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DOE OSTI2016

SU-F-J-161: Prostate Contouring in Patients with Bilateral Hip Prostheses: Impact of Using Artifact-Reduced CT Images and MRI

Purpose: To investigate the usefulness of metal artifact reduction in CT images of patients with bilateral hip prostheses (BHP) for contouring the prostate and determine if the inclusion of MR images provides additional benefits. Methods: Five patients with BHP were CT scanned using our clinical protocol (140kV, 300mAs, 3mm slices, 1.5mm increment, Philips Medical Systems, OH). Images were reconstructed with the orthopaedic metal artifact reduction (O-MAR) algorithm. MRI scanning was then performed (1.5T, GE Healthcare, WI) with a flat table-top (T{sub 2}-weighted, inherent body coil, FRFSE, 3mm slices with 0mm gap). All images were transferred to Pinnacle (Version 9.2, Philips Medical Systems). For each patient, two data sets were produced: one containing the O-MAR-corrected CT images and another containing fused MRI and O-MAR-corrected CT images. Four genito-urinary radiation oncologists contoured the prostate of each patient on the O-MAR-corrected CT data. Two weeks later, they contoured the prostate on the fused data set, blinded to all other contours. During each contouring session, the oncologists reported their confidence in the contours (1=very confident, 3=not confident) and the contouring difficulty that they experienced (1=really easy, 4=very challenging). Prostate volumes were computed from the contours and the conformity index was used to evaluate inter-observer variability. Results: Larger prostate volumes were found on the O-MAR-corrected CT set than on the fused set (p< 0.05, median=36.9cm{sup 3} vs. 26.63 cm{sup 3}). No significant differences were noted in the inter-observer variability between the two data sets (p=0.3). Contouring difficulty decreased with the addition of MRI (p<0.05) while the radiation oncologists reported more confidence in their contours when MRI was fused with the O-MAR-corrected CT data (p<0.05). Conclusion: This preliminary work demonstrated that, while O-MAR correction to CT images improves visualization of anatomy, the addition of MRI enhanced the oncologists’ confidence in contouring the prostate in patients with BHP.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1983

Production and analysis of output data products for Landsat-4 in the engineering check-out phase

The Landsat-D (now Landsat-4) program was initiated by NASA in the mid-1970's. The spacecraft was launched on July 16, 1982. Instruments on the satellite include the fourth Multispectral Scanner (MSS) and the new higher-resolution Thematic Mapper (TM). In order to achieve the planned engineering and scientific objectives, attention has to be given to the validation of spacecraft and instrument performance, the adjustment of ground processing procedures, and the definition of the measures of the TU utility. To satisfy these requirements, a Landsat Assessment System (LAS) was conceived, and the Applications Developmental Data System (ADDS) was instituted. The set of component systems collectively became known as the 'Scrounge' system. The present investigation is concerned with the Scrounge system and the results of radiometric and geometric data evaluations. Attention is given to the TM geometric correction, TM data resampling, a radiometric correction functional description, and the results of the TM geometric and radiometric correction.

Lyon, J. C.↗

NASA NTRS1977

Correction of laser tracking data for the effects of horizontal refractivity gradients

Pulsed laser ranging systems are being used to measure accurately the distance from the earth to retroreflector equipped satellites. At the lower elevation angles horizontal refractivity gradients can introduce centimeter level errors into the range measurements. A correction formula which compensates for the gradient effects is developed and evaluated using typical meteorological data obtained from weather stations located near Washington, D.C.

Gardner, C. S.↗

NASA NTRS1983

Evaluation of the radiometric quality of the TM data using clustering and multispectral distance measures

Radiometrically and geometrically corrected TM data from three different geographic locations were examined. Histograms were inspected for each band to determine the dynamic range of the data, the shape of the distributions, and to verify whether empty bins were introduced by the radiometric correction process. The effect of geometric correction on the radiometry of the resampled pixels was determined. The information content between TM and MSS data sets were compared and the TM data were used to map the thermal effluent discharge into a river ecosystem from a nuclear thermal power plant, and application only possible previously only possible through the acquisition of thermal infrared scanner data from aircraft altitudes.

Bartolucci, L. A.↗

DOE OSTI2025

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from 7 Perennial and 7 Intermittent Streams across San Antonio, Texas (v3)

This dataset supports a broader study examining the effects of intermittency on sediment respiration. The dataset provides sediment and surface water geochemistry and in situ sensor data from 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). Related data were collected and will be published separately in collaboration with A. Veach. The data package was originally published in April 2025. It was updated in June 2025 (v2; modified and new files) and September 2025 (v3; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment percent carbon and nitrogen; (11) sediment X-ray diffraction (XRD) data; (12) gravimetric moisture and averages; (13) a subfolder with sediment incubation respiration data, scripts, and plots; (14) surface water and sediment FTICR methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: The data processing methods for FTICR described in “v3_WHONDRS_AV1_Methods_Codes.csv” mistakenly indicate that users should process the data in Formultitude. The corrected description should read: “Both unprocessed and processed data are provided to allow users flexibility in data processing. Instructions and scripts for processing the data using CoreMS are included.” CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Extracting spectral albedo from NOAA-9 AVHRR multiple view data using an atmospheric correction procedure and an expert system

A 100 km by 200 km area of the Sahel was selected to demonstrate a new method of extracting hemispherical reflectance (albedo) from directional satellite data. Utilizing a stratification of the Gao region of Mali based on soil texture, satellite data for homogeneous areas were selected. These data were employed in a knowledge-based expert system called VEG, which is designed to handle a wide variety of types of input data. The calculated directional reflectance factors at ground level are very similar to ground measurements noted in the literature.

Kimes, D. S.↗

DOE OSTI2024

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗

NASA NTRS2021

Extending the Licklider Transmission Protocol to Multi-Band Links

Most deep space missions return data to Earth using links operating at a single frequency band. Indeed, their data requirements are low enough that bandwidth regulations do not constrain the system. In contrast, spacecraft such as Kepler or Europa Clipper are transitioning to a new operational paradigm where engineering and science data are transmitted through simultaneous links operating at different frequency bands (henceforth termed multi-band links). This ensures, for instance, that critical data is correctly received using a well characterized X-band link, while science data at a much larger data rate can be returned efficiently (both in terms of bandwidth and energy) through a Ka-band link.Having a spacecraft establish two simultaneous links with a ground station opens a large span of potential improvements for space communications and mission operations. In this paper, we consider the problem of running a Licklider Transmission Protocol (LTP) session over a multi-band link. LTP is an implementation of a selective Automatic Repeat reQuest (ARQ) protocol, i.e. it ensures correct delivery of data over an error prone link with potentially long propagation delays. To maximize its efficiency in deep space environments, LTP operates in deferred-ACK mode and is typically included as one of the core protocols in the Delay Tolerant Networking (DTN) suite.The contributions of this paper are as follows: First, we propose an extension to LTP for multi-band links (denoted MBLTP) and sketch how it can be implemented without modifying the current definition of LTP data units. Next, we develop bounds on the performance of MBLTP when transmitting a single data file over a multi-band link. Three metrics are considered, file expected delivery time, total energy spent and bundle jitter. The results of the analytic model are first benchmarked against simulations to ensure validity, and then compared against the performance of both traditional LTP and Parallel LTP (PLTP).We demonstrate that MBLTP can significantly reduce the latency and jitter with which data products are delivered to destination over a deep space link compared to LTP at moderate energy cost. Similarly, we also demonstrate that MBLTP outperforms PLTP in all considered metrics.

Sanchez Net, Marc↗

NASA NTRS2004

Analysis Of AVIRIS Data From LEO-15 Using Tafkaa Atmospheric Correction

We previously developed an algorithm named Tafkaa for atmospheric correction of remote sensing ocean color data from aircraft and satellite platforms. The algorithm allows quick atmospheric correction of hyperspectral data using lookup tables generated with a modified version of Ahmad & Fraser s vector radiative transfer code. During the past few years we have extended the capabilities of the code. Current modifications include the ability to account for within scene variation in solar geometry (important for very long scenes) and view geometries (important for wide fields of view). Additionally, versions of Tafkaa have been made for a variety of multi-spectral sensors, including SeaWiFS and MODIS. In this proceeding we present some initial results of atmospheric correction of AVIRIS data from the 2001 July Hyperspectral Coastal Ocean Dynamics Experiment (HyCODE) at LEO-15.

Montes, Marcos J.↗

DOE OSTI2025

A new HALEU isotopic certified reference material

Candidate certified reference material (CRM) U196 was prepared by gravimetrically mixing and dissolving NNSA NRMP CRM 112-A (natural uranium metal) and CRM 116-A (highly enriched 93.2% 235 U metal) to achieve a high-assay low-enriched uranium (HALEU) isotopic abundance reference material. CRM U196 will be certified for the 233 U/ 238 U, 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios. Gravimetrically determined uranium isotope amount ratios and values derived from the isotope data were calculated from the buoyancy corrected mass data and from certified values for the metal CRMs used to create the solution. The 235 U isotope amount fraction (·100) and expanded uncertainty is 19.5846 ± 0.0028. For attribute verification, total evaporation and modified total evaporation isotope ratio measurements were performed. In conclusion, the reference material is to be distributed as a unit containing 5 mg uranium as dry uranyl nitrate.

High-assay low-enriched uranium↗

DOE OSTI2026

Groundwater and river water elevations and temperature from 2017 to 2022 across Meander Z in the East River Watershed, Colorado

This dataset includes groundwater and river water elevations and temperature data collected in the East River watershed located in the Upper Colorado River Basin. The data were collected in order to investigate the coupling between hydrology and biogeochemical processes in the floodplain. Data was collected at ten groundwater locations in Meander Z (MZ), located just upstream of the confluence with Brush Creek and two river locations directly adjacent to Meander Z from 2017-2019. From 2019-2022, data was collected at five groundwater locations in Meander Z. Note that location names, not location identifiers (IDs), are used in the related publication Dewey et al. (2022). Both location IDs and names are included in data files. Files in this dataset include the main data files for each location zipped into a single folder (waterlevel_data.zip), an installation methods file describing sensor installation (InstallationMethods.csv), a file containing field metadata including GPS (Global Positioning System) coordinates and ground surface elevations (transducers_locations.csv). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This dataset conforms to the ESS-DIVE hydrological reporting format. 2026-04-27 Update: The river water elevation data files (ER-MZR1.csv and ER-MZR2.csv) were corrected. The data for these two locations were inadvertently swapped in the original published data. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A Cloud-Tracking Data Set for the CSAPR2 Adaptive Scanning during TRACER

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility (Mather and Voyles 2013) deployed the first ARM Mobile Facility (AMF1; Miller et al. 2016) near LaPorte, Texas to support the Tracking Aerosol Convection Interactions Experiment (TRACER) (Jensen et al. 2025) near Houston, Texas. From October 2021 to September 2022, AMF1 was deployed to 29.67° N, 95.06° W near LaPorte, Texas and the 2nd Generation C-band Scanning ARM Precipitation Radar (CSAPR2) was deployed to a supplementary site at 29.53° N, 95.28° W (Figure 1). During an intensive operational period (IOP) from 1 June to 30 September 2022, the CSAPR2 sampled precipitation echoes in an adaptive scanning mode following the Multisensor Agile Adaptive Scanning (MAAS) framework (Kollias et al. 2020). MAAS helped optimize the CSAPR2 scan strategy to perform frequent plan position indicator (PPI) and range height indicator (RHI) scans (Lamer et al. 2023). Details of the CSAPR2 scanning, data processing, and calibration procedures used by the principal investigator (PI), and the PI data files are described by Oue et al. (2023). Details of the CSAPR2 operational performance, ARM data processing and correction procedures, and data quality masks are described by Feng et al. (2024a).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Development of baseline random vibration environment criteria for Shuttle pallet payload subsystems

This paper presents a statistical evaluation of measured random vibration response data obtained from the Office of Space Science-1 (OSS-1) pallet payload. The data were measured during the acoustic test simulation (September 1980) and the ascent phase of the flight of STS-3, Orbiter 102 (launched from the Kennedy Space Center on March 22, 1982). Acoustic test efficiency factors are evaluated based on the Dynamic, Acoustic and Thermal Environments (DATE) instrumentation as the source of the measured vibration data. Test efficiency correction to test data is applied in the extrapolation of non-DATE acoustic test data to increase sample population size for improved statistical evaluation. For baseline criteria evaluation and development, data are grouped in accordance with the payload zone in which the component is mounted.

On, F. J.↗

NASA NTRS1983

Development of baseline random vibration criteria for STS pallet payloads

On, F. J.↗

NASA NTRS1987

Forest biomass, canopy structure, and species composition relationships with multipolarization L-band synthetic aperture radar data

The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.

Sader, Steven A.↗

NASA NTRS1989

Multi-temporal airborne synthetic aperture radar data for crop classification

This paper presents an approach to the classification of crop type using multitemporal airborne SAR data. Following radiometric correction of the data, the accuracy of a per-field crop classification reached 90 percent for three classes using data acquired on four dates. A comparable accuracy of 88 percent could be obtained for a classification of the same classes using data acquired on only two dates. Increasing the number of classes from three to seven reduced the classification accuracies to 55 percent and 69 percent when using data from two and four dates respectively.

Foody, G. M.↗

NASA NTRS1983

Atmospheric correction analysis on LANDSAT data over the Amazon region

The Amazon Region natural resources were studied in two ways and compared. A LANDSAT scene and its attributes were selected, and a maximum likelihood classification was made. The scene was atmospherically corrected, taking into account Amazonic peculiarities revealed by (ground truth) of the same area, and the subsequent classification. Comparison shows that the classification improves with the atmospherically corrected images.

Parada, N. D. J.↗

NASA NTRS1993

Hale cycle effects in cosmic ray east-west anisotropy and interplanetary magnetic field

We have reanalyzed diurnal anisotropy data obtained with the shielded ion chamber (IC) at Cheltenham/Fredericksburg and the neutron monitor (NM) at Swarthmore/Newark. IC data are for the 1936-1977 period and NM data are for the 1965-1988 period. We have corrected IC data for the diurnal temperature effect. Application of this correction results in a better agreement between IC and other data sets, thereby making it possible to study the long-term changes in the diurnal anisotropy using IC data. The behavior of the annual mean east-west anisotropy is studied for 53 years of observations. The period encompasses more than two solar magnetic (Hale) cycles. Its amplitude undergoes the expected 11 and 22 year variations, with the largest changes occurring near solar activity minima. Moreover, the data indicate the presence of the subsidiary maxima for the entire 53-year period, following the solar polar field reversals, during the declining phases of activity cycles when high-speed solar wind streams are present in the heliosphere. The data suggest that the amplitude of the subsidiary maximum is large when the solar polar magnetic field points toward the sun in the Northern Hemisphere, and radial anisotropy is absent.

Ahluwalia, H. S.↗