Erratum: “Energies of the X- and L-valleys in In{sub 0.53}Ga{sub 0.47}As from electronic structure calculations” [J. Appl. Phys. 119, 055707 (2016)]
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VALID continues as a library of high-quality models used for testing SCALE and nuclear data. Recent expansion of VALID was the largest impactful change in a decade. Adding 233 U experiments circa 2017 added more cases. There are a huge number of cases in the pipeline, but a lack of qualified staff and funding to complete reviews. Future plans should simplify the process and increase the availability of models and results for external users.
The author has identified the following significant results. Iron deficient and normal grain sorghum plants were sufficiently different spectrally in ERTS-1 band 5 CCT data to detect chlorotic sorghum areas 2.8 acres (1.1 hectares) or larger in size in computer printouts of the MSS data. The ratio of band 5 to band 7 or band 7 minus band 5 relates to vegetation ground cover conditions and helps to select training samples representative of differing vegetation maturity or vigor classes and to estimate ground cover or green vegetation density in the absence of ground information. The four plant parameters; leaf area index, plant population, plant cover, and plant height explained 87 to 93% of the variability in band 6 digital counts and from 59 to 90% of the variation in bands 4 and 5. A ground area 2244 acres in size was classified on a pixel by pixel basis using simultaneously acquired aircraft support and ERTS-1 data. Overall recognition for vegetables, immature crops and mixed shrubs, and bare soil categories was 64.5% for aircraft and 59.6% for spacecraft data, respectively. Overall recognition results on a per field basis were 61.8% for aircraft and 62.8% for ERTS-1 data.
This paper presents diagnostic data obtained from the plume of a graphite composite target during carbon nanotube production by the double-pulse laser oven method. The insitu emission spectrum (300 to 650 nm) is recorded at different locations upstream of the target and at different delay times from the lasers (IR and green). Spectral features are identified as emissions from C2 (Swan System: a (sup 3)pi(sub g) - delta (sup 3)pi(sub u) and C3 (Comet Head System: A (sup 1)pi(sub u) - chi (sup 1)sigma(sub u) (sup +). Experimental spectra are compared with computed spectra to estimate vibrational temperatures of excited state C2 in the range of 2500 to 4000 kappa The temporal evolution of the 510 nm band of C2 is monitored for two target positions in various locations which shows confinement of the plume in the inner tube and increase in plume velocity with temperature. The excitation spectra of C2 are obtained by using a dye laser to pump the (0,1) transition of the Swan System and collecting the Laser Induced Fluorescence signal from C2 These are used to obtain "ground-state" rotational and vibrational temperatures which are close to the oven temperature. Images of the plume are also collected and are compared with the spectral measurements.
An analysis of the longitudinal aerodynamics of the Shuttle Orbiter in the hypersonic flight regime is made through the use of computational fluid dynamics (CFD). Particular attention is given to establishing the cause of the 'pitching moment anomaly' which occurred on the Orbiter's first flight and to computing the aerodynamics of a complete Orbiter configuration at flight conditions. Data from ground based facilities as well as Orbiter flight data are used to validate the computed results. Analysis shows that the 'pitching moment anomaly' is a real gas chemistry effect which cannot be simulated in ground-based facilities. Computed flight aerodynamics for the Orbiter are within 5 percent of the measured flight values and trim bodyflap deflections are predicted to within 10 percent.
This paper focuses on the parallel computation of aerodynamic derivatives via automatic differentiation of the Euler/Navier-Stokes solver CFL3D. The comparison with derivatives obtained by finite differences is presented and the scaling of the time required to obtain the derivatives relative to the number of processors employed for the computation is shown. Finally, the derivative computations are coupled with an optimizer and surface/volume grid deformation tools to perform an optimization to reduce the drag of a three-dimensional wing.
Rotating view of a chromochloris zofingiensis cell dividing into 16 cells from cryo-soft X-ray tomography of a reconstructed cell with segmented nucleus (purple), chloroplast (green), mitochondria (red), lipids (yellow), and starch granules within the chloroplast (blue). Credit: Melissa Roth/HHMI and Andreas Walters/Berkeley Lab News story - https://newscenter.lbl.gov/2017/05/19/green-algae-genome/
This award supports one post-doctoral researcher for 1.5 years. Publications that acknowledge this grant: Refs. 1–14. Refs. 3,10,12 assess current methodology for the evaluation of magnetic exchange couplings in transition metal complexes. In particular, Ref. 10 validates the use of an approximate (non-iterative) Green’s function approach for the calculation of magnetic exchange couplings and will be the foundation for Thrust 2 in this proposal. Refs. 3 and 12 focus on widely used density functional approaches based on the standard energy differences methodology for the particular case of oxo-bridged Fe(III) complexes. Refs. 2,4–7,11 apply current methodologies to problems of practical interest in molecular magnetism. Ref. 13 presents a methodology to explicitly simulate the dynamics of open quantum systems within density functional theory (DFT) calculations based on the Liouville-von Neumann equation of motion for quantum systems driven out-of-equilibrium. Ref. 8 uses non-collinear spin DFT to explain the mechanical behavior of magnetic mono-atomic Pt wires produced in break-junction experiments in the presence of a magnetic field.
First- and second-order accurate numerical methods, implemented for CPUs, underpin the majority of industrial CFD solvers. Whilst this technology has proven very successful at solving steady-state problems via a Reynolds Averaged Navier–Stokes approach, its utility for undertaking scale-resolving simulations of unsteady flows is less clear. High-order methods for unstructured grids and GPU accelerators have been proposed as an enabling technology for unsteady scale-resolving simulations of flow over complex geometries. In this study we systematically compare accuracy and cost of the high-order Flux Reconstruction solver PyFR running on GPUs and the industry-standard solver STAR-CCM+ running on CPUs when applied to a range of unsteady flow problems. Specifically, we perform comparisons of accuracy and cost for isentropic vortex advection (EV), decay of the Taylor–Green vortex (TGV), turbulent flow over a circular cylinder, and turbulent flow over an SD7003 aerofoil. We consider two configurations of STAR-CCM+: a second-order configuration, and a third-order configuration, where the latter was recommended by CD-adapco for more effective computation of unsteady flow problems. Results from both PyFR and STAR-CCM+ demonstrate that third-order schemes can be more accurate than second-order schemes for a given cost e.g. going from second- to third-order, the PyFR simulations of the EV and TGV achieve 75× and 3× error reduction respectively for the same or reduced cost, and STAR-CCM+ simulations of the cylinder recovered wake statistics significantly more accurately for only twice the cost. Moreover, advancing to higher-order schemes on GPUs with PyFR was found to offer even further accuracy vs. cost benefits relative to industry-standard tools.
Experimental measurements and computer simulation of secondary electron emission coefficients for FEP-Teflon, for normal and oblique incidence in the presence of a normal electric field are reported. Knowledge of the electrostatic environment surrounding the specimen calculation of particle trajectories are considered. A simulation using a conformal mapping, a Green's integral, and a trajectory generator provides the necessary mathematical support for the measurements which have been made with normal fields of 1.5 and 2.7 kV/mm. When incidence is normal and energy exceeds the critical energy, the coefficient is given by V.58 and for oblique incidence this expression may be divided by the cosine of the angle. The parameter V sub 0 is a function of normal field. Measurements for values of V sub f are presented.
The structure of unstable planetary waves is computed by a quasi-geostrophic model extending from the surface up to 80 km by means of eigenvalue-eigenfunction techniques in spherical coordinates. Three kinds of unstable modes of distinct phase speeds and vertical structures are identified in the winter climate state: (1) the deep Green mode with its maximum amplitude in the stratosphere; (2) the deep Charney mode with its maximum amplitude in the troposphere: and (3) the shallow Charney mode which is largely confined to the troposphere. Both the Green mode and the deep Charney mode are characterized by very slow phase speeds. They are mainly supported by upward wave energy fluxes, but the local baroclinic energy conversion within the stratosphere also contributes in supporting these deep modes. The mesosphere and the troposphere are dynamically independent in the summer season decoupled by the deep stratospheric easterly. The summer mesosphere supports the easterly unstable waves 1-4. Waves 3 and 4 are identified with the observed mesospheric 2-day wave and 1.7-day wave, respectively.
Corotating energetic ion populations (CEIPs) associated with the forward and reverse shocks of corotating interaction regions (CIRs) are observed in CIRs at places where models say are magnetically unconnected to either shock. Such disconnections between CEIPs and shocks are common and have been documented with data from Pioneers 10 and 11 and confirmed with data from Ulysses. They pose a problem for models that account for these CEIPs in terms of ion energization at the shocks followed by ion propagation along field lines. Two possible resolutions to this problem have been suggested: diffusion of the ions across field lines and extension of the ion energization process to regions beyond the shock waves. Here we quantitatively examine the first of these possibilities. We give the Green's function solution to the convection-diffusion equation applied to idealized CIR geometry, with a source at the reverse shock -- the main producer of CEIPs. Two kinds of diffusion are considered: resonant diffusion and stochastic field line diffusion. We find that for resonant diffusion the computed ratio is many orders of magnitudes below the observed ratio. For stochastic field line diffusion, the computed ratio approximately equals the observed ratio if a diffusion coefficient appropriate to the free solar wind is used. It is several orders of magnitude below the observed ratio, however, if a diffusion coefficient appropriate to CIRs is used. We conclude that cross-field diffusion probably does not account for the presence of energetic ions in regions of CIRs that are magnetically unconnected to its shock waves. We suggest that the alternative possibility -- the energetic ions in regions magnetically unconnected to shocks result from an acceleration process that is independent of shocks -- be pursued to the point where quantitative tests can be performed.
Proteins interact to form protein complex to carry out biological functions such as catalytic chemical reaction. Therefore, it is important to develop computational methods to predict protein-protein interaction and the structures of protein complexes to study and enhance protein function. In this project, we successfully developed several deep learning methods to predict inter-protein contacts and the reinforcement learning and optimization methods to reconstruct protein complex structures from predicted inter-chain contacts. The methods were integrated with the MULTICOM protein complex structure prediction system and applied to predict the complex structures of biomass production-related proteins of green algae. During the two and a half years of research and development, all the specific milestones of the project were achieved successfully. 16 publications/manuscripts were produced. 10 software tools were developed. A patent application was submitted. Our MULTICOM predictors leveraging some tools developed in this project were ranked among the top predictors in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022.
Methods for downstream river flow prediction can be categorized into physics-based and empirical approaches. Although based on well-studied physical relationships, physics-based models rely on numerous hydrologic variables characteristic of the specific river system that can be costly to acquire. Moreover, simulation is often computationally intensive. Conversely, empirical models require less information about the system being modeled and can capture a system’s interactions based on a smaller set of observed data. This article introduces two empirical methods to predict downstream hydraulic variables based on observed stream data: a linear programming (LP) model, and a convolutional neural network (CNN). We apply both empirical models within the Colorado River system to a site located on the Green River, downstream of the Yampa River confluence and Flaming Gorge Dam, and compare it to the physics-based model Streamflow Synthesis and Reservoir Regulation (SSARR) currently used by federal agencies. Results show that both proposed models significantly outperform the SSARR model. Moreover, the CNN model outperforms the LP model for hourly predictions whereas both perform similarly for daily predictions. Although less accurate than the CNN model at finer temporal resolution, the LP model is ideal for linear water scheduling tools.
A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1.
We derive equations of motion for higher order density response functions using the theory of thermodynamic Green’s functions. We also derive expressions for the higher order generalized dielectric functions and polarization functions. Moreover, we relate higher order response functions and higher order collision integrals within the Martin–Schwinger hierarchy. We expect our results to be highly relevant to the study of a variety of quantum many-body systems such as matter under extreme temperatures, densities, and pressures.
Here, we develop a method to construct a microscopic optical potential from chiral interactions for nucleon-nucleus scattering. The optical potential is constructed by combining the Green’s function approach with the coupled-cluster method. To deal with the poles of the Green’s function along the real energy axis we employ a Berggren basis in the complex energy plane combined with the Lanczos method. Using this approach, we perform a proof-of-principle calculation of the optical potential for the elastic neutron scattering on 16 O. For the computation of the ground-state of 16 O, we use the coupled-cluster method in the singles-and-doubles approximation, while for the A ±1 nuclei we use particle-attached/removed equation-of-motion method truncated at two-particle-one-hole and one-particle-two-hole excitations, respectively. We verify the convergence of the optical potential and scattering phase shifts with respect to the model-space size and the number of discretized complex continuum states. We also investigate the absorptive component of the optical potential (which reflects the opening of inelastic channels) by computing its imaginary volume integral and find an almost negligible absorptive component at low-energies. To shed light on this result, we computed excited states of 16 O using equation-of-motion coupled-cluster method with singles-and- doubles excitations and we found no low-lying excited states below 10 MeV. Furthermore, most excited states have a dominant two-particle-two-hole component, making higher-order particle-hole excitations necessary to achieve a precise description of these core-excited states. We conclude that the reduced absorption at low-energies can be attributed to the lack of correlations coming from the low-order cluster truncation in the employed coupled-cluster method.
Purpose: Head and neck (H&N) internal organ motion has previously been determined with low frequency and temporary nature based on population-based pre- and post-treatment studies. Using immobilization masks and adding a 4–6 mm planning-tumor-volume margin, geometric uncertainties of patients are routinely considered clinically inconsequential in H&N radiotherapy. Using the first commercially-available MR-IGRT system, we conducted the first quantitative study on inter-patient, intra- and inter-fractional H&N internal motion patterns to evaluate the necessity of individualized asymmetric internal margins. Methods: Ninety cine sagittal MR image sequences were acquired during the entire treatment course (6–7 weeks) of three H&N cancer patients using the ViewRay™ MR-IGRT system. The images were 5 mm thick and acquired at 4 frames/per second. One of the patients had a tracheostomy tube. The cross-sectional H&N airway (nasopharynx, oropharynx, and laryngopharynx portions) movement was analyzed comprehensively using in-house developed motion detection software. Results: Large inter-patient variations of swallowing frequency (0–1 times/per fraction), swallowing duration (1–3 seconds), and pharyngeal cross-sectional area (238–2516 mm2) were observed. Extensive pharyngeal motion occurred during swallowing, while nonzero and periodic change of airway geometry was observed in resting. For patient 1 with tracheostomy tube replacement, 30.3%, 30.0%, 48.7% and 0.3% of total frames showed ≥ 4 mm displacements in the anterior, posterior, inferior, and superior airway boundaries, respectively; similarly, (5.7%, 0.0%, 0.0%, 0.3%) and (23.3%, 0.0%, 35.7%, 1.7%) occurred for patients 2 and 3. Area overlapping coefficients with respect to the first frame were 76.3+/−6.4%, 90.3+/−0.6%, and 92.3+/−1.2% for the three patients, respectively. Conclusion: Both the resting and swallowing motions varied in frequency and amplitude among the patients and across fractions of a patient’s treatment. Patients receiving surgery that alters their respiratory and swallowing behavior can have significant intra-fractional internal motion. Patient-specific organ/tumor motion analysis may yield individualized asymmetric internal margins and improve the therapeutic ratio.