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DOE OSTI2019

Transverse wobbling in an even-even nucleus

Two new bands built on the two-quasiparticle $π(h_{11/2})^2$ configuration of the even-even nucleus 130 Ba are investigated using constrained triaxial covariant density functional theory combined with quantum particle rotor model calculations. The energy difference between the two bands, as well as the available electromagnetic transition probabilities $B(M1)_{\text{out}}/B(E2)_{\text{in}}$ and $B(E2)_{\text{out}}/B(E2)_{\text{in}}$, are well reproduced. In this work, the analysis of the angular momentum geometry reveals that the higher band represents transverse wobbling motion of a two-quasiparticle configuration. This is the first example of two-quasiparticle wobbling bands in an even-even nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Topological Interpretability for Deep Learning

With the growing adoption of AI-based systems across everyday life, the need to understand their decision-making mechanisms is correspondingly increasing. The level at which we can trust the statistical inferences made from AI-based decision systems is an increasing concern, especially in high-risk systems such as criminal justice or medical diagnosis, where incorrect inferences may have tragic consequences. Despite their successes in providing solutions to problems involving real-world data, deep learning (DL) models cannot quantify the certainty of their predictions. These models are frequently quite confident, even when their solutions are incorrect. This work presents a method to infer prominent features in two DL classification models trained on clinical and non-clinical text by employing techniques from topological and geometric data analysis. We create a graph of a model's feature space and cluster the inputs into the graph's vertices by the similarity of features and prediction statistics. We then extract subgraphs demonstrating high-predictive accuracy for a given label. These subgraphs contain a wealth of information about features that the DL model has recognized as relevant to its decisions. We infer these features for a given label using a distance metric between probability measures, and demonstrate the stability of our method compared to the LIME and SHAP interpretability methods. This work establishes that we may gain insights into the decision mechanism of a DL model. This method allows us to ascertain if the model is making its decisions based on information germane to the problem or identifies extraneous patterns within the data.

Spannaus, Adam↗

DOE OSTI2024

Forcing data (CESM2/CMIP6) for projection of drought impacts (2015-2100) at the K34 site in Manaus, Brazil

Historical and projected output data variables extracted and derived from Community Earth System Model 2 (CESM2) runs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. CESM2 is a fully coupled Earth system model used in simulations of Earth's past, present, and future climates (Danabasoglu et al., 2020). Variables in this dataset are in six-hourly resolution, and include air temperature (both in K and ℃), specific humidity (kg kg-1), air pressure (Pa), relative humidity (%), and vapor pressure deficit (kPa). CESM2 was the only CMIP6 model that provided VPD at the high temporal resolution required for this analysis. Data are included in .csv files, and the text file CESM2-CMIP6_forcing_K34-Manaus_headers.txt provides descriptions of data file headers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Atomic Weights No Longer Constants of Nature

Many of us grew up being taught that the standard atomic weights we found in the back of our chemistry textbooks or on the Periodic Table of the Chemical Elements hanging on the wall of our chemistry classroom are constants of nature. This was common knowledge for more than a century and a half, but not anymore. The following text explains how advances in chemical instrumentation and isotopic analysis has changed the way we view atomic weights and why they are no longer constants of nature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2011

PhyCA-PhyloChip Analysis

PhyCA allows interpretation of a PhyloChip assay. It takes as input, a text file containing the fluorescent intensity from each feature on the microarray surface. PhyCA will determine the background and noise levels, compare probes against controls and determine response scores for each probe pair. It then summarizes a set of probe pair results to determine presence of an operational taxonomic unit as well as its abundance. The PhyCA software is novel from other microarray interpretation software from the following reasons: 1) It leverages spiked-in Quantitative Standards and non-spike-in Negative Controls to build a per-chip model of positive and non-positive responses. 2) It allows a refinement of Presence/Absence calls by evaluating each responding probe against a putative cross-hybridization network. 3) It can be used with phylogenetic microarrays designed for Bacteria, Archaea or Eukaryotes. Hardware req.: PC, MAC; Software req.: OS: Windows, Mac, Linux; Types of files: source code, control information; user guide. The software depends on other software to be installed on the same machine as PhyCA.

Desantis, Todd↗

NASA NTRS1992

User's manual for MacPASCO

A user's manual is presented for MacPASCO, which is an interactive, graphic, preprocessor for panel design. MacPASCO creates input for PASCO, an existing computer code for structural analysis and sizing of longitudinally stiffened composite panels. MacPASCO provides a graphical user interface which simplifies the specification of panel geometry and reduces user input errors. The user draws the initial structural geometry and reduces user input errors. The user draws the initial structural geometry on the computer screen, then uses a combination of graphic and text inputs to: refine the structural geometry; specify information required for analysis such as panel load and boundary conditions; and define design variables and constraints for minimum mass optimization. Only the use of MacPASCO is described, since the use of PASCO has been documented elsewhere.

Lucas, S. H.↗

DOE OSTI2019

Search for rare decays of $\mathrm {Z}$ and Higgs bosons to ${\mathrm {J}/\psi } $ and a photon in proton-proton collisions at $\sqrt{s}$ = 13 $\,\text {TeV}$

Here, a search is presented for decays of $\mathrm {Z}$ and Higgs bosons to a ${\mathrm {J}/\psi } $ meson and a photon, with the subsequent decay of the ${\mathrm {J}/\psi } $ to $\mathrm {\mu ^+}\mathrm {\mu ^-} $ . The analysis uses data from proton-proton collisions with an integrated luminosity of 35.9 $\,\text {fb}^{-1}$ at $\sqrt{s}=13\,\text {TeV} $ collected with the CMS detector at the LHC. The observed limit on the $\mathrm {Z}\rightarrow {\mathrm {J}/\psi } \gamma $ decay branching fraction, assuming that the ${\mathrm {J}/\psi } $ meson is produced unpolarized, is $1.4\times 10^{-6}$ at 95% confidence level, which corresponds to a rate higher than expected in the standard model by a factor of 15. For extreme-polarization scenarios, the observed limit changes from $-13.6$ to $+8.6\%$ with respect to the unpolarized scenario. The observed upper limit on the branching fraction for $\mathrm {H} \rightarrow {\mathrm {J}/\psi } \gamma $ where the ${\mathrm {J}/\psi } $ meson is assumed to be transversely polarized is $7.6\times 10^{-4}$ , a factor of 260 larger than the standard model prediction. The results for the Higgs boson are combined with previous data from proton-proton collisions at $\sqrt{s}=8\,\text {TeV} $ to produce an observed upper limit on the branching fraction for $\mathrm {H} \rightarrow {\mathrm {J}/\psi } \gamma $ that is a factor of 220 larger than the standard model value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Modification of Ni-20Cr corrosion dealloying behavior in molten fluorides via cold work induced plastic deformation

The corrosion dealloying behavior of cold-worked (CW) Ni20Cr alloy (wt%) was studied in molten LiF-NaF-KF (or FLiNaK) salts at 600 °C, equal to a homologous temperature (TH) of 0.52. Alloys were cold-rolled to achieve reductions of thickness of 10%, 30%, and 50% introducing plastic deformation and a high density of dislocations. Potentiostatic holds (Eapplied) were applied in two different electrode potential regimes. At 1.75VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, Cr dealloying to Cr(II) and Cr(III) is predominant, while at 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, both Ni and Cr are oxidized in molten FLiNaK at 600 °C. In these potential regimes, dealloyed Ni20Cr displayed bicontinuous porosity within the grain interior and at grain boundaries, driven by the high driving force for Cr dissolution and sustained by defect mediated outward solid state diffusion of Cr in parallel with surface diffusion of Ni. The bicontinuous porous structure developed was observed to undergo further coarsening and densification of the Ni-rich ligaments at a higher electrode potential. The main effect of CW observed is the introduction of plastic deformation and dislocation substructures that serve as short-circuit paths for Cr solid state diffusion to surfaces exposed to FLiNaK. This modified the evolution of the bicontinuous porous structure which increased with CW substantially. Kinetic analysis reveals that the Cr dealloying at +1.75 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$ and 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$ is initially charge transfer controlled, except for the 50% CW condition at 1.90 VK+/K$${\text{V}}_{{\text{K}}^{+}/{\text{K}}}$$, where the process becomes limited by slow Cr defect mediated bulk diffusion. The rate determining factors are explored and compared to experimental results.

Chan, Ho Lun↗

NASA NTRS2009

Semantic Theme Analysis of Pilot Incident Reports

Pilots report accidents or incidents during take-off, on flight and landing to airline authorities and Federal aviation authority as well. The description of pilot reports for an incident contains technical terms related to Flight instruments and operations. Normal text mining approaches collect keywords from text documents and relate them among documents that are stored in database. Present approach will extract specific theme analysis of incident reports and semantically relate hierarchy of terms assigning weights of themes. Once the theme extraction has been performed for a given document, a unique key can be assigned to that document to cross linking the documents. Semantic linking will be used to categorize the documents based on specific rules that can help an end-user to analyze certain types of accidents. This presentation outlines the architecture of text mining for pilot incident reports for autonomous categorization of pilot incident reports using semantic theme analysis.

Thirumalainambi, Rajkumar↗

NASA NTRS1990

Solar Astronomy Data Base: Packaged Information on Diskette

In its role as a library, the National Geophysical Data Center has transferred to diskette a collection of small, digital files of routinely measured solar indices for use on an IBM-compatible desktop computer. Recording these observations on diskette allows the distribution of specialized information to researchers with a wide range of expertise in computer science and solar astronomy. Every data set was made self-contained by including formats, extraction utilities, and plain-language descriptive text. Moreover, for several archives, two versions of the observations are provided - one suitable for display, the other for analysis with popular software packages. Since the files contain no control characters, each one can be modified with any text editor.

Mckinnon, John A.↗

NASA NTRS2014

Complete Decoding and Reporting of Aviation Routine Weather Reports (METARs)

Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.

METAR Decoder/Parser↗

DOE OSTI2021

Core Mass Estimates in Strong Lensing Galaxy Clusters Using a Single-halo Lens Model

The core mass of galaxy clusters is an important probe of structure formation. Here we evaluate the use of a single-halo model (SHM) as an efficient method to estimate the strong lensing cluster core mass, testing it with ray-traced images from the Outer Rim simulation. Unlike detailed lens models, the SHM represents the cluster mass distribution with a single halo and can be automatically generated from the measured lensing constraints. In this work we find that the projected core mass estimated with this method, $M_{\text{SHM}}$, has a scatter of 8.52% and a bias of 0.90% compared to the "true" mass within the same aperture. Our analysis shows no systematic correlation between the scatter or bias and the lens-source system properties. The bias and scatter can be reduced to 3.26% and 0.34%, respectively, by excluding models that fail a visual inspection test. We find that the SHM success depends on the lensing geometry, with single giant arc configurations accounting for most of the failed cases due to their limiting constraining power. When excluding such cases, we measure a scatter and bias of 3.88% and 0.84%, respectively. Finally, we find that when the source redshift is unknown, the model-predicted redshifts are overestimated, and the $M_{\text{SHM}}$ is underestimated by a few percent, highlighting the importance of securing spectroscopic redshifts of background sources. Our analysis provides a quantitative characterization of $M_{\text{SHM}}$, enabling its efficient use as a tool to estimate the strong lensing cluster core masses in the large samples, expected from current and future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Search for a heavy pseudoscalar boson decaying to a Z and a Higgs boson at $\sqrt{s}=13\,\text {Te}\text {V}$

A search is presented for a heavy pseudoscalar boson $\text {A}$ decaying to a Z boson and a Higgs boson with mass of 125 $\,\text {GeV}$ . In the final state considered, the Higgs boson decays to a bottom quark and antiquark, and the Z boson decays either into a pair of electrons, muons, or neutrinos. The analysis is performed using a data sample corresponding to an integrated luminosity of 35.9 $\,\text {fb}^{-1}$ collected in 2016 by the CMS experiment at the LHC from proton–proton collisions at a center-of-mass energy of 13 $\,\text {Te}\text {V}$ . The data are found to be consistent with the background expectations. Exclusion limits are set in the context of two-Higgs-doublet models in the $\text {A}$ boson mass range between 225 and 1000 $\,\text {GeV}$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2010

Multimedia Analysis plus Visual Analytics = Multimedia Analytics

Multimedia analysis has focused on images, video, and to some extent audio and has made progress in single channels excluding text. Visual analytics has focused on the user interaction with data during the analytic process plus the fundamental mathematics and has continued to treat text as did its precursor, information visualization. The general problem we address in this tutorial is the combining of multimedia analysis and visual analytics to deal with multimedia information gathered from different sources, with different goals or objectives, and containing all media types and combinations in common usage.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Unsupervised word embeddings capture latent knowledge from materials science literature

The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the materials research community has come from structured property databases, which encompass only a small fraction of the knowledge present in the research literature. Beyond property values, publications contain valuable knowledge regarding the connections and relationships between data items as interpreted by the authors. To improve the identification and use of this knowledge, several studies have focused on the retrieval of information from scientific literature using supervised natural language processing, which requires large hand-labelled datasets for training. Here we show that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings (vector representations of words) without human labelling or supervision. Without any explicit insertion of chemical knowledge, these embeddings capture complex materials science concepts such as the underlying structure of the periodic table and structure-property relationships in materials. Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Lastly, our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature.

36 MATERIALS SCIENCE↗

DOE OSTI2022

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2011

VIOLENT FRAMES IN ACTION

We present a computational approach to radical rhetoric that leverages the co-expression of rhetoric and action features in discourse to identify violent intent. The approach combines text mining and machine learning techniques with insights from Frame Analysis and theories that explain the emergence of violence in terms of moral disengagement, the violation of sacred values and social isolation in order to build computational models that identify messages from terrorist sources and estimate their proximity to an attack. We discuss a specific application of this approach to a body of documents from and about radical and terrorist groups in the Middle East and present the results achieved.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗