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U.S. emissions of HFC-134a derived for 2008-2012 from an extensive flask-air sampling network: US emissions of HFC-134a

U.S. national and regional emissions of HFC-134a are derived for 2008-2012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximumlikelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr -1 for the contiguous U.S. during 2008-2012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 2008-2010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 10-20% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO 2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 20-50%.

54 ENVIRONMENTAL SCIENCES↗

SU-E-J-108: Template Matching Based On Multiple Templates Can Improve the Tumor Tracking Performance When There Is Large Tumor Deformation

Purpose: Recently, template matching has been shown to be able to track tumor motion on cine-MRI images. However, artifacts such as deformation, rotation, and/or out-of-plane movement could seriously degrade the performance of this technique. In this work, we demonstrate the utility of multiple templates derived from different phases of tumor motion in reducing the negative effects of artifacts and improving the accuracy of template matching methods. Methods: Data from 2 patients with large tumors and significant tumor deformation were analyzed from a group of 12 patients from an earlier study. Cine-MRI (200 frames) imaging was performed while the patients were instructed to breathe normally. Ground truth tumor position was established on each frame manually by a radiation oncologist. Tumor positions were also automatically determined using template matching with either single or multiple (5) templates. The tracking errors, defined as the absolute differences in tumor positions determined by the manual and automated methods, when using either single or multiple templates were compared in both the AP and SI directions, respectively. Results: Using multiple templates reduced the tracking error of template matching. In the SI direction where the tumor movement and deformation were significant, the mean tracking error decreased from 1.94 mm to 0.91 mm (Patient 1) and from 6.61 mm to 2.06 mm (Patient 2). In the AP direction where the tumor movement was small, the reduction of the mean tracking error was significant in Patient 1 (from 3.36 mm to 1.04 mm), but not in Patient 2 ( from 3.86 mm to 3.80 mm). Conclusion: This study shows the effectiveness of using multiple templates in improving the performance of template matching when artifacts like large tumor deformation or out-of-plane motion exists. Accurate tumor tracking capabilities can be integrated with MRI guided radiation therapy systems. This work was supported in part by grants from NIH/NCI CA 124766 and Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗

Physics-constrained, low-dimensional models for magnetohydrodynamics: First-principles and data-driven approaches

Plasmas are highly nonlinear and multiscale, motivating a hierarchy of models to understand and describe their behavior. However, there is a scarcity of plasma models of lower fidelity than magnetohydrodynamics (MHD), although these reduced models hold promise for understanding key physical mechanisms, efficient computation, and real-time optimization and control. Galerkin models, obtained by projection of the MHD equations onto a truncated modal basis, and data-driven models, obtained by modern machine learning and system identification, can furnish this gap in the lower levels of the model hierarchy. This work develops a reduced-order modeling framework for compressible plasmas, leveraging decades of progress in projection-based and data-driven modeling of fluids. We begin by formalizing projection-based model reduction for nonlinear MHD systems. To avoid separate modal decompositions for the magnetic, velocity, and pressure fields, we introduce an energy inner product to synthesize all of the fields into a dimensionally consistent, reduced-order basis. Next, we obtain an analytic model by Galerkin projection of the Hall-MHD equations onto these modes. We illustrate how global conservation laws constrain the model parameters, revealing symmetries that can be enforced in data-driven models, directly connecting these models to the underlying physics. We demonstrate the effectiveness of this approach on data from high-fidelity numerical simulations of a three-dimensional spheromak experiment. Finally, this manuscript builds a bridge to the extensive Galerkin literature in fluid mechanics and facilitates future principled development of projection-based and data-driven models for plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reducing radiation dose for multi-phase contrast-enhanced dual energy renal CT: pilot study evaluating prior iterative reconstruction

Purpose: Prior iterative reconstruction (PIR) uses spatial information from one phase of enhancement to reduce image noise in other phases. We sought to determine if PIR could reduce radiation dose while preserving observer performance and CT number at multi-phase dual energy (DE) renal CT. Methods: CT projection data from multi-phase DE renal CT examinations were collected. Images corresponding to 40% radiation dose were reconstructed using validated noise insertion and PIR. Three genitourinary radiologists examined routine and 40% dose PIR images. Probability of malignancy was assessed [from 0 to 100] with malignancy assumed at probability ≥ 75. Observer performance was compared on a per patient and per lesion level. CT number accuracy was measured. Results: Twenty-three patients had 49 renal lesions (11 solid renal neoplasms). CT number was nearly identical between techniques (mean CT number difference: unenhanced 2 ± 2 HU; enhanced 4 ± 4 HU). AUC for malignancy was similar between multi-phase routine dose DE and lower dose PIR images [per patient: 0.950 vs. 0.916 (p = 0.356); per lesion: 0.931 vs. 0.884 (p = 0.304)]. Per patient sensitivity was also similar (78% routine dose vs. 82% lower dose [p ≥ 0.99]), as was specificity (91% routine dose vs. 93% lower dose PIR [p > 0.99]), with similar findings on a per lesion level. Subjective image quality was also similar (p = 0.34). Conclusions: Prior iterative reconstruction is a new reconstruction method for multi-phase CT examinations that promises to facilitate radiation dose reduction by over 50% for multi-phase DE renal CT exams without compromising CT number or observer performance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Analytical Techniques for Retrieval of Atmospheric Composition with the Quadrupole Mass Spectrometer of the Sample Analysis at Mars Instrument Suite on Mars Science Laboratory

The Sample Analysis at Mars (SAM) instrument suite is the largest scientific payload on the Mars Science Laboratory (MSL) Curiosity rover, which landed in Mars׳ Gale Crater in August 2012. As a miniature geochemical laboratory, SAM is well-equipped to address multiple aspects of MSL׳s primary science goal, characterizing the potential past or present habitability of Gale Crater. Atmospheric measurements support this goal through compositional investigations relevant to martian climate evolution. SAM instruments include a quadrupole mass spectrometer, a tunable laser spectrometer, and a gas chromatograph that are used to analyze martian atmospheric gases as well as volatiles released by pyrolysis of solid surface materials (Mahaffy et al., 2012). This report presents analytical methods for retrieving the chemical and isotopic composition of Mars׳ atmosphere from measurements obtained with SAM׳s quadrupole mass spectrometer. It provides empirical calibration constants for computing volume mixing ratios of the most abundant atmospheric species and analytical functions to correct for instrument artifacts and to characterize measurement uncertainties. Finally, we discuss differences in volume mixing ratios of the martian atmosphere as determined by SAM (Mahaffy et al., 2013) and Viking (Owen et al., 1977, Oyama and Berdahl, 1977) from an analytical perspective. Although the focus of this paper is atmospheric observations, much of the material concerning corrections for instrumental effects also applies to reduction of data acquired with SAM from analysis of solid samples.

quadropole mass spectometer↗

Bio-fuel effects and seasonal fuel property variations related to abnormal combustion occurrences observed in the field

Since 2015, the automotive industry has regularly observed sharp increases in customer complaints of poor driveability and increased warranty claims during the months of September and October. These persistent seasonal complaint increases have been tracked to occur from increased abnormal combustion events that coincide with the seasonal transition from summer to winter fuel volatility, beginning on September 15th annually. The Reid Vapor Pressure (RVP) of gasoline during this seasonal transition has been found to be the primary property attributed to this annual issue. It’s hypothesized that an increase in volatile butanes and pentanes from advanced petroleum recovery techniques and hydrofracking production has hastened the transition from summer to winter fuel volatility in the marketplace, rather than the gradual increase of the RVP over time as historically intended. At worst, mid-winter fuel, with an RVP ranging from 12 to 16 psi, depending on location in the U.S., enters the market while ambient temperatures can still be above average for the winter season. This combination of high volatility fuel with unseasonably warm weather will increase fuel system flash boiling, injector spray cavitation, and spray collapse inside the engine’s combustion chamber, ultimately linking fuel property variations to abnormal engine combustion processes. This CRADA program will investigate these known knowledge gaps by coupling with two national laboratories, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory to employ both unique tools and expertise throughout the industry to provide the insight, knowledge, and data critical to understand the observed interactions. Overall findings of this work are that fuel wall retention increased SPI proportionally, and fuels with an increased distillation (i.e. energy fraction) above the wall temperature increased fuel retention. Likewise fuels with increased enthalpy of vaporization (HoV) increased fuel retention proportional to the temperature reduction from the HoV (~13K reduction in this work). Thus, fuel with increased HoV and increased fuel distillation above the linear temperature also exhibited increased SPI rates. Fuel with high RVP did exhibit increased fuel spray collapse form spray imaging measurements, but in SPI testing the high volatility of these fuels at the tested conditions did not necessarily increase SPI rates despite exhibiting increased spray collapse in injector imaging and increased spray-wall impingement measured in fired engine testing. It was also found that spray imaging showed collapse was possible at throttled conditions, but this was not relevant to high boost pressures relevant to SPI conditions, however, under transient load and or speed encountered in real-world operation fuel spray collapse could affect fuel retention and real-world SPI that were not probed in the automated high load test sequence of this work.

09 BIOMASS FUELS↗

Method for Estimating Thread Strength Reduction of Damaged Parent Holes with Inserts

During normal assembly and disassembly of bolted-joint components, thread damage and/or deformation may occur. If threads are overloaded, thread damage/deformation can also be anticipated. Typical inspection techniques (e.g. using GO-NO GO gages) may not provide adequate visibility of the extent of thread damage. More detailed inspection techniques have provided actual pitch-diameter profiles of damaged-hardware holes. A method to predict the reduction in thread shear-out capacity of damaged threaded holes has been developed. This method was based on testing and analytical modeling. Test samples were machined to simulate damaged holes in the hardware of interest. Test samples containing pristine parent-holes were also manufactured from the same bar-stock material to provide baseline results for comparison purposes. After the particular parent-hole thread profile was machined into each sample a helical insert was installed into the threaded hole. These samples were tested in a specially designed fixture to determine the maximum load required to shear out the parent threads. It was determined from the pristine-hole samples that, for the specific material tested, each individual thread could resist an average load of 3980 pounds. The shear-out loads of the holes having modified pitch diameters were compared to the ultimate loads of the specimens with pristine holes. An equivalent number of missing helical coil threads was then determined based on the ratio of shear-out loads for each thread configuration. These data were compared with the results from a finite element model (FEM). The model gave insights into the ability of the thread loads to redistribute for both pristine and simulated damage configurations. In this case, it was determined that the overall potential reduction in thread load-carrying capability in the hardware of interest was equal to having up to three fewer threads in the hole that bolt threads could engage. One- half of this potential reduction was due to local pitch-diameter variations and the other half was due to overall pitch-diameter enlargement beyond Class 2 fit. This result was important in that the thread shear capacity for this particular hardware design was the limiting structural capability. The details of the method development, including the supporting testing, data reduction and analytical model results comparison will be discussed hereafter.

Johnson, David L.↗

The First Swift Intensive AGN Accretion Disk Reverberation Mapping Survey

Swift intensive accretion disk reverberation mapping of four AGN yielded light curves sampled ∼200–350 times in 0.3–10 keV X-ray and six UV/optical bands. Uniform reduction and cross-correlation analysis of these data sets yields three main results: (1) The X-ray/UV correlations are much weaker than those within the UV/optical, posing severe problems for the lamp-post reprocessing model in which variations in a central X-ray corona drive and power those in the surrounding accretion disk. (2) The UV/optical interband lags are generally consistent with t μ l4 3 as predicted by the centrally illuminated thin accretion disk model. While the average interband lags are somewhat larger than predicted, these results alone are not inconsistent with the thin disk model given the large systematic uncertainties involved. (3) The one exception is the U band lags, which are on average a factor of ∼2.2 larger than predicted from the surrounding band data and fits. This excess appears to be due to diffuse continuum emission from the broad-line region (BLR). The precise mixing of disk and BLR components cannot be determined from these data alone. The lags in different AGN appear to scale with mass or luminosity. We also find that there are systematic differences between the uncertainties derived by JAVELIN versus more standard lag measurement techniques, with JAVELIN reporting smaller uncertainties by a factor of 2.5 on average. In order to be conservative only standard techniques were used in the analyses reported herein.

R. Edelson↗

Rapid Reflective Facet Characterization Using Fringe Reflection Techniques

Reflective mirror facets for concentrating solar power (CSP) systems have stringent requirements on the surface slope accuracy in order to provide adequate system performance. This paper presents a tool that can fully characterize facets quickly enough for 100% inspection on a production line. A facet for a CSP system, specifically a dish concentrator has a parabolic design shape. This shape will concentrate near-parallel rays from the sun to a point (or a line for trough systems). Deviations of surface slope from the design shape impact the performance of the system, either losing power that misses the target or increasing peak fluxes to undesirable levels. During development or production, accurate knowledge of facet defects can lead to improvements to lower cost or improve performance. The reported characterization system, SOFAST (Sandia Optical Fringe Analysis Slope Tool), has a computer-connected camera that images the reflective surface, which is positioned so that it reflects an active target, such as an LCD screen, to the camera. A series of fringe patterns are displayed on the screen while images are captured. Using the captured information, the reflected target location of each pixel of mirror viewed can be determined, and thus through a mathematical transformation, a surface normal map can be developed. This is then fitted to the selected model equation, and the errors from design are characterized. While similar approaches have been explored, several key developments are presented here. The combination of the display, capture, and data reduction in one system allows rapid characterization. An “electronic boresight” approach is utilized to accommodate physical equipment positioning deviations, making the system insensitive to setup errors. Up to 1.5×10 6 points are characterized on each facet. Finally, while prior automotive industry commercial systems resolve the data to shape determination, SOFAST concentrates on slope characterization and reporting, which is tailored to solar applications. SOFAST can be used for facet analysis during development. However, the real payoff is in production, where complete analysis is performed in about 10s. With optimized coding, this could be further reduced.

14 SOLAR ENERGY↗

Upscaling transpiration in diverse forests: Insights from a tropical premontane site

Upscaling water use of individual trees to stands using sap flux techniques is a common method for partitioning site water balance, but few such studies have occurred in the tropics. Increasing interests in the role of tropical forests in global cycles have spurred upscaling studies in natural tropical forests, which present challenges from greater tree species and functional diversity, and potential factors that would reduce transpiration, such as frequent cloud cover and wet canopy conditions. In a premontane wet tropical forest in central Costa Rica, sap flow was measured in 15 trees stratified into 5 size classes based on tree diameters. None of the trees belonged to the same species, genus, or even family. Here, we also accounted for potential radial variation in sap flux density. Data were scaled to estimate transpiration within a small 2.2-ha watershed using stand surveys of sapwood area. Stand transpiration averaged only 1.4 ± 0.7 mm day -1 within this forested watershed due to persistent low radiation, evaporative demand, and frequent wet canopy conditions. Our systematic approach used tree size attributes to scale water use to the stand, given difficulties to quantify species differences in such a diverse ecosystem. Contrary to previous evidence on temperate trees, the large trees sampled did not exhibit flow reductions in deeper sapwood, which warrants further study. Finally, these results highlight some unique aspects of measuring transpiration in wet tropical forests that are important to consider for future studies in diverse stands.

54 ENVIRONMENTAL SCIENCES↗

Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.

Seasonal influenza results in substantial annual morbidity and mortality in the United States and worldwide. Accurate forecasts of key features of influenza epidemics, such as the timing and severity of the peak incidence in a given season, can inform public health response to outbreaks. As part of ongoing efforts to incorporate data and advanced analytical methods into public health decision-making, the United States Centers for Disease Control and Prevention (CDC) has organized seasonal influenza forecasting challenges since the 2013/2014 season. In the 2017/2018 season, 22 teams participated. A subset of four teams created a research consortium called the FluSight Network in early 2017. During the 2017/2018 season they worked together to produce a collaborative multi-model ensemble that combined 21 separate component models into a single model using a machine learning technique called stacking. This approach creates a weighted average of predictive densities where the weight for each component is determined by maximizing overall ensemble accuracy over past seasons. In the 2017/2018 influenza season, one of the largest seasonal outbreaks in the last 15 years, this multi-model ensemble performed better on average than all individual component models and placed second overall in the CDC challenge. It also outperformed the baseline multi-model ensemble created by the CDC that took a simple average of all models submitted to the forecasting challenge. This project shows that collaborative efforts between research teams to develop ensemble forecasting approaches can bring measurable improvements in forecast accuracy and important reductions in the variability of performance from year to year. Efforts such as this, that emphasize real-time testing and evaluation of forecasting models and facilitate the close collaboration between public health officials and modeling researchers, are essential to improving our understanding of how best to use forecasts to improve public health response to seasonal and emerging epidemic threats.

59 BASIC BIOLOGICAL SCIENCES↗

Playing with DIRT: Building the Framework for a Comprehensive In-Situ Soil Materials Testing Database

Long-term, sustainable planetary exploration will require the ability to "live off the land," relying on In-Situ Resource Utilization (ISRU) and In-Situ Construction as core capabilities. Reduction of both risk and launch mass for lunar construction will require evaluating and comparing regolith materials for use as feedstocks suitable for in-situ beneficiation and fabrication of building components. These material assessment capabilities will inform lunar infrastructure design decisions, with co-benefits for terrestrial construction using in-situ materials. Current planetary construction technology development relies on lunar mapping and orbital data, Apollo-era sample analyses, current simulant inventories, and tests conducted using analog site soils. Requirements for lunar infrastructure design decisions and construction systems will be determined based on specific environmental conditions, mission architectures, and the materials available within traverse range of lunar feedstock processing depots. Critical for success is the capability to identify, evaluate and make effective use of a wide range of materials as they are found in-situ on the lunar surface. This paper discusses the development of a digital repository for data on soil and regolith properties, beginning with their structural performance in both cementitious and non-cementitious building material formulations. The Database for In-situ Resource Testing (DIRT) compiles a catalog of raw materials, additives, and formulations, with notations pertaining to material sources and preparation techniques entered via a web-based user interface. Design of consistent data schemas for site-sourced materials evaluation will facilitate linkage with relevant terrestrial and planetary materials databases while enabling guided data input via templates for participation by broader groups of collaborators. Results of these analyses are compiled in a centralized repository to generate insights applicable for regolith resources and landing sites yet to be precisely defined. Collection of thorough records of material characteristics, applications and performance will support innovative construction solutions not only for space infrastructure but for sustainable, resilient design in the terrestrial built environment.

Sarah Joey Seitz↗

Demonstrating the Effect of Particle Impact Dampers on the Random Vibration Response and Fatigue Life of Printed Wiring Assemblies

In a recent experimental study, small Particle Impact Dampers (PID) were bonded directly to the surface of printed circuit board (PCB) or printed wiring assemblies (PWA), reducing the random vibration response and increasing the fatigue life. This study provides data verifying practicality of this approach. The measured peak strain and acceleration response of the fundamental out of plane bending mode was significantly attenuated by adding a PID device. Attenuation of this mode is most relevant to the fatigue life of a PWA because the local relative displacements between the board and the supported components, which ultimately cause fatigue failures of the electrical leads of the board-mounted components are dominated by this mode. Applying PID damping at the board-level of assembly provides mitigation with a very small mass impact, especially as compared to isolation at an avionics box or shelf level of assembly. When compared with other mitigation techniques at the PWA level (board thickness, stiffeners, constrained layer damping), a compact PID device has the additional advantage of not needing to be an integral part of the design. A PID can simply be bonded to heritage or commercial off the shelf (COTS) hardware to facilitate its use in environments beyond which it was originally qualified. Finite element analysis and test results show that the beneficial effect is not localized and that the attenuation is not due to the simple addition of mass. No significant, detrimental reduction in frequency was observed. Side-by-side life testing of damped and un-damped boards at two different thicknesses (0.070" and 0.090") has shown that the addition of a PID was much more significant to the fatigue life than increasing the thickness. High speed video, accelerometer, and strain measurements have been collected to correlate with analytical results.

Knight, Brent↗

TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration

TorchBraid is a high-performance implementation of layer-parallel training for deep neural networks (DNNs) supporting MPI-based parallelism and GPU acceleration. Layer-parallel training has been developed to overcome the serialization inherent in forward and backward propagation of DNNs that limits utilization of computational resources in the strong scaling limit. To achieve this, TorchBraid integrates the PyTorch neural network framework with the state-of-the-art XBraid time-parallel library. Furthermore, this article presents the use and performance of TorchBraid, in addition to solutions for overcoming the algorithmic challenges inherent in combining automatic differentiation with layer-parallel. Results are presented with and without GPU acceleration for the Tiny ImageNet and MNIST image classification data sets, as well as recurrent neural networks. Overall, TorchBraid enables fast training of DNNs, both in a strong and weak scaling context. In addition to the TorchBraid software, several new advances in applying layer-parallel algorithms are detailed. Integration of layer-parallel with data-parallel algorithms is presented for the first time, showing the computational advantages of the combination. Standard deep learning techniques, like batch-normalization, are developed for layer-parallel training. Finally, a new approach combining layer-parallel with spatial coarsening in order to accelerate training for 3D image classification shows roughly a 10× speedup over serial execution.

Layer-parallel↗

Electrochemical Salt Wasteform Development: A Review of Salt Treatment and Immobilization Options

Electrochemical reprocessing, also referred to as pyroprocessing, is a technique for recycling actinides from used nuclear fuel (UNF) to produce fuel for future reactors. Here, UNF is dissolved in a molten salt (e.g., LiCl-KCl eutectic) within an electrorefiner. After UNF dissolution, fission products are released into the electrolyte salt and converted to chlorides. This paper discusses wasteform options for processing the base electrolyte salt with the fission product salts as well as just the rare-earth fission products (as RECl 3 , REOCl, or REO x ) with the intent of finding optimal methods for reducing total waste salt volumes or partitioning the salt for alternate wasteform options. Furthermore, two of the more detailed partitioning options discussed herein include halide removal from the salt (dehalogenation), which accounts for more than half of the salt on a molar basis, and RE fission product removal for wasteforms with high-RE loadings. Wasteform properties are compared with emphasis on wasteform volume starting from a given amount of (1) total salt cations or (2) RE cations. Comparisons are also made of wasteform chemical durabilities, with the data available from like testing methods. A main conclusion from this work is the justification of subsequent salt processing after electrorefiner operations for achieving significant wasteform volume reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-E-I-78: Improving Prostatic Delineation Using Dual-Energy CT

Purpose: Visual prostatic definition is difficult using conventional CT. This is because the prostate is surrounded closely with tissue of similar electron density. Definition is further hindered when the region contains high-Z material (such as fiducial markers). Dual-energy CT (DECT) is a technique where images are rendered using two tube voltages during a single scan session. This study evaluates DECT as a means of improving prostatic volume delineation for radiation oncology. Methods: The patients were scanned using a Definition AS20 (Siemens Healthcare, Malvern, PA). This device uses a single-tube configuration, where two scans of differing energies are performed in serial. The scans are acquired with tube voltage of 80kVp and 140kVp. Following acquisition, these scan data were used to generate effective monoenergetic scans ranging from 40keV to 190keV. In the current study, the data were presented to observers using a novel program, which allows real-time adjustment of window, level, and effective keV; all while scrolling through volumetric slices. Three patients were scanned, each with a different high-contrast material in or around the prostate: I-125 seeds, gold fiducial markers, and prostatic calcifications. These images are compared to a weighted average of the 80kVp and 140kVP scans, which yield a scan similar to that of a 120 kVp scan, which is a common tube voltage in radiation oncology. Results: Prostatic definition improved in each case. Differentiation of soft tissue from surrounding adipose improved with lower keV, while higher keV provided a reduction of high-z artifacts. Furthermore, the dynamic adjustment of the keV allowed observers to better recognize regions of differing tissue composition within this relatively homogeneous area. Conclusion: By simultaneously providing the observer with the benefits of high-energy images and low-energy images, and allowing adjustment in real-time, improved imaging in highly homogeneous regions such as the male pelvis is achievable.

60 APPLIED LIFE SCIENCES↗

"Development and Commercialization of Alternative Carbon Precursors and Conversion Technologies" (CRADA Final Report)

The overall objective of the collaborative research performed by the Oak Ridge National Laboratory (ORNL) and the Dow Chemical Company under this Cooperative Research And Development Agreement (CRADA NFE-10-02991) was to develop and establish pathways to commercialize new carbon fiber precursor and conversion technology. This technology is to produce alternative polymer fiber precursor formulations as well as scaled energy-efficient advanced conversion technology to enable continuous mode conversion to obtain carbonized fibers that are technically and economically viable in industrial markets such as transportation, wind energy, infrastructure and oil drilling applications. There have been efforts in the past to produce a low cost carbon fiber. These attempts have to be interpreted against the backdrop of the market needs at the time, which were strictly military aircraft and high-end aerospace components. In fact, manufacturing costs have been reduced from those days to current practice, where both process optimization and volume production have enabled carbon fiber to become available at prices below $20/lb. However, the requirements of the lucrative aerospace market limits further price reductions from current practice. This approach is different because specific industrial applications are targeted, most specifically wind turbine blade and light vehicle transportation, where aircraft grade carbon fiber is not required. As a result, researchers are free to adjust both manufacturing process and precursor chemistry to meet the relaxed physical specifications at a lower cost. This report documents the approach and findings of this cooperative research in alternative precursors and advanced conversion for production of cost-effective carbon fiber for energy missions. Due to export control, proprietary restrictions, and CRADA protected data considerations, specific design details and processing parameters are not included in this report.

01 COAL, LIGNITE, AND PEAT↗

Evaluating State Space Discovery by Persistent Cohomology in the Spatial Representation System

Persistent cohomology is a powerful technique for discovering topological structure in data. Strategies for its use in neuroscience are still undergoing development. We comprehensively and rigorously assess its performance in simulated neural recordings of the brain's spatial representation system. Grid, head direction, and conjunctive cell populations each span low-dimensional topological structures embedded in high-dimensional neural activity space. We evaluate the ability for persistent cohomology to discover these structures for different dataset dimensions, variations in spatial tuning, and forms of noise. We quantify its ability to decode simulated animal trajectories contained within these topological structures. We also identify regimes under which mixtures of populations form product topologies that can be detected. Our results reveal how dataset parameters affect the success of topological discovery and suggest principles for applying persistent cohomology, as well as persistent homology, to experimental neural recordings.

59 BASIC BIOLOGICAL SCIENCES↗