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At least 1,477 records · Page 82

Deuterium target data for precision neutrino-nucleus cross sections

Amplitudes derived from scattering data on elementary targets are basic inputs to neutrino-nucleus cross section predictions. A prominent example is the isovector axial nucleon form factor, F A (q 2 ), which controls charged current signal processes at accelerator-based neutrino oscillation experiments. Previous extractions of F A from neutrino-deuteron scattering data rely on a dipole shape assumption that introduces an unquantified error. A new analysis of world data for neutrino-deuteron scattering is performed using a model-independent, and systematically improvable, representation of F A . A complete error budget for the nucleon isovector axial radius leads to r A 2 = 0.46(22)fm 2 , with a much larger uncertainty than determined in the original analyses. The quasielastic neutrino-neutron cross section is determined as σ(ν μ n → μ - p)| E v =1 GeV = 10.1(0.9)×10 -39 cm 2 . The propagation of nucleon-level constraints and uncertainties to nuclear cross sections is illustrated using MINERvA data and the GENIE event generator. Furthermore, these techniques can be readily extended to other amplitudes and processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Skill of Mesoscale Models in Forecasting Springtime Macrophysical Cloud Properties at the Savannah River Site in the Southeastern US

Predicting boundary layer clouds is important for the accurate modeling of pollutant dispersion. Higher resolution mesoscale models would be expected to produce better forecasts of cloud properties that affect dispersion. Using ceilometer observations, we assess the skill of two operational mesoscale models (RAMS and WRF) to forecast cloud base altitude and cloud fraction at the Savannah River Site in the southeastern US during the springtime. Verifications were performed at small spatial and temporal scales necessary for dispersion modeling. Both models were unreliable with a 50% (RAMS) and a 46% (WRF) rate of predicting clouds observed by the ceilometer which led to low cloud fraction predictions. Results indicated that WRF better predicted daytime cloud bases from convection that occurred frequently later in the period and RAMS better predicted nighttime cloud bases. Using root mean squared error (RMSE) to score the forecast periods also highlighted this diurnal dichotomy, with WRF scores better during the day and RAMS scores better at night. Analysis of forecast errors revealed divergent model cloud base biases—WRF low and RAMS high. A hybrid solution which weighs more heavily the RAMS nighttime forecasts and WRF daytime forecasts will likely provide the best prediction of cloud properties for dispersion.

54 ENVIRONMENTAL SCIENCES↗

Displacement Compensation of Temperature Probe Data

Analysis of temperature data from a probe in a vertical Bridgman furnace growing germanium crystals revealed a displacement of the temperature profile due to conduction error. A theoretical analysis shows that the displacement compensation is independent of local temperature gradient. A displacement compensation value should become a standard characteristic of temperature probes used for temperature profile measurements.

Welch, Christopher S.↗

Numerical discreteness errors in multispecies cosmological N -body simulations

ABSTRACT We present a detailed analysis of numerical discreteness errors in two-species, gravity-only, cosmological simulations using the density power spectrum as a diagnostic probe. In a simple set-up where both species are initialized with the same total matter transfer function, biased growth of power forms on small scales when the solver force resolution is finer than the mean interparticle separation. The artificial bias is more severe when individual density and velocity transfer functions are applied. In particular, significant large-scale offsets in power are measured between simulations with conventional offset grid initial conditions when compared against converged high-resolution results where the force resolution scale is matched to the interparticle separation. These offsets persist even when the cosmology is chosen so that the two particle species have the same mass, indicating that the error is sourced from discreteness in the total matter field as opposed to unequal particle mass. We further investigate two mitigation strategies to address discreteness errors: the frozen potential method and softened interspecies short-range forces. The former evolves particles under the approximately ‘frozen’ total matter potential in linear theory at early times, while the latter filters cross-species gravitational interactions on small scales in low-density regions. By modelling closer to the continuum limit, both mitigation strategies demonstrate considerable reductions in large-scale power spectrum offsets.

79 ASTRONOMY AND ASTROPHYSICS↗

WE-A-17A-09: Exploiting Electromagnetic Technologies for Real-Time Seed Drop Position Validation in Permanent Implant Brachytherapy

Purpose: To report on preliminary results validating the performance of a specially designed LDR brachytherapy needle prototype possessing both electromagnetic (EM) tracking and seed drop detection abilities. Methods: An EM hollow needle prototype has been designed and constructed in collaboration with research partner Philips Healthcare. The needle possesses conventional 3D tracking capabilities, along with a novel seed drop detection mechanism exploiting local changes of electromagnetic properties generated by the passage of seeds in the needle's embedded sensor coils. These two capabilities are exploited by proprietary engineering and signal processing techniques to generate seed drop position estimates in real-time treatment delivery. The electromagnetic tracking system (EMTS) used for the experiment is the NDI Aurora Planar Field Generator. The experiment consisted of dropping a total of 35 seeds in a prismatic agarose phantom, and comparing the 3D seed drop positions of the EMTS to those obtained by an image analysis of subsequent micro-CT scans. Drop position error computations and statistical analysis were performed after a 3D registration of the two seed distributions. Results: Of the 35 seeds dropped in the phantom, 32 were properly detected by the needle prototype. Absolute drop position errors among the detected seeds ranged from 0.5 to 4.8 mm with mean and standard deviation values of 1.6 and 0.9 mm, respectively. Error measurements also include undesirable and uncontrollable effects such as seed motion upon deposition. The true accuracy performance of the needle prototype is therefore underestimated. Conclusion: This preliminary study demonstrates the potential benefits of EM technologies in detecting the passage of seeds in a hollow needle as a means of generating drop position estimates in real-time treatment delivery. Such tools could therefore represent a potentially interesting addition to existing brachytherapy protocols for rapid dosimetry validation. Equipments and fundings for this project were provided by Philips Medical.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Effects of the ephemeris error on effective pointing for a spaceborne SAR

Both Magellan SAR data acquisition and image processing require the knowledge of both the ephemeris (spacecraft position and velocity) and the radar pointing direction. Error in the knowledge of the radar pointing direction results in a loss of SNR in the image product. An error in the ephemeris data has a similar effect. To facilitate SNR performance analysis, an effective pointing error is defined to characterize the effect of the ephemeris error. A systematic approach to relate the ephemeris error to the effective pointing errors is described. Result of this analysis has led to a formal accuracy requirement levied on the Magellan navigation system.

Jin, Michael Y.↗

System wide analyses have underestimated protein abundances and the importance of transcription in mammals

Large scale surveys in mammalian tissue culture cells suggest that the protein expressed at the median abundance is present at 8000–16 000 molecules per cell and that differences in mRNA expression between genes explain only 10–40% of the differences in protein levels. We find, however, that these surveys have significantly underestimated protein abundances and the relative importance of transcription. Using individual measurements for 61 housekeeping proteins to rescale whole proteome data from Schwanhausser et al. (2011), we find that the median protein detected is expressed at 170 000 molecules per cell and that our corrected protein abundance estimates show a higher correlation with mRNA abundances than do the uncorrected protein data. In addition, we estimated the impact of further errors in mRNA and protein abundances using direct experimental measurements of these errors. The resulting analysis suggests that mRNA levels explain at least 56% of the differences in protein abundance for the 4212 genes detected by Schwanhausser et al. (2011), though because one major source of error could not be estimated the true percent contribution should be higher. We also employed a second, independent strategy to determine the contribution of mRNA levels to protein expression. We show that the variance in translation rates directly measured by ribosome profiling is only 12% of that inferred by Schwanhausser et al. (2011), and that the measured and inferred translation rates correlate poorly (R2 = 0.13). Based on this, our second strategy suggests that mRNA levels explain ~81% of the variance in protein levels. We also determined the percent contributions of transcription, RNA degradation, translation and protein degradation to the variance in protein abundances using both of our strategies. While the magnitudes of the two estimates vary, they both suggest that transcription plays a more important role than the earlier studies implied and translation a much smaller role. Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately 40% of genes in a given cell within a population express no mRNA. Since there can be no translation in the absence of mRNA, we argue that differences in translation rates can play no role in determining the expression levels for the ~40% of genes that are non-expressed.

59 BASIC BIOLOGICAL SCIENCES↗

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗

Experimental results on tracking performance of the MTDD Costas loop with UQPSK signal

The carrier tracking performance of the breadboard Costas Loop of the Multimegabit Telemetry Demodulator Detector System was tested with unbalanced quadriphase shift keying (UQPSK) signals. An S-band UQPSK modulator was built for the tests. The experimental results are very close to the theoretical rms phase error calculations. The test and analysis show that the rms phase error for UQPSK signals is less than 5 deg at the design point if the I-to-Q channel power ratio is larger than 6 dB.

Park, Y. H.↗

Model error estimation for large space systems

In-flight estimation of large structure model errors may have to be carried out in order to detect inevitable deficiencies in large structure controller/estimator models. These error estimates can most efficiently be obtained by the minimization of a quadratic functional of the model errors and on the subsequent analysis of the resulting optimal model error estimates. An integral operator approach to estimation leads to a geometrical interpretation of the model error estimation process. One of the significant insights gained with this interpretation is that the actual but unknown model errors can be decomposed as the sum of two distinct components that are orthogonal in some sense. One of these components is a so-called minimal error vector that retains many of the significant dynamics of the actual errors. The basic ideas in the model error estimation approach are first set forth with a two-dimensional analogy that has most of the essential features of the general estimation problem. The generalized results are then established and their application to a reference large structure model illustrated.

Rodriguez, G.↗

Tailoring a Human Reliability Analysis to Your Industry Needs

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

DeMott, D. L.↗

Impact of baryonic processes on weak-lensing cosmology: Power spectrum, nonlocal statistics, and parameter bias

We study the impact of baryonic physics on cosmological parameter estimation with weak-lensing surveys. We run a set of cosmological hydrodynamics simulations with different galaxy formation models. We then perform ray-tracing simulations through the total matter density field to generate 100 independent convergence maps with a field of view of 25 deg{sup 2}, and we use them to examine the ability of the following three lensing statistics as cosmological probes: power spectrum (PS), peak counts, and Minkowski functionals (MFs). For the upcoming wide-field observations, such as the Subaru Hyper Suprime-Cam (HSC) survey with a sky coverage of 1400 deg{sup 2}, these three statistics provide tight constraints on the matter density, density fluctuation amplitude, and dark energy equation of state, but parameter bias is induced by baryonic processes such as gas cooling and stellar feedback. When we use PS, peak counts, and MFs, the magnitude of relative bias in the dark energy equation of state parameter w is at a level of, respectively, δw∼0.017, 0.061, and 0.0011. For the HSC survey, these values are smaller than the statistical errors estimated from Fisher analysis. The bias could be significant when the statistical errors become small in future observations with a much larger survey area. We find that the bias is induced in different directions in the parameter space depending on the statistics employed. While the two-point statistic, i.e., PS, yields robust results against baryonic effects, the overall constraining power is weak compared with peak counts and MFs. On the other hand, using one of peak counts or MFs, or combined analysis with multiple statistics, results in a biased parameter estimate. The bias can be as large as 1σ for the HSC survey and will be more significant for upcoming wider-area surveys. We suggest to use an optimized combination so that the baryonic effects on parameter estimation are mitigated. Such a “calibrated” combination can place stringent and robust constraints on cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

Long and short arc altitude determination for GEOS-C

The accuracy with which the GEOS-C altitude may be estimated over long (7 day) and short (40 minute) orbital arcs is investigated. Over the long are excellent agreement was attained between a simulation of the orbit determination process and a covariance analysis. Both approaches yielded RMS altitude errors of about 1.5 meters over the Caribbean calibration area and approximately 7.5 meters overall. The geopotential was identified as the largest error source. For the short arc, the covariance analysis revealed that the propagated altitude error is linearly dependent upon station survey component errors which are also the largest source of altitude errors. An Appendix contains the mathematics of covariance analysis as applied to orbit determination.

Koch, D.↗

SU-C-BRD-04: Comparison of Shallow Fluence to Deep Point Dose Measurements for Spine VMAT SBRT Patient-Specific QA

Purpose: To investigate the sensitivity of traditional gamma-index-based fluence measurements for patient-specific measurements in VMAT delivered spine SBRT. Methods: The ten most recent cases for spine SBRT were selected. All cases were planned with Eclipse RapidArc for a TrueBeam STx. The delivery was verified using a point dose measurement with a Pinpoint 3D micro-ion chamber in a Standard Imaging Stereotactic Dose Verification Phantom. Two points were selected for each case, one within the target in a low dose-gradient region and one in the spinal cord. Measurements were localized using on-board CBCT. Cumulative and separate arc measurements were acquired with the ArcCheck and assessed using the SNC patient software with a 3%/3mm and 2%/2mm gamma analysis with global normalization and a 10% dose threshold. Correlations between data were determined using the Pearson Product-Moment Correlation. Results: For our cohort of patients, the measured doses were higher than calculated ranging from 2.2%–9.7% for the target and 1.0%–8.2% for the spinal cord. There was strong correlation between 3%/3mm and 2%/2mm passing rates (r=0.91). Moderate correlation was found between target and cord dose with a weak fit (r=0.67, R-Square=0.45). The cumulative ArcCheck measurements showed poor correlation with the measured point doses for both the target and cord (r=0.20, r=0.35). If the arcs are assessed separately with an acceptance criteria applied to the minimum passing rate between all arcs, a moderate negative correlation was found for the target and cord (r=−0.48, r= −0.71). The case with the highest dose difference (9.7%) received a passing rate of 97.2% for the cumulative arcs and 87.8% for the minimum with separate arcs. Conclusion: Our data suggest that traditional passing criteria using ArcCheck with cumulative measurements do not correlate well with dose errors. Separate arc analysis shows better correlation but may still miss large dose errors. Point dose verifications are recommended.

60 APPLIED LIFE SCIENCES↗

Error in temperature measurements due to conduction along the sensors

When a sensor is embedded in a solid body to measure its internal temperature, any conduction to or from its sensing element may cause the indicated temperature to be different from the true temperature. This paper describes an analysis of the error caused by conduction when there is an arbitrary temperature distribution in the body along the sensor. The sensor is modeled as a cylindrical fin and the appropriate conduction equation is solved. The solution gives a correction for the error which depends on such parameters as, depth of immersion, thermocouple wire and insulation properties, contact between the sensor and the body, and temperature distribution in the body. The latter may not be known, but the measured temperature distribution can be used as a first approximation. The corrected value can then be used to obtain a better estimate of the error. The results show good agreement with experimental observations.

Singh, B. S.↗

Effect of model uncertainty on failure detection - The threshold selector

The performance of all failure detection, isolation, and accomodation (DIA) algorithms is influenced by the presence of model uncertainty. A unique framework is presented to incorporate a knowledge of modeling error in the analysis and design of failure detection systems. The tools being used are very similar to those in robust control theory. A concept is introduced called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals. The threshold selector represents an innovative tool for analysis and synthesis of DIA algorithms. It identifies the optimal threshold to be used in innovations-based DIA algorithms. The optimal threshold is shown to be a function of the bound on modeling errors, the noise properties, the speed of DIA filters, and the classes of reference and failure signals. The size of the smallest detectable failure is also determined. The results are applied to a multivariable turbofan jet engine example, which demonstrates improvements compared to previous studies.

Emami-Naeini, Abbas↗

Quality Assurance With Plan Veto: Reincarnation of a Record and Verify System and Its Potential Value

Purpose: To quantify the potential impact of the Integrating the Healthcare Enterprise–Radiation Oncology Quality Assurance with Plan Veto (QAPV) on patient safety of external beam radiation therapy (RT) operations. Methods and Materials: An institutional database of events (errors and near-misses) was used to evaluate the ability of QAPV to prevent clinically observed events. We analyzed reported events that were related to Digital Imaging and Communications in Medicine RT plan parameter inconsistencies between the intended treatment (on the treatment planning system) and the delivered treatment (on the treatment machine). Critical Digital Imaging and Communications in Medicine RT plan parameters were identified. Each event was scored for importance using the Failure Mode and Effects Analysis methodology. Potential error occurrence (frequency) was derived according to the collected event data, along with the potential event severity, and the probability of detection with and without the theoretical implementation of the QAPV plan comparison check. Failure Mode and Effects Analysis Risk Priority Numbers (RPNs) with and without QAPV were compared to quantify the potential benefit of clinical implementation of QAPV. Results: The implementation of QAPV could reduce the RPN values for 15 of 22 (71%) of evaluated parameters, with an overall average reduction in RPN of 68 (range, 0-216). For the 6 high-risk parameters (>200), the average reduction in RPN value was 163 (range, 108-216). The RPN value reduction for the intermediate-risk (200 > RPN > 100) parameters was (0-140). With QAPV, the largest RPN value for “Beam Meterset” was reduced from 324 to 108. The maximum reduction in RPN value was for Beam Meterset (216, 66.7%), whereas the maximum percentage reduction was for Cumulative Meterset Weight (80, 88.9%). Conclusion: This analysis quantifies the value of the Integrating the Healthcare Enterprise–Radiation Oncology QAPV implementation in clinical workflow. We demonstrate that although QAPV does not provide a comprehensive solution for error prevention in RT, it can have a significant impact on a subset of the most severe clinically observed events.

62 RADIOLOGY AND NUCLEAR MEDICINE↗