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NASA NTRS1994

Dust extinction and molecular gas in the dark cloud IC 5146

In this paper we describe a powerful method for mapping the distribution of dust through a molecular cloud using data obtained in large-scale, multiwavelength, infrared imaging surveys. This method combines direct measurements of near-infrared color excess and certain techniques of star counting to derive mean extinctions and map the dust column density distribution through a cloud at higher angular resolutions and greater optical depths than those achieved previously by optical star counting. We report the initial results of the application of this method to a dark cloud complex near the cluster IC 5146, where we have performed coordinated, near-infrared, JHK imaging and (13)CO, C(18)O, and CS millimeter-wave, molecular-line surveys of a large portion of the complex. More than 4000 stars were detected in our JHK survey of the cloud. Of these, all but about a dozen appear to be field stars not associated with the cloud. Star count maps at J band show a striking and detailed anticorrelation between the surface density of J-band sources and CO and CS molecular-line emission. We used the (H-K) colors and positions of nearly 1300 sources to directly measure and map the extinction and thus trace the dust column density through the cloud at an effective angular resolution of 1 min .5. We report an interesting correlation between the measured dispersion in our extinction determinations and the extinction. Modeling this relation indicates that effects of small-scale cloud structure dominate the uncertainties in our measurements. Moreover, we demonstrate that such observations can be used to place constraints on the nature of the spatial distribution of extinction on scales smaller than our resolution. In particular, we show that models in which the dust is distributed uniformly or in discrete high-extinction clumps on scales smaller than (1 min .5) are inconsistent with the observations. We have derived extinctions at the same positions and at the same angular resolution (1 min .7) as our molecular-line observations. This enabled a direct comparison of (13)CO, C(18)O, and CS integrated intensities and column densities with A(sub V) for more than 500 positions in the cloud, corresponding to a range in A(sub V) between 0 to 32 mag of extinction. We found the integrated intensities of (13)CO, C(18)O, and CS to be roughly linearly correlated with extinction over different ranges of extinction. However, for all three molecules we find the scatter in the observed relations to be larger than can be accounted for by instrumental error, suggesting that there are large intrinsic variations in the abundances or excitation of the molecules through the cloud. Mean abundances for all the molecules relative to hydrogen were directly derived from the data. The ratio of (13)CO to C(18)O abundances was found to be significantly higher than the terrestrial ratio in regions where extinction is less than 10 mag. In the same region, the dispersion in the abundance ratio is also found to be very large, suggesting that the abundances of one or both molecules are very unstable even at relatively large cloud optical depths. Beyond 10 mag of extinction the abundances of both species appear very stable with their ratio close to the terrestrial value.

Lada, Charles J.↗
DOE OSTI2023

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

Machine learning (ML) models, and Long Short-Term Memory (LSTM) networks in particular, have demonstrated remarkable performance in streamflow prediction and are increasingly being used by the hydrological research community. However, most of these applications do not include uncertainty quantification (UQ). ML models are data driven and can suffer from large extrapolation errors when applied to changing climate/environmental conditions. UQ is required to quantify the influence of data noises on model predictions and avoid overconfident projections in extrapolation. In this work, we integrate a novel UQ method, called PI3NN, with LSTM networks for streamflow prediction. PI3NN calculates Prediction Intervals by training 3 Neural Networks. It can precisely quantify the predictive uncertainty caused by the data noise and identify out-of-distribution (OOD) data in a non-stationary condition to avoid overconfident predictions. We apply the PI3NN-LSTM method in the snow-dominant East River Watershed in the western US and in the rain-driven Walker Branch Watershed in the southeastern US. Results indicate that for the prediction data which have similar features as the training data, PI3NN precisely quantifies the predictive uncertainty with the desired confidence level; and for the OOD data where the LSTM network fails to make accurate predictions, PI3NN produces a reasonably large uncertainty indicating that the results are not trustworthy and should avoid overconfidence. PI3NN is computationally efficient, robust in performance, and generalizable to various network structures and data with no distributional assumptions. It can be broadly applied in ML-based hydrological simulations for credible prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Linear Combination of Atomic Dipoles to Calculate the Bond and Molecular Dipole Moments of Molecules and Molecular Liquids

Here we report a linear combination of atomic dipole (LCAD) method for calculating the bond dipole moments of molecules. We show that the LCAD method reproduces the known molecular dipole moments of small to large molecules with a small error with respect to experimental and benchmark ab initio calculations, and molecular dipole distributions of bulk water that agree with maximally localized Wannier functions. The bond dipole moments derived from LCAD are also chemically interpretable in terms of the trend in bond ionicity in going from neutral to charged molecules. Moreover, the LCAD method accurately captures the influence of electric fields, supported by the correct trend in the change of the dipole moment under a uniform external electric field. The better grounding of bond dipole calculations indicates that it should also serve as a useful approach to bond dipole-field models used in catalysis or to reconstruct the small dipole of a H-terminated graphene flake.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Space Station flexible dynamics under plume impingement

Assembly of the Space Station requires numerous construction flights by the Space Shuttle. A particularly challenging problem is that of control of each intermediate station configuration when the shuttle orbiter is approaching it to deliver the next component. The necessary braking maneuvers cause orbiter thruster plumes to impinge on the station, especially its solar arrays. This in turn causes both overall attitude errors and excitation of flexible-body vibration modes. These plume loads are predicted to lead to CMG saturation during the approach of the orbiter to the SC-5 station configuration, necessitating the use of the station RCS jets for desaturation. They are also expected to lead to significant excitation of solar array vibrations. It is therefore of great practical importance to investigate the effects of plume loads on the flexible dynamics of station configuration SC-5 as accurately as possible. However, this system possesses a great many flexible modes (89 below 5 rad/s), making analysis time-consuming and complicated. Model reduction techniques can be used to overcome this problem, reducing the system model to one which retains only the significant dynamics, i.e. those which are strongly excited by the control inputs or plume disturbance forces and which strongly couple with the measured outputs. The particular technique to be used in this study is the subsystem balancing approach which was previously developed by the present investigator. This method is very efficient computationally. Furthermore, it gives accurate results even for the difficult case where the structure has many closed-spaced natural frequencies, when standard modal truncation can give misleading results. Station configuration SC-5 is a good example of such a structure.

Williams, Trevor↗
NASA NTRS1995

Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR images in synoptic modes are used to generate the parameter maps. The maps are then combined to generate mosaic maps over the BOREAS modeling grid.

Saatchi, Sasan↗
DOE OSTI2021

Modeling Liquid Water by Climbing up Jacob’s Ladder in Density Functional Theory Facilitated by Using Deep Neural Network Potentials

Within the framework of Kohn–Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately normed (SCAN) functional has been extensively demonstrated in recent years. Here, we further advance the modeling of water by building a more accurate model on the fourth rung of Jacob’s ladder with the hybrid functional, SCAN0. In particular, we carry out both classical and Feynman path-integral molecular dynamics calculations of water with the SCAN0 functional and the isobaric–isothermal ensemble. To generate the equilibrated structure of water, a deep neural network potential is trained from the atomic potential energy surface based on ab initio data obtained from SCAN0 DFT calculations. For the electronic properties of water, a separate deep neural network potential is trained by using the Deep Wannier method based on the maximally localized Wannier functions of the equilibrated trajectory at the SCAN0 level. The structural, dynamic, and electric properties of water were analyzed. The hydrogen-bond structures, density, infrared spectra, diffusion coefficients, and dielectric constants of water, in the electronic ground state, are computed by using a large simulation box and long simulation time. For the properties involving electronic excitations, we apply the GW approximation within many-body perturbation theory to calculate the quasiparticle density of states and bandgap of water. Compared to the SCAN functional, mixing exact exchange mitigates the self-interaction error in the meta-generalized-gradient approximation and further softens liquid water toward the experimental direction. For most of the water properties, the SCAN0 functional shows a systematic improvement over the SCAN functional. However, some important discrepancies remain. The H-bond network predicted by the SCAN0 functional is still slightly overstructured compared to the experimental results.

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

The H I absorption zoo: JVLA extension to z ~ 0.4

Here, we present an H I 21 cm absorption study of a sample of 26 radio-loud active galactic nuclei (AGN) at 0.25 < z < 0.4 carried out with the Karl G. Jansky Very Large Array. Our aim was to study the rate of incidence of H I in different classes of radio AGN, the morphology and kinematics of the detected H I, and the nature of the interaction between the H I and the radio source at these redshifts. Our sample consists of 14 sources with sizes of up to tens of kpc and 12 compact sources (< a few kpc) in the radio-power range 10 25.7 W Hz –1 –10 26.5 W Hz –1 . We detect H I in five sources, corresponding to a detection rate of ~19%. Within the error bars, this agrees with the detection rate found at lower redshifts. We find that the rest-frame UV luminosities of most of the sources in the sample, including all the detections, are below the proposed threshold above which the H I is supposed to have been ionised. An analysis of the optical emission-line spectra of the sources shows that despite their high radio powers, about one-third of the sample, including two detections, are low-ionisation sources. The radio continuum emission from the sources detected in H I is unresolved at ~5 to 10 kpc scales in our observations, but shows extended structure on parsec scales. We analysed the H I 21 cm absorption spectra of the detections to understand the morphology and kinematics of H I. The absorption profiles are mostly complex with widths between the nulls ranging from ~60 km s –1 to 700 km s –1 . These detections also exhibit remarkably high H I column densities in the range ~10 21 cm –2 –10 22 cm –2 for T spin = 100 K and unit covering factor. Our modelling of the H I 21 cm absorption profiles suggests that in two sources the gas appears to be disturbed, and in three cases, including one with disturbed H I, the majority of the absorption is consistent with it arising from an H I disc. Despite the high radio power of our sources, we do not detect fast outflows. However, the optical emission lines in these detections show the presence of significantly disturbed gas in the nuclear regions in the form of very wide and highly blueshifted emission-line components. Since some of our detections are also low-ionisation AGN, it is quite possible that this disturbance is caused by the radio jets. Overall, our findings point towards a continuation of the low-z trends in the H I detection rate and the incidence of H I in radio AGN up to z ~ 0.4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Analyzing rotational bands in odd-mass nuclei using effective field theory and Bayesian methods

We recently developed an Effective Field Theory (EFT) for rotational bands in odd-mass nuclei. Here we use EFT expressions to perform a Bayesian analysis of data on the rotational energy levels of 99 Tc, 155,157 Gd, 159 Dy, 167,169 Er, 167,169 Tm, 183 W, 235 U and 239 Pu. The error model in our Bayesian analysis includes both experimental and EFT truncation uncertainties. It also accounts for the fact that low-energy constants (LECs) at even and odd orders are expected to have different sizes. We use Markov Chain Monte Carlo (MCMC) sampling to explore the joint posterior of the EFT and error-model parameters and show both the LECs and the breakdown scale can be reliably determined. We extract the LECs up to fourth order in the EFT and find that, provided we correctly account for EFT truncation errors in our likelihood, results for lower-order LECs are stable as we go to higher orders. LEC results are also stable with respect to the addition of higher-energy data. We extract the expansion parameter for all the nuclei listed above and find a clear correlation between the extracted and the expected value of the inverse breakdown scale, W, based on the single-particle and vibrational energy scales. However, the W that actually determines the convergence of the EFT expansion is markedly smaller than would be naively expected based on those scales.

EFT↗
NASA NTRS2001

Diagnosing Tropical Divergent Circulations From Satellite-Derived Diabatic Forcing and Variational Integral Constraints

Large-scale divergent circulations are part of the atmospheric dynamic response to diabatic heating from condensation, radiative processes, and surface energy fluxes. Vertical motion and the associated divergent wind is thus intimately tied to the hydrologic cycle and the global beat balance. Despite its importance, the divergent circulation is too small in comparison to the rotational flow to measure directly with any accuracy. Vertical motions are recovered diagnostically from reanalyses and, as such, are subject to shortcomings in model physics, numerics, and data availability. While reanalysis estimates of tropical divergent circulations are much improved over those from the Global Weather Experiment, there are still substantial differences between products from operational centers. This is because these circulations are still forced largely by model physics and only secondarily by observations. In order to produce a refined estimate of tropical divergence and its interannual variability we have used a number of remotely-sensed data sets along with variational constraints to improve upon reanalysis estimates. Among these are: precipitation from SSM/I and GPCP, TOVS Path-A vertical cloud distributions; ISCCP radiative cooling rates; TOA radiative fluxes from ERBS, surface radiative fluxes from the SRB project, and surface latent and sensible flux estimates from SSM/I. The TOVS Path-A data constrain the divergent outflow in precipitating regions to have the same vertical structure as observed cloudiness. Using integral constraints for moisture, heat, and mass balance, we retrieve consistent divergent wind flows. We examine the ability of this type analysis to capture regional details of ENSO related perturbations to the divergent wind and associated tropical energy balance. Precipitation from satellite is found to be the major constraint in supplying this horizontal structure. We also consider the ability of this analysis to quantify integrated (land vs. ocean) fluctuations in the global monsoonal flow and energy balance. This depends, of course, on the error characteristics of the data constraints. Some estimate of these properties and their relative importance is provided.

Robertson, Franklin R.↗
NASA NTRS2003

XMM-Newton and Chandra Observations of the Galaxy Group NGC 5044: Evidence for Limited Multiphase Hot Gas - 1

Using new XMM and Chandra observations, we present an analysis of the temperature structure of the hot gas within a radius of 100 kpc of the bright nearby galaxy group NGC 5044. A spectral deprojection analysis of data extracted from circular annuli reveals that a two-temperature model (2T) of the hot gas is favored over single-phase or cooling flow (M = 4.5 +/- 0.2 solar mass/yr) models within the central approx.30 kpc. Alternatively, the data can be fitted equally well if the temperature within each spherical shell varies continuously from approx.T(sub h) to T(sub c) approx. T(sub h)/2, but no lower. The high spatial resolution of the Chandra data allows us to determine that the temperature excursion T(sub h) approaches T(sub c) required in each shell exceeds the temperature range between the boundaries of the same shell in the best-fitting single-phase model. This is strong evidence for a multiphase gas having a limited temperature range. We do not find any evidence that azimuthal temperature variations within each annulus on the sky can account for the range in temperatures within each shell. We provide a detailed investigation of the systematic errors on the derived spectral models considering the effects of calibration, plasma codes, bandwidth, variable NH, and background rate. We find that the RGS gratings and the EPIC and ACIS CCDs give fully consistent results when the same models are fitted over the same energy ranges for each instrument. The cooler component of the 2T model has a temperature (T(sub c) approx. 0.7 keV) similar to the kinetic temperature of the stars. The hot phase has a temperature (T(sub h) approx. 1.4 keV) characteristic of the virial temperature of the solar mass halo expected in the NGC 5044 group. However, in view of the morphological disturbances and X-ray holes visible in the Chandra image within R approx. equals 10 kpc, bubbles of gas heated to approx.T(sub h) in this region may be formed by intermittent AGN feedback. Some additional heating at larger radii may be associated with the evolution of the cold front near R approx. 50 kpc, as suggested by the sharp edge in the EPIC images. Subject headings: cooling flows - galaxies: formation - galaxies: halos - intergalactic medium - X-rays: galaxies: clusters

Buote, David A.↗
DOE OSTI2024

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources

Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. To quantify motion blur, a 1D shock wave through PMMA was investigated experimentally at The Dynamic Compression Sector at The Advanced Photon Source (DCS@APS) with tapered broadband and 25.46 ± 1.06 keV narrowband X-rays. Four cameras with different exposure times were used for each experiment to compare the effect that exposure time has on motion blur. In addition, our methodology to accurately simulate motion blur in terms of transmission and shape is presented and compared to our experimental results and quantified. There is a high level of agreement between the experimental and simulation results across the range of data sets investigated in this study with a percent difference range of 0.29–1.31% for the four shots. The methodology of this work serves as a steppingstone towards a physically validated model that could be used in conjunction with experimental results to deconvolve physical parameters, densities, and interfaces of interest in a way that would not be possible with experimental results alone.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Iterative metal artifact reduction for x-ray computed tomography using unmatched projector/backprojector pairs

Purpose: Metal artifact reduction (MAR) is a major problem and a challenging issue in x-ray computed tomography (CT) examinations. Iterative reconstruction from sinograms unaffected by metals shows promising potential in detail recovery. This reconstruction has been the subject of much research in recent years. However, conventional iterative reconstruction methods easily introduce new artifacts around metal implants because of incomplete data reconstruction and inconsistencies in practical data acquisition. Hence, this work aims at developing a method to suppress newly introduced artifacts and improve the image quality around metal implants for the iterative MAR scheme. Methods: The proposed method consists of two steps based on the general iterative MAR framework. An uncorrected image is initially reconstructed, and the corresponding metal trace is obtained. The iterative reconstruction method is then used to reconstruct images from the unaffected sinogram. In the reconstruction step of this work, an iterative strategy utilizing unmatched projector/backprojector pairs is used. A ramp filter is introduced into the back-projection procedure to restrain the inconsistency components in low frequencies and generate more reliable images of the regions around metals. Furthermore, a constrained total variation (TV) minimization model is also incorporated to enhance efficiency. The proposed strategy is implemented based on an iterative FBP and an alternating direction minimization (ADM) scheme, respectively. The developed algorithms are referred to as “iFBP-TV” and “TV-FADM,” respectively. Two projection-completion-based MAR methods and three iterative MAR methods are performed simultaneously for comparison. Results: The proposed method performs reasonably on both simulation and real CT-scanned datasets. This approach could reduce streak metal artifacts effectively and avoid the mentioned effects in the vicinity of the metals. The improvements are evaluated by inspecting regions of interest and by comparing the root-mean-square errors, normalized mean absolute distance, and universal quality index metrics of the images. Both iFBP-TV and TV-FADM methods outperform other counterparts in all cases. Unlike the conventional iterative methods, the proposed strategy utilizing unmatched projector/backprojector pairs shows excellent performance in detail preservation and prevention of the introduction of new artifacts. Conclusions: Qualitative and quantitative evaluations of experimental results indicate that the developed method outperforms classical MAR algorithms in suppressing streak artifacts and preserving the edge structural information of the object. In particular, structures lying close to metals can be gradually recovered because of the reduction of artifacts caused by inconsistency effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Modeling receptor flexibility in the structure-based design of KRAS G12C inhibitors

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus Clouds Based on Three-Dimensional Path-Tracing

The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high-resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi-dimensional spatial information. In this study, a path-tracing algorithm is used to generate virtual camera images of resolved clouds in large-eddy simulations (LES). These images are then used as a camera network simulator, allowing reconstructions of three-dimensional cloud edges from the model output. Because the actual LES cloud field is fully known, the combined path-tracing and reconstruction method can be statistically analyzed. The method is applied to LES realizations of summertime shallow cumulus at the Jülich Observatory for Cloud Evolution (JOYCE), Germany, which also routinely operates a camera network. We find that the path-tracing method allows accurate reconstruction of up to 70% of the visible cloud edges. Additional sensitivity tests show that the method is robust for changes in its hyperparameters. The sensitivity to cloud optical thickness is also investigated, finding a cloud boundary placement error of approximately 182 m. This error can be considered typical for cloud boundary reconstruction using real stereo camera imagery. The results provide proof of principle for future use of the method for evaluating LES clouds against camera network imagery, and for further optimizing the configuration of such camera networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

How does a probe inserted into the discharge influence the plasma structure?

Shielding the bias applied to the probe by the sheath formed around it and determination of parameters of unperturbed plasmas are in the basis of the probe diagnostics. The results from a two-dimensional model of a discharge with a probe inserted in it show that the probe influences the spatial distribution of the plasma parameters in the entire discharge. The increase (although slight) in the electron temperature, due to the increased losses of charged particles on the additional wall in the discharge (mainly the probe holder), leads to redistribution of the plasma density and plasma potential, as shown by the results obtained at the floating potential of the probe. The deviations due to the bias applied to the probe tip are stronger in the ion saturation region of the probe characteristics. The pattern of the spatial redistribution of the plasma parameters advances together with the movement of the probe deeper in the discharge. Although probe sheaths and probe characteristics resulting from the model are shown, the study does not aim at discussions on the theories for determination of the plasma density from the ion saturation current. Regardless of the modifications in the plasma behavior in the entire discharge, the deviations of the plasma parameters at the position of the probe tip and, respectively, the uncertainty which should be added as an error when the accuracy of the probe diagnostics is estimated do not exceed 10%. Consequently, the electron density and temperature obtained, respectively, at the position of the plasma potential on the probe characteristics and from its transition region are in reasonable agreement with the results from the model of the discharge without a probe. Being in the scope of research on a source of negative hydrogen ions with the design of a matrix of small radius inductive discharges, the model is specified for a low-pressure hydrogen discharge sustained in a small-radius tube.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Neutrino Flavor Model Building and the Origins of Flavor and CP Violation

The neutrino sector offers one of the most sensitive probes of new physics beyond the Standard Model of Particle Physics (SM). The mechanism of neutrino mass generation is still unknown. The observed suppression of neutrino masses hints at a large scale, conceivably of the order of the scale of a rand unified theory (GUT), which is a unique feature of neutrinos that is not shared by the charged fermions. The origin of neutrino masses and mixing is part of the outstanding puzzle of fermion masses and mixings, which is not explained ab initio in the SM. Flavor model building for both quark and lepton sectors is important in order to gain a better understanding of the origin of the structure of mass hierarchy and flavor mixing, which constitute the dominant fraction of the SM parameters. Recent activities in neutrino flavor model building based on non-Abelian discrete flavor symmetries and modular flavor symmetries have been shown to be a promising direction to explore. The emerging models provide a framework that has a significantly reduced number of undetermined parameters in the flavor sector. In addition, such a framework affords a novel origin of CP violation from group theory due to the intimate connection between physical CP transformation and group theoretical properties of non-Abelian discrete groups. Model building based on non-Abelian discrete flavor symmetries and their modular variants enables the particle physics community to interpret the current and anticipated upcoming data from neutrino experiments. Non-Abelian discrete flavor symmetries and their modular variants can result from compactification of a higher-dimensional theory. Pursuit of flavor model building based on such frameworks thus also provides the connection to possible UV completions: in particular, to string theory. We emphasize the importance of constructing models in which the uncertainties of theoretical predictions are smaller than, or at most compatible with, the error bars of measurements in neutrino experiments. While there exist proof-of-principle versions of bottom-up models in which the theoretical uncertainties are under control, it is remarkable that the key ingredients of such constructions were discovered first in top-down model building. We outline how a successful unification of bottom-up and top-down ideas and techniques may guide us towards a new era of precision flavor model building in which future experimental results can give us crucial insights into the UV completion of the SM.

Almumin, Yahya (ORCID:0000000196396772)↗