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Results for “identifiability”
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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Identifying and quantifying a complete set of full-power initiating events during early design stages of high-temperature gas-cooled reactors
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Identifying schools at high-risk for elevated lead in drinking water using only publicly available data
Estimating the risk of lead contamination of schools' drinking water at the State level is a complex, important, and unexplored challenge. Variable water quality among water systems and changes in water chemistry during distribution affect lead dissolution rates from pipes and fittings. In addition, the locations of lead-bearing plumbing materials are uncertain. We tested the capability of six machine learning models to predict the likelihood of lead contamination of drinking water at the schools' taps using only publicly available datasets. The predictive features used in the models correspond to those with a proven correlation to the dominant, but commonly unavailable, factors that govern lead leaching: the presence of lead-bearing plumbing materials and water quality conducive to lead corrosion. By combining water chemistry data from public reports, socioeconomic information from the US census, and spatial features using Geographic Information Systems, we trained and tested models to estimate the likelihood of lead contaminated tap water in over 8,000 schools across California and Massachusetts. Our best-performing model was a Random Forest, with a 10-fold cross validation score of 0.88 for Massachusetts and 0.78 for California using the average Area Under the Receiver Operating Characteristic Curve (ROC AUC) metric. The model was then used to assign a lead leaching risk category to half of the schools across California (the other half was used for training). There was good agreement between the modeled risk categories and the actual lead leaching outcomes for every school; however, the model overestimated the lead leaching risk in up to 17% of the schools. This model is the first of its kind to offer a tool to predict the risk of lead leaching in schools at the State level. Further use of this model can help deploy limited resources more effectively to prevent childhood lead exposure from school drinking water.
Identifying snowfall elevation patterns by assimilating satellite-based snow depth retrievals
Precipitation in mountain regions is highly variable and poorly measured, posing important challenges to water resource management. Traditional methods to estimate precipitation include in-situ gauges, Doppler weather radars, satellite radars and radiometers, numerical modeling and reanalysis products. Each of these methods is unable to adequately capture complex orographic precipitation. Here, we propose a novel approach to characterize orographic snowfall over mountain regions. We use a particle batch smoother to leverage satellite information from Sentinel-1 derived snow depth retrievals and to correct various gridded precipitation products. This novel approach is tested using a simple snow model for an alpine basin located in Trentino Alto Adige, Italy. Here, we quantify the precipitation biases across the basin and found that the assimilation method (i) corrects for snowfall biases and uncertainties, (ii) leads to cumulative snowfall elevation patterns that are consistent across precipitation products, and (iii) results in overall improved basin-wide snow variables (snow depth and snow cover area) and basin streamflow estimates.
The 1 H T 1 dispersion curve of fentanyl citrate to identify NQR parameters
We report the 1 H T 1 dispersion curve between 0 and 5 MHz for the synthetic opioid fentanyl citrate (C 28 H 36 N 2 O 8 ). The structures in the curve can be used to estimate the 14 N nuclear quadrupole resonance (NQR) frequencies of the material. Density functional theory predictions of the NQR parameters of several fentanyl citrate compounds are also reported. The predictions for the aniline nitrogen are consistent with structures in the observed T 1 data. To help interpret the fentanyl citrate results the T 1 dispersion curve for the explosive ammonium nitrate is also presented.
Structure-Function Analyses of a Keratin Heterotypic Complex Identify Specific Keratin Regions Invol
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A Global Ramachandran Score Identifies Protein Structures with Unlikely Stereochemistry
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Comparative functional genomics identifies an iron-limited bottleneck in a Saccharomyces cerevisiae strain with a cytosolic-localized isobutanol pathway
Metabolic engineering strategies have been successfully implemented to improve the production of isobutanol, a next-generation biofuel, in Saccharomyces cerevisiae. Here, we explore how two of these strategies, pathway relocalization and redox cofactor-balancing, affect the performance and physiology of isobutanol producing strains. We equipped yeast with isobutanol cassettes which had either a mitochondrial or cytosolic localized isobutanol pathway and used either a redox-imbalanced (NADPH-dependent) or redox-balanced (NADHdependent) ketol-acid reductoisomerase enzyme. We then conducted transcriptomic, proteomic and metabolomic analyses to elucidate molecular differences between the engineered strains. Pathway localization had a large effect on isobutanol production with the strain expressing the mitochondrial-localized enzymes producing 3.8-fold more isobutanol than strains expressing the cytosolic enzymes. Cofactor-balancing did not improve isobutanol titers and instead the strain with the redox-imbalanced pathway produced 1.5-fold more isobutanol than the balanced version, albeit at low overall pathway flux. Functional genomic analyses suggested that the poor performances of the cytosolic pathway strains were in part due to a shortage in cytosolic Fe–S clusters, which are required cofactors for the dihydroxyacid dehydratase enzyme. We then demonstrated that this cofactor limitation may be partially recovered by disrupting iron homeostasis with a fra2 mutation, thereby increasing cellular iron levels. The resulting isobutanol titer of the fra2 null strain harboring a cytosolic-localized isobutanol pathway outperformed the strain with the mitochondrial-localized pathway by 1.3-fold, demonstrating that both localizations can support flux to isobutanol.
Identifying mitigation strategies for $\mathrm{COVID}$-$\mathrm{19}$ superspreading on flights using models that account for passenger movement
Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures. We modeled infection risk from seating and fine-grained movement patterns – boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections. Here our results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95–100%, while cloth masks would have reduced it by only 40–80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty. Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
Structural variants identified using non-Mendelian inheritance patterns advance the mechanistic understanding of autism spectrum disorder
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Identifying Lanthanide Energy Levels in Semiconductor Nanoparticles Enables Tailored Multicolor Emission through Rational Dopant Combinations
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Scanning Electrochemical Microscopy for Kinetic Investigations in Viscous Deep Eutectic Solvents: Identifying Practical Approach Curves and Deviations from Electron Transfer Models
Determining heterogeneous electrochemical electron transfer (ET) kinetics in electrolytes with a wide range of physical properties is of great interest for achieving high-performance redox flow batteries. Among such electrolytes, concentrated hydrogen-bonded electrolytes (CoHBEs), including deep eutectic solvents (DESs), have recently garnered significant attention. Unfortunately, traditional Tafel analysis using macroelectrodes often encounters issues with mass transfer limitations in CoHBEs with high viscosities, thereby restricting kinetic analysis to a narrow potential window. Here, in this work, we introduce a methodology for evaluating ET kinetics in viscous DES using the scanning electrochemical microscopy (SECM). We first determined practical solutions to SECM tip positioning in ethaline DES, which yield pseudopositive feedback responses. Lattice Boltzmann method (LBM) simulations helped us rationalize the impact of the fluid and concentration fields, as well as tip geometry, tip approach velocity v, and the solvent viscosity ηs, on the shape of the approach curves. In addition to successfully recreating approach curves over a variety of conditions, we found that approaching a conductor ensured a practical point where the normalized tip response (Ni T = 2) converged at L = 0.7 within ∼10% error regardless of tip velocity. With positioning capabilities at hand, we investigated the kinetics of Fe 3+ /Fe 2+ redox couple in aqueous and the ethaline media. The experimental kinetic results were interpreted using the Butler–Volmer (BV) and Marcus–Hush–Chidsey (MHC) models. For ethaline, a nonideal kinetic behavior was observed, potentially attributed to solvent dynamics within DESs or to the interplay of chloride anions in the charge transfer process.
Identifying Structural Determinants of Product Specificity in Leishmania major Farnesyl Diphosphate Synthase
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A Newly Identified Peripheral Duplex Anchors and Stabilizes the MALAT1 Triplex
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Identifying University Chemicals That Pose Security Risks: A Simple Qualitative Approach
Various laboratory-focused tools and methodologies for completing a safety risk assessment have been published, yet few similar resources to address chemical security exist. Herein, we describe a chemical security risk assessment case study at a university in a developing country. In this case study, we demonstrate a chemical security risk assessment for a university chemistry department, using an original inventory of 645 entries which was condensed to 295 chemicals after removing duplicates and erroneous entries. We then prioritized to highlight 83 chemicals of interest based on hazardous or dual-use properties that could lead to unacceptable consequences. We further refined to a list of 34 high-risk chemicals that required action, 48 chemicals that may need further justification and consideration for additional protection, and 1 chemical that did not need further consideration for additional protection.