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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

NMDC Field Notes Phone Application (NMDC Field Notes) v1.0

This software is for an application, designed for phones and/or tablets, to assist microbiome researchers collecting samples in the field to also collect metadata in a standardized and systematic way. The type of samples covered would be e.g. soil sample from a forest, sediment sample from a lake, or water sample in the ocean. The app allows users to collect sample information and metadata in an easy and intuitive way, and connects to the NMDC submission portal (https://data.microbiomedata.org/submission/home) a website from where users can review the samples they collected and add more information if necessary.

Kalita, Patrick↗
DOE OSTI2024

Question-answering system extracts information on injection drug use from clinical notes

Background. Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods. Here, to address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information from temporally out-of-distribution data. Results. Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions. Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes

Question Answering (QA) in clinical notes has gained a lot of attention in the past few years. Existing machine reading comprehension approaches in clinical domain can only handle questions about a single block of clinical texts and fail to retrieve information about different patients and clinical notes. To handle more complex questions, we aim at creating knowledge base from clinical notes to link different patients and clinical notes, and performing knowledge base question answering (KBQA). Based on the expert annotations in n2c2, we first created the ClinicalKBQA dataset that includes 8,952 QA pairs and covers questions about seven medical topics through 322 question templates. Then, we proposed an attention-based aspect reasoning (AAR) method for KBQA and investigated the impact of different aspects of answers (e.g., entity, type, path, and context) for prediction. The AAR method achieves better performance due to the well-designed encoder and attention mechanism. In the experiments, we find that both aspects, type and path, enable the model to identify answers satisfying the general conditions and produce lower precision and higher recall. On the other hand, the aspects, entity and context, limit the answers by node-specific information and lead to higher precision and lower recall.

Wang, Ping↗
NASA NTRS1958

Notes on Space Technology

These notes are part of a space technology course given at the Flight Research Division of the NACA Langley Aeronautical Laboratory during the early part of 1958. The course was conducted as a self-education program within the Flight Research Division and the various Sections of the notes were prepared for the most part by members of the Division; however, four of the seventeen Sections were prepared by personnel from the Pilotless Aircraft Research Division and the Compressibility Research Division who were very helpful in making the program more complete. The notes have been compiled on a brief time schedule and it will be apparent to the reader that the present version is incomplete and to some extent may lack uniformity in length, type of presentation, and technical detail in the various Sections. Nevertheless, there has been a demand for the notes from those who have seen them, and it is thought that they might serve a useful purpose if they were made available on a wider basis. It is believed that for the sake of expediency this goal is best achieved by making the material available now in its present unedited form instead of following the usual NACA editing procedures.

Henry A Pearson↗
NASA NTRS2007

The NIRCam Optical Telescope Simulator (NOTES)

The Near Infra-Red Camera (NIRCam), the 0.6-5.0 micron imager and wavefront sensing instrument for the James Webb Space Telescope (JWST), will be used on orbit both as a science instrument, and to tune the alignment of the telescope. The NIRCam Optical Telescope Element Simulator (NOTES) will be used during ground testing to provide an external stimulus to verify wavefront error, imaging characteristics, and wavefront sensing performance of this crucial instrument. NOTES is being designed and built by NASA Goddard Space Flight Center with the help of Swales Aerospace and Orbital Sciences Corporation. It is a single-point imaging system that uses an elliptical mirror to form an U20 image of a point source. The point source will be fed via optical fibers from outside the vacuum chamber. A tip/tilt mirror is used to change the chief ray angle of the beam as it passes through the aperture stop and thus steer the image over NIRCam's field of view without moving the pupil or introducing field aberrations. Interchangeable aperture stop elements allow us to simulate perfect JWST wavefronts for wavefront error testing, or introduce transmissive phase plates to simulate a misaligned JWST segmented mirror for wavefront sensing verification. NOTES will be maintained at an operating temperature of 80K during testing using thermal switches, allowing it to operate within the same test chamber as the NIRCam instrument. We discuss NOTES' current design status and on-going development activities.

Kubalak, David↗
DOE OSTI2024

Surface science insight note: A linear algebraic approach to elucidate native films on Fe 3 O 4 surface

Standard materials are often used to obtain spectra that can be compared to those from unknown samples. Spectra measured from these known substances are also used as a means of computing sensitivity factors to allow quantification by X-ray photoelectron spectroscopy (XPS) of less well-defined materials. Spectra from known materials also provide line shapes suitable for inclusion in spectral models which, when fitted to spectra, permit the chemical state for a sample to be assessed. Both types of information depend on isolating photoemission signals from the inelastically scattered signal. In this Insight note, technical issues associated with the use of XPS of as received Fe 3 O 4 powder sample surface are discussed. The Insight note is designed to show how linear algebraic techniques applied to data collected from a sample marketed as pure Fe 3 O 4 powder are used to verify that XPS has been performed on chemistry representative of the sample. The methods described in this Insight note can further be utilized in elucidating complex XPS data obtained from thin films formed or evolved during cyclic/non-steady use of complex (electro)catalyst surfaces, especially in the presence of contaminants.

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

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning. However, very few studies rely solely on unstructured clinical notes from the EHR for mortality prediction. In this work, we propose a framework to predict short, mid, and long-term mortality in adult ICU patients using unstructured clinical notes from the MIMIC III database, natural language processing (NLP), and machine learning (ML) models. Depending on the statistical description of the patients’ length of stay, we define the short-term as 48-hour and 4-day period, the mid-term as 7-day and 10-day period, and the long-term as 15-day and 30-day period after admission. We found that by only using clinical notes within the 24 hours of admission, our framework can achieve a high area under the receiver operating characteristics (AU-ROC) score for short, mid and long-term mortality prediction tasks. The test AU-ROC scores are 0.87, 0.83, 0.83, 0.82, 0.82, and 0.82 for 48-hour, 4-day, 7-day, 10-day, 15-day, and 30-day period mortality prediction, respectively. We also provide a comparative study among three types of feature extraction techniques from NLP: frequency-based technique, fixed embedding-based technique, and dynamic embedding-based technique. Lastly, we provide an interpretation of the NLP-based predictive models using feature-importance scores.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Bituminous Coal and Natural Gas to Electricity: >90% Capture Cases Technical Note

This technical note provides cost and performance estimates for post combustion carbon capture (PCCC) systems designed for greater than 90 percent capture on conventional PC- and NG-fueled power plants. The cost and performance estimates provided here were developed using the National Energy Technology Laboratory’s (NETL’s) well-documented methodology for conducting technoeconomic analysis of fossil energy conversion systems and leveraging published performance and cost projections for higher capture rate systems. Included in this technical note is a brief description of the method used to adjust select 90 percent capture cases from NETL’s Cost and Performance Baselines for Fossil Energy Systems Volume 1: Bituminous Coal and Natural Gas to Electricity, hereafter referred to as the Baseline Study. This technical note is intended to serve as an interim update to NETL’s Baseline Study cases by providing cost and performance estimates for high capture PCCC technology that can be deployed in the near-term at fossil-fueled electricity generating units.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Notes by LANL scientists for science teacher professional development [Slides]

The notes presented in this presentation are an example of taking notes working at the computer while working with data files. The presenter helped collect the data in Antarctica, and they took notes while they collected the data. Later, to use the data once they were back home, the researcher spent many hours looking at the files on the computer to connect two types of data files: GPR and GPS.

58 GEOSCIENCES↗
NASA NTRS2016

LUVOIR Tech Notes

We present nine "tech notes" prepared by the Large UV/Optical/Infrared (LUVOIR) Science and Technology Definition Team (STDT), Study Office, and Technology Working Group. These tech notes are intended to highlight technical challenges that represent boundaries in the trade space for developing the LUVOIR architecture that may impact the science objectives being developed by the STDT. These tech notes are intended to be high-level discussions of the technical challenges and will serve as starting points for more in-depth analysis as the LUVOIR study progresses.

large aperture↗
NASA NTRS2016

Kepler Data Release 25 Notes (Q0-Q17)

These Data Release Notes provide information specific to the current reprocessing and re-export of the Q0-Q17 data. The data products included in this data release include target pixel files, light curve files, FFIs,CBVs, ARP, Background, and Collateral files. This release marks the final processing of the Kepler Mission Data. See Tables 1 and 2 for a list of the reprocessed Kepler cadence data. See Table 3 for a list of the available FFIs. The Long Cadence Data, Short Cadence Data, and FFI data are documented in these data release notes. The ancillary files (i.e., cotrending basis vectors, artifact removal pixels, background, and collateral data) are described in the Archive Manual (Thompson et al., 2016).

Data Release Notes↗
DOE OSTI2023

Surface Analysis Insight Note: Observations relating to photoemission peak shapes, oxidation state, and chemistry of titanium oxide films

It is common practice to describe the coordination of metal atoms in a binding configuration with their nearest neighbors in terms of oxidation state, a measure by which the number of electrons redistributed between atoms forming chemical bonds. In XPS terms, change to an oxidation state is commonly inferred by correlating photoemission signal with binding energy. The assumption, when classifying photoemission signals into distinct spectral shapes, is that a distribution of intensities shifted to lower binding energy is evidence of a reduction in oxidation state. In this Insight note, we raise the prospect that changes in photoemission peak shape may occur without obvious changes, determined by XPS in stoichiometry for a material. It is well known that TiO 2 measured by XPS yields reproducible Ti 2p photoemission peaks. However, on exposing TiO 2 to ion beams, Ti 2p photoemission evolves to complex distributions in intensity, which are particularly difficult to analyze by traditional fitting of bell-shaped curves to these data. For these reasons, in this Insight note, a thin film of TiO 2 deposited on a silicon substrate is chosen for analysis by XPS and linear algebraic techniques. Alterations in spectral shapes created from modified TiO 2 , which might be interpreted as the change in oxidation state, are assessed in terms of relative proportions of titanium to oxygen. It is found through detailed analysis of spectra that quantification by XPS, using procedures routinely used in practice, is not in accord with the typical interpretations of photoemission shapes. The data processing methods used and results presented in this work are of particular relevance to elucidating fundamental phenomena governing the surface evolution of materials-enabled energy processes where cyclic/non-steady usage changes the nature of bonding, especially in the presence of contaminants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Decoding substance use disorder severity from clinical notes using a large language model

Substance use disorder (SUD) poses a major concern due to its detrimental effects on health and society. SUD identification and treatment depend on a variety of factors such as severity, co-determinants (e.g., withdrawal symptoms), and social determinants of health. Existing diagnostic coding systems used by insurance providers, like the International Classification of Diseases (ICD-10), lack granularity for certain diagnoses, but American clinicians will add this granularity (as that found within the Diagnostic and Statistical Manual of Mental Disorders classification or DSM-5) as supplemental unstructured text in clinical notes. Traditional natural language processing (NLP) methods face limitations in accurately parsing such diverse clinical language. Large language models (LLMs) offer promise in overcoming these challenges by adapting to diverse language patterns. This study investigates the application of LLMs for extracting severity-related information for various SUD diagnoses from clinical notes. We propose a workflow employing zero-shot learning of LLMs with carefully crafted prompts and post-processing techniques. Through experimentation with Flan-T5, an open-source LLM, we demonstrate its superior recall compared to the rule-based approach. Focusing on 11 categories of SUD diagnoses, we show the effectiveness of LLMs in extracting severity information, contributing to improved risk assessment and treatment planning for SUD patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

LHC EFT WG note: SMEFT predictions, event reweighting, and simulation

This note provides a comprehensive overview of tools for predicting observables in the Standard Model effective field theory (SMEFT) at both tree level and one loop using event generators. We evaluate three primary methodologies–event reweighting, separate simulation of squared matrix elements, and full SMEFT process simulation–focusing on their statistical performance, computational efficiency, and potential biases. Each approach is assessed in terms of its accuracy, highlighting trade-offs between precision and resource demands. Practical insights into their applicability for high-energy physics analyses are offered, with particular attention to processes where SMEFT effects are significant. Additionally, we discuss the role of helicity in reweighting strategies and its impact on the quality of predictions. By comparing the methods across various LHC processes, this note provides guidance for selecting the most effective strategy for various SMEFT studies, ensuring robust predictions while optimizing computational resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Notes on the 2 to 1 bunch merge with application to polarized proton bunches in AGS

A simple and useful program to produce a 2 to 1 bunch merge is developed in these notes and applied to polarized proton bunches in AGS. The notes are summarized in Sections 1 through 4. The reader may refer to the additional sections as needed. Given the large number of pages and references to various sections, it is recommended that the document viewer be set up to increment and decrement the page number with single key strokes. This gives fast access to the sections and allows sequences of figures to be viewed as movies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Development of Hydropower Biological Evaluation Toolset (HBET): V2.1.9 Release Notes for HBET

The following release notes reflect changes made to HBET for proposed changes to be released in July 2024. Notes are broken up into three sections: 1) Key Improvements, 2) Bug Fixes, and 3) Data Changes • Key Improvements: primary features added and changes to existing features that affect the user experience. • Bug Fixes: Issues discovered or reported that were fixed in the proposed work to be released. • Data Changes: Any work done on the databases directly or the process to calculate data for the system.

13 HYDRO ENERGY↗
NASA NTRS1998

A Note About HARP's State Trimming Method

This short note provides some additional insight into how the HARP program works. In some cases, it is possible for HARP to tdm away too many states and obtain an optimistic result. The HARP Version 7.0 manual warns the user that 'Unlike the ALL model, the SAME model can automatically drop failure modes for certain system models. The user is cautioned to insure that no important failure modes are dropped; otherwise, a non-conservative result can be given.' This note provides an example of where this occurs and a pointer to further documentation that gives a means of bounding the error associated with trimming these states.

Butler, Ricky W.↗