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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Main and Satellite Features in the Ni 2p XPS of NiO

The origin and assignment of the complex main and satellite XPS features of the cations in ionic compounds has been the subject of extensive theoretical studies using different methods. There is agreement that within a molecular orbital model one needs to take into account different types of configurations. Specifically, those where a core electron is removed but no other configuration changes are made and those where in addition to ionization there are also shake or charge transfer changes to the ionic configuration. However, there are strong disagreements about the assignment of XPS features to these configurations. The present work is directed toward resolving the origin of main and satellite features for the Ni 2p XPS of NiO based on ab initio molecular orbital wavefunctions for a cluster model of NiO. A major problem in earlier ab initio XPS studies of ionic compounds has been the use of a common set of orbitals that was not able to properly describe all the ionic configurations that contribute to the full XPS spectra. This is resolved in the present work by using orbitals that are optimized for averages of the occupations of the different configurations that contribute to the XPS. The approach of using State Averaged orbitals is validated through comparisons between different averages and through use of higher order excitations in the wavefunctions for the ionic states. It represents a major extension of our earlier work on the main and satellite features of the Fe 2p XPS of Fe 2 O 3 and proves the reliability and the generality of the assignments of the character and origin of the different features of the XPS obtained with orbitals optimized for State Averages. These molecular orbital methods permit the characterization of the ionic states in terms of the importance of shake excitations and of the coupling of ionization of 2p 1/2 and 2p 3/2 spin-orbit split sub shells. Further, the work lays the foundation for definitive assignments of the character of main and satellite XPS features and points to their origin in the electronic structure of the material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Overview of the Morphology and Chemistry of Diagenetic Features in the Clay-Rich Glen Torridon Unit of Gale Crater, Mars

The clay-rich Glen Torridon region of Gale crater, Mars, was explored between sols 2300 and 3007. Here, we analyzed the diagenetic features observed by Curiosity, including veins, cements, nodules, and nodular bedrock, using the ChemCam, Mastcam, and Mars Hand Lens Imager instruments. We discovered many diagenetic features in Glen Torridon, including dark-toned iron- and manganese-rich veins, magnesium- and fluorine-rich linear features, Ca-sulfate cemented bedrock, manganese-rich nodules, and iron-rich strata. We have characterized the chemistry and morphology of these features, which are most widespread in the higher stratigraphic members in Glen Torridon, and exhibit a wide range of chemistries. These discoveries are strong evidence for multiple generations of fluids from multiple chemical endmembers that likely underwent redox reactions to form some of these features. In a few cases, we may be able to use mineralogy and chemistry to constrain formation conditions of the diagenetic features. For example, the dark-toned veins likely formed in warmer, highly alkaline, and highly reducing conditions, while manganese-rich nodules likely formed in oxidizing and circumneutral conditions. We also hypothesize that an initial enrichment of soluble elements, including fluorine, occurred during hydrothermal alteration early in Gale crater history to account for elemental enrichment in nodules and veins. The presence of redox-active elements, including Fe and Mn, and elements required for life, including P and S, in these fluids is strong evidence for habitability of Gale crater groundwater. Hydrothermal alteration also has interesting implications for prebiotic chemistry during the earliest stages of the crater’s evolution and early Mars.

58 GEOSCIENCES↗
DOE OSTI2022

Classical cosmological collider physics and primordial features

Features in the inflationary landscape can inject extra energies to inflation models and produce on-shell particles with masses much larger than the Hubble scale of inflation. This possibility extends the energy reach of the program of cosmological collider physics, in which signals associated with these particles are generically Boltzmann-suppressed. Here we study the mechanisms of this classical cosmological collider in two categories of primordial features. In the first category, the primordial feature is classical oscillation, which includes the case of coherent oscillation of a massive field and the case of oscillatory features in the inflationary potential. The second category includes any sharp feature in the inflation model. All these classical features can excite unsuppressed quantum modes of other heavy fields which leave observational signatures in primordial non-Gaussianities, including the information about the particle spectra of these heavy degrees of freedom.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation

Graph convolutional networks leverage both graph structures and features on nodes and edges for improved learning performance in comparison with classical machine learning approaches. Spiking neuromorphic computers natively implement network-like computation and have been shown to be successful at implementing graph learning without features. Incorporating graph features brings the challenge of efficient feature representation and balancing the contribution of topology and features in learning. In this work, we present our design of a simulated network of spiking neurons to perform semi-supervised learning on graph data using both the graph structure and the node features. We explore various design choices, present preliminary results, and discuss the opportunities for using neuromorphic computers for this task in the future.

Cong, Guojing↗
DOE OSTI2025

A Flang Plugin for Fortran Feature Characterization

As new compute systems are developed, there is still a need to compile and execute codes authored in Fortran on these leading edge systems. In order to achieve this, development of compilers that support the latest hardware is continuously under development. Though the specification of Fortran is extensive, it is helpful to compiler authors to be able to prioritize the development of key features in order to get certain codes deemed important, e.g., applications of interest to leadership computing facilities, executable on leading edge compute systems. Identifying key features though is largely done through querying software experts or users of the Fortran applications of interest, who then manually report what features are and are not present. This exercise can both time consuming and error prone. To automate this process, we present a compiler plugin to Flang, the Fortran frontend for LLVM. This plugin is a tool that operates on the parse tree representation generated by Flang and detects key features based on walking parse tree nodes that correspond to features of interest. We show the result of our tool on four applications, three of which were manually profiled by software experts. We show the discrepancies between our tool and the manual characterization of the three applications, as well as generate a characterization for an application not yet profiled. We intend to open-source our tool in order to invite the community to benefit from the tool and make contributions for other features.

Cabrera, Anthony [ORNL]↗
DOE OSTI2023

Evaluating generative networks using Gaussian mixtures of image features

We develop a measure for evaluating the performance of generative networks given two sets of images. A popular performance measure currently used to do this is the Fréchet Inception Distance (FID). However, FID assumes that images featurized using the penultimate layer of Inception follow a Gaussian distribution. This assumption allows FID to be easily computed, since FID uses the 2-Wasserstein distance of two Gaussian distributions fitted to the featurized images. However, we show that Inception features of the ImageNet dataset are not Gaussian; in particular, each marginal is not Gaussian. To remedy this problem, we model the featurized images using Gaussian mixture models (GMMs) and compute the 2-Wasserstein distance restricted to GMMs. We define a performance measure, which we call WaM, on two sets of images by using inception (or another classifier) to featurize the images, estimate two GMMs, and use the restricted 2-Wasserstein distance to compare the GMMs. We experimentally show the advantages of WaM over FID, including how FID is more sensitive than WaM to image perturbations. By modelling the non-Gaussian features obtained from inception as GMMs and using a GMM metric, we can more accurately evaluate generative network performance.

machine learning, genrative adversarial networks↗
DOE OSTI2022

Multi-head attention-based U-Nets for predicting protein domain boundaries using 1D sequence features and 2D distance maps

Abstract The information about the domain architecture of proteins is useful for studying protein structure and function. However, accurate prediction of protein domain boundaries (i.e., sequence regions separating two domains) from sequence remains a significant challenge. In this work, we develop a deep learning method based on multi-head U-Nets (called DistDom) to predict protein domain boundaries utilizing 1D sequence features and predicted 2D inter-residue distance map as input. The 1D features contain the evolutionary and physicochemical information of protein sequences, whereas the 2D distance map includes the structural information of proteins that was rarely used in domain boundary prediction before. The 1D and 2D features are processed by the 1D and 2D U-Nets respectively to generate hidden features. The hidden features are then used by the multi-head attention to predict the probability of each residue of a protein being in a domain boundary, leveraging both local and global information in the features. The residue-level domain boundary predictions can be used to classify proteins as single-domain or multi-domain proteins. It classifies the CASP14 single-domain and multi-domain targets at the accuracy of 75.9%, 13.28% more accurate than the state-of-the-art method. Tested on the CASP14 multi-domain protein targets with expert annotated domain boundaries, the average per-target F1 measure score of the domain boundary prediction by DistDom is 0.263, 29.56% higher than the state-of-the-art method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Ranking Biological Features in Soil-Based Microbial Multi-Omics Data with Integration Modeling

Distinguishing the most important features (e.g. proteins, metabolites, etc.) per group (e.g. control and treatment) is a critical challenge in feature-rich multi-omics experiments, especially in soil data. Traditional feature identification and ranking approaches, such as differential expression, are based on single omics and thus not directly translatable to multi-omics experiments. Here, 5 multi-omics integration models (DIABLO, JACA, MOFA, MultiMLP, and SLIDE) that were not explicitly built for soil data applications were tested using a soil-based multi-omics experiment. The data were obtained from an experimental setup of an autoclaved soil system inoculated with 8 bacteria and using chitin as the carbon source and including samples collected at 0- (control), 4-, 8-, and 12-weeks post-inoculation. The omics data included metaproteomics, 16S rRNA sequencing, and LC-MS/MS metabolomics (in positive and negative mode). Each multi-omics integration model was implemented, and top features were compared to differential univariate statistics per omic type, demonstrating that integration approaches cut the potential number of top features from 2957 identified by differential statistics to 13-224 (a 99.6% to 92.4% reduction). Interestingly, most top features across integration models were not shared; though, scaling and averaging ranks across models shared similar patterns. This work highlights the usefulness of multi-omics integration models in soil-based microbial studies and the power of using multiple integration models together to interpret results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

DELVE-ing into the Milky Way’s Globular Clusters: Assessing Extratidal Features in NGC 5897, NGC 7492, and Testing Detectability with Deeper Photometry

Extratidal features around globular clusters (GCs) are tracers of their disruption, stellar stream formation, and their host’s gravitational potential. However, these features remain challenging to detect due to their low surface brightness. We conduct a systematic search for such features around 19 GCs in the DECam Local Volume Exploration (DELVE) survey Data Release 2, discovering a new extra-tidal envelope around NGC 5897 and find tentative evidence for an extended envelope surrounding NGC 7492. Through a combination of dynamical modeling and analyzing synthetic stellar populations, we demonstrate these envelopes may have formed through tidal disruption. We use these models to explore the detectability of these features in the upcoming Legacy Survey of Space and Time (LSST), finding that while LSST’s deeper photometry will enhance detection significance, additional methods for foreground removal like proper motions or metallicities may be important for robust stream detection. Our results both add to the sample of globular clusters with extratidal features and provide insights on interpreting similar features in current and upcoming data.

Chiti, A. [Univ. of Chicago, IL (United States); S↗
NASA NTRS1973

Recognition of beach and nearshore depositional features of Chesapeake Bay

Beach and nearshore depositional features are being mapped with the objectives of determining a quick-look analysis of littoral drift and sedimentation patterns in areas of little or no data. Evaluation of beach and nearshore features aid in the selection of small boat harbors, shoreline protective structures, and general coastal zone development. Through ERTS-1 aircraft support imagery, beach depositional features mapped are cuspate forelands, welded beach ridges, and recurved spits. The nearshore depositional features exhibit a bar and trough topography with three distinct types of sedimentary structures; longshore, transverse, and reticulated bars. Synoptic coverage of beach and nearshore depositional features by ERTS-1 data help in determining the general sedimentation patterns, growth of the beach features and stability of the bar and trough topography.

Kerhin, R. T.↗
NASA NTRS1975

An algorithm for optimal single linear feature extraction from several Gaussian pattern classes

A computational algorithm is presented for the extraction of an optimal single linear feature from several Gaussian pattern classes. The algorithm minimizes the increase in the probability of misclassification in the transformed (feature) space. Numerical results on the application of this procedure to the remotely sensed data from the Purdue Cl flight line as well as LANDSAT data are presented. It was found that classification using the optimal single linear feature yielded a value for the probability of misclassification on the order of 30% less than that obtained by using the best single untransformed feature. Also, the optimal single linear feature gave performance results comparable to those obtained by using the two features which maximized the average divergence.

Starks, S. A.↗
NASA NTRS1976

A new computer approach to mixed feature classification for forestry application

A computer approach for mapping mixed forest features (i.e., types, classes) from computer classification maps is discussed. Mixed features such as mixed softwood/hardwood stands are treated as admixtures of softwood and hardwood areas. Large-area mixed features are identified and small-area features neglected when the nominal size of a mixed feature can be specified. The computer program merges small isolated areas into surrounding areas by the iterative manipulation of the postprocessing algorithm that eliminates small connected sets. For a forestry application, computer-classified LANDSAT multispectral scanner data of the Sam Houston National Forest were used to demonstrate the proposed approach. The technique was successful in cleaning the salt-and-pepper appearance of multiclass classification maps and in mapping admixtures of softwood areas and hardwood areas. However, the computer-mapped mixed areas matched very poorly with the ground truth because of inadequate resolution and inappropriate definition of mixed features.

Kan, E. P.↗
NASA NTRS1978

On the append and continue features in NASTRAN

The APPEND feature is described which is applicable in the case of real eigenvalue analysis. This feature permitted the addition of new eigenvalues and eigenvectors to those already computed in a previously checkpointed run without re-executing the entire problem. The next feature was the CONTINUE feature which was applicable in the case of transient analysis of coupled equations. This feature enabled the integration of coupled equations to be continued beyond the last output time for which the solution was obtained in a previously checkpointed run (without re-executing the entire problem). These two features are illustrated by suitable examples.

Pamidi, P. R.↗
NASA NTRS1977

Faint emission features in the Mg II resonance-line wings

Data obtained with a rocket-borne echelle spectrograph are presented which indicate the presence of three faint emission features deep in the cores of the Mg II h and k resonance-line wings in the solar Fraunhofer spectrum. Results of wavelength measurements are discussed, and the relative intensities of the emission features are examined. It is tentatively suggested that the first feature be identified with the Fe II line at 2797.037 A, the second feature is probably the V II line at 2803.469 A, and the third feature may originate in Fe II emission at 2804.021 A. Possible emission mechanisms are proposed, and it is concluded that the detected features may be of potential diagnostic value for the analysis of depth variations of temperature and velocity in the lower chromosphere as well as for solar and possibly stellar spectroscopy.

Allen, M. S.↗
NASA NTRS1980

On the congruent feature in NASTRAN

The congruent feature, which is a capability in NASTRAN that can contribute to significant increases in computational efficiencies, is discussed. The usage of the capability and the software design characteristics affecting it are explained. The factors affecting the efficiency of the feature are pointed out. The details pertaining to the software design of the congruent feature are presented; in particular, the congruent element table is described. Serveral examples employing the congruent feature are considered and comparisons of Element Matrix Generator module computer program update times with and without this feature are presented. The results clearly demonstrate the role of the congruent feature in increasing computational efficiencies and its applicability to large-size problems.

Pamidi, P. R.↗
NASA NTRS1980

Excitation mechanisms for the unidentified infrared emission features

Infrared and radio observations of various objects are analyzed to put observational constraints on the mechanism which gives rise to the unidentified emission features at 3.3, 3.4, 6.2, 7.7, 8.6, and 11.3 microns. The results show that gas-grain collisions or fluorescence is not likely to be the excitation mechanism responsible for the observed features. Thermal emission by dust is reanalyzed and it is concluded that this mechanism can explain the emission features. A simple model in which the emission features arise in a population of small, hot, interstellar grains is constructed. These grains are very efficient radiators, and the emitting materials only need be a minor grain constituent to provide the power that is emitted in the features. The model offers, therefore, a simple explanation for the absence of these features in absorption.

Dwek, E.↗
NASA NTRS1985

Permafrost features on Earth and Mars: Similarities, differences

Typical permafrost features on Earth are polygonal structures, pingos and soli-/gelifluxion features. In areas around the poles and in mountain ranges the precipitation accumulates to inland ice or ice streams. On Mars the same features were identified: polygonal features cover the larger part of the northern lowlands indicating probably an ice wedge-/sand wedge system or desiccation cracks. These features indicate the extend of large mud accumulations which seem to be related to large outflow events of the chaotic terrains. The shore line of this mud accumulation is indicated by a special set of relief types. In some areas large pingo-like hills were identified. In the vicinity of the largest martian volcano, Olympus Mons, the melting of underlying permafrost and/or ground ice led to the downslope sliding of large parts of the primary shield which formed the aureole around Olympus Mons. Glacier-like features are identified along the escarpment which separates the Southern Uplands from the Northern Lowlands.

Joens, H. P.↗
NASA NTRS1988

Topological numbering of features on a mesh

Assume a nxn binary image is given containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. The problem of assigning topological numbers to such features is considered; i.e., assign a number to every feature f so that all features to the left of f have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. A parallel algorithm to solve the topological numbering problem in O(n) time on an nxn mesh of processors is presented. The key idea of the solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.

Atallah, Mikhail J.↗