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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ventilation in Residential Care Environments

The purpose of this study was to evaluate the effect of ventilation rate, directional airflow (e.g. pressure relationships) and airflow barriers on bioaerosol concentration and movement within assisted-living and residential care environments. Included within this report is a comprehensive literature review, field data collection test plan and, an evaluation of commercially available mitigation technologies related to the transmission of COVID-19 in LTC environments. Additionally, this report includes aerosol testing in an actual LTC facility using the test plan developed herein. Nearly 1.5 million people live in 16,000 nursing homes in the U.S. As of December 20, 2020 the Centers for Medicare and Medicaid Services (CMS) identified a total of 662,549 confirmed and suspected COVID-19 cases in these and other long-term care (LTC) facilities resulting in 92,373 deaths. At this time, COVID-19 cases in LTC facilities accounted for only 3% of the U.S. total of 21M confirmed cases yet nearly a third of the 350,000 total U.S. deaths. Preliminary studies have found little correlation between the quality of care and transmission of COVID-19 in these facilities, suggesting that even the best infection control practices may not be effective in containing the spread of this potentially airborne disease. As a result, many LTC facilities have implemented quarantine procedures and other measures to isolate infectious residents from the general population. Unfortunately, most LTC facilities were not designed for airborne infection control and guidance for retrofitting existing LTC spaces for airborne isolation is limited.

42 ENGINEERING↗
DOE OSTI2022

Smart soft contact lenses for continuous 24-hour monitoring of intraocular pressure in glaucoma care

Continuous monitoring of intraocular pressure, particularly during sleep, remains a grand challenge in glaucoma care. Here we introduce a class of smart soft contact lenses, enabling the continuous 24-hour monitoring of intraocular pressure, even during sleep. Uniquely, the smart soft contact lenses are built upon various commercial brands of soft contact lenses without altering their intrinsic properties such as lens power, biocompatibility, softness, transparency, wettability, oxygen transmissibility, and overnight wearability. We show that the smart soft contact lenses can seamlessly fit across different corneal curvatures and thicknesses in human eyes and therefore accurately measure absolute intraocular pressure under ambulatory conditions. We perform a comprehensive set of in vivo evaluations in rabbit, dog, and human eyes from normal to hypertension to confirm the superior measurement accuracy, within-subject repeatability, and user comfort of the smart soft contact lenses beyond current wearable ocular tonometers. We envision that the smart soft contact lenses will be effective in glaucoma care.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Flux-Assisted Boron Chalcogen Mixture (BCM) Method for Synthesizing Mixed Chalcogenide Semiconductors (AkRE 2 Si 2 Se x S 8– x and CaRE 2 Si 2 Se 8 ) ( Ak = Ca and Sr; RE = La, Ce, Pr, Nd, and Sm): Investigation of Their Magnetic and Optical Properties

We report a detailed structural analysis of a series of ten quaternary rare-earth-containing seleno-thiosilicates AkRE 2 Si 2 Se x S 8-x and selenosilicates, CaRE 2 Si 2 Se 8 (Ak = Ca and Sr; RE = La, Ce, Pr, Nd, and Sm). Single crystals were obtained by using the flux-assisted boron chalcogen mixture (BCM) method and single crystal X-ray diffraction was used to determine their structures. All members of the AkRE 2 Si 2 Se x S 8-x and CaRE 2 Si 2 Se 8 series crystallize in the space group R$\bar{3}$c (space group number 167) of the trigonal crystal system. The single-crystal X-ray diffraction analysis revealed a strong preference for Se/S atoms to occupy one vs. the other of the two available sites. Polycrystalline samples were used for magnetic susceptibility and UV–visible diffuse reflectance measurements. Magnetic measurements show that CaCe₂Si₂Se₁.₇₃S₆.₂₇ and CaNd₂Si₂Se₂.₅S₅.₅ are paramagnetic with negative Weiss constants (θ = –60.1 and –26.2). Diffuse reflectance analysis gives optical band gaps of 2.7(1) eV (CaLa₂Si₂Se₂.₃₈S₅.₆₂), 2.2(1) eV (CaCe₂Si₂Se₁.₇₃S₆.₂₇), 2.5(1) eV (CaNd₂Si₂Se₂.₅S₅.₅), and 2.0(1) eV (CaCe₂Si₂Se₈), consistent with density functional theory calculations. By partially or fully replacing S sites with Se it was possible to achieve band gap tuning. Photoluminescence behavior was also investigated for CaCe 2 Si 2 Se 1.73 S 6.27 via irradiation with 375 nm ultraviolet light.

BCM method↗
DOE OSTI2024

iFair: Achieving Fairness in the Allocation of Scarce Resources for Senior Health Care

Efficient resource allocation is crucial in many domains, particularly in senior care, where assigning resources to older adults must consider uncertainties associated with vulnerable populations. In collaboration with Senior Health Facilities (SHFs) and domain experts, this paper presents iFair, a novel framework designed to assist decision-makers in equitably allocating scarce resources to older adults. iFair was prototyped in the context of ongoing work on a data exchange platform, CAREDEX, used for enhancing older adults' resilience during disasters. A key novelty of iFair focuses on aligning resident preferences with resources in urgent situations, expediting care, and enhancing task efficiency. We integrate static and dynamic environmental data, including facility layouts and sensor data, with detailed resident profiles to cater to the individual needs and preferences of residents. While our framework primarily focuses on allocation within facilities, it also extends to a regional scale to support the planning and transfer of seniors to mutual aid facilities. Our experiments adapt data from a real SHF to emulate resource allocation in an emergency fire evacuation setting and highlight the delicate balance that decision-makers can achieve between efficiency and fairness.

Kenne, Modeste Mefenya↗
DOE OSTI2020

Corrective Action Management Unit Report of Post-Closure Care Activities Calendar Year 2019

The Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department (NMED) issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015) to the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA) and its Management and Operating (M&O) contractor. The current M&O contractor is National Technology & Engineering Solutions of Sandia, LLC (NTESS). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2019, as required by the Permit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Chemical Waste Landfill Annual Post-Closure Care Report, Calendar Year 2019

The Chemical Waste Landfill (CWL) at Sandia National Laboratories/New Mexico (SNL/NM) is a remediated hazardous waste landfill that underwent closure in accordance with Title 20, Chapter 4, Part 1 of the New Mexico Administrative Code (20.4.1.600 NMAC), incorporating Title 40, Code of Federal Regulations (CFR), Part 265, (40 CFR § 265) Subpart G, and the CWL Final Closure Plan (SNL/NM December 1992 and subsequent revisions). The CWL Post- Closure Care Permit (PCCP) (NMED October 2009), which became effective June 2, 2011 (Kieling June 2011) and as modified, defines all post-closure requirements. This ninth CWL Annual Post-Closure Care Report documents all activities and results as required by the PCCP Attachment 1, Section 1.12.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Corrective Action Management Unit Report of Post-Closure Care Activities. Calendar Year 2020

he Corrective Action Management Unit (CAMU) at Sandia National Laboratories, New Mexico (SNL/NM) consists of a containment cell and ancillary systems that underwent closure in 2003 in accordance with the Closure Plan in Appendix D of the Class 3 Permit Modification (SNL/NM September 1997). The containment cell was closed with wastes in place. On January 27, 2015, the New Mexico Environment Department issued the Hazardous Waste Facility Operating Permit (Permit) for Sandia National Laboratories (NMED January 2015) to the U.S. Department of Energy/National Nuclear Security Administration (DOE/NNSA) and its Management and Operating (M&O) contractor. The current M&O contractor is National Technology & Engineering Solutions of Sandia, LLC (NTESS). The Permit became effective February 26, 2015. The CAMU is undergoing post-closure care in accordance with the Permit, as revised and updated. This CAMU Report of Post-Closure Care Activities documents all activities and results for calendar year (CY) 2020, as required by the Permit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

DeepCare: Improving Patient Care using Deep Learning on Electronic Health Records

Coordinating patient care using electronic health records (EHR) data presents an exciting but formidable opportunity in data extraction, analysis and modeling. Traditional methods use a manual feature driven approach to model patients with age, family history and symptoms to predict disease outcomes. We propose a novel approach to model patients based on their streaming electronic health records data combined with information from medical knowledge bases, which has been gained over years of medical research. Using a combination of representation learning and long short term memory (LSTM) networks we plan to model patient evolution over time, leading to more accurate and individualized predictive models for patient’s diseases. Our approach will be transformative in providing critical decision support for patient care, enabling accurate understanding and evolution of diseases in patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deep learning models for interpretation of point of care ultrasound in military working dogs

Introduction: Military working dogs (MWDs) are essential for military operations in a wide range of missions. With this pivotal role, MWDs can become casualties requiring specialized veterinary care that may not always be available far forward on the battlefield. Some injuries such as pneumothorax, hemothorax, or abdominal hemorrhage can be diagnosed using point of care ultrasound (POCUS) such as the Global FAST® exam. This presents a unique opportunity for artificial intelligence (AI) to aid in the interpretation of ultrasound images. In this article, deep learning classification neural networks were developed for POCUS assessment in MWDs. Methods: Images were collected in five MWDs under general anesthesia or deep sedation for all scan points in the Global FAST® exam. For representative injuries, a cadaver model was used from which positive and negative injury images were captured. A total of 327 ultrasound clips were captured and split across scan points for training three different AI network architectures: MobileNetV2, DarkNet-19, and ShrapML. Gradient class activation mapping (GradCAM) overlays were generated for representative images to better explain AI predictions. Results: Performance of AI models reached over 82% accuracy for all scan points. The model with the highest performance was trained with the MobileNetV2 network for the cystocolic scan point achieving 99.8% accuracy. Across all trained networks the diaphragmatic hepatorenal scan point had the best overall performance. However, GradCAM overlays showed that the models with highest accuracy, like MobileNetV2, were not always identifying relevant features. Conversely, the GradCAM heatmaps for ShrapML show general agreement with regions most indicative of fluid accumulation. Discussion: Overall, the AI models developed can automate POCUS predictions in MWDs. Preliminarily, ShrapML had the strongest performance and prediction rate paired with accurately tracking fluid accumulation sites, making it the most suitable option for eventual real-time deployment with ultrasound systems. Further integration of this technology with imaging technologies will expand use of POCUS-based triage of MWDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Screening and Brief Interventions for Alcohol Use During Pregnancy: Practices Among US Primary Care Clinicians, DocStyles 2019

Alcohol use during pregnancy can cause birth defects and developmental disabilities. From 2018 through 2020, 13.5% of pregnant women reported current drinking. The US Preventive Services Task Force recommends evidence-based tools (eg, AUDIT-C and SASQ) for implementing screening and brief interventions to reduce excessive alcohol use among adults, including pregnant people, for whom any alcohol use is considered excessive. We used DocStyles 2019 data to conduct a cross-sectional analysis to examine current screening and brief intervention practices that primary care clinicians conduct among pregnant patients; clinicians’ confidence levels in conducting screening, brief interventions, and referral to treatment; and the documentation of brief interventions in the medical record. A total of 1,500 US adult medicine clinicians completed the entire survey. Among the respondents who conduct screening (N = 1,373) and brief interventions (N = 1,357) in their practice, nearly all reported implementing screening (94.6%) and brief interventions (94.9%) with their pregnant patients for alcohol use, but fewer than half felt confident about conducting their screening practices (46.5%). Two-thirds (64%) reported using a tool that met the criteria recommended by the US Preventive Services Task Force (USPSTF). Over half documented brief interventions in electronic health record notes (51.7%) or designated space (50.7%). Pregnancy presents a unique opportunity for clinicians to incorporate screening into routine obstetric care and encourage behavior change among patients. Most providers reported always screening their pregnant patients for alcohol use, but fewer used evidence-based USPSTF-recommended screening tools. Increased clinician confidence in screening and brief intervention, the use of standardized screening tools tailored to pregnant people, and maximal use of electronic health record technology may enhance the benefits of their application to alcohol use, which ultimately can reduce adverse outcomes associated with alcohol use during pregnancy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Bayesian inference of heterogeneous epidemic models: Application to COVID-19 spread accounting for long-term care facilities

Here we propose a high dimensional Bayesian inference framework for learning heterogeneous dynamics of a COVID-19 model, with a specific application to the dynamics and severity of COVID-19 inside and outside long-term care (LTC) facilities. We develop a heterogeneous compartmental model that accounts for the heterogeneity of the time-varying spread and severity of COVID-19 inside and outside LTC facilities, which is characterized by time-dependent stochastic processes and time-independent parameters in ~ 1500 dimensions after discretization. To infer these parameters, we use reported data on the number of confirmed, hospitalized, and deceased cases with suitable post-processing in both a deterministic inversion approach with appropriate regularization as a first step, followed by Bayesian inversion with proper prior distributions. To address the curse of dimensionality and the ill-posedness of the high-dimensional inference problem, we propose use of a dimension-independent projected Stein variational gradient descent method, and demonstrate the intrinsic low-dimensionality of the inverse problem. We present inference results with quantified uncertainties for both New Jersey and Texas, which experienced different epidemic phases and patterns. Moreover, we also present forecasting and validation results based on the empirical posterior samples of our inference for the future trajectory of COVID-19.

42 ENGINEERING↗
DOE OSTI2021

LAMP Diagnostics at the Point-of-Care: Emerging Trends and Perspectives for the Developer Community

Over the past decade, loop-mediated isothermal amplification (LAMP) technology has played an important role in molecular diagnostics. Amongst numerous nucleic acid amplification assays, LAMP stands out in terms of sample-to-answer time, sensitivity, specificity, cost, robustness, and accessibility, making it ideal for field-deployable diagnostics in resource-limited regions. In this review, we outline the front-end LAMP design practices for point-of-care (POC) applications, including sample handling and various signal readout methodologies. Next, we explore existing LAMP technologies that have been validated with clinical samples in the field. We summarize recent work that utilizes reverse transcription (RT) LAMP to rapidly detect SARS-CoV-2 as an alternative to standard PCR protocols. Finally, we describe challenges in translating LAMP from the benchtop to the field and opportunities for future LAMP assay development and performance reporting. Despite the popularity of LAMP in the academic research community and a recent surge in interest in LAMP due to the COVID-19 pandemic, there are numerous areas for improvement in the fundamental understanding of LAMP, which are needed to elevate the field of LAMP assay development and characterization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Adapting Reinforcement Learning Treatment Policies Using Limited Data to Personalize Critical Care

We report reinforcement learning (RL) demonstrates promise for developing effective treatment policies in critical care settings. However, existing RL methods often require large and comprehensive patient data sets and do not readily lend themselves to settings in which certain patient subpopulations are severely underrepresented. In this study, we develop a new method, noisy Bayesian policy updates (NBPU), for selecting high-performing reinforcement learning–based treatment policies for underrepresented patient subpopulations using limited observations. Our method uses variational inference to learn a probability distribution over treatment policies based on a reference patient subpopulation for which sufficient data are available. It then exploits limited data from an underrepresented patient subpopulation to update this probability distribution and adapts its recommendations to this subpopulation. We demonstrate our method’s utility on a data set of ICU patients receiving intravenous blood anticoagulant medication. Our results show that NBPU outperforms state-of-the-art methods in terms of both selecting effective treatment policies for patients with nontypical clinical characteristics and predicting the corresponding policies’ performance for these patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children With Medical Complexity Presenting With Severe Sepsis

Objectives: Of the Social Determinants of Health (SDoH), we evaluated socioeconomic and neighborhood-related factors which may affect children with medical complexity (CMC) admitted to a Pediatric Intensive Care Unit (PICU) in Shelby County, Tennessee with severe sepsis and their association with PICU length of stay (LOS). We hypothesized that census tract-level socioeconomic and neighborhood factors were associated with prolonged PICU LOS in CMC admitted with severe sepsis in the underserved community. Methods: This single-center retrospective observational study included CMC living in Shelby County, Tennessee admitted to the ICU with severe sepsis over an 18-month period. Severe sepsis CMC patients were identified using an existing algorithm incorporated into the electronic medical record at a freestanding children's hospital. SDoH information was collected and analyzed using patient records and publicly available census-tract level data, with ICU length of stay as the primary outcome. Results: 83 encounters representing 73 patients were included in the analysis. The median PICU LOS was 9.04 days (IQR 3.99–20.35). The population was 53% male with a median age of 4.1 years (IQR 1.96–12.02). There were 57 Black/African American patients (68.7%) and 85.5% had public insurance. Based on census tract-level data, about half (49.4%) of the CMC severe sepsis population lived in census tracts classified as suffering from high social vulnerability. There were no statistically significant relationships between any socioeconomic and neighborhood level factors and PICU LOS. Conclusion: Pediatric CMC severe sepsis patients admitted to the PICU do not have prolonged lengths of ICU stay related to socioeconomic and neighborhood-level SDoH at our center. A larger sample with the use of individual-level screening would need to be evaluated for associations between social determinants of health and PICU outcomes of these patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Single-Atomic Site Catalyst Enhanced Lateral Flow Immunoassay for Point-of-Care Detection of Herbicide

Point-of-care (POC) detection of herbicides is of great importance due to their impact on the environment and potential risks to human health. Here, we design a single-atomic site catalyst (SASC) with excellent peroxidase-like (POD-like) catalytic activity, which enhances the detection performance of corresponding lateral flow immunoassay (LFIA). The iron single-atomic site catalyst (Fe-SASC) is synthesized from hemin-doped ZIF-8, creating active sites that mimic the Fe active center coordination environment of natural enzyme and their functions. Due to its atomically dispersed iron active sites that result in maximum utilization of active metal atoms, the Fe-SASC exhibits superior POD-like activity, which has great potential to replace its natural counterparts. Also, the catalytic mechanism of Fe-SASC is systematically investigated. Utilizing its outstanding catalytic activity, the Fe-SASC is used as label to construct LFIA (Fe-SASC-LFIA) for herbicide detection. The 2,4-dichlorophenoxyacetic acid (2,4-D) is selected as a target here, since it is a commonly used herbicide as well as a biomarker for herbicide exposure evaluation. A linear detection range of 1-250 ng/mL with a low limit of detection (LOD) of 0.82 ng/mL has been achieved. Meanwhile, excellent specificity and selectivity towards 2,4-D have been obtained. The outstanding detection performance of the Fe-SASC-LFIA has also been demonstrated in the detection of human urine samples, indicating the practicability of this POC detection platform for analyzing the 2,4-D exposure level of a person. We believe this proposed Fe-SASC-LFIA has potential as a portable, rapid, and high-sensitive POC detection strategy for pesticide exposure evaluation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances via Discovery in Physical Sciences

Over several months, representatives from the U.S. Department of Energy (DOE) Office of Science and National Institutes of Health (NIH) had a number of meetings that lead to the conclusion that innovations in the Nation's health care could be realized by more directed interactions between NIH and DOE. It became clear that the expertise amassed and instrumentation advances developed at the DOE physical science laboratories to enable cutting-edge research in particle physics could also feed innovation in medical healthcare. To meet their scientific mission, the DOE laboratories created advances in such technologies as particle beam generation, radioisotope production, high-energy particle detection and imaging, superconducting particle accelerators, superconducting magnets, cryogenics, high-speed electronics, artificial intelligence, and big data. To move forward, NIH and DOE initiated the process of convening a joint work- shop which occurred on July 12th and 13th, 2021. Here, this Special Report presents a summary of the findings of the collaborative workshop and introduces the goals of the next one.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

The Influence of Patient–Provider Language Concordance in Cancer Care: Results of the Hispanic Outcomes by Language Approach (HOLA) Randomized Trial

Delivering linguistically competent care is critical to serving patients who have limited English proficiency (LEP) and represents a key national strategy to help reduce health disparities. Current acceptable standards of communication with patients who have LEP include providers communicating through professional interpretive services or bilingual providers speaking the patients’ preferred language directly. This randomized clinical trial tests the effect of patient-provider language concordance on patient satisfaction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Clusters of COVID ‐19 in long‐term care hospitals and facilities in Japan from 16 January to 9 May 2020

Aim To clarify the association of cluster number and size of coronavirus disease 2019 (COVID‐19) in long‐term care (LTC) hospitals/facilities, general medical/welfare facilities and non‐medical/welfare facilities with morbidity and mortality in 47 prefectures during 16 January to 9 May 2020 in Japan. Methods Information on COVID‐19 clusters ( n ≥2), and morbidity and mortality of COVID‐19 was collected. Results A total of 381 clusters with 3786 infected cases were collected, accounting for 23.9% of 15 852 cumulated cases on 9 May 2020. Although the cluster number (/10 7 subjects) in LTC hospitals/facilities was significantly smaller compared with those in the other two groups, the cluster size in LTC hospitals/facilities was significantly larger than that in non‐medical/welfare facilities. Cluster numbers in general medical/welfare facilities and in non‐medical/welfare facilities were significantly positively correlated with morbidity (/10 5 ), indicating relatively early identification of clusters in these facilities. Unlike in these facilities, cluster size in LTC hospitals/facilities was significantly positively correlated with morbidity, indicating that clusters in LTC hospitals/facilities were finally identified after already having grown to a large size in areas where infection was prevalent. Multivariate logistic regression analysis showed that both cluster number and cluster size only in LTC hospitals/facilities were independently associated with higher mortality (≥median 0.64/10 5 subjects) after adjustment. Conclusions Preventive efforts against COVID‐19 outbreaks even at the early phase of the epidemic are critically important in LTC hospitals/facilities, as both the larger number and size of clusters only in LTC hospitals/facilities were independently linked to higher mortality in prefectures in Japan. Geriatr Gerontol Int 2020; 20: 715–719 .

Iritani, Osamu↗