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In Schiemann et al. (2017), a mistake occurred in Fig. 11 in how the area-weighted cor-relation and root-mean-square error (RMSE) were calculated. The corrected figure appears below. This has no impact on the interpretation of the figure and on the conclusions of the paper. Any future quantitative comparisons will need to refer to the corrected version of the figure. We regret any inconvenience this may cause.
Recent studies have noted extensive inconsistencies in gene start sites among orthologous genes in related microbial genomes. Here we provide the first documented evidence that imposing gene start consistency improves the accuracy of gene start-site prediction. We applied an algorithm using a genome majority vote (GMV) scheme to increase the consistency of gene starts among orthologs. We used a set of validated Escherichia coli genes as a standard to quantify accuracy. Results showed that the GMV algorithm can correct hundreds of gene prediction errors in sets of five or ten genomes while introducing few errors. Using a conservative calculation, we project that GMV would resolve many inconsistencies and errors in publicly available microbial gene maps. Our simple and logical solution provides a notable advance toward accurate gene maps.
We develop a data-driven framework for learning and correcting nonautonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exhibit inherent model-form uncertainty, motivating the need for data-driven correction. Moreover, nonautonomous dynamics are governed by time-dependent control inputs, which pose challenges in learning predictive models directly from temporal snapshot data. To address these, we reformulate the vehicle dynamics via a local parameterization of the time-dependent inputs, yielding a modified system composed ofa sequence of local parametric dynamical systems. Here, we approximate these parametric systems using two complementary approaches. First, we employ the dimension reduction and interpolation in parameter space (DRIPS) methodology to construct efficient linear surrogate models, equipped with lifted observable spaces and manifold-based operator interpolation. This enables data-efficient learning of vehicle models whose dynamics admit accurate linear representations in the lifted spaces. Second, for more strongly nonlinear systems, we employ flow map learning (FML), a deep neural network (DNN) approach that approximates the parametric evolution map without requiring special treatment of nonlinearities. We further extend FML with a transfer-learning-based model correction procedure, enabling the correction of misspecified prior models using only a sparse set of high-fidelity or experimental measurements, without assuming a prescribed form for the correction term. Through a suite of numerical experiments on unicycle, simplified bicycle, and slip-based bicycle models, we demonstrate that DRIPS offers robust and highly data-efficient learning of nonautonomous vehicle dynamics, while FML provides expressive nonlinear modeling and effective correction of model-form errors under severe data scarcity.
In the past, comparisons between emittance measurements obtained using ionization profile monitors, Vernier scans (using as input the measured rates from the zero degree counters, or ZDCs), the polarimeters and the Schottky detectors evidenced significant variations of up to 100%. In this report we present studies of the RHIC ionization profile monitors (IPMs). After identifying and correcting for two systematic instrumental errors in the beam size measurements, we present experimental results showing that the remaining dominant error in beam emittance measurements at RHIC using the IPMs was imprecise knowledge of the local beta functions. After removal of the systematic errors and implementation of measured beta functions, precise emittance measurements result. Also, consistency between the emittances measured by the IPMs and those derived from the ZDCs was demonstrated.
Passive microwave radiometers (MWRs) are the most commonly used and accurate instruments the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility has to retrieve cloud liquid water path (LWP). The MWR measurements (microwave radiances or brightness temperatures) are often used to derive LWP using climatological constraints, but are frequently also combined with measurements from radar and other instruments for cloud microphysical retrievals. Nominally this latter approach improves the retrieval of LWP and other cloud microphysical quantities (such as effective radius or number concentration), but this also means that when MWR data are poor, other cloud microphysical quantities are also negatively affected. Unfortunately, current MWR data is often contaminated by water on the MWR radome. This water makes a substantial contribution to the measured radiance and typically results in retrievals of cloud liquid water and column water vapor that are biased high. While it is obvious when the contamination by standing water is large (and retrieval biases are large), much of the time it is difficult to know with confidence that there is no contamination. At present there is no attempt to estimate or correct for this source of error, and identification of problems is largely left to users. Typically users are advised to simply throw out all data when the MWR “wet-window” resistance-based sensor indicates water is present, but this sensor is adjusted by hand and is known to be temperamental. In order to address this problem, a pair of ARM microwave radiometers was deployed to the University of Washington (UW) in Seattle, Washington, USA. The radiometers were operated such that one radiometer was scanned under a cover that (nominally) prevents this radiometer radome from gathering water and permits measurements away from zenith; while the other radiometer is operated normally – open or uncovered - with the radome exposed to the sky. The idea is that (1) the covered radiometer data can provide LWP (and water vapor) along the off-zenith slant path and (2) the two sets of measurements can be compared to identify when wet-radome contamination is occurring.
The objective of this report is threefold. First, it details a method for deriving a semi-analytic solution to the Noh Problem when using a “black-box” equation of state. Such capability allows us to perform verification on complicated, more realistic equations of state. Examples include Steinberg equations of state for materials and tabulated equations of state. The second objective is to apply the methodology to verify the singularity-eos equation of state library. We do so by solving the Rankine-Hugoinot jump conditions for the Noh Problem, ensuring singularity derives the correct solution and comparing the error to an exact implementation of the equation of state. The third objective is to perform verification of the xRAGE Eulerian hydrodynamics code when interfaced with singularity. We provide the theory, analysis, documentation for a python implementation of the proposed solver, and verification results.
This work tests a systematic procedure for analyzing data acquired by the Nuclear Materials Identification System (NMIS) at Oak Ridge National Laboratory with fast-neutron imaging and high-purity germanium (HPGe) gamma spectrometry capabilities. NMIS has been under development by the US Department of Energy Office of Nuclear Verification since the mid-1990s, and prior to that by the National Nuclear Security Administration Y-12 National Security Complex, with NMIS having been used at Y-12 for template matching to confirm inventory and receipts. In this present work, a complete set of NMIS time coincidence, fast-neutron imaging, fission mapping, and HPGe gamma-ray spectrometry data was obtained from Monte Carlo simulations for a configuration of fissile and nonfissile materials. The data were then presented for analysis to someone who had no prior knowledge of the unknown object to accurately determine the description of the object by applying the previously mentioned procedure to the simulated data. The best approximation indicated that the unknown object was composed of concentric cylinders: a void inside highly enriched uranium (HEU) (84.7 {+-} 1.9 wt % 235 U), surrounded by depleted uranium, surrounded by polyethylene. The final estimation of the unknown object had the correct materials and geometry, with error in the radius estimates of material regions varying from 1.58% at best and 4.25% at worst; error in the height estimates varied from 2% to 12%. The error in the HEU enrichment estimate was 5.9 wt % (within 2.5Σ of the true value). The accuracies of the determinations could be adequate for arms control applications. Future work will apply this iterative reconstructive procedure to other unknown objects to further test and refine it.
This paper evaluates experiment-based superposition thermal modeling for Laser Powder Bed Fusion (LPBF) with a pulsed laser. An analytical pulsed laser thermal model establishes the modeling procedure. The framework inverts a powder bed’s single pulse temperature response from experimental spatiotemporal Short-Wave Infrared (SWIR) camera data. Superimposing this response along a scan path simulates multi-pulse LPBF. Results show the experimentally informed superposition model rapidly and accurately predicts a layer’s temperature history. The model has applications in correction of thermally driven LPBF errors and in-situ part qualification.
Japan has recently started the technical development of the direct disposal of used nuclear fuel (UNF) to prepare various disposal options. Unlike the disposal of radioactive waste from UNF reprocessing, criticality safety is important here because of the presence of a certain amount of fissile nuclides in UNF. This paper provides an outline of the research to be addressed in this field and the relevant studies in Japan. It especially includes the first result of a criticality safety evaluation of a disposal canister model adopting burnup credit. In this evaluation, it was assumed that a steel disposal canister loaded with fuel assemblies was surrounded by a clay buffer material, and the fuel assemblies and the disposal canister were intact. Conditions representative of discharged pressurized-water reactor (PWR) fuel were applied in this study - initial U-235 enrichment of 4.5 wt% and burnup of 45 GWd/t. The isotopic composition of the burnt fuel was evaluated using SWAT3.1 code. In the depletion calculation, conservative parameters were applied within the typical PWR operation range. The effective neutron multiplication factor (k{sub eff}) was then calculated using a continuous-energy Monte Carlo code MVP-2.0, adopting the JENDL-4.0 nuclear data library. Uncertainty in k{sub eff} due to depletion calculation errors was evaluated using the correction factors of isotopic composition, which were obtained via multiple comparisons between the calculated and measured isotopic concentrations of irradiated fuels. In addition, the effects of axial burnup profile and horizontal burnup gradient on k{sub eff} were evaluated using the open burnup distribution database. The k{sub eff} including the uncertainties and conservatism was found to be below 0.95 for both actinide-only and actinide and fission product considerations when the fuel assemblies and the disposal canister were assumed to be intact. (authors)
Purpose: Six dimensional positional shifts (translational and rotational) determined by a volumetric imaging system were mathematically combined and incorporated as simple translational shifts and the resultant impact on dose characteristics was studied. Methods: Thirty patients who underwent either single fraction (12 Gy) or five fractions (5 Gy per fraction) stereotactic treatments were included in this study. They were immobilized using a double layered thermoplastic mask from BrainLAB. Isocenter matching was done using infrared marker of ExacTrac. An initial cone beam CT (CBCT) gave positional shifts in 6-dimensions that were applied through 6-D motion enabled couch. A verification CBCT was done following corrections before treatment. These 6-D positional shifts determined at each imaging session from the first CBCT were mathematically combined to give three simple translational shifts. Doses were recalculated in the patient matrix with these positional errors present by moving the whole image dataset. Doses were also recalculated after second CBCT with only residual errors present. PTV dose statistics were compared. Results: For the approved plans V100%(PTV), V100%(GTV), D95%(PTV), D95%(GTV), D1%(PTV) and D1%(GTV) were 96.2±3.0%, 98.2±1.4%, 102%±1.7%, 103±1.2%, 107.9±8.9% and 109.3±7.5% of prescription dose respectively. With the positional errors present (after 1st CBCT) the corresponding values were 86.7±4.9%, 91.3±2.9%, 89.6±4.2%, 95.9±3.7%, 108.3±9.9% and 108.6±4.5%. Post-correction (after 2nd CBCT) with only residual errors present, values were 94.5±5.7%, 97.3±2.9%, 99.3%±3.2%, 102%±2.1%, 107.6±8.5% and 109.0±7.6% respectively. Significant and nominal OAR dose variation was observed between pre- and post-table corrections. Conclusion: Positional errors significantly affect PTV dose statistics. They need to be corrected before delivery of stereotactic treatments although the magnitude of dose changes can vary from patient-to-patient depending on the tumor location. As expected after the table corrections, residual errors result in insignificant dose deviations. For frameless stereotactic treatments having a six-dimensional motion enabled couch is highly recommended to reduce quantum of dose deviations.
The ability of first-principles computational methods to reproduce ground-state crystal structure selection is key to their application in the discovery of new materials, and yet presents a formidable challenge due to the low-energy scale of the problem and lack of systematic error cancellation. The recently developed Strongly Constrained and Appropriately Normed (SCAN) functional is notable for accurately calculating physical properties such as formation energies and in particular, correctly predicting ground-state structures. Here in this paper, we attempt to rationalize the improved structure prediction accuracy in SCAN by investigating the relationship between preferred coordination environments, the description of attractive van der Waals (vdW) interactions, and the overall ground-state prediction in bulk main-group solids. We observe a systematic undercoordination error in the traditional Perdew, Burke, and Ernzerhof (PBE) functional which is not present in SCAN results and find that semiempirical dispersion corrections in the form of PBE + D 3 fail to correct this error in a consistent or physical manner. We conclude that the medium-range vdW interaction is correctly parametrized in SCAN and yields meaningful relative energies between coordination environments.
Advancements in computer-controlled polishing, metrology, and replication have led to an x-ray mirror fabrication process that is capable of producing high-resolution Wolter microscopes. Here, we present the fabrication and test of a nickel–cobalt replicated full-shell x-ray mirror that was electroformed from a finely figured and polished mandrel. This mandrel was designed for an 8-m source-to-detector-distance microscope, with 10× magnification, and was optimized to reduce shell distortions that occur within 20 mm of the shell ends. This, in combination with an improved replication tooling design and refined bath parameters informed by a detailed COMSOL Multiphysics® model, has led to reductions in replication errors in the mirrors. Mandrel surface fabrication was improved by implementing a computer-controlled polishing process that corrected the low-frequency mandrel figure error and achieved <2.0 nm RMS convergence error. X-ray tests performed on a pair of mirror shells replicated from the mandrel have demonstrated <10 μm full-width at half-maximum (FWHM) spatial resolution. Here, we discuss the development process, highlight results from metrology and x-ray testing, and define a path for achieving a program goal of 5 μm FWHM resolution.
The wavelength dependence of atmospheric refraction causes elongation of finite-bandwidth images along the elevation vector, which produces spurious signals in weak gravitational lensing shear measurements unless this atmospheric dispersion is calibrated and removed to high precision. Because astrometric solutions and PSF characteristics are typically calibrated from stellar images, differences between the reference stars' spectra and the galaxies' spectra will leave residual errors in both the astrometric positions (dr) and in the second moment (width) of the wavelength-averaged PSF (dv) for galaxies.We estimate the level of dv that will induce spurious weak lensing signals in PSF-corrected galaxy shapes that exceed the statistical errors of the DES and the LSST cosmic-shear experiments. We also estimate the dr signals that will produce unacceptable spurious distortions after stacking of exposures taken at different airmasses and hour angles. We also calculate the errors in the griz bands, and find that dispersion systematics, uncorrected, are up to 6 and 2 times larger in g and r bands,respectively, than the requirements for the DES error budget, but can be safely ignored in i and z bands. For the LSST requirements, the factors are about 30, 10, and 3 in g, r, and i bands,respectively. We find that a simple correction linear in galaxy color is accurate enough to reduce dispersion shear systematics to insignificant levels in the r band for DES and i band for LSST,but still as much as 5 times than the requirements for LSST r-band observations. More complex corrections will likely be able to reduce the systematic cosmic-shear errors below statistical errors for LSST r band. But g-band effects remain large enough that it seems likely that induced systematics will dominate the statistical errors of both surveys, and cosmic-shear measurements should rely on the redder bands.
Most ocean data assimilation systems are tuned to process and assimilate observations to constrain features on the order of the mesoscale and larger. Typically this involves removal of observations or computing averaged observations. This procedure, while necessary, eliminates many observations from the analysis step and can reduce the overall effectiveness of a particular observing platform. Simply including these observations is not an option as doing so can produce an overdetermined, ill-conditioned problem that is more difficult to solve. An approach, presented here, aims to avoid such issues while at the same time increasing the number of observations within the assimilation. A two-step assimilation procedure with the four-dimensional variational data assimilation (4DVAR) system is adopted. The first step attempts to constrain the large-scale features by assimilating a set of super observations with appropriate background error correlation scales and error variances. The second step then attempts to correct smaller-scale features by assimilating the full observation set with shorter background error correlation scales and appropriate error variances; here the background state is taken as the analysis from the first step. Results using a real high-density observation set from underwater gliders in the region southeast of Iceland, collected during the 2017 Nordic Recognized Environmental Picture (NREP) experiment, will be shown using the Navy Coastal Ocean Model 4DVAR (NCOM-4DVAR).
We report an experimental determination of the diamagnetic correction to the {sup 9}Be{sup +} ground state hyperfine constant A. We measured A = -625 008 837.371(11) Hz at a magnetic field B of 4.4609 T. Comparison with previous results, obtained at lower values of B (0.68 T and 0.82 T), yields the diamagnetic shift coefficient k = 2.63(18)x10{sup -11} T{sup -2}, where A(B)=A{sub 0}(1+kB{sup 2}). The zero-field hyperfine constant A{sub 0} is determined to be -625 008 837.044(12) Hz. The g-factor ratio g{sub I}{sup '}/g{sub J} is determined to be 2.134 779 852 7(10)x10{sup -4}, which is equal to the value measured at lower B to within experimental error. Upper limits are placed on some other corrections to the Breit-Rabi formula. The measured value of k agrees with theoretical estimates.
Purpose: The purpose of this study was to verify clinical target volume–planning target volume (CTV-PTV) margins in single vocal cord irradiation (SVCI) of T1a larynx tumors and characterize inter- and intrafraction target motion. Methods and Materials: For 42 patients, a single vocal cord was irradiated using intensity modulated radiation therapy at a total dose of 58.1 Gy (16 fractions × 3.63 Gy). A daily cone beam computed tomography (CBCT) scan was performed to online correct the setup of the thyroid cartilage after patient positioning with in-room lasers (interfraction motion correction). To monitor intrafraction motion, CBCT scans were also acquired just after patient repositioning and after dose delivery. A mixed online-offline setup correction protocol (“O2 protocol”) was designed to compensate for both inter- and intrafraction motion. Results: Observed interfraction, systematic (Σ), and random (σ) setup errors in left-right (LR), craniocaudal (CC), and anteroposterior (AP) directions were 0.9, 2.0, and 1.1 mm and 1.0, 1.6, and 1.0 mm, respectively. After correction of these errors, the following intrafraction movements derived from the CBCT acquired after dose delivery were: Σ = 0.4, 1.3, and 0.7 mm, and σ = 0.8, 1.4, and 0.8 mm. More than half of the patients showed a systematic non-zero intrafraction shift in target position, (ie, the mean intrafraction displacement over the treatment fractions was statistically significantly different from zero; P<.05). With the applied CTV-PTV margins (for most patients 3, 5, and 3 mm in LR, CC, and AP directions, respectively), the minimum CTV dose, estimated from the target displacements observed in the last CBCT, was at least 94% of the prescribed dose for all patients and more than 98% for most patients (37 of 42). The proposed O2 protocol could effectively reduce the systematic intrafraction errors observed after dose delivery to almost zero (Σ = 0.1, 0.2, 0.2 mm). Conclusions: With adequate image guidance and CTV-PTV margins in LR, CC, and AP directions of 3, 5, and 3 mm, respectively, excellent target coverage in SVCI could be ensured.
Purpose: To implement an entire workflow quality assurance (QA) process in the radiotherapy department and to reduce the error rates of radiotherapy based on the entire workflow management in the developing country. Methods: The entire workflow QA process management starts from patient registration to the end of last treatment including all steps through the entire radiotherapy process. Error rate of chartcheck is used to evaluate the the entire workflow QA process. Two to three qualified senior medical physicists checked the documents before the first treatment fraction of every patient. Random check of the treatment history during treatment was also performed. A total of around 6000 patients treatment data before and after implementing the entire workflow QA process were compared from May, 2014 to December, 2015. Results: A systemic checklist was established. It mainly includes patient’s registration, treatment plan QA, information exporting to OIS(Oncology Information System), documents of treatment QAand QA of the treatment history. The error rate derived from the chart check decreases from 1.7% to 0.9% after our the entire workflow QA process. All checked errors before the first treatment fraction were corrected as soon as oncologist re-confirmed them and reinforce staff training was accordingly followed to prevent those errors. Conclusion: The entire workflow QA process improved the safety, quality of radiotherapy in our department and we consider that our QA experience can be applicable for the heavily-loaded radiotherapy departments in developing country.
Electronic structure methods based on low-order “n-body” expansions are an increasingly popular means to defeat the highly nonlinear scaling of ab initio quantum chemistry calculations, taking advantage of the inherently distributable nature of the numerous subsystem calculations. Here, we examine how the finite precision of these subsystem calculations manifests in applications to large systems, in this case, a sequence of water clusters ranging in size up to (H{sub 2}O){sub 47}. Using two different computer implementations of the n-body expansion, one fully integrated into a quantum chemistry program and the other written as a separate driver routine for the same program, we examine the reproducibility of total binding energies as a function of cluster size. The combinatorial nature of the n-body expansion amplifies subtle differences between the two implementations, especially for n ⩾ 4, leading to total energies that differ by as much as several kcal/mol between two implementations of what is ostensibly the same method. This behavior can be understood based on a propagation-of-errors analysis applied to a closed-form expression for the n-body expansion, which is derived here for the first time. Discrepancies between the two implementations arise primarily from the Coulomb self-energy correction that is required when electrostatic embedding charges are implemented by means of an external driver program. For reliable results in large systems, our analysis suggests that script- or driver-based implementations should read binary output files from an electronic structure program, in full double precision, or better yet be fully integrated in a way that avoids the need to compute the aforementioned self-energy. Moreover, four-body and higher-order expansions may be too sensitive to numerical thresholds to be of practical use in large systems.