Search NASA⌕ Search

SEARCH · Search NASA

Results for “partially”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Coherent High-Frequency Axial Oscillations in a Partially Magnetized Direct Current Magnetron Discharge

High-frequency oscillations are observed in a neon plasma of a direct current magnetron discharge. At low discharge currents, we see highly coherent 60 MHz fluctuations. Above a distinct current threshold, secondary 5–10 MHz fluctuations emerge in addition to turbulent fluctuations in the 60–100 MHz range. The oscillations in the total discharge current suggest axial wave propagation. A lower-hybrid wave theory is invoked to model the high-frequency oscillations. Here, we attribute the low-frequency modes to a turbulence-driven inverse cascade process, as suggested by recent simulations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Techno-Economic Impact of Partial String Failure in Multi-string Energy Storage Systems

Electric utilities and large industrial/commercial customers, which integrate multi-MW multi-string energy storage systems (ESS), are typically at a significant risk of string failure. This results in the loss of system performance and capacity. In order to evaluate the accurate costs and benefits associated with a particular battery system, it is essential to incorporate the costs associated with battery string failure and, as a result, reduced capacity. This report analyzes how the economic losses can be estimated based on market rules and ESS availability. A framework for calculation of economic losses is developed and implemented with an illustrative string failure case for Independent System Operator (ISO-NE) forward capacity market. Further scenarios and case studies are analyzed by varying the probability of string failure as well as the capacity bid into the market. These scenarios are used to assess the variability of economic losses and the impact of string failure on the final realized benefits from the battery's market participation.

Fotedar, Vanshika↗
DOE OSTI2021

CRISPR-Cas9 editing of CAFFEOYL SHIKIMATE ESTERASE 1 and 2 shows their importance and partial redundancy in lignification in Populus tremula × P. alba

Lignins are cell wall-located aromatic polymers that provide strength and hydrophobicity to woody tissues. Lignin monomers are synthesized via the phenylpropanoid pathway, wherein CAFFEOYL SHIKIMATE ESTERASE (CSE) converts caffeoyl shikimate into caffeic acid. Here, we explored the role of the two CSE homologs in poplar (Populus tremula × P. alba). Reporter lines showed that the expression conferred by both CSE1 and CSE2 promoters is similar. CRISPR-Cas9-generated cse1 and cse2 single mutants had a wild-type lignin level. Nevertheless, CSE1 and CSE2 are not completely redundant, as both single mutants accumulated caffeoyl shikimate. In contrast, the cse1 cse2 double mutants had a 35% reduction in lignin and associated growth penalty. The reduced-lignin content translated into a fourfold increase in cellulose-to-glucose conversion upon limited saccharification. Phenolic profiling of the double mutants revealed large metabolic shifts, including an accumulation of p-coumaroyl, 5-hydroxyferuloyl, feruloyl and sinapoyl shikimate, in addition to caffeoyl shikimate. This indicates that the CSEs have a broad substrate specificity, which was confirmed by in vitro enzyme kinetics. Taken together, our results suggest an alternative path within the phenylpropanoid pathway at the level of the hydroxycinnamoyl-shikimates, and show that CSE is a promising target to improve plants for the biorefinery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Exploring the Meta-regulon of the CRP/FNR Family of Global Transcriptional Regulators in a Partial-Nitritation Anammox Microbiome

Microbiomes are important contributors to many ecosystems, including ones where nutrient cycling is stimulated by aeration control. Optimizing cyclic aeration helps reduce energy needs and maximize microbiome performance during wastewater treatment; however, little is known about how most microbial community members respond to these alternating conditions.

transcription factors↗
DOE OSTI2023

Qompress: Efficient Compilation for Ququarts Exploiting Partial and Mixed Radix Operations for Communication Reduction

Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the 0 and 1 states. Furthermore, it is often possible to access the 2 or even 3 states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state ququart via a compression scheme. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits.

compilation↗
DOE OSTI2023

Crystal Diffraction Prediction and Partiality estimation using Gaussian basis functions

A small dataset with good data quality, useful as a benchmark. There exists a two-fold indexing ambiguity, so when processing with CrystFEL you will need to do: ambigator -o disambiguated.stream -y m-3 -w m-3m -j 72 ambiguous.stream Please check the README file for more information about the dataset. ----- Begin unit cell ----- CrystFEL unit cell file version 1.0 lattice_type = cubic centering = I a = 103.40 A b = 103.40 A c = 103.40 A al = 90.00 deg be = 90.00 deg ga = 90.00 deg ; Please note: this is the target unit cell. ; The actual unit cells produced by indexing depend on many other factors. ----- End unit cell -----

Cydia pomonella granulovirus hull protein↗
DOE OSTI2021

Heat capacity and thermodynamic functions of partially dehydrated sodium and zinc zeolite A (LTA)

Zeolite A (LTA) is an industrially important zeolite that exhibits sorption-induced framework flexibility, the thermodynamics of which are poorly understood. In this work, we report heat capacity measurements on zinc and sodium zeolite A from 1.8 to 300 K and compare the heat capacity of water in sodium zeolite A with that of water in other zeolites. The heat capacity of zeolitic water varies significantly depending on the hydration level and identity of the host zeolite, and more tightly bound water exhibits strong inflections in its heat capacity curve. This suggests a combination of effects, including differences in water-framework binding strength and hydration-dependent flexibility transitions. We also report fits of the heat capacity data using theoretical functions, and we report values for $C_{P,m}^°$,$Δ_0^TS_m^°$,$Δ_0^TH_m^°$, and $Φ_m^°$ from 0 to 300 K. These results contribute to a systematic thermodynamic understanding of the effects of cation exchange, guest molecule confinement, and sorbate-dependent flexibility transitions in zeolites.

Geochemistry & Geophysics↗
DOE OSTI2022

Entanglement, partial set of measurements, and diagonality of the density matrix in the parton model

To study quantum properties of the hadron wavefunction at small x, we derived the reduced density matrix for soft gluons in the CGC framework. We explicitly showed that the reduced density matrix is not diagonal in the particle number basis. The off-diagonal components are usually ignored in the conventional parton model. We thus defined the density matrix of ignorance by keeping only the part of the reduced density matrix which can be probed in a limited set of experimental measurements. We calculated Von Neumann entropy for both the reduced and ignorance density matrices. The entropy of ignorance is always greater than the entanglement entropy (computed drom the reduced density matrix) of gluons. Finally, we showed that the CGC reduced density matrix for soft gluons can be diagonalized in a thermal basis with Boltzmann weights suggesting thermalization of new quasi-particle states which we dubbed entangolons.

Duan, Haowu↗