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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Community vulnerability is the key determinant of diverse energy burdens in the United States

Low-income households generally experience a high energy burden; however, the factors influencing energy burdens are beyond socio-economics. This study explores the relationships between the multidimensionality of community vulnerability factors and energy burden across multiple geospatial levels in the United States. Our study found the distribution of energy burden in 2020 showed a great deal of variety, ranging from a minimum of 2.93 % to a maximum of 30.45 % across 3142 counties. The results of non-spatial and spatial regressions showed that the vulnerability ranks of socioeconomic, household composition and disability, minority and language, household type and transportation, and COVID mortality rate are significant predictors of energy burdens at the national level. However, at the regional level, only socioeconomic, minority and language significantly influence energy burdens. Minority and language negatively impact energy burdens except for the South East-Central region. Additionally, our analyses highlight the need to consider community vulnerability indicators' spatial homogeneity and heterogeneity. At the national level, only the epidemiological factors index is a spatially homogeneous predictor; on the regional and state level, the spatially homogeneous predictors such as socioeconomic status, household composition and disability, and household type and transportation vary by region. Such a region-sensitive relationship between energy burden and the predictors indicates spatial heterogeneity. Here this study suggests policy recommendations through the lens of the multidimensionality of community vulnerability factors. Implementing flexible national energy policies while making particular energy assistance policies for the vulnerable population at the regional or state levels is essential.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Broadly neutralizing anti-S2 antibodies protect against all three human betacoronaviruses that cause deadly disease

Pan-betacoronavirus neutralizing antibodies may hold the key to developing broadly protective vaccines against novel pandemic coronaviruses and to more effectively respond to SARS-CoV-2 variants. The emergence of Omicron and subvariants of SARS-CoV-2 illustrates the limitations of solely targeting the receptor-binding domain (RBD) of the spike (S) protein. Here, we isolated a large panel of broadly neutralizing antibodies (bnAbs) from SARS-CoV-2 recovered-vaccinated donors, which targets a conserved S2 region in the betacoronavirus spike fusion machinery. Select bnAbs showed broad in vivo protection against all three deadly betacoronaviruses, SARS-CoV-1, SARS-CoV-2, and MERS-CoV, which have spilled over into humans in the past two decades. Structural studies of these bnAbs delineated the molecular basis for their broad reactivity and revealed common antibody features targetable by broad vaccination strategies. These bnAbs provide new insights and opportunities for antibody-based interventions and for developing pan-betacoronavirus vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Room-temperature structural studies of SARS-CoV-2 protein NendoU with an X-ray free-electron laser

NendoU from SARS-CoV-2 is responsible for the virus’s ability to evade the innate immune system by cleaving the polyuridine leader sequence of antisense viral RNA. Here we report the room-temperature structure of NendoU, solved by serial femtosecond crystallography at an X-ray free-electron laser to 2.6 Å resolution. The room-temperature structure provides insight into the flexibility, dynamics, and other intrinsic properties of NendoU, with indications that the enzyme functions as an allosteric switch. Functional studies examining cleavage specificity in solution and in crystals support the uridine-purine cleavage preference, and we demonstrate that enzyme activity is fully maintained in crystal form. Optimizing the purification of NendoU and identifying suitable crystallization conditions set the benchmark for future time-resolved serial femtosecond crystallography studies. This could advance the design of antivirals with higher efficacy in treating coronaviral infections, since drugs that block allosteric conformational changes are less prone to drug resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification and Exploration of a Series of SARS-Cov-2 M Pro Cyano-Based Inhibitors Revealing Ortho-Substitution Effects within the P3 Biphenyl Group

Starting from a simple scaffold hopping exercise based on our previous exploration of cysteine protease inhibitors against legumain, compound 6a was identified as a starting point for the development of a SARS-CoV-2 main protease (M Pro ) inhibitor. Compound 6a displayed submicromolar biochemical potency in the ultrasensitive assay developed by Drag and coworkers. Through an iterative structure−activity relationship campaign, we discovered an unexpected improvement in both biochemical and cellular potency through the incorporation of an ortho substituent within the P3 benzamide. X-ray crystallography revealed that incorporation of the ortho substituent caused a subtle but important binding enhancement of the P1 glutamate group within the M Pro S1 pocket. While incorporation of the ortho substituent improved the potency, the off-target selectivity against a panel of cysteine proteases and cell activity remained suboptimal. Further scanning of the P2 core revealed that incorporation of the 3.1.0 proline could address these issues and afford compound 22e, a highly potent and cellularly active M Pro inhibitor.

COVID-19 infection↗
DOE OSTI2023

Targeting the Spike Receptor Binding Domain Class V Cryptic Epitope by an Antibody with Pan-Sarbecovirus Activity

Novel therapeutic monoclonal antibodies (MAbs) must accommodate comprehensive breadth of activity against diverse sarbecoviruses and high neutralization potency to overcome emerging variants. Here, in this study, we report the crystal structure of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain (RBD) in complex with MAb WRAIR-2063, a moderate-potency neutralizing antibody with exceptional sarbecovirus breadth, that targets the highly conserved cryptic class V epitope. This epitope overlaps substantially with the spike protein N-terminal domain (NTD) -interacting region and is exposed only when the spike is in the open conformation, with one or more RBDs accessible. WRAIR-2063 binds the RBD of SARS-CoV-2 WA-1, all variants of concern (VoCs), and clade 1 to 4 sarbecoviruses with high affinity, demonstrating the conservation of this epitope and potential resiliency against variation. We compare structural features of additional class V antibodies with their reported neutralization capacity to further explore the utility of the class V epitope as a pan-sarbecovirus vaccine and therapeutic target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Nonparametric Inference for the Reproductive Rate in Generalized Compartmental Models

We develop a tractable nonparametric model for the time-varying reproductive rate of infectious diseases that combines the structure of a deterministic compartmental model and a stochastic model for incidence data. We use Bayesian inference to estimate, with uncertainty, the reproductive rate of the Coronavirus 2019 outbreak in the U.S. states of California, Florida, Michigan, New Mexico, New York, and Texas from January 2020 to March 2022. Employing the inferred reproductive rates, we estimate the posterior distribution of the time-varying reproduction numbers for each state. Compering the time-varying reproduction numbers across the states, we identify some epidemic waves, potentially driven from changes in human behavior and virus mutations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences

We describe our development of ab initio protein-ligand binding pose prediction models based on transformers and binding affinity prediction models based on the neural tangent kernel (NTK). Folding both protein and ligand, the TwoFold models achieve efficient and quality predictions matching state-of-the-art implementations while additionally reconstructing protein structures. In conclusion, solving NTK models points to a new use case for highly optimized linear solver benchmarking codes on HPC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

FTR for: Reducing plug-load electricity footprint of residential buildings through low-cost, non-intrusive sub-metering and personalized feedback technology

The project started in October 2016 and ended in December 2022. The project's principal goals and achievements were: (i) Measure real and reactive electric power consumption in ~400 apartments in multifamily settings of varying size and vintage and publish the data; data was published according to New York State's recommended 15x15 rule continuously from Jan 2019 through December 2022 (10 second time resolution); with the combination of large number of apartments, real and reactive power, as well as high time resolution (10-seconds), the dataset is first of its kind worldwide; because the dataset New York City apartment consumption pre, during, and post pandemic, it further offers unique insights into changes in residential electricity consumption during lockdowns and after modified work from home schedules. (ii) Measure effectiveness of different feedback types to prompt residents to lower their electricity consumption; achieved 11% (kWh-weighted) reduction versus baseline consumption; confirmed previous studies that social comparisons elicit above average responses; showed, for the first time, that the so called boomerang effect in power consumption feedback projects can be explained by a previously hypothesized norm-conforming "magnet effect" (rather than a non-conforming defiance effect), thus substantially advancing the research in the field. (iii) Disaggregate apartment-level consumption to appliance level; because the hardware for electricity consumption unexpectedly allowed only for 10-second time resolution (rather than the 1-second resolution we had planned on), the disaggregation algorithms we developed on sample data could not be applied to the actual field data we collected. The project has yielded high visibility, with a total of 17 publications, from peer reviewed journals, published data sets (free access), blog posts, NY Times, National Public Radio, and CNN.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Predicting SARS-CoV-2 Variant Using Non-Invasive Hand Odor Analysis: A Pilot Study

The adaptable nature of the SARS-CoV-2 virus has led to the emergence of multiple viral variants of concern. This research builds upon a previous demonstration of sampling human hand odor to distinguish SARS-CoV-2 infection status in order to incorporate considerations of the disease variants. This study demonstrates the ability of human odor expression to be implemented as a non-invasive medium for the differentiation of SARS-CoV-2 variants. Volatile organic compounds (VOCs) were extracted from SARS-CoV-2-positive samples using solid phase microextraction (SPME) coupled with gas chromatography–mass spectrometry (GC–MS). Sparse partial least squares discriminant analysis (sPLS-DA) modeling revealed that supervised machine learning could be used to predict the variant identity of a sample using VOC expression alone. The class discrimination of Delta and Omicron BA.5 variant samples was performed with 95.2% (±0.4) accuracy. Omicron BA.2 and Omicron BA.5 variants were correctly classified with 78.5% (±0.8) accuracy. Lastly, Delta and Omicron BA.2 samples were assigned with 71.2% (±1.0) accuracy. This work builds upon the framework of non-invasive techniques producing diagnostics through the analysis of human odor expression, all in support of public health monitoring.

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

A Review of Rattlesnake Venoms

Venom components are invaluable in biomedical research owing to their specificity and potency. Many of these components exist in two genera of rattlesnakes, Crotalus and Sistrurus, with high toxicity and proteolytic activity variation. This review focuses on venom components within rattlesnakes, and offers a comparison and itemized list of factors dictating venom composition, as well as presenting their known characteristics, activities, and significant applications in biosciences. There are 64 families and subfamilies of proteins present in Crotalus and Sistrurus venom. Snake venom serine proteases (SVSP), snake venom metalloproteases (SVMP), and phospholipases A2 (PLA2) are the standard components in Crotalus and Sistrurus venom. Through this review, we highlight gaps in the knowledge of rattlesnake venom; there needs to be more information on the venom composition of three Crotalus species and one Sistrurus subspecies. We discuss the activity and importance of both major and minor components in biomedical research and drug development.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Tracking 2020 Decreases in Carbon Dioxide Due to the COVID19 Pandemic in NASA’s GEOS Modeling system: Implications for Space-Based Carbon Monitoring

The COVID19 pandemic led to abrupt, worldwide changes in human activity and related emissions of air pollutants and greenhouse gases that are unprecedented in modern times. NASA satellites have demonstrated their ability to observe some of these impacts, particularly in relation to short-lived gases like nitrogen dioxide (NO2), which is emitted primarily from transportation. Bottom-up analyses of carbon dioxide (CO2) emissions suggest that the growth of atmospheric CO2 has also slowed, but differences are much more subtle than for NO2 because of the lifetime of atmospheric CO2 and sectoral differences in emission reductions. Estimates of CO2 from NASA’s Orbiting Carbon Observatory 2 (OCO-2) provide a unique view of COVID19 impacts, but observed changes in the column-average CO2 can be difficult to interpret because of gaps in spatial coverage. Assimilating these data into the Goddard Earth Observing System (GEOS), an integrated Earth system model with an advanced Constituent Data Assimilation System (CoDAS), helped to reveal changes in CO2 that are consistent with separate, bottom-up analyses of emissions reductions. Both indicate that from February-April of 2020, the growth in CO2 over Europe, North America, and Asia was roughly 0.3 ppm less than during the previous four years. Anomalies derived from gap-filled GEOS OCO-2 CoDAS products contribute to a joint effort by the world’s space agencies to track COVID19 impacts on the Earth. However, attribution of these changes is complicated by interannual variability in atmospheric circulation and the influence of climate on ocean and land carbon sinks. We discuss these results from the perspective of space-based carbon monitoring, which has received considerable support over the past decade from NASA. Our results demonstrate the accomplishments of current sensors and data assimilation systems, but also highlight challenges in providing high quality, low latency information to the public. In particular, understanding and attributing CO2 changes during 2020 requires year-specific information about land and ocean fluxes, which is often delayed for months or even years. We discuss current limitations and potential solutions to address these lags, which would support more reliable and timely space-based carbon monitoring.

COVID-19↗
NASA NTRS2022

Tropospheric Ozone Retrieval By A Combination of TROPOMI/S5P Measurements With BASCOE Assimilated Data

We present a new tropospheric ozone dataset based on TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P) total ozone measurements combined with stratospheric ozone data from the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by assimilating ozone observations from the Microwave Limb Sounder (MLS). The BASCOE stratospheric data are interpolated to the S5P observations and subtracted from the TROPOMI total ozone data. The difference is equal to the tropospheric ozone residual column from the surface up to the tropopause. The tropospheric ozone columns are retrieved at the full spatial resolution of the TROPOMI sensor (5.5×3.5 km 2 ) with daily global coverage. Compared to the Ozone Mapping and Profiler Suite Modern-Era Retrospective analysis for Research and Applications 2 (OMPS-MERRA-2) data, a global mean positive bias of 3.3 DU is found for the analysed period April 2018 to June 2020. A small negative bias of about −0.91 DU is observed in the tropics relative to the operational TROPOMI tropical tropospheric data based on the convective cloud differential (CCD) algorithm throughout the same period. The new tropospheric ozone data (S5P-BASCOE) are compared to a set of globally distributed ozonesonde data integrated up to the tropopause level. We found 2254 comparisons with cloud-free TROPOMI observations within 25 km of the stations. In the global mean, S5P-BASCOE deviates by 2.6 DU from the integrated ozonesondes. Depending on the latitude the S5P-BASCOE deviate from the sondes and between −4.8 and 7.9 DU, indicating a good agreement. However, some exceptional larger positive deviations up to 12 DU are found, especially in the northern polar regions (north of 70∘). The monthly mean tropospheric column and time series for selected areas showed the expected spatial and temporal pattern, such as the wave one structure in the tropics or the seasonal cycle, including a summer maximum, in the mid-latitudes.

Satellite Retrieval↗
DOE OSTI2023

Chimeric Forecasting

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Bayesian Melding, COVID-19↗