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At least 1,279 records · Page 71

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗

Visualizing the impact of quenched disorder on 2D electron Wigner solids

Electron Wigner solids (WSs) provide an ideal system for understanding the competing effects of electron–electron and electron–disorder interactions, a central unsolved problem in condensed matter physics. Progress in this topic has been limited by a lack of single-defect-resolved experimental measurements as well as accurate theoretical tools to enable realistic experiment/theory comparison. Here, in this study, we overcome these limitations by combining atomically resolved scanning tunnelling microscopy (STM) with neural-quantum-state quantum Monte Carlo (NQS-QMC) simulation of disordered 2D electron WSs to discover new disorder-induced physical regimes of correlated electron behaviour. STM was used to image the electron density (n e )-dependent evolution of electron WSs in gate-tunable bilayer MoSe 2 (BL-MoSe 2 ) devices with varying long-range (n LR ) and short-range (n SR ) disorder densities. These images were compared with NQS-QMC simulations using realistic disorder maps extracted from experiment, thus allowing the roles of different disorder types to be disentangled. We identify two distinct physical regimes for disordered electron WSs that depend on n SR . For n SR ≲ n e , the WS behaviour is dominated by long-range disorder and features extensive mixed solid–liquid phases, a new type of local re-entrant melting/crystallization and prominent Friedel oscillations. By contrast, when n SR ≫ n e , these features are suppressed and a more robust amorphous WS phase emerges that persists to higher n e , highlighting the importance of short-range disorder in this regime. Our work establishes a powerful framework for studying disordered quantum solids through a combined experimental–theoretical approach.

Ge, Zhehao [University of California, Berkeley, CA↗

POST-MERGER SIGNATURES OF RED-SEQUENCE GALAXIES IN RICH ABELL CLUSTERS AT z {approx}< 0.1

We have investigated the post-merger signatures of red-sequence galaxies in rich Abell clusters at z {approx}< 0.1: A119, A2670, A3330, and A389. Deep images in u', g', r', and medium-resolution galaxy spectra were taken using MOSAIC II CCD and Hydra MOS mounted on a Blanco 4 m telescope at Cerro Tololo Inter-American Observatory. Post-merger features are identified by visual inspection based on asymmetric disturbed features, faint structures, discontinuous halo structures, rings, and dust lanes. We found that {approx}25% of bright (M{sub r} < -20) cluster red-sequence galaxies show post-merger signatures in four clusters consistently. Most ({approx}71%) of the featured galaxies were found to be bulge dominated, and for the subsample of bulge-dominated red-sequence galaxies, the post-merger fraction rises to {approx}38%. We also found that roughly 4% of bulge-dominated red-sequence galaxies interact (ongoing merger). A total of 42% (38% post-merger, 4% ongoing merger) of galaxies show merger-related features. Compared to a field galaxy study with a similar limiting magnitude by van Dokkum in 2005, our cluster study presents a similar post-merger fraction but a markedly lower ongoing merger fraction. The merger fraction derived is surprisingly high for the high density of our clusters, where the fast internal motions of galaxies are thought to play a negative role in galaxy mergers. The fraction of post-merger and ongoing merger galaxies can be explained as follows. Most of the post-merger galaxies may have carried over their merger features from their previous halo environment, whereas interacting galaxies interact in the current cluster in situ. According to our semi-analytic calculation, massive cluster halos may very well have experienced tens of halo mergers over the last 4-5 Gyr; post-merger features last that long, allowing these features to be detected in our clusters today. The apparent lack of dependence of the merger fraction on the clustocentric distance is naturally explained this way. In this scenario, the galaxy morphology and properties can be properly interpreted only when the halo evolution characteristics are understood first.

79 ASTRONOMY AND ASTROPHYSICS↗

Fractal dimension of optical cirrus in Stripe82

ABSTRACT The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the 2D fractal dimension D of a cloud projected on to the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2–1.4. In this work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69^{+0.05}_{-0.05}$ which is significantly larger than the fractal dimension of its IR counterparts $\langle D\rangle =1.38^{+0.07}_{-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it.

79 ASTRONOMY AND ASTROPHYSICS↗

WE-AB-207A-03: A CBCT Head Scanner for Point-Of-Care Imaging of Intracranial Hemorrhage

Purpose: This work reports the design, development, and first technical assessment of a cone-beam CT (CBCT) scanner developed specifically for imaging of acute intracranial hemorrhage (ICH) at the point of care, with target applications in diagnosis and monitoring of traumatic brain injury, stroke, and postsurgical hemorrhage. Methods: System design employed a task-based image quality model to quantify the influence of factors such as additive noise and high-gain (HG) detector readout on ICH detectability. Three bowtie filters with varying bare-beam attenuation strength and curvature were designed to enable HG readout without detector saturation, and a polyenergetic gain correction was developed to minimize artifacts from bowtie flood-field calibration. Image reconstruction used an iterative penalized weighted least squares (PWLS) method with artifact correction including Monte Carlo scatter estimation, Joseph-Spital beam hardening correction, and spatiotemporal deconvolution of detector glare and lag. Radiation dose was characterized for half-scan and full-scan protocols at various kV, and imaging performance was assessed in a head phantom presenting simulated ICH with diameter ranging 2–12 mm. Results: The image quality model guided system design and was validated by measurements on a CBCT imaging bench. Compared to low-gain readout without a bowtie filter, the combination of HG readout and a modest bowtie improved the contrast-to-noise ratio (CNR per unit square-root dose) by 20% in the center of the image but degraded noise performance near the periphery (20% reduction in CNR). Low-frequency bowtie artifacts (∼100 HU magnitude) were corrected by the polyenergetic gain correction. Image reconstructions on the prototype scanner demonstrate clear visibility of the smallest ICH insert (2 mm diameter) in both HG readout (with a bowtie) and dual-gain readout (without bowtie). Conclusion: Technical assessment of the prototype scanner suggests the capability for reliable visualization of small (2 mm), low-contrast (50 HU) ICH at <20 mGy dose and motivates translation to clinical studies, now underway. Xiaohui Wang and David Foos (co-authors) are employees of Carestream Health. Research funding support from Carestream Health.

60 APPLIED LIFE SCIENCES↗

Angle Assessment for Upper Limb Rehabilitation: A Novel Light Detection and Ranging (LiDAR)-Based Approach

The accurate measurement of joint angles during patient rehabilitation is crucial for informed decision making by physiotherapists. Presently, visual inspection stands as one of the prevalent methods for angle assessment. Although it could appear the most straightforward way to assess the angles, it presents a problem related to the high susceptibility to error in the angle estimation. In light of this, this study investigates the possibility of using a new approach to angle calculation: a hybrid approach leveraging both a camera and LiDAR technology, merging image data with point cloud information. This method employs AI-driven techniques to identify the individual and their joints, utilizing the cloud-point data for angle computation. The tests, considering different exercises with different perspectives and distances, showed a slight improvement compared to using YOLO v7 for angle calculation. However, the improvement comes with higher system costs when compared with other image-based approaches due to the necessity of equipment such as LiDAR and a loss of fluidity during the exercise performance. Therefore, the cost–benefit of the proposed approach could be questionable. Nonetheless, the results hint at a promising field for further exploration and the potential viability of using the proposed methodology.

Klein, Luan C. (ORCID:000000016306574X)↗

Synchrotron‐source micro‐x‐ray computed tomography for examining butterfly eyes

Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro-x-ray computed tomography (syn-μXCT) combined with machine learning algorithms for high-throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm 3 at 600 nm 3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species-independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.

59 BASIC BIOLOGICAL SCIENCES↗

LAMP detection assays for boxwood blight pathogens: A comparative genomics approach

Rapid and accurate molecular diagnostic tools are critical to efforts to minimize the impact and spread of emergent pathogens. The identification of diagnostic markers for novel pathogens presents several challenges, especially in the absence of information about population diversity and where genetic resources are limited. The objective of this study was to use comparative genomics datasets to find unique target regions suitable for the diagnosis of two fungal species causing a newly emergent blight disease of boxwood. Candidate marker regions for loop-mediated isothermal amplification (LAMP) assays were identified from draft genomes of Calonectria henricotiae and C. pseudonaviculata , as well as three related species not associated with this disease. To increase the probability of identifying unique targets, we used three approaches to mine genome datasets, based on (i) unique regions, (ii) polymorphisms, and (iii) presence/absence of regions across datasets. From a pool of candidate markers, we demonstrate LAMP assay specificity by testing related fungal species, common boxwood pathogens, and environmental samples containing 445 diverse fungal taxa. In conclusion, this comparative-genomics-based approach to the development of LAMP diagnostic assays is the first of its kind for fungi and could be easily applied to diagnostic marker development for other newly emergent plant pathogens.

1st report↗

TU-F-18C-07: Hardware Advances for MTF Improvement in Dedicated Breast CT

Purpose: In this study, we have designed and implemented a prototype dedicated breast CT system (bCT) to improve the spatial resolution characteristics, in order to improve detection of micro-calcifications. Methods: A 10.8 kW water-cooled, tungsten anode x-ray tube, running up to 240 mA at 60 kV, coupled with an x-ray generator specifically designed for this application, and 0.3 mm of added copper filter was used to generate x-ray pulses. A CsI CMOS flat panel detector with a pixel pitch of 0.075 mm in native binning mode was used. The system geometry was designed in a way to achieve an FOV on par with similar bCT prototypes, resulting in a magnification factor of 1.39. A 0.013 mm tungsten wire was used to generate point spread functions. Multiple scans were performed with different numbers of projections, different reconstruction kernel sizes and different reconstruction filters to study the effects of each parameter on MTF. The resulting MTFs were then evaluated quantitatively using the generated PFSs. Duplicate scans with the same parameters were performed on two other dedicated breast CT systems to compare the performance of the new prototype. Results: The results of the MTF experiments demonstrate a significant improvement in the spatial resolution characteristics. In the new prototype, using the pulsed x-ray source results in a restoration of the azimuthal MTF degradation, due to motion blurring previously seen in other bCT systems. Moreover, employing the higher resolution x-ray detector considerably improves the MTF. The MTF at 10% of the new system is at 3.5 1/mm, a factor of 4.36 greater than an earlier bCT scanner. Conclusion: The MTF analysis of the new prototype bCT shows that using the new hardware and control results in a significant improvement in visualization of finer detail. This suggests that the visualization of micro-calcifications will be significantly improved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗

A Hierarchical Feature-Based Methodology to Perform Cervical Cancer Classification

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. We investigate eight traditional machine learning methods to perform a hierarchical classification. We propose a hierarchical classification methodology for computer-aided screening of cell lesions, which can recommend fields of view from the microscopy image based on the nuclei detection of cervical cells. We evaluate the performance of several algorithms against the Herlev and CRIC databases, using a varying number of classes during image classification. Results indicate that the hierarchical classification performed best when using Random Forest as the key classifier, particularly when compared with decision trees, k-NN, and the Ridge methods.

60 APPLIED LIFE SCIENCES↗

Improving I/O-aware Workflow Scheduling via Data Flow Characterization and trade-off Analysis

The scientific computing paradigm has transitioned from compute-intensive to I/O-intensive and memory-intensive in the past decade, especially when data-driven science has become common practice. Numerous empirical I/O-aware scheduling optimizations have been developed by incorporating I/O capacity and bandwidth as constraints into scheduling. Unfortunately, there is a lack of data flow (I/O) characterization tool and an understanding of trade-offs between concurrency, locality, and I/O bandwidth. To bridge the gap, this work 1) presents a set of descriptors to characterize, organize, and visualize I/O profiles, including flow size, I/O bandwidth, and operation count, which group data flows by I/O types, tasks, and files; 2) proposes an I/O Roofline model-based trade-off analysis to find the optimal trade-off between flow operational intensity, concurrency, and flow performance. The I/O descriptors generate useful insights into complicated I/O behaviors, suggesting distinct concurrency, storage, and scheduling to be used by types, tasks, and files. The proposed trade-off analysis guides scheduling decisions that generate resource assignment with the best flow parallelism. We evaluate our I/O-aware scheduling methodology on a highly I/O-intensive workflow–1000 Genomes. The experimental results demonstrate speedups of up to 2.4× compared to the state-of-the- art methods.

Guo, Luanzheng [BATTELLE (PACIFIC NW LAB)]↗

Instability, mixing, and transition to turbulence in a laser-driven counterflowing shear experiment

In a turbulence experiment conducted at the Omega Laser Facility [Boehly et al., Opt. Commun. 133, 495 (1997)]], regions of 60 mg/cc foam are separated by an aluminum plate running the length of a 1.6 mm shock tube. Two counter-propagating laser-driven shocks are used to create a high speed, {Delta}V=140 km/s shear flow environment, sustained for {approx}10 ns, while canceling the transverse pressure gradient across the interface. The spreading of the aluminum by shear-instability-induced mixing is measured by x-ray radiography. The width of the mix region is compared to simulations. Reynolds numbers Greater-Than-Or-Equivalent-To 4 Multiplication-Sign 10{sup 5} are achieved within the layer. Following the onset of shear, we observe striations corresponding to the dominant mode growth and their transition through non-linear structures to developed turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Visualization of defects in single-crystal and thin-film PdCoO 2 using aberration-corrected scanning transmission electron microscopy

Single-crystal delafossite PdCoO 2 is known to have an extremely low intrinsic impurity concentration of ~0.001%, demonstrating extraordinarily high conductivity with a mean free path of ~20 μm at low temperatures. However, when grown as thin films, the resistivity at room temperature increases by a factor of 3–80 times, depending on the film thickness. Using scanning transmission electron microscopy, we identify different classes of defects for the single crystal vs epitaxial thin film. The dominant defect for single-crystal PdCoO 2 is found to be ribbonlike defects. For the thin films, we identify different types of defects arising in epitaxial thin films mainly due to substrate termination that disrupt the lateral connectivity of the conducting planes. Further, our results are consistent with the high conductivity of single crystals and increased electrical resistivity of the thin films compared to that of single crystals, suggesting that selecting a proper substrate, improving surface quality, and reducing the step density are the keys to enhance the film quality for utilizing PdCoO 2 as a platform for future applications.

36 MATERIALS SCIENCE↗

The impact of hot-press conditions on the durability of polymer electrolyte membrane fuel cells

The proton exchange membrane integrity can be compromised during hot-press fabrication of membrane electrode assemblies (MEAs) causing premature cell failures during operation. In this work, infrared (IR) thermography was used as a diagnostic tool to spatially visualize hydrogen (H 2 ) crossover and identify process-induced-membrane irregularities (PIMs). These irregularities were identified as seed locations for MEA failures. Fine tuning of hot-press conditions was used to mitigate premature cell failures informed by accelerated stress testing (AST). The impact of PIMs on the initial performance, high-frequency resistances, open-circuit voltage, and H 2 crossover are reported. Nafion XL and 212 membranes, hot-pressed with a force of 16 kg/cm 2 and temperature of 120°C, were found to be consistently irregularity-free. Irregularity-free MEAs using Nafion 211, 212, and XL membranes demonstrated AST lifetime improvements of 58, 64 and 400%, respectively, compared to those fabricated with non-optimized conditions. In conclusion, this work highlights the importance of fabrication parameters on premature cell failures.

08 HYDROGEN↗

3D localization of electrophysiology catheters from a single x-ray cone-beam projection

Purpose: X-ray images allow the visualization of percutaneous devices such as catheters in real time but inherently lack depth information. The provision of 3D localization of these devices from cone beam x-ray projections would be advantageous for interventions such as electrophysiology (EP), whereby the operator needs to return a device to the same anatomical locations during the procedure. A method to achieve real-time 3D single view localization (SVL) of an object of known geometry from a single x-ray image is presented. SVL exploits the change in the magnification of an object as its distance from the x-ray source is varied. The x-ray projection of an object of interest is compared to a synthetic x-ray projection of a model of said object as its pose is varied. Methods: SVL was tested with a 3 mm spherical marker and an electrophysiology catheter. The effect of x-ray acquisition parameters on SVL was investigated. An independent reference localization method was developed to compare results when imaging a catheter translated via a computer controlled three-axes stage. SVL was also performed on clinical fluoroscopy image sequences. A commercial navigation system was used in some clinical image sequences for comparison. Results: SVL estimates exhibited little change as x-ray acquisition parameters were varied. The reproducibility of catheter position estimates in phantoms denoted by the standard deviations, (σ{sub x}, σ{sub y}, σ{sub z}) = (0.099 mm, 0.093 mm, 2.2 mm), where x and y are parallel to the detector plane and z is the distance from the x-ray source. Position estimates (x, y, z) exhibited a 4% systematic error (underestimation) when compared to the reference method. The authors demonstrated that EP catheters can be tracked in clinical fluoroscopic images. Conclusions: It has been shown that EP catheters can be localized in real time in phantoms and clinical images at fluoroscopic exposure rates. Further work is required to characterize performance in clinical images as well as the sensitivity to clinical image quality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Independent Confirmatory Survey Summary and Results for the Ford Nuclear Reactor, Ann Arbor, Michigan

At the NRC's request, ORAU conducted confirmatory surveys of the FNR during the period of December 4 through 6, 2012. The survey activities included visual inspections and measurement and sampling activities. Confirmatory activities also included the review and assessment of UM's project documentation and methodologies. Surface scans identified elevated activity in two areas. The first area was on a wall outside of Room 3103 and the second area was in the southwest section on the first floor. The first area was remediated to background levels. However, the second area was due to gamma shine from a neighboring source storage area. A retrospective analysis of UM's FSS data shows that for the SUs investigated by the ORAU survey team, UM met the survey requirements set forth in the FSSP. The total mean surface activity values were directly compared with the mean total surface activity reported by UM. Mean surface activity values determined by UM were within two standard deviations of the mean determined by ORAU. Additionally, all surface activity values were less than the corresponding gross beta DCGLW. Laboratory analysis of the soil showed that COC concentrations were less than the respective DCGLW values. For the inter-lab comparison, the DER was above 3 for only one sample. However, since the sum of fractions for each of the soil samples was below 1, thus none of the samples would fail to meet release guidelines. Based on the findings of the side-by-side direct measurements, and after discussion with the NRC and ORAU, UM decided to use a more appropriate source efficiency in their direct measurement calculations and changed their source efficiency from 0.37 to 0.25.

54 ENVIRONMENTAL SCIENCES↗