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The use of a benign fast-growing cyanobacterial species to control microcystin synthesis from Microcystis aeruginosa

Introduction Microcystis aeruginosa(M. aeruginosa), one of the most abundant blue-green algae in aquatic environments, produces microcystin by causing harmful algal blooms (HABs). This study investigated the combined effects of nutrients and competition among cyanobacterial subpopulations on the synthesis of microcystin-LR. Methods Under varying nitrogen and phosphorus concentrations, cyanobacterial coculture, and the presence of algicidal DCMU, the growth was monitored by optical density analysis or microscopic counting, and the microcystin production was analyzed using high-performance liquid chromatography-UV. Furthermore, growth and toxin production were predicted using a kinetic model. Results and discussion First, coculture with the fast-growing cyanobacteriumSynechococcus elongatusUTEX 2973 (S. elongatus) reducedM. aeruginosabiomass and microcystin production at 30°C. Under high nitrogen and low phosphorus conditions,S. elongatuswas most effective, limitingM. aeruginosagrowth and toxin synthesis by up to 94.7% and 92.4%, respectively. Second, this biological strategy became less effective at 23°C, whereS. elongatusgrew more slowly. Third, the photosynthesis inhibitor DCMU (3-(3,4-dichlorophenyl)-1,1-dimethylurea) inhibitedM. aeruginosagrowth (at 0.1 mg/L) and microcystin production (at 0.02 mg/L). DCMU was also effective in controlling microcystin production inS. elongatus–M. aeruginosacocultures. Based on the experimental results, a multi-substrate, multi-species kinetic model was built to describe coculture growth and population interactions. Conclusion Microcystin from representative toxin-producingM. aeruginosacan be controlled by coculturing fast-growing benign cyanobacteria, which can be made even more efficient if appropriate algicide is applied. This study improved the understanding of the biological control of microcystin production under complex environmental conditions.

Microbiology↗

Radio astronomy aspects of the NASA SETI Sky Survey

The application of SETI data to radio astronomy is studied. The number of continuum radio sources in the 1-10 GHz region to be counted and cataloged is predicted. The radio luminosity functions for steep and flat spectrum sources at 2, 8, and 22 GHz are derived using the model of Peacock and Gull (1981). The relation between source number and flux density is analyzed and the sensitivity of the system is evaluated.

Klein, Michael J.↗

A cosmic book

A system of assigning odds to the basic elements of cosmological theories is proposed in order to evaluate the strengths and weaknesses of the theories. A figure of merit for the theories is obtained by counting and weighing the plausibility of each of the basic elements that is not substantially supported by observation or mature fundamental theory. The magnetized strong model is found to be the most probable. In order of decreasing probability, the ranking for the rest of the models is: (1) the magnetized string model with no exotic matter and the baryon adiabatic model; (2) the hot dark matter model and the model of cosmic string loops; (3) the canonical cold dark matter model, the cosmic string loops model with hot dark matter, and the baryonic isocurvature model; and (4) the cosmic string loops model with no exotic matter.

Peebles, P. J. E.↗

Self-ordering physics in an open universe

This Letter presents an analytical model for the generation of density fluctuations likely to be appropriate for defects such as gauged and global strings, global monopoles, and textures, as well as for nontopological textures in an open or flat universe. For a reasonable range of parameters, these models in an open universe are compatible with both the level of MW fluctuations detected by COBE and with the fluctuations observed in the galaxy counts.

Spergel, David N.↗

Gamma-Ray Burst Afterglows as Probes of Environment and Blastwave Physics II: The Distribution of p and Structure of the Circumburst Medium

We constrain blastwave parameters and the circumburst media of a subsample of BeppoSAX Gamma-Ray Bursts. For this sample we derive the values of the injected electron energy distribution index, p, and the density structure index of the circumburst medium, k, from simultaneous spectral fits to their X-ray, optical and nIR afterglow data. The spectral fits have been done in count space and include the effects of metallicity, and are compared with the previously reported optical and X-ray temporal behaviour. Assuming the fireball model, we can find a mean value of p for the sample as a whole of 2.035. A statistical analysis Of the distribution demonstrates that the p values in this sample are inconsistent with a single universal value for p at the 3sigma level or greater. This approach provides us with a measured distribution of circumburst density structures rather than considering only the cases of k = 0 (homogeneous) and k = 2 (wind-like). We find five GRBs for which k can be well constrained, and in four of these cases the circumburst medium is clearly wind-like. The fifth source has a value of 0 less than or equal to k less than or equal to 1, consistent with a homogeneous circumburst medium.

Starling, R. L. C.↗

Gamma-Ray Burst Afterglows as Probes of Environment and Blast Wave Physics. II. The Distribution of rho and Structure of the Circumburst Medium

We constrain blast wave parameters and the circumburst media ofa subsample of 10 BeppoSAX gamma-ray bursts (GRBs). For this sample we derive the values of the injected electron energy distribution index, p, and the density structure index of the circumburst medium, k, from simultaneous spectral fits to their X-ray, optical, and NIR afterglow data. The spectral fits have been done in count space and include the effects ofmetallicity, and are compared with the previously reported optical and X-ray temporal behavior. Using the blast wave model and some assumptions which include on-axis viewing and standard jet structure, constant blast wave energy, and no evolution of the microphysical parameters, we find a mean value ofp for the sample as a whole of 9.... oa -0.003.0" 2 a_ statistical analysis of the distribution demonstrates that the p-values in this sample are inconsistent with a single universal value forp at the 3 _ level or greater, which has significant implications for particle acceleration models. This approach provides us with a measured distribution ofcircumburst density structures rather than considering only the cases of k ----0 (homogeneous) and k - 2 (windlike). We find five GRBs for which k can be well constrained, and in four of these cases the circumburst medium is clearly windlike. The fifth source has a value of 0 < k < 1, consistent with a homogeneous circumburst medium.

Starling, R. L. C.↗

US Tropical Cyclone Activity in the 2030s Based on Projected Changes in Tropical Sea-Surface Temperature

We use a statistical tropical cyclone (TC) model, the North Atlantic Stochastic Hurricane Model (NASHM), in combination with sea-surface temperature (SST) projections from climate models, to estimate regional changes in US TC activity into the 2030s. NASHM is trained on historical variations in TC characteristics with two SST indices: global-tropical mean SST and the difference between tropical North-Atlantic (NA) SST and the rest of the global tropics, often referred to as “relative SST.” Testing confirms the model’s ability to reproduce historical US TC activity, as well as to make skillful predictions. When NASHM is driven by SST projections into the 2030s, overall NA annual TC counts increase, and the fractional increase is the greatest at the highest wind intensities. However, an eastward anomaly in mean TC tracks and an eastward shift in TC formation region result in a geographically-varied signal in US coastal activity. Florida’s Gulf coast is projected to see significant increases in TC activity, compared to the long-term historical mean, and these increases are fractionally greatest at the highest intensities. By contrast, the northwestern US Gulf and the US East Coast will see little change.

tropical cyclone (TC) model↗

Evaluating Effects of Altered Gravity on the Nervous System Using D. melanogaster

A comprehensive understanding of the effects of spaceflight and altered gravity on human physiology is necessary for continued human space exploration and long-term space habitation. The oxidative stress response has been identified in astronauts exposed to short- and long-term space missions that are exposed to the multitude of stress factors of spaceflight, including altered gravity and radiation exposure. Reactive oxygen species (ROS) are byproducts of homeostatic cellular metabolism, yet when overproduced the oxidative stress response ensues, rendering molecules destructive causing cell death and inflammation. Controlling aberrant ROS production is necessary to prevent pathological consequences, in particular within the nervous system, since neurons are extremely sensitive overexpressed ROS insults. We hypothesize that exposure to altered gravity triggers the oxidative stress response, leading to impairments in the nervous system. In this study, we used a well-established spaceflight model organism, Drosophila melanogaster, to assess altered gravity associated changes in the nervous system using a ground-based hypergravity model. Acute hypergravity resulted in an induction of oxidative stress-related genes with an increase in reactive oxygen species (ROS) in fly brains (p<0.001). Also, qPCR analysis shows that parkin gene expression is significantly reduced in these fly brains(p<0.05). Additionally, chronic hypergravity resulted in depressed locomotor phenotype in these flies (p<0.05) in conjunction to decreased dopaminergic neuron counts (p<0.0001) and increased apoptosis in these fly brains (p<0.0001). Further, assessment of neurological changes, including the neuronal architecture, synaptic integrity and genetic regulation caused by hypergravity conditions were noted. Overall, our results validate chronic hypergravity simulation as a behavioral model to study spaceflight effects, and oxidative stress pathway as a potential avenue for countermeasure development for astronauts undergoing short- and long-term missions and for neurodegenerative research on Earth.

Mhatre, Siddhita↗

Extracting the Galactic Center excess’ source-count distribution with neural nets

The two leading hypotheses for the Galactic Center excess (GCE) in the Fermi data are an unresolved population of faint millisecond pulsars (MSPs) and dark-matter (DM) annihilation. The dichotomy between these explanations is typically reflected by modeling them as two separate emission components. However, point sources (PSs) such as MSPs become statistically degenerate with smooth Poisson emission in the ultrafaint limit (formally where each source is expected to contribute much less than one photon on average), leading to an ambiguity that can render questions such as whether the emission is PS-like or Poissonian in nature ill defined. We present a conceptually new approach that describes the PS and Poisson emission in a unified manner and only afterwards derives constraints on the Poissonian component from the so obtained results. For the implementation of this approach, we leverage deep learning techniques, centered around a neural network-based method for histogram regression that expresses uncertainties in terms of quantiles. We demonstrate that our method is robust against a number of systematics that have plagued previous approaches, in particular DM/PS misattribution. In the Fermi data, we find a faint GCE described by a median source-count distribution (SCD) peaked at a flux of ~ 4 x 10 -11 counts cm -2 s -1 (corresponding to ~ 3-4 expected counts per PS), which would require N ~ $\mathscr{O}$(10 4 ) sources to explain the entire excess (median value N = 29,300 across the sky). Although faint, this SCD allows us to derive the constraint η ρ ≤ 66% for the Poissonian fraction of the GCE flux η ρ at 95% confidence, suggesting that a substantial amount of the GCE flux is due to PSs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A new compact solid-state neutral particle analyser at ASDEX Upgrade: Setup and physics modeling

At ASDEX Upgrade (AUG), a new compact solid-state detector has been installed to measure the energy spectrum of fast neutrals based on the principle described by Shinohara et al. [Rev. Sci. Instrum. 75, 3640 (2004)]. The diagnostic relies on the usual charge exchange of supra-thermal fast-ions with neutrals in the plasma. Therefore, the measured energy spectra directly correspond to those of confined fast-ions with a pitch angle defined by the line of sight of the detector. Experiments in AUG showed the good signal to noise characteristics of the detector. It is energy calibrated and can measure energies of 40-200 keV with count rates of up to 140 kcps. The detector has an active view on one of the heating beams. The heating beam increases the neutral density locally; thereby, information about the central fast-ion velocity distribution is obtained. The measured fluxes are modeled with a newly developed module for the 3D Monte Carlo code F90FIDASIM [Geiger et al., Plasma Phys. Controlled Fusion 53, 65010 (2011)]. The modeling allows to distinguish between the active (beam) and passive contributions to the signal. Thereby, the birth profile of the measured fast neutrals can be reconstructed. This model reproduces the measured energy spectra with good accuracy when the passive contribution is taken into account.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Probabilistic Study Conducted on Sensor-Based Engine Life Calculation

Turbine engine life management is a very complicated process to ensure the safe operation of an engine subjected to complex usage. The challenge of life management is to find a reasonable compromise between the safe operation and the maximum usage of critical parts to reduce maintenance costs. The commonly used "cycle count" approach does not take the engine operation conditions into account, and it oversimplifies the calculation of the life usage. Because of the shortcomings, many engine components are regularly pulled for maintenance before their usable life is over. And, if an engine has been running regularly under more severe conditions, components might not be taken out of service before they exceed their designed risk of failure. The NASA Glenn Research Center and its industrial and academic partners have been using measurable parameters to improve engine life estimation. This study was based on the Monte Carlo simulation of 5000 typical flights under various operating conditions. First a closed-loop engine model was developed to simulate the engine operation across the mission profile and a thermomechanical fatigue (TMF) damage model was used to calculate the actual damage during takeoff, where the maximum TMF accumulates. Next, a Weibull distribution was used to estimate the implied probability of failure for a given accumulated cycle count. Monte Carlo simulations were then employed to find the profiles of the TMF damage under different operating assumptions including parameter uncertainties. Finally, probabilities of failure for different operating conditions were analyzed to demonstrate the importance of a sensor-based damage calculation in order to better manage the risk of failure and on-wing life.

Guo, Ten-Huei↗

Updated Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code RDEIM Model Report for MACCS v4.2

This report updates the Regional Disruption Economic Impact Model (RDEIM) GDP-based model described in Bixler et al. (2020) used in the MACCS accident consequence analysis code. MACCS is the U.S. Nuclear Regulatory Commission (NRC) used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. The update of the RDEIM model in version 4.2 expresses the national recovery calculation explicitly, rather than implicitly as in the previous version. The calculation of the total national GDP losses remains unchanged. However, anticipated gains from recovery are now allocated across all the GDP loss types – direct, indirect, and induced – whereas in version 4.1, all recovery gains were accounted for in the indirect loss type. To achieve this, we’ve introduced new methodology to streamline and simplify the calculation of all types of losses and recovery. In addition, RDEIM includes other kinds of losses, including tangible wealth. This includes loss of tangible assets (e.g., depreciation) and accident expenditures (e.g., decontamination). This document describes the updated RDEIM economic model and provides examples of loss and recovery calculation, results analysis, and presentation. Changes to the tangible cost calculation and accident expenditures are described in section 2.2. The updates to the RDEIM input-output (I-O) model are not expected to affect the final benchmark results Bixler et al. (2020), as the RDEIM calculation for the total national GDP losses remains unchanged. The reader is referred to the MACCS revision history for other cost modelling changes since version 4.0 that may affect the benchmark. RDEIM has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS. It is based on I-O theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in in its treatment and estimation of indirect loss multipliers, elimination of double-counting associated with inter-industry trade in the affected area, and that it is intended to be used for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Geodata Modeling and Query in Geographic Information Systems

Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.

Adam, Nabil↗

Using Nucleon Multiplicities to Analyze Anti-Neutrino Interactions with Nuclei

The most commonly used, simple interaction models have not accurately described the nuclear effects on either neutrino-nucleus or anti-neutrino-nucleus interactions. Comparison of data collected by the MINERvA experiment and these models shows a discrepancy in the reconstructed hadronic energy distribution at momentum transfers below 0.8 GeV. Two nuclear model effects that were previously not modeled are possible culprits of this discrepancy. The first is known as random-phase-approximation and the second is the addition of a meson exchange current process, also known as two-particle two-hole due to its result in two particles leaving the nucleus with two holes left in their place. For the first time a neutron counting software algorithm has been created and used to compare the multiplicity and spatial distributions of neutrons between the simulation and data. There is localized sensitivity to the RPA and 2p2h effects and both help the simulation better describe the data. Ad ditional systematic or model effects are present which cause the simulation to overproduce neutrons, and potential causes are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Economic Model for Estimation of GDP Losses in the MACCS Offsite Consequence Analysis Code

The MACCS (MELCOR Accident Consequence Code System) code is the U.S. Nuclear Regulatory Commission (NRC) tool used to perform probabilistic health and economic consequence assessments for atmospheric releases of radionuclides. It is also used by international organizations, both reactor owners and regulators. It is intended and most commonly used for hypothetical accidents that could potentially occur in the future rather than to evaluate past accidents or to provide emergency response during an ongoing accident. It is designed to support probabilistic risk and consequence analyses and is used by the NRC, U.S. nuclear licensees, the Department of Energy, and international vendors, licensees, and regulators. This report describes the modeling framework, implementation, verification, and benchmarking of a GDP-based model for economic losses that has recently been developed as an alternative to the original cost-based economic loss model in MACCS. The GDP-based model has its roots in a code developed by Sandia National Laboratories for the Department of Homeland Security to estimate short-term losses from natural and manmade accidents, called the Regional Economic Accounting analysis tool (REAcct). This model was adapted and modified for MACCS and is now called the Regional Disruption Economic Impact Model (RDEIM). It is based on input-output theory, which is widely used in economic modeling. It accounts for direct losses to a disrupted region affected by an accident, indirect losses to the national economy due to disruption of the supply chain, and induced losses from reduced spending by displaced workers. RDEIM differs from REAcct in its treatment and estimation of indirect loss multipliers, elimination of double counting associated with inter-industry trade in the affected area, and that it is designed to be used to estimate impacts for extended periods that can occur from a major nuclear reactor accident, such as the one that occurred at the Fukushima Daiichi site in Japan. Most input-output models do not account for economic adaptation and recovery, and in this regard RDEIM differs from its parent, REAcct, because it allows for a user-definable national recovery period. Implementation of a recovery period was one of several recommendations made by an independent peer review panel to ensure that RDEIM is state-of-practice. For this and several other reasons, RDEIM differs from REAcct. Both the original and the RDEIM economic loss models account for costs from evacuation and relocation, decontamination, depreciation, and condemnation. Where the original model accounts for an expected rate of return, based on the value of property, that is lost during interdiction, the RDEIM model instead accounts for losses of GDP based on the industrial sectors located within a county. The original model includes costs for disposal of crops and milk that the RDEIM model currently does not, but these costs tend to contribute insignificantly to the overall losses. This document discusses three verification exercises to demonstrate that the RDEIM model is implemented correctly in MACCS. It also describes a benchmark study at five nuclear power plants chosen to represent the spectrum of U.S. commercial sites. The benchmarks provide perspective on the expected differences between the RDEIM and the original cost-based economic loss models. The RDEIM model is shown to consistently predict larger losses than the original model, probably in part because it accounts for national losses by including indirect and induced losses; whereas, the original model only accounts for regional losses. Nonetheless, the RDEIM model predicts losses that are remarkably consistent with the original cost-based model, differing by 16% at most for the five sites combined with three source terms considered in this benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗

Matrix-free preconditioning for high-order H (curl) discretizations

The greater arithmetic intensity of high-order finite element discretizations makes them attractive for implementation on next-generation hardware, but assembly of high-order finite element operators as matrices is prohibitively expensive. As a result, the development of general algebraic solvers for such operators has been an open research challenge. Fast matrix-free application of high-order operators has received significant attention in the literature in the context of Poisson-type problems, but preconditioners and solvers for inverting more general operators are not very well-developed. In this paper, we consider the problem of preconditioning a definite Maxwell operator at high polynomial order without assembling a matrix. We show that given efficient preconditioners for high-order H 1 finite element problems on the same mesh, efficient H(curl) preconditioners can be constructed in an auxiliary space framework. We demonstrate the resulting preconditioners in a practical setting with tensor-product basis functions on an unstructured mesh of quadrilaterals. Overall, our approach uses a sparsified H 1 solver constructed on a low-order mesh of the nodal points of the underlying high-order space, and we show that the resulting H(curl) preconditioner is effective at very high polynomial orders for two-dimensional model problems with complicated geometry, varying piecewise constant coefficients, and curved elements. The resulting preconditioner scales with nearly optimal O(p d+1 ) floating point operation count and optimal O(p d ) memory transfer requirements, outperforming existing Maxwell preconditioners in the high-order regime.

97 MATHEMATICS AND COMPUTING↗

Correlation Between Radiation Dose to {sup 18}F-FDG-PET Defined Active Bone Marrow Subregions and Acute Hematologic Toxicity in Cervical Cancer Patients Treated With Chemoradiotherapy

Purpose: To test the hypothesis that radiation dose to {sup 18}F-fluorodeoxyglucose positron emission tomography ({sup 18}F-FDG-PET)-defined active bone marrow (BM{sub ACT}) subregions is correlated with hematologic toxicity in cervical cancer patients treated with chemoradiotherapy. Methods and Materials: The conditions of 26 women with cervical cancer who underwent {sup 18}F-FDG-PET before treatment with concurrent cisplatin and intensity-modulated radiation therapy were analyzed. BM{sub ACT} was defined as the subregion of total bone marrow (BM{sub TOT}) with a standardized uptake value (SUV) equal to or above the mean for that individual. Inactive bone marrow (BM{sub INACT}) was defined as BM{sub TOT} - BM{sub ACT}. Generalized linear modeling was used to test the correlation between BM{sub ACT} and BM{sub INACT} dose-volume metrics and hematologic nadirs, particularly white blood cell count (WBC) and absolute neutrophil count (ANC). Results: Increased BM{sub ACT} mean dose was significantly associated with decreased log(WBC) nadir ({beta} = -0.04; 95% CI, -0.07to -0.01; p = 0.009), decreased log(ANC) nadir ({beta} = -0.05; 95% CI, -0.08 to -0.02; p = 0.006), decreased hemoglobin nadir ({beta} = -0.16; 95% CI, -0.27 to -0.05; p = 0.010), and decreased platelet nadir ({beta} = -6.16; 95% CI, -9.37 to -2.96; p < 0.001). By contrast, there was no association between BM{sub INACT} mean dose and log(WBC) nadir ({beta} = -0.01; 95% CI, -0.06 to 0.05; p = 0.84), log(ANC) nadir ({beta} = -0.03; 95% CI, -0.10 to 0.04; p = 0.40), hemoglobin nadir ({beta} = -0.09; 95% CI, -0.31 to 0.14; p = 0.452), or platelet nadir ({beta} = -3.47; 95% CI, -10.44 to 3.50; p = 0.339). Conclusions: Irradiation of BM subregions with higher {sup 18}F-FDG-PET activity was associated with hematologic toxicity, supporting the hypothesis that reducing dose to BM{sub ACT} subregions could mitigate hematologic toxicity. Future investigation should seek to confirm these findings and to identify optimal SUV thresholds to define BM{sub ACT}.

62 RADIOLOGY AND NUCLEAR MEDICINE↗