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At least 1,405 records · Page 78

TU-C-18A-01: Models of Risk From Low-Dose Radiation Exposures: What Does the Evidence Say?

At dose levels of (approximately) 500 mSv or more, increased cancer incidence and mortality have been clearly demonstrated. However, at the low doses of radiation used in medical imaging, the relationship between dose and cancer risk is not well established. As such, assumptions about the shape of the dose-response curve are made. These assumptions, or risk models, are used to estimate potential long term effects. Common models include 1) the linear non-threshold (LNT) model, 2) threshold models with either a linear or curvilinear dose response above the threshold, and 3) a hormetic model, where the risk is initially decreased below background levels before increasing. The choice of model used when making radiation risk or protection calculations and decisions can have significant implications on public policy and health care decisions. However, the ongoing debate about which risk model best describes the dose-response relationship at low doses of radiation makes informed decision making difficult. This symposium will review the two fundamental approaches to determining the risk associated with low doses of ionizing radiation, namely radiation epidemiology and radiation biology. The strengths and limitations of each approach will be reviewed, the results of recent studies presented, and the appropriateness of different risk models for various real world scenarios discussed. Examples of well-designed and poorly-designed studies will be provided to assist medical physicists in 1) critically evaluating publications in the field and 2) communicating accurate information to medical professionals, patients, and members of the general public. Equipped with the best information that radiation epidemiology and radiation biology can currently provide, and an understanding of the limitations of such information, individuals and organizations will be able to make more informed decisions regarding questions such as 1) how much shielding to install at medical facilities, 2) at what dose level are risk vs. benefit discussions with patients appropriate, 3) at what dose level should we tell a pregnant woman that the baby’s health risk from a prenatal radiation exposure is “significant”, 4) is informed consent needed for patients undergoing medical imaging, and 5) at what dose level is evacuation appropriate after a radiological accident. Examples of the tremendous impact that choosing different risks models can have on the answers to these types of questions will be given.A moderated panel discussion will allow audience members to pose questions to the faculty members, each of whom is an established expert in his respective discipline. Learning Objectives: Understand the fundamental principles, strengths and limitations of radiation epidemiology and radiation biology for determining the risk from exposures to low doses of ionizing radiation Become familiar with common models of risk used to describe the dose-response relationship at low dose levels Learn to identify strengths and weaknesses in studies designed to measure the effect of low doses of ionizing radiation Understand the implications of different risk models on public policy and health care decisions.

60 APPLIED LIFE SCIENCES↗

Reliability, stability during long-term storage, and intra-individual variation of circulating levels of osteopontin, osteoprotegerin, vascular endothelial growth factor-A, and interleukin-17A

Background: Studies in many populations have reported associations between circulating cytokine levels and various physiological or pathological conditions. However, the reliability of cytokine measurements in population studies, which measure cytokines in multiple assays over a prolonged period, has not been adequately examined; nor has stability during sample storage or intra-individual variation been assessed. Methods: We assessed (1) analytical reliability in short- and long-term repeated measurements; (2) stability and analytical reliability during long-term sample storage, and (3) variability within individuals over seasons, of four cytokines—osteopontin (OPN), osteoprotegerin (OPG), vascular endothelial growth factor-A (VEGF-A), and interleukin-17A (IL-17A). Measurements in plasma or serum samples were made with commercial kits according to standard procedures. Estimation was performed by fitting a random or mixed effects linear model on the log scale. Results: In repeated assays over a short period, OPN, OPG, and VEGF-A had acceptable reliability, with intra- and inter-assay coefficients of variation (CV) less than 0.11. Reliability of IL-17A was poor, with inter- and intra-assay CV 0.85 and 0.43, respectively. During long-term storage, OPG significantly decayed (-33% per year; 95% confidence interval [-54, -3.7]), but not OPN or VEGF-A (-0.3% or -6.3% per year, respectively). Intra- and inter-assay CV over a long period were comparable to that in a short period except for a slight increase in inter-assay CV of VEGF-A. Within-individual variation was small for OPN and VEGF-A, with intra-class correlations (ICC) 0.68 and 0.83, respectively, but large for OPG (ICC 0.11). Conclusions: We conclude that OPN and VEGF-A can be reliably measured in a large population, that IL-17A is suitable only for small experiments, and that OPG should be assessed with caution due to degradation during storage and intra-individual variation. The overall results of our study illustrate the need for validation under relevant conditions when measuring circulating cytokines in population studies.

60 APPLIED LIFE SCIENCES↗

MFNets: Multifidelity data-driven networks for Bayesian learning and prediction

This paper presents a multifidelity uncertainty quantification framework called MFNets. We seek to address three existing challenges that arise when experimental and simulation data from different sources are used to enhance statistical estimation and prediction with quantified uncertainty. Specifically, we demonstrate that MFNets can (1) fuse heterogeneous data sources arising from simulations with different parameterizations, e.g simulation models with different uncertain parameters or data sets collected under different environmental conditions; (2) encode known relationships among data sources to reduce data requirements; and (3) improve the robustness of existing multi-fidelity approaches to corrupted data. MFNets construct a network of latent variables (LVs) to facilitate the fusion of data from an ensemble of sources of varying credibility and cost. These LVs are posited as explanatory variables that provide the source of correlation in the observed data. Furthermore, MFNets provide a way to encode prior physical knowledge to enable efficient estimation of statistics and/or construction of surrogates via conditional independence relations on the LVs. We highlight the utility of our framework with a number of theoretical results which assess the quality of the posterior mean as a frequentist estimator and compare it to standard sampling approaches that use single fidelity, multilevel, and control variate Monte Carlo estimators. We also use the proposed framework to derive the Monte Carlo-based control variate estimator entirely from the use of Bayes rule and linear-Gaussian models -- to our knowledge the first such derivation. Finally, we demonstrate the ability to work with different uncertain parameters across different models.

97 MATHEMATICS AND COMPUTING↗

Quantification of MagLIF Morphology using the Mallat Scattering Transformation

The morphology of the stagnated plasma resulting from Magnetized Liner Inertial Fusion (MagLIF) is measured by imaging the self-emission x-rays coming from the multi-keV plasma, and the evolution of the imploding liner is measured by radiographs. Equivalent diagnostic response can be derived from integrated rad-MHD simulations from programs such as Hydra and Gorgon. There have been only limited quantitative ways to compare the image morphology, that is the texture, of simulations and experiments. We have developed a metric of image morphology based on the Mallat Scattering Transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters. This metric has demonstrated excellent performance in classifying ensembles of synthetic stagnation images. We use this metric to quantitatively compare simulations to experimental images, cross experimental images, and to estimate the parameters of the images with uncertainty via a linear regression of the synthetic images to the parameter used to generate them. This coordinate space has proved very adept at doing a sophisticated relative back-ground subtraction in the MST space. This was needed to compare the experimental self emission images to the rad-MHD simulation images. We have also developed theory that connects the transformation to the causal dynamics of physical systems. This has been done from the classical kinetic perspective and from the field theory perspective, where the MST is the generalized Green's function, or S-matrix of the field theory in the scale basis. From both perspectives the first order MST is the current state of the system, and the second order MST are the transition rates from one state to another. An efficient, GPU accelerated, Python implementation of the MST was developed. Future applications are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Retrospective Analysis of Backwater Habitat Availability Using Remote Sensing

Low-velocity channel-margin habitats serve as important nursery habitats for the endangered Colorado pikeminnow (Ptychocheilus lucius) in the middle Green River between Jensen and Ouray, Utah. These habitats, known as backwaters, are associated with emergent sandbars, and are shaped and reformed annually by peak flows. Our recent knowledge about backwater characteristics and dynamics that is summarized in the synthesis report (Grippo et al. 2015) was based on detailed annual survey data from a relatively small sample of backwaters that were collected from 2003 to 2014 and reach-wide evaluations of backwater surface area based on manual interpretation of aerial and satellite imagery. Methods that bridge the gap between the detailed surveys from a small number of backwaters and the reach-wide assessment of their surface area would enable an assessment of the availability of backwater habitats that meet the minimum depth requirements for suitable habitat for Colorado pikeminnow. In 2015 Argonne National Laboratory (Argonne) tested three regression models—linear, multiple, and partial least square (PLS) regression models—for estimating backwater depth using National Agriculture Imagery Program (NAIP) imagery collected in July 2006 that covered the Jensen-Ouray reach of the Green River (Hamada and LaGory 2016). The results suggested that a PLS regression model showed high correlation with the reference depth (R 2 = 0.69) and had the most unbiased and consistent estimate of backwater depth. The results also indicated that the PLS model would provide reasonable estimates of the amount of habitat providing a minimum suitable depth of 30 cm for young-of-the-year Colorado pikeminnow, even though absolute depth estimates may be uncertain for backwater areas deeper than approximately 40 cm. The study also provided insights regarding the amount and the selection of calibration and validation (cal-val) data needed for improving the accuracy of depth prediction.

54 ENVIRONMENTAL SCIENCES↗

The relationship between urinary selenium levels and risk of gestational diabetes mellitus: A nested case–control study

Background Selenium (Se) is an essential trace element for the human body. Serum Se and urinary Se are also biomarkers to assess Se exposure status. However, studies focusing on the association between urinary Se and the risk of gestational diabetes mellitus (GDM) are rare. Objective To investigate the association between urinary Se and the risk of GDM. Methods A nested case–control study based on a prospective birth cohort in Wuhan, China, which focuses on the effects of prenatal environmental factors exposure on pregnant women and children’s health was conducted. Two hundred and twenty-six cases and 452 controls were included. Maternal urine samples were collected before GDM diagnosis, and the urinary Se levels were determined. We assessed the association of urinary Se with GDM by conditional logistic regression with maternal urinary Se level as a categorical variable, and estimated the association between Se and glucose levels by multiple linear regression. The potential modifier roles of maternal age and fetal sex have also been assessed. Results Lower urinary level of Se was significantly associated with a higher risk of GDM (OR = 2.35 for the tertile 1, 95% CI:1.36-4.06; adjusted OR = 1.79 for the tertile 2, 95%CI:1.09-2.95; p for trend = 0.01). Fetal sex had an interaction with Se in the association with GDM. The association was more pronounced among pregnant women with female fetuses than with male fetuses. Discussion Our study suggested a significant negative association between urinary Se and the risk of GDM, and this association may vary depending on the fetal sex.

Liu, Yuanxia↗

Toward Development of a Stochastic Wake Model: Validation Using LES and Turbine Loads

Wind turbines within an array do not experience free-stream undisturbed flow fields. Rather, the flow fields on internal turbines are influenced by wakes generated by upwind unit and exhibit different dynamic characteristics relative to the free stream. The International Electrotechnical Commission (IEC) standard 61400-1 for the design of wind turbines only considers a deterministic wake model for the design of a wind plant. This study is focused on the development of a stochastic model for waked wind fields. First, high-fidelity physics-based waked wind velocity fields are generated using Large-Eddy Simulation (LES). Stochastic characteristics of these LES waked wind velocity field, including mean and turbulence components, are analyzed. Wake-related mean and turbulence field-related parameters are then estimated for use with a stochastic model, using Multivariate Multiple Linear Regression (MMLR) with the LES data. To validate the simulated wind fields based on the stochastic model, wind turbine tower and blade loads are generated using aeroelastic simulation for utility-scale wind turbine models and compared with those based directly on the LES inflow. The study’s overall objective is to offer efficient and validated stochastic approaches that are computationally tractable for assessing the performance and loads of turbines operating in wakes.

17 WIND ENERGY↗

Sensitivity aspects of linear digital control systems.

Linear computer-controlled closed loop systems sensitivity analysis, deriving estimation error incremental covariance to demonstrate quality deterioration under perturbed initial conditions, parameters, etc

Christie, L. A.↗

An efficient technique for determining apparent temperature distributions from antenna temperature measurements

A method by which the apparent microwave temperature characteristic of a flat scene is estimated from dual polarized measurements is derived and interpreted. Approximate linear relationships between antenna and apparent temperatures are established by weighting emission components in spherical bands under the assumption that the surface is isotropic. The weighting factors are formed by integrating the antenna pattern functions over these bands. The vector aspect of the formulation is retained to account for the difference between the definition of the antenna polarizations and the polarizations of the emitted fields. The method is largely applicable to the measurement of smooth temperature distributions by an antenna having good spatial resolution of the distributions and is considered efficient for inverting large volumes of measurements. Sample cases are presented and the implications of these cases on remote radiometer observations are discussed. It is shown that cross-coupling occurs between the polarizations of the emitted fields and the polarizations of the antenna. For this reason and because practical antennas have cross-polarized patterns associated with them, it is necessary to conduct measurements at both horizontal and vertical polarizations to realize the inversion. It is also made evident that thorough inversions require that the apparent temperatures be sampled at a sufficient number of points between nadir and zenith.

Claassen, J. P.↗

M558 radioactive tracer diffusion

This experiment was performed in Skylab 3 with two objectives in mind. First, the experimental self-diffusion coefficients for liquid zinc were to be determined in a convection-free environment. Secondly the reduction in convective mixing in earth gravity by going into the zero-gravity environment of space was to be estimated. The experiment was designed to utilize high temperatures and linear thermal gradients provided by the M518 Multipurpose Electric Furnace, and the radioactivity of zinc-65 of 245-day half-life to investigate self-diffusion in liquid zinc. The distribution of zinc-65 tracer, after melting, maintaining at soak temperature for 1 hour of soak time and then resolidifying, was obtained by sample sectioning. The concentration of activity of each section (microcurie-gram) was plotted against positions along the sample axial and radial position. Experimental data and theoretical results from solution of Fick's law of diffusion in one dimensional were compared. Samples tested on earth showed very rapid diffusion. Diffusion coefficient in unit gravity was 50 times the zero-gravity diffusion coefficient of Skylab.

Ukanwa, A. O.↗

Variational Algorithms for Nonlinear Smoothing Applications

A variational approach is presented for solving a nonlinear, fixed-interval smoothing problem with application to offline processing of noisy data for trajectory reconstruction and parameter estimation. The nonlinear problem is solved as a sequence of linear two-point boundary value problems. Second-order convergence properties are demonstrated. Algorithms for both continuous and discrete versions of the problem are given, and example solutions are provided.

Bach, Ralph E. Jr.↗

Laser range measurements using non-Gaussian pulse shapes

Many optical ranging systems currently use laser pulses of approximately Gaussian shape with widths of a few nanoseconds or less. The present paper shows that a substantial improvement in accuracy can be obtained for a given pulse length by means of laser ranging systems using conventional length (long) pulses with a sharp leading edge pulse distribution. The accuracy in such a case will improve roughly linearly with the signal strength. Order statistics is used to estimate the round-trip level travel time from the arrival time of the earliest photoelectron.

Ghigo, F. D.↗

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Klein, V.↗

A three-axis angular monitoring system for the magnetic field satellite /MAGSAT/ mission

An electro-optical attitude transfer system was developed to monitor the angular orientation of magnetometers deployed at the end of a 20-foot boom extending outboard from the Magsat spacecraft. One autocollimator monitors pitch and yaw attitude, cooperating with a plane mirror at the end of the boom; a second monitors roll (twist) from an offset look-angle, using one dihedral reflector at the boom end and a second on the spacecraft. RMS errors due to all causes including linearity, G-forces, cross-coupling and translation are estimated to be 3.9 arcsec over + or - 180 arcsec excursion in pitch and yaw, and 5.3 to 7.5 arcsec over + or - 300 arcsec roll. Design and fabrication problems relative to the remote dihedral refector proved to be the most challenging, and solutions to these problems will be described.

Collyer, P. W.↗

On the flight derived/aerodynamic data base performance comparisons for the NASA Space Shuttle entries during the hypersonic regime

Aerodynamic performance data from the first four Shuttle reentry flights are compared with preflight predictions covering hypersonic longitudinal mode down to Mach 2. The extraction of the flight coefficients, as measured by the spacecraft angular rates and the linear accelerations, derived from the inertial measurement unit, the best estimate trajectory, and the remotely measured atmosphere are discussed. The ground predictions were developed from 30,000 hr of wind tunnel testing. Actual flight data are presented for 80-260 kft, from Mach 2-26, comprising the dynamic pressure, the vehicle air relative attitude angles, control surface deflections, reaction jet activity, and body axis rates and accelerations. The second and fourth flights gave results which deviated from predictions between 230-260 kft. The accuracy limits of the derived atmospheric densities are considered, together with potential data base updates in the light of limitations imposed on the corrections by available flight data.

Findlay, J. T.↗

Kinetics and mechanism of HO2 and DO2 disproportionations

A flash photolysis/UV abosrption technique was used to study the HO2 + HO2 and DO2 + DO2 reactions in the gas phase. Rate constants were measured at pressures between 100 and 700 torr of Ar and N2, and at temperatures between 230 and 420 K with up to 10 torr of added water vapor. The overall disproportionation rate constants for the reaction is given as the sum of pressure-independent and pressure-dependent terms. A kinetic analysis shows that both reactions have a zero-pressure bimolecular component and a termolecular component which is linearly dependent on pressure up to 700 torr. A priori estimates of the vibrational frequencies of the product of the HO2 + HO2 reaction suggest binding energies of 12-20 kcal per mol (for the initial association).

Kircher, C. C.↗

Phase error statistics of a phase-locked loop synchronized direct detection optical PPM communication system

Receiver timing synchronization of an optical Pulse-Position Modulation (PPM) communication system can be achieved using a phased-locked loop (PLL), provided the photodetector output is suitably processed. The magnitude of the PLL phase error is a good indicator of the timing error at the receiver decoder. The statistics of the phase error are investigated while varying several key system parameters such as PPM order, signal and background strengths, and PPL bandwidth. A practical optical communication system utilizing a laser diode transmitter and an avalanche photodiode in the receiver is described, and the sampled phase error data are presented. A linear regression analysis is applied to the data to obtain estimates of the relational constants involving the phase error variance and incident signal power.

Natarajan, Suresh↗

Response of joint dominated space structures

An approximate method is developed for estimating the transient response of nonlinear systems in terms of linearized modes of response. Its advantages are that it is computationally more efficient than the time integration method and that it is possible to view the design problem in the more traditional physical terms of modal response. The major drawback of the approximate method is loss of accuracy. It seems that both approximate methods and time integration have their roles in design. Approximate methods provide efficient tools for performing parametric studies and they supply physical insights into how to optimize system performance that are not easily inferred from strictly numerical methods. Time integration provides a method for assessing the accuracy of the approximate solution for key simulations and for fine tuning the final design. In the procedure presented the nonlinear system is approximated by an equivalent linear system in which the system parameters are constant over the range of transient response.

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