwork elements and the chromospheric background were separated using the histogram method. The intensity and area of these separated features, as well as the full disk intensity, were derived. The spatial K index was compared to the spectral CaII K index derived from line profiles. It was found that the spatial K index and intensity of plages, the network elements and the intranetwork and background regions were highly correlated with the MgII h and k c/w ratio.

Kariyappa, R.↗

Experimental Visualizations of a Generic Launch Vehicle Flow Field: Time-Resolved Shadowgraph and Infrared Imaging

Time-Resolved shadowgraph and infrared (IR) imaging were performed to investigate off-body and on-body flow features of a generic, 'hammer-head' launch vehicle geometry previously tested by Coe and Nute (1962). The measurements discussed here were one part of a large range of wind tunnel test techniques that included steady-state pressure sensitive paint (PSP), dynamic PSP, unsteady surface pressures, and unsteady force measurements. Image data was captured over a Mach number range of 0.6 less than or equal to M less than or equal to 1.2 at a Reynolds number of 3 million per foot. Both shadowgraph and IR imagery were captured in conjunction with unsteady pressures and forces and correlated with IRIG-B timing. High-speed shadowgraph imagery was used to identify wake structure and reattachment behind the payload fairing of the vehicle. Various data processing strategies were employed and ultimately these results correlated well with the location and magnitude of unsteady surface pressure measurements. Two research grade IR cameras were positioned to image boundary layer transition at the vehicle nose and flow reattachment behind the payload fairing. The poor emissivity of the model surface treatment (fast PSP) proved to be challenging for the infrared measurement. Reference image subtraction and contrast limited adaptive histogram equalization (CLAHE) were used to analyze this dataset. Ultimately turbulent boundary layer transition was observed and located forward of the trip dot line at the model sphere-cone junction. Flow reattachment location was identified behind the payload fairing in both steady and unsteady thermal data. As demonstrated in this effort, recent advances in high-speed and thermal imaging technology have modernized classical techniques providing a new viewpoint for the modern researcher

Shadowgraph↗

Search for solar neutrons using NM-64 equipment

Two years (1980 to 1982) neutron monitor data from the Chacaltaya (geographic coordinates: N16.32 deg W68. 15 deg; cutoff rigidity: 13.1 GV; altitude: 5,300 m a.s.l.) station has been scanned; the sampling time of the 12NM-64 neutron monitor is 5 min. The nucleonic component increases have been correlated with 66 hard X-, gamma rays satellite data from solar origin, as reported by several groups. Typical neutron monitor time profiles of the events are presented. Chree-analysis was performed discriminating the events according to its solar coordinates. Ground data from solar limb locii are more enhanced at the time of the onset than other geometrically visible flares. Chree histograms of neutron monitor output profiles are also presented from geometrically invisible events from the Chacaltaya station.

Martinic, N. J.↗

Correcting for digital image correlation speckle inversion at high temperature using color cameras

Digital image correlation (DIC) is a popular, noncontacting technique to measure full-field deformation by using cameras to track the motion of an applied surface pattern. Because it is noncontacting, DIC can be performed for extreme temperature applications (e.g., hot-fire rocket testing of carbon composite rocket nozzles) under harsh conditions during which bonded gauges are damaged. Speckle pattern inversion is a phenomenon that sometimes occurs while performing high-temperature DIC. During speckle pattern inversion, portions of the surface pattern that were initially darker at room temperature (e.g., graphite) may emit more light due to blackbody radiation than the portions that were initially paler, thereby producing images in which the pattern appears inverted at high temperature relative to the initial pattern at room temperature. This phenomenon can prevent the correlation algorithm from being able to resolve the displacements between images. This work compares three methods to mitigate speckle pattern inversion: (A) the subtraction method, a recently-published technique in which two high-temperature images are subtracted to remove unwanted light; (B) the filtering method, a popular technique in which optical bandpass filters screen out unwanted light; and (C) the histogram rescaling method, a proposed new method that pairs a color camera with a blue light source and uses information from the green sensor of the camera to correct against inversion in the blue sensor through postprocessing. The histogram rescaling method is shown to successfully eliminate speckle pattern inversion and has the added advantages that it does not require quasi-static loading to be able to compensate for speckle pattern inversion, nor does it impose thick-glass distortions caused by the optical filter.

Rowley, Lindsey J.↗

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗

Charge-induced secondary atomization in diffusion flames of electrostatic sprays

The combustion of electrostatic sprays of heptane in laminar counterflow diffusion flames was experimentally studied by measuring droplet size and velocity distributions, as well as the gas-phase temperature. A detailed examination of the evolution of droplet size distribution as droplets approach the flame shows that, if substantial evaporation occurs before droplets interact with the flame, an initially monodisperse size distribution becomes bimodal. A secondary sharp peak in the size histogram develops in correspondence of diameters about one order of magnitude smaller than the mean. No evaporation mechanism can account for the development of such bimodality, that can be explained only in terms of a disintegration of droplets into finer fragments of size much smaller than that of the parent. Other evidence in support of this interpretation is offered by the measurements of droplet size-velocity correlation and velocity component distributions, showing that, as a consequence of the ejection process, the droplets responsible for the secondary peak have velocities uncorrelated with the mean flow. The fission is induced by the electric charge. When a droplet evaporates, in fact, the electric charge density on the droplet surface increases while the droplet shrinks, until the so-called Rayleigh limit is reached at which point the repulsion of electric charges overcomes the surface tension cohesive force, ultimately leading to a disintegraton into finer fragments. We report on the first observation of such fissions in combustion environments. If, on the other hand, insufficient evaporation has occurred before droplets enter the high temperature region, there appears to be no significant evidence of bimodality in their size distribution. In this case, in fact, the concentration of flame chemi-ions or, in the case of positively charged droplets, electrons may be sufficient for them to neutralize the charge on the droplets and to prevent disruption.

Gomez, Alessandro↗