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At least 1,207 records · Page 67

Massive compression for high data rate macromolecular crystallography (HDRMX): impact on diffraction data and subsequent structural analysis

New higher-count-rate, integrating, large-area X-ray detectors with framing rates as high as 17400 images per second are beginning to be available. These will soon be used for specialized macromolecular crystallography experiments but will require optimal lossy compression algorithms to enable systems to keep up with data throughput. Some information may be lost. Can we minimize this loss with acceptable impact on structural information? To explore this question, we have considered several approaches: summing short sequences of images, binning to create the effect of larger pixels, use of JPEG-2000 lossy wavelet-based compression, and use of Hcompress, which is a Haar-wavelet-based lossy compression borrowed from astronomy. We also explore the effect of the combination of summing, binning, and Hcompress or JPEG-2000. In each of these last two methods one can specify approximately how much one wants the result to be compressed from the starting file size. These provide particularly effective lossy compressions that retain essential information for structure solution from Bragg reflections.

47 OTHER INSTRUMENTATION↗

Perceive: Proactive Exploration of Risky Concept Emergence for Identifying Vulnerabilities & Exposures

National databases that collect various kinds of textual threat reports such as ASRS, CERT, and NVD manually process their reports individually. They then offer data products to disseminate the aggregate information, like newsletters, alerts or individual report searching. The goal of this research is to connect these individual reports thematically and temporally to identify emerging or recurring threats, by analyzing large collections of text, source code, collaboration and communication patterns. This capability, I argue, enables us to identify the emergence and recurrence of such themes, and the contexts in which they re-occur, facilitating faster and more capable mitigation. I propose two models to shed light on this goal: An empirical model of vulnerabilities as bugs, the commit flow model, and one of the vulnerabilities and aviation safety threats as topics, the topic flow model. I use as gold standard existing manual workflows in both domains, reflected in the existing data products by these organizations, and empirically evaluate if the automated model scan match or outperform existing manual practices.

ASRS↗

The Tropospheric Products of the International VLBI Service for Geodesy and Astrometry

The IVS runs two tropospheric products: The IVS tropospheric parameter rapid combination monitors the zenith wet delay (ZWD) and zenith total delay (ZTD) of the rapid turnaround sessions R1 and R4. Goal of the combination is the identification and the exclusion of outliers by comparison and the assessment of the precision of current VLBI solutions in terms of tropospheric parameters. The rapid combination is done on a weekly basis four weeks after the observation files are released on IVS Data Centers. Since tropospheric and geodetic parameters, such as vertical station components, can significantly correlate, the consistency of the ZTD can be a measure of the consistency of the corresponding TRF as well. The ZWD mainly rely on accurate atmospheric pressure data. Thus, besides estimation techniques, modeling and analyst s noise, ZWD reflects differences in the atmospheric pressure data applied to the VLBI analysis. The second product, called tropospheric parameter long-term combination, aims for an accurate determination of climatological signals, such as trends of the atmospheric water vapor observed by VLBI. Therefore, the long-term homogeneity of atmospheric pressure data plays a crucial role for this product. The paper reviews the methods applied and results achieved so far and describes the new maintenance through DGFI.

Heinkelmann, Robert↗

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. Ground truth spectral signature data for various types of scenes, including ground with and without annuals, and various shrubs, were collected. When these signature data are plotted with infrared (MSS band 6 or 7) reflectivity on one axis and red (MSS band 5) reflectivity on the other axis, clusters of data from the various types of scenes are distinct. This method of expressing spectral signature data appears to be more useful for distinguishing types of scenes than a simple infrared to red reflectivity ration. Large areas of varnished desert pavement are visible and mappable on ERTS-1 and high altitude aircraft imagery. A large scale vegetation pattern was found to be correlated with the presence of the desert pavement. The large scale correlation was used in mapping the vegetation of the area. It was found that a distinctive soil type was associated with the presence of the varnished desert pavement. The high salinity and exchangeable sodium percentage of this soil type provide a basis for the explanation of both the large scale and small scale vegetation pattern.

Mcginnies, W. G.↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was -1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching -3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗

A Long Look at MCG-5-23-16 with NuSTAR. I. Relativistic Reflection and Coronal Properties

MCG-5-23-16 was targeted in early 2015 with a half mega-second observing campaign using NuSTAR. Here we present the spectral analysis of these data sets along with an earlier observation and study the relativistic reflection and the primary coronal source. The data show strong reflection features in the form of both narrow and broad iron lines plus a Compton reflection hump. A cutoff energy is significantly detected in all exposures. The shape of the reflection spectrum does not change in the two years spanned by the observations, suggesting a stable geometry. A strong positive correlation is found between the cutoff energy and both the hard X-ray flux and spectral index. The measurements imply that the coronal plasma is not at the runaway electron-positron pair limit, and instead contains mostly electrons. The observed variability in the coronal properties is driven by a variable optical depth. A constant heating-to-cooling ratio is measured, implying that there is a feedback mechanism in which a significant fraction of the photons cooling the corona are due to reprocessed hard X-rays.

black hole physics – galaxies: active – galaxi↗

Deconvolution of spectra for intimate mixtures

Visible to near infrared reflectance spectra of macroscopic mixtures have been shown to be linear combinations of the reflections of the pure mineral components in the mixture. However, for microscopic mixtures the mixing systematics are in general nonlinear. The systematics may be linearized by conversion of reflectance to single scattering albedo (w), where the equations which relate reflectance to w depend on the method of data collection. Several proposed mixing models may be used to estimate mineral abundances from the reflectance spectra of intimate mixtures. These models are summarized and a revised model is presented. A noniterative (linear) least squares approach was used for curve fitting and the data, measured as bi-directional reflectance with incidence and emergence angles of 30 and 0 deg were converted to w by a simplified version of Hapke's equation for bi-directional reflectance. This model was tested with two mixture series composed of 45 to 75 micron particles: an anorthite-enstatite series and an olivine-magnetite series. The data indicate that the simplified Hapke's equation may be used to convolve reflectance spectra into mineral abundances if appropriate endmembers are known or derived from other techniques. For surfaces that contain a significant component of very low albedo material, a somewhat modified version of this technique will need to be developed. Since the abundances are calculated using a noniterative approach, the application of this method is especially efficient for large spectral data sets, such as those produced by mapping spectrometers.

Mustard, John F.↗

Algal Biomass Production via Open Pond Algae Farm Cultivation: 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is an essential activity for platform research conducted under the Bioenergy Technologies Office (BETO). It allows for the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and furnished by partner organizations) to be quantified in terms of economic improvements in the overall biofuel production process for a particular biomass processing pathway, whether based on terrestrial or algal biomass feedstocks. As such, initial benchmarks can be established for currently demonstrated performance, and progress can be tracked toward out-year goals to ultimately demonstrate economically viable biofuel technologies. NREL's algae SOT benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL's "combined algae processing" (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) consortium efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted primarily under NREL research and development projects. This report focuses on front-end algal biomass production, documenting the pertinent algal biomass cultivation parameters that were input to the NREL open pond algae farm model. Through partnerships under DISCOVR, collaborators at ASU furnished details on cultivation performance metrics including biomass productivity and harvest densities for recent growth trials done at the AzCATI site. The resulting biomass productivity was calculated at 18.5 g/m2/day (ash-free dry weight [AFDW], annual average) for seasonal cultivation of Picochlorum celeri, Tetraselmis striata LANL1001, and Monoraphidium minutum 26B-AM biomass strains at the ASU site. Picochlorum celeri achieved the best productivity from May to September, with Monoraphidium minutum 26B-AM being used in October, November, March, and April, and Tetraselmis striata employed during winter months (December through February). Beyond the standard SOT models, in Appendix C of this report we also present an industry case study evaluating several scenarios reflective of outdoor cultivation data furnished by an industry collaborator. This case study provides a supplementary datapoint on work being performed elsewhere achieving comparable cultivation productivity with more favorable compositional quality, producing biomass enriched in lipids as may be more optimal for conversion upgrading to fuels and products.

09 BIOMASS FUELS↗

Reflectance measurements for the detection and mapping of soil limitations

During 1971 and 1972 research was conducted on two fallow fields in the proposed Oahe Irrigation Project to investigate the relationship between the tonal variations observed on aerial photographs and the principal soil limitations of the area. A grid sampling procedure was used to collected detailed field data during the 1972 growing season. The field data was compared to imagery collected on May 14, 1971 at 3050 meters altitude. The imagery and field data were initially evaluated by a visual analysis. Correlation and regression analysis revealed a highly significant correlation and regression analysis revealed a highly significant correlation between the digitized color infrared film data and soil properties such as organic matter content, color, depth to carbonates, bulk density and reflectivity. Computer classification of the multiemulsion film data resulted in maps delineating the areas containing claypan and erosion limitations. Reflectance data from the red spectral band provided the best results.

Benson, L. A.↗

Grazing incidence X-ray reflectivity - Studies for the AXAF observatory

The energy bandwidth and total throughput of a grazing incidence optics system is a strong function of the X-ray reflectivity of the surface coating. In support of the Advanced X-ray Astrophysics Facility (AXAF), studies are underway to evaluate and characterize the reflectivity of potential AXAF coatings. Here we report on results obtained for Au, Ir, and Ni coatings produced by electron-beam evaporation, evaporation with ion-assist, and sputtering. Effects of coating thickness and deposition angle have been evaluated at 6.4 and 8.1 keV; the highest reflectivities are those of the thinner, about 200 A vs about 700 A, coatings. While considerable variations exist, the best Ir samples have higher reflectivity than any of the Au coatings. Data results have been compared with models for theoretical reflectivity, particularly with regard to the effective density of the coatings. Independent measurements of the coating densities have been carried out for comparison with the reflectivity results.

Slane, P.↗

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗

Effect of Scattering Angle on DSCOVR/EPIC Observations

The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) routinely captures reflected radiation from the whole sunlit side of the Earth in the near backward direction to monitor the changing planet. The instrument had routinely operated until 27 June 2019, when the spacecraft was placed in an extended safe hold due to degradation of an inertial navigation unit. DSCOVR returned to full operations on 2 March 2020. Since then, the range of scattering angles between the incident sunlight and sensor direction has been larger than before and the largest scattering angle reaches ∼178°, only 2° from perfect backscattering, proving a unique opportunity to study the top-of-atmosphere (TOA) reflectance under such extreme conditions. In the paper, we compare EPIC global spectral reflectances in 2021–2016. We found that there are four occasions when the scattering angle reaches about 178° and associated with them enhanced global daily average spectral reflectances in 2021. The scattering angle related reflectance enhancements are not found in 2016 data when the maximum scattering angle is about 174.5°. CERES data do not show such occasions in global daily reflected shortwave flux. As a result, those enhanced reflectance occasions are primarily due to the change in scattering angle. The enhancement due to changes in scattering angle depends strongly on wavelength, primarily because of wavelength dependence of cloud scattering phase function. Radiative transfer calculations show that the change in scattering angles has the largest impact on reflectance in the red and NIR channels at 680 nm and 780 nm and the smallest influence on reflectance in the UV channel at 388 nm, consistent with EPIC observations. The change of global average cloud amount also plays an important role in the reflectance enhancement. The influence of the cloud effect depends on whether the change is in phase or not with the change of scattering angle.

DSCOVR EPIC↗

A sparse Gaussian sigmoid basis function approximation of hyperspectral data for detection of solids

We define a new characterization of emissivity and reflectance curves for compositional exploitation of hyperspectral data. Here, our method decomposes each spectrum into a sparse set of Gaussian sigmoid components using penalized regression. Detection is based on the combination of Gaussian sigmoid components unique to a target material. Focusing on the presence of spectral upslopes and downslopes rather than spectral correlations makes detection more robust to both target variation and spectral variability from atmosphere and background encountered during the collection process. We present simulation studies that demonstrate the potential to reduce false positive rates without compromising sensitivity. Characterization of long–wave infrared (LWIR) experimental data validates our method using minerals of different particle sizes, measurement angles, and collection conditions.

97 MATHEMATICS AND COMPUTING↗

HCMM hydrological analysis in Utah

The feasibility of applying a linear model to HCMM data in hopes of obtaining an accurate linear correlation was investigated. The relationship among HCMM sensed data surface temperature and red reflectivity on Utah Lake and water quality factors including algae concentrations, algae type, and nutrient and turbidity concentrations was established and evaluated. Correlation (composite) images of day infrared and reflectance imagery were assessed to determine if remote sensing offers the capability of using masses of accurate and comprehensive data in calculating evaporation. The effects of algae on temperature and evaporation were studied and the possibility of using satellite thermal data to locate areas within Utah Lake where significant thermal sources exist and areas of near surface groundwater was examined.

Miller, A. W.↗

Implications of Microwave Holography Using Minimum Required Frequency Samples for Weakly- and Strongly-Scattering Indications

Microwave imaging techniques, an integral component of nondestructive testing and evaluation (NDTE), have received significant attention in the past decade. These techniques have included the implementation of synthetic aperture focusing (SAF) algorithms for obtaining high spatial resolution images. The next important step in these developments is the implementation of 3-D holographic imaging algorithms. These are well-known wideband imaging technique requiring a swept-frequency (i.e., wideband), which unlike SAF that is a single frequency technique, are not easily performed on a real-time basis. This is due to the fact that a significant number of data points (in the frequency domain) must be obtained within the frequency band of interest. This not only makes for a complex imaging system design, it also significantly increases the image-production time. Consequently in an attempt to reduce the measurement time and system complexity, an investigation was conducted to determine the minimum required number of frequency samples needed to image a specific object while preserving a desired maximum measurement range and range resolution. To this end the 3-D holographic algorithm was modified to use properlyinterpolated frequency data. Measurements of the complex reflection coefficient for several samples were conducted using a swept-frequency approach. Subsequently, holographical images were generated using data containing a relatively large number of frequency samples and were compared with images generated by the reduced data set data. Quantitative metrics such as average, contrast, and signal-to-noise ratio were used to evaluate the quality of images generated using reduced data sets. Furthermore, this approach was applied to both weakly- and strongly-scattering indications. This paper presents the methods used and the results of this investigation.

Fallahpour, M.↗

The reflectance characteristics of snow covered surfaces

Data analysis techniques were developed to most efficiently use available satellite measurements to determine and understand components of the surface energy budget for ice and snow-covered areas. The emphasis is placed on identifying the important components of the heat budget related to snow surfaces, specifically the albedo and the energy consumed in the melting process. Ice and snow charts are prepared by NOAA from satellite observations which map areas into three relative reflectivity zones. Field measurements are analyzed of the reflectivity of an open snow field to assist in the interpretation of the NOAA reflectivity zones.

Batten, E. S.↗