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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Analysis of degradation in residential battery energy storage systems for rate-based use-cases

This article examines the impact of residential battery energy storage (BES) systems' operational modes on the life (i.e. usable energy capacity) of the battery under several climatic conditions and battery chemistries. The sharp increase in residential BES installations has been a result of decreasing costs of batteries, increase in rate structures motivated applications such as solar self-consumption and time-of-use energy management, and customers purchasing these systems for backup power. While these different modes of operations provide a combination of increased bill savings, reliability of supply, and energy sustainability to the customer, their operational characteristics vary significantly between use-cases. Functional life of BES systems is known to be strongly dependent on their operating conditions. In this article, we analyze the operation of residential BES systems under different rate-based use-cases, for different battery chemistries and cell designs, and under different environmental conditions. This is conducted by simulating the control of BES operations using rate-based cycling algorithms and analyzing the prognosis of multiple battery lifetime models that consider complex nonlinear dependencies of operational stress factors such as state-of-charge, depth-of-discharge, and temperature on degradation. Significant variations in battery life are observed owing to the differences in characteristics of the uses-cases coupled with environmental conditions and battery chemistries. Such differences lead to the conclusion that choice of residential BES technologies and chemistries should account for their intended use-cases.

25 ENERGY STORAGE↗
DOE OSTI2025

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗
DOE OSTI2023

A study of examiner accuracy in cartridge case comparisons. Part 1: Examiner error rates

This report describes a study undertaken to estimate examiner (not laboratory) error rates for false Identifications and false Eliminations when comparing an unknown to a collection of three known cartridge cases. Volunteer active examiners with Association of Firearm and Toolmark Examiners (AFTE) membership or working in laboratories that participate in the Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. In addition to determining whether the known and questioned cartridge cases were fired with the same handgun, examiners were also asked to assess how many of the three knowns in each set were suitable for comparison, providing an estimated rate of how often each firearm used in the study produces useable, quality marks. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false Eliminations was estimated as 0.367% from comparisons known to be from the same firearm but reported as Eliminations. The overall rate of false Identifications was estimated as 1.01% from comparisons known to be from different firearms but reported as Identifications. The rates are not uniform across the sample population with a few examiners providing most of the false Identification responses. Rates of poor-quality mark production varied across the 25 sample handguns; those rates were 2.3% (±1.4%). Both false Elimination and false Identification rates are comparable to or lower than the rate of production of poor-quality marks by the firearms used in this study.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

A study of examiner accuracy in cartridge case comparisons. Part 2: Examiner use of the AFTE range of conclusions

Here, this report describes an analysis of how examiners used the Association of Firearm and Toolmark Examiners (AFTE) Range of Conclusions in a controlled study undertaken to estimate examiner error rates in comparing cartridge cases. Results of the error rate analysis are reported in [1]; this paper focuses on a broader analysis of how the entire collection of classification categories, especially those in the Inconclusive range, were used by the participating examiners. Volunteer active examiners with AFTE membership or working in laboratories that participate in Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false-negatives was estimated as 0.367 % from comparisons known to be from the same firearm but reported as eliminations. The overall rate of false-positives was estimated as 1.01 % from comparisons known to be from different firearms but reported as identifications. In the case of true different-source examinations, it is clear that the three Inconclusive categories and the Elimination category are not used consistently by all examiners. We identify five different apparent patterns of use of the AFTE Range of Conclusions scale, and discuss possible reasons for and implications of these differences.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Direct, simple and efficient computation of all components of the virtual-casing magnetic field in axisymmetric geometries with Kapur–Rokhlin quadrature

In a recent publication (Toler et al., J. Plasma Phys., vol. 89, issue 2, 2023, p. 905890210), we demonstrated that for axisymmetric geometries, the Kapur–Rokhlin quadrature rule provided an efficient and high-order accurate method for computing the normal component, on the plasma surface, of the magnetic field due to the toroidal current flowing in the plasma, via the virtual-casing principle. The calculation was indirect, as it required the prior computation of the magnetic vector potential from the virtual-casing principle, followed by the computation of its tangential derivative by Fourier differentiation, to obtain the normal component of the magnetic field. Our approach did not provide the other components of the virtual-casing magnetic field. In this letter, we show that a more direct and more general approach is available for the computation of the virtual-casing magnetic field. The Kapur–Rokhlin quadrature rule accurately calculates the principal value integrals in the expression for all the components of the magnetic field on the plasma boundary, and the numerical error converges at a rate nearly as high as the indirect method we presented previously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

We used social media data from “covid19positive” subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021–09/2021) and Omicron (12/2021–03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The top five common symptoms extracted in the early period were coughing (57%), fever (55%), loss of sense of smell (41%), headache (40%), and sore throat (40%). During the Delta period, these symptoms remained as the top five symptoms with percent authors reporting symptoms reduced to half or fewer than the early period. During the Omicron period, loss of sense of smell was reported less while sore throat was reported more. Our study demonstrated that NLP can be used to identify COVID-19 cases accurately and extracted symptoms efficiently.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Evaluation of overtime phenotypic variation of yeasts in chronic vulvovaginal candidosis cases

Abstract Chronic vulvovaginal candidosis results either from reinfection or from the ability of Candida spp. to persist in the vulva and/or vagina. Persistence is usually associated with increased antifungal (mainly azoles) resistance rates, which can explain treatment failure, and/or increased expression of virulence factors by Candida spp. The aim of this study was to assess the mechanisms leading to Candida spp persistence, by studying sequential isolates from women with chronic vulvovaginal candidosis, focusing on strains genotypes, azole resistance, and ability to form biofilms along the period of clinical evaluation. The strains were identified at species level by automated analysis of biochemical profiles and molecular typing evaluated by polymorphic DNA analysis. The capacity to form biofilm was assessed with a microtiter plate assay. Fluconazole susceptibility was determined by the microdilution broth assay at both pH 7 (following the recommended guideline) and pH 4.5 (as representative of vaginal pH). We studied samples from 17 clinically recurrent cases. In 53% of the chronic cases there were two or more isolates that had a phylogenetic relationship while the remaining (47%) were caused by different species. In those cases where related strains were involved in recurrence, we verified an increase in MIC at pH 7 and also an increased capacity to form biofilms over time. Significant correlation between these two parameters was observed only in cases caused by C. glabrata, evidencing the importance of these two factors to enhance persistence in the vaginal mucosa for this particular species.

Faria-Gonçalves, Paula↗
DOE OSTI2020

Using case-level context to classify cancer pathology reports

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence—for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks—site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Comparing Capacity Credit Calculations for Wind: A Case Study in Texas

The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.

17 WIND ENERGY↗
DOE OSTI2022

Price response of waste resources under demand shocks: four case studies

To quantify potential price changes of waste feedstocks that may be caused by increased demand, this study explored four case studies: 1) recyclable materials at local waste collection and recycling facilities in seven US states, 2) recyclable materials on internationally traded markets, 3) a wood-powered plant in Reading, PA, and 4) an MSW-powered plant in Tulsa, OK. The four case studies provided a total of ninety-one waste material price observations yielding twenty-seven price-supply relationships expressed as price elasticity of supply (PES) and unit price change with change in demand. For the two case studies related to recyclable materials with a global market shock, price changes vary widely from $0.08-$7.84 per ton with each percent change in demand. For the two case studies related to local market shocks in biomass used for energy, observed price changes range from $0.08-$0.23 per ton per percent change in demand. Based on these results, a base range of $0.10-$0.20 per ton per percent change in demand is recommended for local market shocks. I.e., for a facility that collects organic wastes on the order of 200,000-400,000 tons per year at price near zero, a doubling of demand could increase procurement prices by about $10.00-$20.00 per ton. Actual price changes with respect to change in demand may be non-linear. Shocks with broader geographic extent may increase price response due to a reduced opportunity for surrounding markets to mitigate localized market changes.

09 BIOMASS FUELS↗
DOE OSTI2022

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.5)

Oak Ridge National Laboratory (ORNL)’s Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) architecture project, titled “An Open Federated Architecture for the Laboratory of the Future”, creates an open federated hardware/software architecture for the laboratory of the future using a novel system of systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The project describes science use cases as design patterns that identify and abstract the involved hardware/software components and their interactions in terms of control, work and data flow. It creates a SoS architecture of the federated hardware/software ecosystem that clarifies terms, architectural elements, the interactions between them and compliance. It further designs a federated microservice architecture, mapping science use case design patterns to the SoS architecture with loosely coupled microservices, standardized interfaces and multi programming language support. The primary deliverable of this project is an INTERSECT Open Architecture Specification, containing the science use case design pattern catalog, the federated SoS architecture specification and the federated microservice architecture specification. This document represents the science use case design pattern catalog of the INTERSECT Open Architecture Specification.

42 ENGINEERING↗
DOE OSTI2023

Real Time and Forecasted DLR: Use Cases

This document contains two use cases for the utilization of dynamic line ratings in operational practices. These use cases were developed in support of the Transmission Optimization and Grid Enhancing Technology (TOGETS) task force aimed at facilitating the deployment of dynamic line rating and power flow technologies across the United States. The project included a demonstration of the technology on the Idaho National Laboratory system. The procurement documents, tests scripts, and field-validated results from multiple vendors will be published to improve industry’s familiarity with the products. Because of the urgency in performing this work and INL’s unique test setup, the Task Force identified a need for additional public information on the information exchanges required for operationalizing DLR (i.e. integrating DLR’s within actual system operations). As such, this use case document and an accompanying interoperability profile have been developed with input from the Task Force and various vendors whose systems would ultimately support the functionality described. The use case and interoperability profile support two distinct functionalities with different purposes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Summary of FY 2024 A709 Code Case testing at ANL, INL and ORNL

A collaborative research and development effort in support of the Alloy 709 Code Case qualification in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors is being carried out at Oak Ridge National Laboratory (ORNL), Idaho National Laboratory (INL), and Argonne National Laboratory (ANL). Key testing data for the Alloy 709 100,000-hr near-term Code Case submittal to ASME is expected to be completed by the end of 2024, with design parameters anticipated to be finalized in FY 2025. This report summarizes the testing results for three commercial heats of Alloy 709 conducted across three laboratories, reviews the current testing status, and outlines the remaining data needed to support the first Alloy 709 Code Case submittal to ASME. The Alloy 709 Code Case plan remains on schedule.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Direct Air Capture Case Studies: Sorbent System (Rev. 1)

In 2022, the National Energy Technology Laboratory published a techno-economic assessment (TEA) examining the performance and cost of a generic solid sorbent-based direct air capture (DAC) system, “Direct Air Capture Case Studies: Sorbent System”. Revision 1 of this report builds on the previous effort by updating assumptions to reflect the evolving industry and recent developments in the DAC research and development (R&D) portfolio. Revision 1 of the report also expands the case list to examine a variety of sorbent DAC system configurations. The objective of this series is to present transparent and independent TEAs that can serve as a guideline for sorbent DAC TEA development and highlight potential avenues for cost reductions that can inform R&D. The sorbent considered is not reflective of any one material type; rather, it represents an approximate average of reported material performance in the literature. The base cases presented in this series do not represent optimized systems due to the nascence of the technology and lack of publicly available information. The base cases serve as a reference for informative sensitivity analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Technology Case Study: Economic, Sustainability, and Deployment Considerations for Sustainable Aviation Fuels Produced via Lignocellulosic Sugar Catalysis

This report presents a technology case study reflecting one exemplary representative pathway for the conversion of lignocellulosic sugars to sustainable aviation fuels (SAF) via aqueous phase reforming (APR) catalysis, considered within a broader integrated biorefinery framework based on biochemical processing operations. While far from the only option for converting sugars to SAF, this pathway was selected as a case study here based on its relatively high technology maturity and simplistic processing approach (avoiding complex separations or other equipment scalability challenges), coupled with the potential for high fuel yields and favorable costs/carbon intensities with opportunities for further near-term optimization. The report considers key process integration and engineering design considerations for a modeled hypothetical, nth-plant commercial biorefinery, reflecting a number of processing options and parameters envisioned to be achievable as future goals. Resultant outputs from Aspen Plus process simulations are evaluated through techno-economic and life cycle analyses (TEA and LCA), including implications for marginal cost of CO2 abatement and inclusion of currently-applicable policy incentives. Moving beyond base case configurations, a number of alternative scenarios are also evaluated for their ability to further improve economics, greenhouse gas (GHG) emissions, and marginal cost of abatement, highlighting a path to achieve deep decarbonization goals of more than 70% GHG reduction for SAF (with the potential to reach net-negative carbon intensities in some cases) under reasonable fuel production costs. The report also highlights future opportunities and gaps for further research on this technology pathway.

09 BIOMASS FUELS↗
DOE OSTI2020

Multipole-based cable braid electromagnetic penetration model: magnetic penetration case

The goal of this paper is to present, for the first time, calculations of the magnetic penetration case of a first principles multipole-based cable braid electromagnetic penetration model. As a first test case, a one-dimensional array of perfect electrically conducting wires, for which an analytical solution is known, is investigated: we compare both the self-inductance and the transfer inductance results from our first principles cable braid electromagnetic penetration model to those obtained using the analytical solution. These results are found in good agreement up to a radius to half spacing ratio of about 0.78, demonstrating a robustness needed for many commercial and non-commercial cables. We then analyze a second set of test cases of a square array of wires whose solution is the same as the one-dimensional array result and of a rhomboidal array whose solution can be estimated from Kley's model. As a final test case, we consider two layers of one-dimensional arrays of wires to investigate porpoising effects analytically. We find good agreement with analytical and Kley's results for these geometries, verifying our proposed multipole model. Note that only our multipole model accounts for the full dependence on the actual cable geometry which enables us to model more complicated cable geometries.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada

West Nile virus is the most common mosquito borne disease in North America and the leading cause of viral encephalitis. West Nile virus is primarily transmitted between birds and mosquitoes while humans are incidental, dead-end hosts. Climate change may increase the risk of human infections as climatic variables have been shown to affect the mosquito life cycle, biting rate, incubation period of the disease in mosquitoes, and bird migration patterns. We develop a zero-inflated Poisson model to investigate how human West Nile virus case counts vary with respect to mosquito abundance and infection rates, bird abundance, and other environmental covariates. We use a Bayesian paradigm to fit our model to data from 2010–2019 in Ontario, Canada. Our results show mosquito infection rate, temperature, precipitation, and crow abundance are positively correlated with human cases while NDVI and robin abundance are negatively correlated with human cases. We find the inclusion of spatial random effects allows for more accurate predictions, particularly in years where cases are higher. Our model is able to accurately predict the magnitude and timing of yearly West Nile virus outbreaks and could be a valuable tool for public health officials to implement prevention strategies to mitigate these outbreaks.

60 APPLIED LIFE SCIENCES↗