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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Utility of parentage‐based tagging for monitoring Coho salmon ( Oncorhynchus kisutch ) in the interior Columbia River basin

Abstract By the 1980s, after decades of declining numbers in the mid‐1900s, Coho salmon ( Oncorhynchus kisutch ) were considered extirpated from the interior Columbia River. In the mid‐1990s, the Confederated Tribes of the Umatilla Indian Reservation, the Confederated Tribes and Bands of the Yakama Nation, and the Nez Perce Tribe began successful reintroduction programs of Coho salmon upstream of Bonneville Dam, but which were initially sourced from lower Columbia River hatcheries. Here we present the first Coho salmon parentage‐based tagging (PBT) baseline from seven hatchery programs located in the interior Columbia River basin, and two sites at or downstream of Bonneville Dam, composed of over 32,000 broodstock samples. Analyses of baseline collections revealed that genetic structure followed a temporal pattern based on 3‐year broodlines rather than geographic location or stocking history. Across hatchery programs, similar levels of genetic diversity was present. The PBT baseline provided multiple direct applications such as identification of origin for Coho salmon collected in a mixed stock at Priest Rapids Dam and the detection of the proportion and distribution of hatchery‐origin fish on the spawning grounds in the Methow River basin. The PBT baseline for Coho salmon is freely available for use and can be downloaded from FishGen.net .

Horn, Rebekah L.↗
DOE OSTI2013

Toward correcting drift in target position during radiotherapy via computer-controlled couch adjustments on a programmable Linac

Purpose: Real-time tracking of respiratory target motion during radiation therapy is technically challenging, owing to rapid and possibly irregular breathing variations. The authors report on a method to predict and correct respiration-averaged drift in target position by means of couch adjustments on an accelerator equipped with such capability. Methods: Dose delivery is broken up into a sequence of 10 s field segments, each followed by a couch adjustment based on analysis of breathing motion from an external monitor as a surrogate of internal target motion. Signal averaging over three respiratory cycles yields a baseline representing target drift. A Kalman filter predicts the baseline position 5 s in advance, for determination of the couch correction. The method's feasibility is tested with a motion phantom programmed according to previously recorded patient signals. Computed couch corrections are preprogrammed into a research mode of an accelerator capable of computer-controlled couch translations synchronized with the motion phantom. The method's performance is evaluated with five cases recorded during hypofractionated treatment and five from respiration-correlated CT simulation, using a root-mean-squared deviation (RMSD) of the baseline from the treatment planned position. Results: RMSD is reduced in all 10 cases, from a mean of 4.9 mm (range 2.7-9.4 mm) before correction to 1.7 mm (range 0.7-2.3 mm) after correction. Treatment time is increased {approx}5% relative to that for no corrections. Conclusions: This work illustrates the potential for reduction in baseline respiratory drift with periodic adjustments in couch position during treatment. Future treatment machine capabilities will enable the use of 'on-the-fly' couch adjustments during treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-G-17A-05: PET Image Deblurring Using Adaptive Dictionary Learning

Purpose: The aim of this work is to deblur PET images while suppressing Poisson noise effects using adaptive dictionary learning (DL) techniques. Methods: The model that relates a blurred and noisy PET image to the desired image is described as a linear transform y=Hm+n where m is the desired image, H is a blur kernel, n is Poisson noise and y is the blurred image. The approach we follow to recover m involves the sparse representation of y over a learned dictionary, since the image has lots of repeated patterns, edges, textures and smooth regions. The recovery is based on an optimization of a cost function having four major terms: adaptive dictionary learning term, sparsity term, regularization term, and MLEM Poisson noise estimation term. The optimization is solved by a variable splitting method that introduces additional variables. We simulated a 128×128 Hoffman brain PET image (baseline) with varying kernel types and sizes (Gaussian 9×9, σ=5.4mm; Uniform 5×5, σ=2.9mm) with additive Poisson noise (Blurred). Image recovery was performed once when the kernel type was included in the model optimization and once with the model blinded to kernel type. The recovered image was compared to the baseline as well as another recovery algorithm PIDSPLIT+ (Setzer et. al.) by calculating PSNR (Peak SNR) and normalized average differences in pixel intensities (NADPI) of line profiles across the images. Results: For known kernel types, the PSNR of the Gaussian (Uniform) was 28.73 (25.1) and 25.18 (23.4) for DL and PIDSPLIT+ respectively. For blinded deblurring the PSNRs were 25.32 and 22.86 for DL and PIDSPLIT+ respectively. NADPI between baseline and DL, and baseline and blurred for the Gaussian kernel was 2.5 and 10.8 respectively. Conclusion: PET image deblurring using dictionary learning seems to be a good approach to restore image resolution in presence of Poisson noise. GE Health Care.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Regional radiation dose susceptibility within the parotid gland: Effects on salivary loss and recovery

Purpose: Xerostomia is one of the most likely late toxic effects of radiotherapy treatment in patients with head-and-neck cancers. Modern treatment techniques can incorporate knowledge of complication risk into treatment plans. To this end, the authors attempt to quantify the regional radiotherapy dose-dependence of salivary output loss and recovery in a prospective study. Methods: Salivary output was collected from patients undergoing radiotherapy treatment for head-and-neck cancers at the BC Cancer Agency between February 2008 and May 2013. Regional dose-dependence (i.e., dose susceptibility) of loss and recovery is quantified using nonparametric (Spearman’s rank correlation coefficients, local linear regression) and parametric (least-sum of squares, least-median of squares) techniques. Results: Salivary flow recovery was seen in 79 of 102 patients considered (p < 0.0001, Wilcoxon sign rank test). Output loss was strongly correlated with left- and right parotid combined dose φ = min (D{sub L}, 45 Gy) + min (D{sub R}, 45 Gy), and can be accurately predicted. Median early loss (three months) was 72% of baseline, while median overall loss (1 yr) was 56% of baseline. Fitting an exponential model to whole parotid yields dose sensitivities A{sub 3m} = 0.0604 Gy{sup −1} and A{sub 1y} = 0.0379 Gy{sup −1}. Recovery was not significantly associated with dose. Hints of lateral organ sub-segment dose–response dimorphism were observed. Conclusions: Sub-segmentation appears to predict neither loss nor recovery with any greater precision than whole parotid mean dose, though it is not any worse. Sparing the parotid to a combined dose φ of <50 Gy is recommended for a patient to keep ≈40% of baseline function and thus avoid severe xerostomia at 12 months post-treatment. It seems unlikely that a population’s mean recovery will exceed 20%–30% of baseline output at 1 yr after radiotherapy treatment using current (whole-organ based) clinical guidelines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-249: Characterization of Gynecological Tumor Heterogeneity Using Texture Analysis in the Context of An 18F-FDG PET Adaptive Protocol

Purpose: We propose a method to examine gynecological tumor heterogeneity using texture analysis in the context of an adaptive PET protocol in order to establish if texture metrics from baseline PET-CT predict tumor response better than SUV metrics alone as well as determine texture features correlating with tumor response during radiation therapy. Methods: This IRB approved protocol included 29 women with node positive gynecological cancers visible on FDG-PET treated with EBRT to the PET positive nodes. A baseline and intra-treatment PET-CT was obtained. Tumor outcome was determined based on RECIST on posttreatment PET-CT. Primary GTVs were segmented using 40% threshold and a semi-automatic gradient-based contouring tool, PET Edge (MIM Software Inc., Cleveland, OH). SUV histogram features, Metabolic Volume (MV), and Total Lesion Glycolysis (TLG) were calculated. Four 3D texture matrices describing local and regional relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 texture features were calculated. Prognostic power of baseline features derived from gradientbased and threshold GTVs were determined using the Wilcoxon rank-sum test. Receiver Operating Characteristics and logistic regression was performed using JMP (SAS Institute Inc., Cary, NC) to find probabilities of predicting response. Changes in features during treatment were determined using the Wilcoxon signed-rank test. Results: Of the 29 patients, there were 16 complete responders, 7 partial responders, and 6 non-responders. Comparing CR/PR vs. NR for gradient-based GTVs, 7 texture values, TLG, and SUV kurtosis had a p < 0.05. Threshold GTVs yielded 4 texture features and TLG with p < 0.05. From baseline to intra-treatment, 14 texture features, SUVmean, SUVmax, MV, and TLG changed with p < 0.05. Conclusion: Texture analysis of PET imaged gynecological tumors is an effective method for early prognosis and should be used complimentary to SUV metrics, especially when using gradient based segmentation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRB-07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online-Adaptive Radiotherapy

Purpose: To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online-adaptive radiotherapy plans using similarity metrics. Methods: The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam-on time), the tool computes and presents histograms of derived metrics (e.g. step-and-shoot segment field sizes, segment average leaf gaps). Such metrics were investigated for their ability to predict that an online-adapted plan reasonably similar to a baseline plan where deliverability has already been established. Results: In the realm of online-adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re-optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online-adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements. Conclusion: The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online-adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to increased assurance of plan quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Technical Report: TG-142 compliant and comprehensive quality assurance tests for respiratory gating

Purpose: To develop and establish a comprehensive gating commissioning and quality assurance procedure in compliance with TG-142. Methods: Eight Varian TrueBeam Linacs were used for this study. Gating commissioning included an end-to-end test and baseline establishment. The end-to-end test was performed using a CIRS dynamic thoracic phantom with a moving cylinder inside the lung, which was used for carrying both optically simulated luminescence detectors (OSLDs) and Gafchromic EBT2 films while the target is moving, for a point dose check and 2D profile check. In addition, baselines were established for beam-on temporal delay and calibration of the surrogate, for both megavoltage (MV) and kilovoltage (kV) beams. A motion simulation device (MotionSim) was used to provide periodic motion on a platform, in synchronizing with a surrogate motion. The overall accuracy and uncertainties were analyzed and compared. Results: The OSLD readings were within 5% compared to the planned dose (within measurement uncertainty) for both phase and amplitude gated deliveries. Film results showed less than 3% agreement to the predicted dose with a standard sinusoid motion. The gate-on temporal accuracy was averaged at 139 ± 10 ms for MV beams and 92 ± 11 ms for kV beams. The temporal delay of the surrogate motion depends on the motion speed and was averaged at 54.6 ± 3.1 ms for slow, 24.9 ± 2.9 ms for intermediate, and 23.0 ± 20.1 ms for fast speed. Conclusions: A comprehensive gating commissioning procedure was introduced for verifying the output accuracy and establishing the temporal accuracy baselines with respiratory gating. The baselines are needed for routine quality assurance tests, as suggested by TG-142.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-222: Using PET Imaging to Evaluate Proliferation and Blood Flow in Irradiated and Non-Irradiated Bone Marrow 1 Year After Chemoradiation Therapy

Purpose: To compare proliferation and blood flow in pelvic and thoracic bone marrow 1 year after pelvic chemoradiation. Methods: Sixteen pelvic cancer patients were enrolled in an IRB-approved protocol to acquire FLT PET images during radiation therapy simulation (baseline) and 1 year after chemoradiation therapy. Three subjects also had optional O-15 water PET images acquired 1 year after chemoradiation therapy. Baseline FLT PET images were used to create IMRT plans to spare pelvic bone marrow identified as regions with FLT SUV ≥ 2 without compromising PTV coverage or OAR sparing. Marrow VOIs were defined using a 50% maximum pixel value threshold on baseline FLT PET images (VIEW, PMOD version 3.5) in the sacrum and thoracic spine representing irradiated and non-irradiated regions, respectively. FLT PET and O-15 water PET images acquired 1 year after therapy were co-registered to baseline images (FUSION PMOD) and the same VOIs were used to measure proliferation (FLT SUV) and blood flow (O-15 water uptake). Separate image-based input functions were used for blood flow quantitation in each VOI. Results: Mean 1 year FLT SUV in sacral and thoracic VOIs for were 1.1 ± 0.4 and 6.5 ± 1.7, respectively for N = 16 subjects and were 1.2 ± 0.2 and 5.6 ± 1.6, respectively for N = 3 subjects who also underwent O-15 water imaging. Blood flow measures in equivalent sacral and thoracic marrow regions (N = 3) were 21.3 ± 8.7 and 18.3 ± 4.9 mL/min/100mL respectively. Conclusion: Decreased bone marrow proliferation measured by FLT SUV does not appear to correspond to decreased blood flow as measured by O-15 water PET imaging. Based on this small sample at a single time point, reduced blood supply does not explain reductions in bone marrow proliferative activity 1 year after chemoradiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Sources of Uncertainty in Modeled Land Carbon Storage within and across Three MIPs: Diagnosis with Three New Techniques

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land–Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. Here in this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Finally, since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Design and performance of optimal detectors for guided wave structural health monitoring

Ultrasonic guided wave measurements in a long term structural health monitoring system are affected by measurement noise, environmental conditions, transducer aging and malfunction. This results in measurement variability which affects detection performance, especially in complex structures where baseline data comparison is required. This paper derives the optimal detector structure, within the framework of detection theory, where a guided wave signal at the sensor is represented by a single feature value that can be used for comparison with a threshold. Three different types of detectors are derived depending on the underlying structure’s complexity: (i) Simple structures where defect reflections can be identified without the need for baseline data; (ii) Simple structures that require baseline data due to overlap of defect scatter with scatter from structural features; (iii) Complex structure with dense structural features that require baseline data. The detectors are derived by modeling the effects of variabilities and uncertainties as random processes. Analytical solutions for the performance of detectors in terms of the probability of detection and false alarm are derived. A finite element model is used to generate guided wave signals and the performance results of a Monte-Carlo simulation are compared with the theoretical performance. initial results demonstrate that the problems of signal complexity and environmental variability can in fact be exploited to improve detection performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Preclinical evaluation of 18 F-ML-10 to determine timing of apoptotic response to chemotherapy in solid tumors

Here, we investigated 2-(5-fluoro-pentyl)-2-methyl-malonic acid ( 18 F-ML-10) positron emission tomography (PET) imaging of apoptosis posttherapy to determine optimal timing for predicting chemotherapy response in a mouse head/neck xenograft cancer model. BALB/c nude mice (4-8 weeks old) were implanted with UM-SCC-22B tumors. The treatment group received 2 doses of doxorubicin (10 mg/kg, days 0, 2). Small animal 18 F-ML-10 PET/computed tomography was performed before and on days 1, 3, and 7 postchemotherapy. Using regions of interest around tumors, 18 F-ML-10 uptake change was measured as %ID/g and uptake relative to liver. Terminal Uridine Nick-End Labeling (TUNEL) immunohistochemistry assay was performed using tumor samples of baseline and on days 1, 3, and 7 posttreatment. As a result, treated mice demonstrated increased 18 F-ML-10 uptake compared to baseline and controls, and 10 of 13 mice showed tumor volume decreases. All control mice showed tumor volume increases. Tumor-to-liver (T/L) ratios from the control group mice did not show significant change from baseline ( P > .05); however, T/L ratios of the treatment group showed significant 18 F-ML-10 uptake differences from baseline compared to days 3 and 7 posttreatment ( P < .05), but no significant difference at 1 day posttreatment. In conclusion, 2-(5-Fluoro-pentyl)-2-methyl-malonic acid PET imaging has the potential for early assessment of treatment-induced apoptosis. Timing and image analysis strategies may require optimization, depending on the type of tumor and cancer treatment.

18F-ML-10↗
DOE OSTI2012

How to overcome inter-electrode variability and instability to quantify dissolved oxygen, Fe(II), mn(II), and S(-II) in undisturbed soils and sediments using voltammetry

Background: Although uniquely capable of measuring multiple redox constituents nearly simultaneously with no or minimal sample pretreatment, voltammetry is currently underutilized in characterizing redox conditions in aquatic and terrestrial systems. Investigation of undisturbed media such as pore water requires a solid-state electrode, and such electrodes can be difficult to fabricate reproducibly. An approach to determine the concentrations of electroactive constituents using indirectly calibrated electrodes has been developed, but the protocol for and accuracy of this approach—the pilot ion method—has not been documented in detail. Results: A detailed procedure for testing electrode quality is provided, and the application and limitations of the pilot ion method have been documented. To quantify Fe(II) and Mn(II), subtraction of non-linear baseline functions from voltammetric signals produced better calibration curves than did linear baselines, enabled lower detection limits and reliable deconvolution of overlapping signals, and was successfully applied to sediment pore water signals. We observed that electrode sensitivities often vary by tens of percent, and that the sensitivity declines over time. The ratio of calibration slopes of Mn(II) to Fe(II) varied by no more than 11% from one Hg/Au electrode to another and Fe(II) concentrations predicted by the Mn(II) pilot ion were, on average, 13% different from their actual values. However, concentration predictions by the pilot ion method were worse for less than 15 μM Fe(II) (46% different on average). The ratio of calibration slopes of Mn(II) to S(-II) varied by almost 20% from one Hg/Au electrode to another, and S(-II) predicted concentrations were as much as 58% different from their actual values. These predictions of Fe(II) and S(-II) concentrations indicate that the accuracy of the pilot ion method depends on how independent calibration slope ratios are from the electrode used. At medium-to-high concentration for the ocean, naturally derived dissolved organic carbon did not significantly affect the baseline-corrected electrode response of Mn(II) and Fe(II), but did significantly affect the response of S(-II). Conclusions: Despite their intrinsic variability, Hg/Au electrodes fabricated by hand can be used to quantify O2, S (-II), Fe(II), and Mn(II) without calibrating every electrode for every constituent of interest. The pilot ion method can achieve accuracies to within 20% or less, provided that the underlying principle—the independence of slope ratios—is demonstrated for all voltammetric techniques used, and effects of the physicochemical properties of the system on voltammetric signals are addressed through baseline subtraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Geothermal Exploration Cost and Time

This paper describes the methodology used to define the baseline exploration suite of techniques (baseline), as well as the approach that was used to create the cost and time data set that populates the baseline. The resulting product, an online tool for measuring impact, and the aggregated cost and time data are available on the Open Energy Information website (OpenEI, http://en.openei.org) for public access. The Department of Energy's Geothermal Technology Office (GTO) provides RD&D funding for geothermal exploration technologies with the goal of lowering the risks and costs of geothermal development and exploration. The National Renewable Energy Laboratory (NREL) developed this cost and time metric included collecting cost and time data for exploration techniques, creating a baseline suite of exploration techniques to which future exploration cost and time improvements can be compared, and developing an online tool for graphically showing potential project impacts (all available at http://en.openei.org/wiki/Gateway: Geothermal).

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Topsoil bulk geochemical compositions - An updated harmonized global dataset

Mineral weathering is a key biogeochemical process because of the capacity of minerals to stabilize organic matter. However, predicting soil weathering status across large spatial areas still isn’t possible due to a lack of global data and theoretical frameworks. To address this knowledge gap, multiple global datasets of bulk topsoil geochemical compositions have been harmonized using R. These datasets document topsoil bulk geochemical compositions across five continents (n = ~16,000 observations). Source data for these observations include the EuroGEOSurveys Geochemical Baseline Database (FOREGS), the US Geological Survey National Geochemical Database (NASGLP), the Geochemical Atlas of Australia (GAA), the US Geological Survey Alaska Geochemical Database (AGD84), the National Cooperative Soil Survey (NCSS), the European Geochemical Mapping of Agricultural Soil (GEMAS), Ecorespira-Amazon (ERA), the New Zealand Geochemical Baseline Survey (NZ_GBS), and the African Soil Information Service (AFSIS). Major elements observed include Aluminum (Al), Calcium (Ca), Iron (Fe), Potassium (K), Magnesium (Mg), Sodium (Na), Titanium (Ti), Manganese (Mn), Phosphorus (P), Carbon (C), and Sulfur (S). This data package includes the harmonized dataset itself, and the R scripts necessary to harmonize these datasets, in addition to metadata that describes all columns, files, and databases used in this project. Methods & Sampling Step 1 – Databases of geochemical data identified This study aimed to leverage existing measurements of topsoil geochemical data. Databases were first identified and deemed appropriate for inclusion if they were measuring soils and performed these measurements on the <2mm soil fraction. Databases such as NCSS and AGD84 needed more post processing to include in the database and this was done using the NCSS_datamerge_031626 R file and Alaska_USGSmerge_031626 R file, respectively. Step 2 – Database harmonization Once appropriate databases were identified, they were harmonized for ease of analysis using the R script Database_Harmonization_031826. This included removing columns from original datasets that would not be used in analysis (removed columns are noted in the code). Then, data cleaning procedures specific to each dataset were undertaken. This includes standardizing columns to include units and adding metadata columns regarding procedures for analyzing specific elements. Functions for standardizing measurements and units are outline in R files: calculate element_mg_kg_031626, calculate_oxide_wt_perc_031626, change_oxide_caps_031626, and conv_2_numeric_031626. This also included adding a unique identifier for each sample to identify it with its respective database (see CD_ID in data dictionary). Geographic information: Data reflect a compilation of datasets collected globally. Geographic areas covered by each of the datasets include: - EuroGEOSurveys Geochemical Baseline Database (FOREGS) - European continent - North American Soil Geochemical Landscapes (NASGLP) - continental United States and limited parts of Canada (see database key for more details) - National Geochemical Survey of Australia (GAA) - Australia - Alaska geochemical database (AGDB4) - Alaska - National Cooperative Soil Survey (NCSS) - Global measurements, but concentrated in the continental United States - Geochemical data for arable land and land under permanent grass cover in continental Europe (GEMAS) - continental Europe - Ecorespira-Amazon (ERA) - Geochemical data from the Amazon basin - Geochemical baseline data for New Zealand (NZGBS) - New Zealand - Geochemical data collected across continental Africa (AfSIS) - Measurements across Africa

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2026

Data and Scripts Associated with "Modeling Ecohydrological Responses of Vegetation to Urban Microclimates Using the E3SM Land Model"

This dataset supports the study of vegetation ecohydrological responses to urban microclimates using the land component of the Energy Exascale Earth System Model (ELM) at four urban sites in Knoxville, Tennessee, USA. It includes the model inputs, simulation outputs, and associated scripts for running ELM simulations and analyzing the resulting data. The Model_Inputs folder includes static surface data, satellite-derived phenology (i.e., leaf area index), and atmospheric forcing data used to drive ELM simulations. Detailed descriptions of these datasets are provided in Section 2.3.2 of the associated manuscript. The Model_Outputs folder contains simulation results for the baseline, treatment, and ensemble experiments. Outputs from the baseline and treatment simulations are provided as raw ELM NetCDF files. Because the raw outputs from the 4,000-member ensemble are prohibitively large, the ensemble results are provided as summarized CSV files, which also serve as the source data for Figure 5 of the associated manuscript. The Scripts folder contains three components: E3SM, the core codebase of the Energy Exascale Earth System Model (E3SM); elm-olmt, the Offline Land Model Testbed (OLMT) used to perform the simulations; and knoxville_elm, which contains the analysis scripts used to process model outputs and generate the figures and results presented in the associated manuscript. Additional information is provided in Scripts_readme.txt within the Scripts directory.

Lu, Xiaoman [ORNL] (ORCID:0000000306698780)↗
DOE OSTI2023

The Effect of Prostate-Specific Antigen (PSA) Test on Radiation Risk Estimate for Prostate Cancer Incidence among Atomic-Bomb Survivors

Following our previous report on the radiation doseresponse for prostate cancer incidence rates in the Life Span Study (LSS) cohort of atomic bomb survivors, we reevaluated the radiation-related risk adjusting for differences in baseline cancer incidence rates among three subsets of the LSS cohort defined by the timing of their first participation in biennial health examinations offered to the Adult Health Study (AHS) sub-cohort members and prostate-specificantigen (PSA) testing status for AHS participants: 1. nonAHS participants, 2. AHS participants before receiving PSA test, and 3. AHS participants after receiving PSA test. We found a 2.9-fold increase in the baseline incidence rates among AHS participants after receiving PSA test. After adjusting for the PSA-testing-status effects on the baseline rates the estimated excess relative risk (ERR) per Gy was 0.54 (95% CI: 0.15, 1.05), which was almost identical to the previously reported unadjusted ERR estimate (0.57, 95% CI: 0.21, 1.00). The current results confirmed that, while the PSA testing among AHS participants increased the baseline incidence rates, it did not impact the radiation risk estimate, strengthening the previously reported dose-response relationship for prostate cancer incidence in the LSS. As the use of PSA tests continue in screening and medical settings, analyses of possible effects of PSA testing should be an important aspect of future epidemiological studies of the association between radiation exposure and prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Muon-neutrino disappearance with multiple liquid argon time projection chambers in the Fermilab Booster neutrino beam

The Short Baseline Neutrino (SBN) program consists of three liquid argon time projection chamber (LArTPC) experiments: SBND, MicroBooNE and ICARUS, with 110 m, 470 m and 600 m baselines respectively. The detectors are located in the Booster Neutrino Beam (BNB) at Fermilab which has a peak energy around 0.7 GeV and contains predominantly muon neutrinos. The baseline and energy range of the SBN program is conducive to measuring neutrino oscillation parameters under various sterile neutrino hypotheses. Sterile neutrinos have been proposed as a possible solution to the numerous short baseline anomalies. The proposed particles must be sterile in nature such that they do not interact via the weak force, however they may undergo oscillations with the active neutrino flavours. Their existence may consequently be confirmed through measurements of the appearance and disappearance of the active flavours. The analyses presented in this thesis aimed to calculate and understand the sensitivity of the SBN program to measuring the ?µ disappearance parameters under the (3+1) sterile neutrino oscillation hypothesis. The sensitivity of SBN to measuring the ?µ disappearance sterile oscillation parameters, sin2 2?µµ, ?m2 41, was calculated through semi-exclusive joint fits of the ?µ CC 0p and ?µ CC Other reconstructed neutrino energy spectra. The first iteration used truth-level Monte Carlo (MC) events, and determined that the 5s SBN sensitivity is comparable to the 90% MINOS/MINOS+ confidence level and supersedes the 90% MiniBooNE confidence level across entire phase space. Semi-exclusive joint fits of the aforementioned sample spectra were performed between the MC and multiple mock data sets in SBND. This analysis assessed the accuracy with which the near detector can disentangle systematic from physics effects in the oscillation analysis. The result was a 5.49% discrepancy between the ICARUS Monte Carlo and mock data event rates, when the systematic constraints from the near detector fit were extrapolated to the far detector. The second iteration of the SBN sensitivity analysis involved the application of an event selection procedure developed in SBND, following the full reconstruction chain. ?µ CC 0p events were selected from sample of neutrinos with 84.5% efficiency and 84.3% purity. The sterile neutrino sensitivity was determined once more at the near detector with these samples, and was shown to be consistent with the truth-level studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Development of CdS/CdTe Thin Film Devices for St. Gobain Coated Glass (CRADA Final Report)

Research performed at NREL to produce CdS/CdTe devices on St. Gobain coated-glass material to establish a baseline CdS/CdTe device process and determine baseline device performance parameters on St. Gobain material. Performance of these baseline devices compared to similar devices produced by applying the established baseline CdS/CdTe process on alternative St. Gobain coated-glass materials.

14 SOLAR ENERGY↗