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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantitatively accurate activity measurements with a dedicated cardiac SPECT camera: Physical phantom experiments

Purpose: Recently, there has been increased interest in dedicated cardiac single photon emission computed tomography (SPECT) scanners with pinhole collimation and improved detector technology due to their improved count sensitivity and resolution over traditional parallel-hole cameras. With traditional cameras, energy-based approaches are often used in the clinic for scatter compensation because they are fast and easily implemented. Some of the cardiac cameras use cadmium-zinc-telluride (CZT) detectors which can complicate the use of energy-based scatter correction (SC) due to the low-energy tail—an increased number of unscattered photons detected with reduced energy. Modified energy-based scatter correction methods can be implemented, but their level of accuracy is unclear. In this study, the authors validated by physical phantom experiments the quantitative accuracy and reproducibility of easily implemented correction techniques applied to {sup 99m}Tc myocardial imaging with a CZT-detector-based gamma camera with multiple heads, each with a single-pinhole collimator. Methods: Activity in the cardiac compartment of an Anthropomorphic Torso phantom (Data Spectrum Corporation) was measured through 15 {sup 99m}Tc-SPECT acquisitions. The ratio of activity concentrations in organ compartments resembled a clinical {sup 99m}Tc-sestamibi scan and was kept consistent across all experiments (1.2:1 heart to liver and 1.5:1 heart to lung). Two background activity levels were considered: no activity (cold) and an activity concentration 1/10th of the heart (hot). A plastic “lesion” was placed inside of the septal wall of the myocardial insert to simulate the presence of a region without tracer uptake and contrast in this lesion was calculated for all images. The true net activity in each compartment was measured with a dose calibrator (CRC-25R, Capintec, Inc.). A 10 min SPECT image was acquired using a dedicated cardiac camera with CZT detectors (Discovery NM530c, GE Healthcare), followed by a CT scan for attenuation correction (AC). For each experiment, separate images were created including reconstruction with no corrections (NC), with AC, with attenuation and dual-energy window (DEW) scatter correction (ACSC), with attenuation and partial volume correction (PVC) applied (ACPVC), and with attenuation, scatter, and PVC applied (ACSCPVC). The DEW SC method used was modified to account for the presence of the low-energy tail. Results: T-tests showed that the mean error in absolute activity measurement was reduced significantly for AC and ACSC compared to NC for both (hot and cold) datasets (p < 0.001) and that ACSC, ACPVC, and ACSCPVC show significant reductions in mean differences compared to AC (p ≤ 0.001) without increasing the uncertainty (p > 0.4). The effect of SC and PVC was significant in reducing errors over AC in both datasets (p < 0.001 and p < 0.01, respectively), resulting in a mean error of 5% ± 4%. Conclusions: Quantitative measurements of cardiac {sup 99m}Tc activity are achievable using attenuation and scatter corrections, with the authors’ dedicated cardiac SPECT camera. Partial volume corrections offer improvements in measurement accuracy in AC images and ACSC images with elevated background activity; however, these improvements are not significant in ACSC images with low background activity.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Errors introduced in fission neutron spectrum measurements using a single reference

Measurements of physical quantities are often made relative to a reference quantity, simplifying the interpretation of the measurement and its uncertainties. However, if applied without careful considerations, this technique can carry with it a significant and complex systematic error that is usually ignored. For example, measurements of continuous neutron spectra relative to a reference spectrum yield a result that does not properly include the important effects of neutron scattering in the experimental environment. These effects act to distort the measured spectrum shape and create notable errors in spectrum-integrated quantities. While this effect is one of a series of known potential sources of systematic error including, but not limited to target impurities, angular distributions, incident beam flux, and others, the error introduced from differences in environmental scattering effects between the reference and desired spectra are frequently overlooked. In this work, we demonstrate the origin of this error using simulated data corresponding to measurements of the neutron-induced prompt fission neutron spectra of 233 U, 235 U, 238 U, and 239 Pu as well as the spontaneous fission neutron spectrum of 252 Cf. Errors in the spectrum shape can be as high as 10%–15% depending on the combination of incident and outgoing neutron energy. The spectrum integral and average spectrum energy also contain errors that change with incident neutron energy and can be as high as ~2%. Although this study is based on simulated data, we also show a method for proving that this error exists in an experimental data set and we show a correction that can be applied to results of this type to obtain a more accurate result, thereby largely removing systematic errors from environmental scattering effects. The potential for these kinds of errors should be considered in measurements producing continuous neutron spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Beam correction for multi-pass arcs in FFA@CEBAF: status update

This work examines the multi-pass steering of six electron beams in an FFA arc ranging from approximately 10.5 GeV to 22 GeV. Shown here is an algorithm based on singular value decomposition (SVD) to successfully steer all six beams through the arc given precise knowledge of all beam positions at each of one hundred and one diagnostic locations with one hundred individual corrector magnets: that is successive application of SVD to different 100 × 101 response matrices—one for each beam energy. Further, a machine learning scheme is developed which only requires knowledge of the energy-averaged beam position at each location to provide equivalent steering. Extension of this scheme to other beam optics quantities as well as transverse and longitudinal coupling is explored.

Accelerator Physics↗
DOE OSTI2020

DPM: A deep learning PDE augmentation method with application to large-eddy simulation

A framework is introduced that leverages known physics to reduce overfitting in machine learning for scientific applications. The partial differential equation (PDE) that expresses the physics is augmented with a neural network that uses available data to learn a description of the corresponding unknown or unrepresented physics. Training within this combined system corrects for missing, unknown, or erroneously represented physics, including discretization errors associated with the PDE's numerical solution. For optimization of the network within the PDE, an adjoint PDE is solved to provide high-dimensional gradients, and a stochastic adjoint method (SAM) further accelerates training. Additionally, the approach is demonstrated for large-eddy simulation (LES) of turbulence. High-fidelity direct numerical simulations (DNS) of decaying isotropic turbulence provide the training data used to learn sub-filter-scale closures for the filtered Navier–Stokes equations. Out-of-sample comparisons show that the deep learning PDE method outperforms widely-used models, even for filter sizes so large that they become qualitatively incorrect. It also significantly outperforms the same neural network when a priori trained based on simple data mismatch, not accounting for the full PDE. Measures of discretization errors, which are well-known to be consequential in LES, point to the importance of the unified training formulation's design, which without modification corrects for them. For comparable accuracy, simulation runtime is significantly reduced. A relaxation of the typical discrete enforcement of the divergence-free constraint in the solver is also successful, instead allowing the DPM to approximately enforce incompressibility physics. Since the training loss function is not restricted to correspond directly to the closure to be learned, training can incorporate diverse data, including experimental data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

EVOLUTION OF THE VELOCITY-DISPERSION FUNCTION OF LUMINOUS RED GALAXIES: A HIERARCHICAL BAYESIAN MEASUREMENT

We present a hierarchical Bayesian determination of the velocity-dispersion function of approximately 430,000 massive luminous red galaxies observed at relatively low spectroscopic signal-to-noise ratio (S/N {approx} 3-5 per 69 km s{sup -1}) by the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. We marginalize over spectroscopic redshift errors, and use the full velocity-dispersion likelihood function for each galaxy to make a self-consistent determination of the velocity-dispersion distribution parameters as a function of absolute magnitude and redshift, correcting as well for the effects of broadband magnitude errors on our binning. Parameterizing the distribution at each point in the luminosity-redshift plane with a log-normal form, we detect significant evolution in the width of the distribution toward higher intrinsic scatter at higher redshifts. Using a subset of deep re-observations of BOSS galaxies, we demonstrate that our distribution-parameter estimates are unbiased regardless of spectroscopic S/N. We also show through simulation that our method introduces no systematic parameter bias with redshift. We highlight the advantage of the hierarchical Bayesian method over frequentist 'stacking' of spectra, and illustrate how our measured distribution parameters can be adopted as informative priors for velocity-dispersion measurements from individual noisy spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

An error reduction algorithm to improve lidar turbulence estimates for wind energy

Abstract. Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine-learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI) error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

17 WIND ENERGY↗
DOE OSTI2012

Prevention of a wrong-location misadministration through the use of an intradepartmental incident learning system

Purpose: A series of examples are presented in which potential errors in the delivery of radiation therapy were prevented through use of incident learning. These examples underscore the value of reporting near miss incidents. Methods: Using a departmental incident learning system, eight incidents were noted over a two-year period in which fields were treated 'out-of-sequence,' that is, fields from a boost phase were treated, while the patient was still in the initial phase of treatment. As a result, an error-prevention policy was instituted in which radiation treatment fields are 'hidden' within the oncology information system (OIS) when they are not in current use. In this way, fields are only available to be treated in the intended sequence and, importantly, old fields cannot be activated at the linear accelerator control console. Results: No out-of-sequence treatments have been reported in more than two years since the policy change. Furthermore, at least three near-miss incidents were detected and corrected as a result of the policy change. In the first two, the policy operated as intended to directly prevent an error in field scheduling. In the third near-miss, the policy operated 'off target' to prevent a type of error scenario that it was not directly intended to prevent. In this incident, an incorrect digitally reconstructed radiograph (DRR) was scheduled in the OIS for a patient receiving lung cancer treatment. The incorrect DRR had an isocenter which was misplaced by approximately two centimeters. The error was a result of a field from an old plan being scheduled instead of the intended new plan. As a result of the policy described above, the DRR field could not be activated for treatment however and the error was discovered and corrected. Other quality control barriers in place would have been unlikely to have detected this error. Conclusions: In these examples, a policy was adopted based on incident learning, which prevented several errors, at least one of which was potentially severe. These examples underscore the need for a rigorous, systematic incident learning process within each clinic. The experiences reported in this technical note demonstrate the value of near-miss incident reporting to improve patient safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Quantifying model structural error: Efficient Bayesian calibration of a regional groundwater flow model using surrogates and a data-driven error model

Groundwater model structural error is ubiquitous, due to simplification and/or misrepresentation of real aquifer systems. During model calibration, the basic hydrogeological parameters may be adjusted to compensate for structural error. This may result in biased predictions when such calibrated models are used to forecast aquifer responses to new forcing. Here, we investigate the impact of model structural error on calibration and prediction of a real-world groundwater flow model, using a Bayesian method with a data-driven error model to explicitly account for model structural error. The error-explicit Bayesian method jointly infers model parameters and structural error and thereby reduces parameter compensation. In this study, Bayesian inference is facilitated using high performance computing and fast surrogate models (based on machine learning techniques) as a substitute for the computationally expensive groundwater model. We demonstrate that with explicit treatment of model structural error, the Bayesian method yields parameter posterior distributions that are substantially different from those derived using classical Bayesian calibration that does not account for model structural error. We also found that the error-explicit Bayesian method gives signficantly more accurate prediction along with reasonable credible intervals. Finally, through variance decomposition, we provide a comprehensive assessment of prediction uncertainty contributed from parameter, model structure, and measurement uncertainty. The results suggest that the error-explicit Bayesian approach provides a solution to real-world modeling applications for which data support the presence of model structural error, yet model deficiency cannot be specifically identified or corrected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Feynman diagrams for matter wave interferometry

We introduce a new theoretical framework based on Feynman diagrams to compute phase shifts in matter wave interferometry. The method allows for analytic computation of higher order quantum corrections, beyond the traditional semi-classical approximation. These additional terms depend on the finite size of the initial matter wavefunction and/or have higher order dependence on ℏ. We apply the method to compute the response of matter wave interferometers to power law potentials and potentials with an arbitrary spatial dependence. The analytic expressions are validated by comparing to numerical simulations, and estimates are provided for the scale of the quantum corrections to the phase shift response to the gravitational field of the earth, anharmonic trapping potentials, and gravitational fields from local proof masses. We also find that for certain experimentally feasible parameters, these corrections are large enough to be measured and could lead to systematic errors if they are not mitigated. We find that to first order in a spatially dependent potential, quantum corrections vanish when the initial matter wavepacket has spherical symmetry and the potential satisfies Laplace's equation. We anticipate these quantum corrections will be especially important for trapped matter wave interferometers and for free-space matter wave interferometers in the presence of proof masses. These interferometers are becoming increasingly sensitive tools for mobile inertial sensing, gravity surveying, tests of gravity and its interplay with quantum mechanics, and searches for dark energy.

Glick, Jonah [Northwestern U.; Fermilab] (ORCID:00↗
DOE OSTI2015

Communication: Quantitative multi-site frequency maps for amide I vibrational spectroscopy

An accurate method for predicting the amide I vibrational spectrum of a given protein structure has been sought for many years. Significant progress has been made recently by sampling structures from molecular dynamics simulations and mapping local electrostatic variables onto the frequencies of individual amide bonds. Agreement with experiment, however, has remained largely qualitative. Previously, we used dipeptide fragments and isotope-labeled constructs of the protein G mimic NuG2b as experimental standards for developing and testing amide I frequency maps. Here, we combine these datasets to test different frequency-map models and develop a novel method to produce an optimized four-site potential (4P) map based on the CHARMM27 force field. Together with a charge correction for glycine residues, the optimized map accurately describes both experimental datasets, with average frequency errors of 2–3 cm{sup −1}. This 4P map is shown to be convertible to a three-site field map which provides equivalent performance, highlighting the viability of both field- and potential-based maps for amide I spectral modeling. The use of multiple sampling points for local electrostatics is found to be essential for accurate map performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Monte Carlo MP2-F12 for Noncovalent Interactions: The C 60 Dimer

A scalable stochastic algorithm is presented that can evaluate explicitly correlated (F12) second-order many-body perturbation (MP2) energies of weak, noncovalent, intermolecular interactions. It first transforms the formulas of the MP2 and F12 energy differences into a short sum of high-dimensional integrals of Green’s functions in real space and imaginary time. Furthermore, these integrals are then evaluated by the Monte Carlo method augmented by parallel execution, redundant-walker convergence acceleration, direct-sampling autocorrelation elimination, and control-variate error reduction. By sharing electron-pair walkers across the supermolecule and its subsystems spanned by the joint basis set, the statistical uncertainty is reduced by one to 2 orders of magnitude in the MP2 binding energy corrected for the basis-set incompleteness and superposition errors. The method predicts the MP2-F12/aug-cc-pVDZ binding energy of 19.1 ± 4.0 kcal mol –1 for the C 60 dimer at the center distance of 9.748 Å.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2010

Manifold corrections on spinning compact binaries

This paper deals mainly with a discussion of three new manifold correction methods and three existing ones, which can numerically preserve or correct all integrals in the conservative post-Newtonian Hamiltonian formulation of spinning compact binaries. Two of them are listed here. One is a new momentum-position scaling scheme for complete consistency of both the total energy and the magnitude of the total angular momentum, and the other is the Nacozy's approach with least-squares correction of the four integrals including the total energy and the total angular momentum vector. The post-Newtonian contributions, the spin effects, and the classification of orbits play an important role in the effectiveness of these six manifold corrections. They are all nearly equivalent to correct the integrals at the level of the machine epsilon for the pure Kepler problem. Once the third-order post-Newtonian contributions are added to the pure orbital part, three of these corrections have only minor effects on controlling the errors of these integrals. When the spin effects are also included, the effectiveness of the Nacozy's approach becomes further weakened, and even gets useless for the chaotic case. In all cases tested, the new momentum-position scaling scheme always shows the optimal performance. It requires a little but not much expensive additional computational cost when the spin effects exist and several time-saving techniques are used. As an interesting case, the efficiency of the correction to chaotic eccentric orbits is generally better than one to quasicircular regular orbits. Besides this, the corrected fast Lyapunov indicators and Lyapunov exponents of chaotic eccentric orbits are large as compared with the uncorrected counterparts. The amplification is a true expression of the original dynamical behavior. With the aid of both the manifold correction added to a certain low-order integration algorithm as a fast and high-precision device and the fast Lyapunov indicators of two nearby trajectories, phase space scans for chaos in the spinning compact binary system are given.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the accuracy of MR-AC and MR-RTP applications. Please note that the project was completed with partial funding from the Ohio Department of Development grant TECH 11-063 and a sponsored research agreement with Philips Healthcare that is managed by Case Western Reserve University. As noted in the affiliations, some of the authors are Philips employees.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Parameter Estimation for Thurstone Choice Models

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-D-206-07: CBCT Scatter Correction Based On Rotating Collimator

Purpose: Scatter correction in cone-beam computed tomography (CBCT) has obvious effect on the removal of image noise, the cup artifact and the increase of image contrast. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, the inconvenience of mechanics and propensity to residual artifacts limited the further evolution of basic and clinical research. Here, we propose a rotating collimator-based approach, in conjunction with reconstruction based on a discrete Radon transform and Tchebichef moments algorithm, to correct scatter-induced artifacts. Methods: A rotating-collimator, comprising round tungsten alloy strips, was mounted on a linear actuator. The rotating-collimator is divided into 6 portions equally. The round strips space is evenly spaced on each portion but staggered between different portions. A step motor connected to the rotating collimator drove the blocker to around x-ray source during the CBCT acquisition. The CBCT reconstruction based on a discrete Radon transform and Tchebichef moments algorithm is performed. Experimental studies using water phantom and Catphan504 were carried out to evaluate the performance of the proposed scheme. Results: The proposed algorithm was tested on both the Monte Carlo simulation and actual experiments with the Catphan504 phantom. From the simulation result, the mean square error of the reconstruction error decreases from 16% to 1.18%, the cupping (τcup) from 14.005% to 0.66%, and the peak signal-to-noise ratio increase from 16.9594 to 31.45. From the actual experiments, the induced visual artifacts are significantly reduced. Conclusion: We conducted an experiment on CBCT imaging system with a rotating collimator to develop and optimize x-ray scatter control and reduction technique. The proposed method is attractive in applications where a high CBCT image quality is critical, for example, dose calculation in adaptive radiation therapy. We want to thank Dr. Lei Xing and Dr. Yong Yang in the Stanford University School of Medicine for this work. This work was jointly supported by NSFC (61471226), Natural Science Foundation for Distinguished Young Scholars of Shandong Province (JQ201516), and China Postdoctoral Science Foundation (2015T80739, 2014M551949).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Correction to “Ruthenium Dye Excitations and Relaxations in Natural Sunlight”

An error in computing the optical rate coefficients for dye RuP was discovered in Table S4 of the Supporting Information Section S8 Model S? for this article, published in J. Phys. Chem. A, 2021, 125, 4365-4372, 10.1021/acs.jpca.1c02386. The optical rate coefficients include absorption, stimulated emission, and ground-state bleach associated with the ground state and the singlet and triplet excited states as well as for the excited-state absorption between the excited states and implicit higher-energy excited states. The optical rate coefficients for continuous solar irradiance were computed using eq 3 of the main text in which the product of the individual signal components and the solar spectrum are integrated and multiplied by the fundamental optical rate coefficient. We determined the incorrect signal components were used for RuP in the published Supporting Information Table S4. The corrected Table S4 column for RuP is presented with the reported values from the original paper in the corrected Supporting Information. New simulations have been performed using the corrected values, and the results were used to update Figures 5 and 6 and also Figure S9 in the corrected Supporting Information. The published conclusions are unchanged. The populations of RuP excited states, Figure 5, are only marginally smaller, which should be expected with minor changes to the optical rate coefficients. There is not a significant change in the results for the number of radiative and nonradiative interactions per dye per second (the optical transitions and nonradiative transitions increased, respectively, by approximately 2% and 10%, Figure 6A). The occurrence of excited-state absorption (ESA) and excited-state emission (ESE) events, Figure 6C, both decreased from the original simulation results by 20% and 33%. The most notable difference is exhibited in Figure 6B; the fraction of population moving from the lowest-energy singlet state (i.e., intersystem crossing or ultrafast nonradiative relaxation) and nonradiative relaxation from the triplet state have decreased from ~0.45 to ~0.4 and increased from ~0.35 to ~0.4, respectively..

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Sequence polymorphism in an insect RNA virus field population: A snapshot from a single point in space and time reveals stochastic differences among and within individual hosts

Population structure of Homalodisca coagulata Virus-1 (HoCV-1) among and within field-collected insects sampled from a single point in space and time was examined. Polymorphism in complete consensus sequences among single-insect isolates was dominated by synonymous substitutions. The mutant spectrum of the C2 helicase region within each single-insect isolate was unique and dominated by nonsynonymous singletons. Bootstrapping was used to correct the within-isolate nonsynonymous:synonymous arithmetic ratio (N:S) for RT-PCR error, yielding an N:S value ~one log-unit greater than that of consensus sequences. Probability of all possible single-base substitutions for the C2 region predicted N:S values within 95% confidence limits of the corrected within-isolate N:S when the only constraint imposed was viral polymerase error bias for transitions over transversions. These results indicate that bottlenecks coupled with strong negative/purifying selection drive consensus sequences toward neutral sequence space, and that most polymorphism within single-insect isolates is composed of newly-minted mutations sampled prior to selection. -- Highlights: •Sampling protocol minimized differential selection/history among isolates. •Polymorphism among consensus sequences dominated by negative/purifying selection. •Within-isolate N:S ratio corrected for RT-PCR error by bootstrapping. •Within-isolate mutant spectrum dominated by new mutations yet to undergo selection.

60 APPLIED LIFE SCIENCES↗