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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Proteolytic dissection of Zab, the Z-DNA-binding domain of human ADAR1

Zalpha is a peptide motif that binds to Z-DNA with high affinity. This motif binds to alternating dC-dG sequences stabilized in the Z-conformation by means of bromination or supercoiling, but not to B-DNA. Zalpha is part of the N-terminal region of double-stranded RNA adenosine deaminase (ADAR1), a candidate enzyme for nuclear pre-mRNA editing in mammals. Zalpha is conserved in ADAR1 from many species; in each case, there is a second similar motif, Zbeta, separated from Zalpha by a more divergent linker. To investigate the structure-function relationship of Zalpha, its domain structure was studied by limited proteolysis. Proteolytic profiles indicated that Zalpha is part of a domain, Zab, of 229 amino acids (residues 133-361 in human ADAR1). This domain contains both Zalpha and Zbeta as well as a tandem repeat of a 49-amino acid linker module. Prolonged proteolysis revealed a minimal core domain of 77 amino acids (positions 133-209), containing only Zalpha, which is sufficient to bind left-handed Z-DNA; however, the substrate binding is strikingly different from that of Zab. The second motif, Zbeta, retains its structural integrity only in the context of Zab and does not bind Z-DNA as a separate entity. These results suggest that Zalpha and Zbeta act as a single bipartite domain. In the presence of substrate DNA, Zab becomes more resistant to proteases, suggesting that it adopts a more rigid structure when bound to its substrate, possibly with conformational changes in parts of the protein.

Non-NASA Center↗
NASA NTRS2009

Virtex-4VQ dynamic and mitigated single event upset characterization summary

This report is the result of funding by the NASA Electronic Parts and Packaging Program (NEPP) and the combined efforts of members within the Xilinx Radiation Test Consortium (XRTC), sometimes known as the Xilinx Single Event Effects (SEE) Test Consortium. The XRTC is a voluntary association of aerospace entities, including leading aerospace companies, universitie and national laboratories, combining resources to characterize reconfigurable, field programmable gate arrays (FPGAs) for aerospace applications. Previous publications of Virtex-4 radiation results are for commercial (non-epitaxial) devices; see, for example, Refs. 1–5. A notable exception is Ref. 6, which presents XRTC upset measurements of storage elements in the PowerPC405s in the XQR4VFX60. This work represents a continuation of the efforts reported in the “Virtex-4QV Static SEU Characterization Summary” [7]. The contents of this report describe various Single Event Functional Interrupt (SEFI) and Single Event Upset (SEU) modes seen while dynamically exercising the clocked resources within Virtex-4 devices and the corresponding mitigation techniques related to the aforementioned observed SEFI modes.

Allen, Gregory↗
NASA NTRS1989

Basic mathematical function libraries for scientific computation

Ada packages implementing selected mathematical functions for the support of scientific and engineering applications were written. The packages provide the Ada programmer with the mathematical function support found in the languages Pascal and FORTRAN as well as an extended precision arithmetic and a complete complex arithmetic. The algorithms used are fully described and analyzed. Implementation assumes that the Ada type FLOAT objects fully conform to the IEEE 754-1985 standard for single binary floating-point arithmetic, and that INTEGER objects are 32-bit entities. Codes for the Ada packages are included as appendixes.

Galant, David C.↗
NASA NTRS2001

Organic Signature of Dust from the Interstellar Medium (ISM)

Dust in the ISM carries an "organic" signature in form of a distinct group of C-H stretching bands, both in emission and absorption, around 3.4 micrometers. These bands agree with the symmetrical and asymmetrical C-H stretching vibrations of aliphatic -CH2- entities and are thought to be associated with organic molecules on the surface of dust grains. We show that this interpretation is inconsistent with laboratory experiments. Synthetic MgO and natural olivine single crystals, grown from a CO/CO2/H2O-saturated melt, exhibit the same C-H stretching bands but those bands are clearly associated with C-H entities inside the dense mineral matrix. The multitude of C-H stretching bands suggests that the C-H bonds arise from polyatomic C(sub n) entities. We heated the MgO and olivine crystals to temperatures between 550-1000 K to pyrolyze the C-H bonds and to cause the C-H stretching bands to disappear. Upon annealing at moderate temperatures between 300-390 K the C-H stretching bands reappear within a few days to weeks. The C-H stretching band intensity increases linearly with the square root of time. Thus, while the pyrolysis broke the C-H bonds and caused the H to disperse in the mineral matrix, the H atoms (or H2 molecules) are sufficiently mobile to return during annealing and reestablish the C-H bonds. Dust grains that condense in a gas-laden environment (outflow of late-stage stars or in dense molecular clouds) probably incorporate the same type of Cn-H entities. Imbedded in and in part bonded to the surrounding mineral matrix, the Cn-H entities display C-H stretching bands in the 3.4 micrometer region, but their lower frequency librational modes are so strongly coupled to the lattice modes that they broaden excessively and thus become unobservable.

Freund, Friedemann↗
DOE OSTI2020

Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Organizing to Implement Technology in the NASA Science Organization

As part of a NASA reorganization to support the new Vision for Space Exploration, a number of space and Earth science activities were combined into a single organization. This merger provided an opportunity to review and revise technology development within the new entity. While this process has yet to be finalized, an overview . of some of the options and considerations is provided. Examples from one portion of the new entity, the Earth-Sun System Technology program, are used as illustrations.

Bauer, Robert↗
NASA NTRS2002

C-H Hot Bands in the Near-IR Emission Spectra of Leonids

The reported infrared (IR) emission spectra from 1999 Leonid fireballs show a 3.4 micron C-H emission band and unidentified bands at longer wavelengths. Upon atmospheric entry, the Leonid meteorites were flash-heated to temperatures around 2400K, which would destroy any organics on the surface of the meteorite grains. We propose that the nu(sub )CH emission band in the Leonid emission spectra arises from matrix-embedded C(sub n)-H-O entities that are protected from instant pyrolysis. Our model is based on IR absorption nu(sub )CH bands, which we observed in laboratory-grown MgO and natural olivine single crystals, where they arise from C(sub n)-H-O units imbedded in the mineral matrix, indicative of aliphatic -CH2- and -CH3 organics. Instead of being pyrolyzed, the C(sub n)-H-O entities in the Leonid trails become vibrationally excited to higher levels n = 1, 2, 3 etc. During de-excitation they emit at 3.4 microns, due to the (0 => 1) transition, and at longer wavelengths, due to hot bands. As a first step toward verifying this hypothesis we measured the C-H vibrational manifold of hexane (C6H14). The calculated positions of the (2 => l ) , (3 => 2), and possibly (4 => 3) hot bands agree with the Leonid emission bands at 3.5, 3.8 and 4.l microns.

Freund, F. T.↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗
DOE OSTI2022

Broad-spectrum CRISPR-Cas13a enables efficient phage genome editing

Abstract CRISPR-Cas13 proteins are RNA-guided RNA nucleases that defend against incoming RNA and DNA phages by binding to complementary target phage transcripts followed by general, non-specific RNA degradation. Here we analysed the defensive capabilities of LbuCas13a from Leptotrichia buccalis and found it to have robust antiviral activity unaffected by target phage gene essentiality, gene expression timing or target sequence location. Furthermore, we find LbuCas13a antiviral activity to be broadly effective against a wide range of phages by challenging LbuCas13a against nine E. coli phages from diverse phylogenetic groups. Leveraging the versatility and potency enabled by LbuCas13a targeting, we applied LbuCas13a towards broad-spectrum phage editing. Using a two-step phage-editing and enrichment method, we achieved seven markerless genome edits in three diverse phages with 100% efficiency, including edits as large as multi-gene deletions and as small as replacing a single codon. Cas13a can be applied as a generalizable tool for editing the most abundant and diverse biological entities on Earth.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗
DOE OSTI2022

Centralized and Decentralized Distributed Energy Resource Access Control Implementation Considerations.

A global transition to power grids with high penetrations of renewable energy generation is being driven in part by rapid installations of distributed energy resources (DER). New DER equipment includes standardized IEEE 1547-2018 communication interfaces and proprietary communications capabilities. Interoperable DER provides new monitoring and control capabilities. The existence of multiple entities with different roles and responsibilities within the DER ecosystem makes the Access Control (AC) mechanism necessary. In this paper, we introduce and compare two novel architectures, which provide a Role-Based Access Control (RBAC) service to the DER ecosystem’s entities. Selecting an appropriate RBAC technology is important for the RBAC administrator and users who request DER access authorization. The first architecture is centralized, based on the OpenLDAP, an open source implementation of the Lightweight Directory Access Protocol (LDAP). The second approach is decentralized, based on a private Ethereum blockchain test network, where the RBAC model is stored and efficiently retrieved via the utilization of a single Smart Contract. We have implemented two end-to-end Proofs-of-Concept (PoC), respectively, to offer the RBAC service to the DER entities as web applications. Finally, an evaluation of the two approaches is presented, highlighting the key speed, cost, usability, and security features.

42 ENGINEERING↗
NASA NTRS1990

An innovative approach for distributed and integrated resources planning for the Space Station Freedom

This paper presents a planning approach to the Space Station Freedom program which takes into account the widely distributed nature of that program. The program management structure is organized into three major levels: a strategic level, a tactical level, and an execution level. For each level, resource availabilities are determined, the resources are distributed, schedules are built independently within the resource limits, the schedules are integrated into a single schedule, and conflicts are resolved by negotiating requirements and/or relaxing contraints. This approach distributes resources to multiple planning entities in such a way that when the multiple plans are collected, they fit together with minimal modification. The up-front distribution is planned in such a way and to a sufficient degree that a fit is virtually assured.

Hornstein, Rhoda S.↗
NASA NTRS1996

Perceived visual speed constrained by image segmentation

Little is known about how or where the visual system parses the visual scene into objects or surfaces. However, it is generally assumed that the segmentation and grouping of pieces of the image into discrete entities is due to 'later' processing stages, after the 'early' processing of the visual image by local mechanisms selective for attributes such as colour, orientation, depth, and motion. Speed perception is also thought to be mediated by early mechanisms tuned for speed. Here we show that manipulating the way in which an image is parsed changes the way in which local speed information is processed. Manipulations that cause multiple stimuli to appear as parts of a single patch degrade speed discrimination, whereas manipulations that perceptually divide a single large stimulus into parts improve discrimination. These results indicate that processes as early as speed perception may be constrained by the parsing of the visual image into discrete entities.

NASA Discipline Neuroscience↗
NASA NTRS2001

Organic Protomolecule Assembly in Igneous Minerals

C-H stretching bands in the infrared spectrum of single crystals of nominally high purity, laboratory-grown MgO and of natural upper mantle olivine provide an "organic" signature that closely resembles the symmetrical and asymmetrical C-H stretching modes of aliphatic -CH2- units. The C-H stretching bands indicate that H20 and CO2, dissolved in the matrix of these minerals, converted to form H2 and chemically reduced C, which in turn formed C-H entities, probably through segregation into defects such as dislocations. Heating causes the C-H bonds to pyrolyze and the C-H stretching bands to disappear, but annealing at 70 C causes them to reappear within a few days or weeks. Modeling dislocations in MgO suggests that the segregation of C can lead to Cx chains, x less than or equal to 4, with the terminal C atoms anchored to the MgO matrix by bonding to two U. Allowing H2 to react with such Cx chains leads to [O2C(CH2)2CO2] or similar precipitates. It is suggested that such Cx-Hy-Oz entities represent protomolecules from which derive the short-chain carboxylic and dicarboxylic and of the medium-chain fatty acids that have been solvent-extracted from crushed MgO and olivine single crystals, respectively. Thus it appears that the hard, dense matrix of igneous minerals represents a medium in which protomolecular units can be assembled. During weathering of rocks the protomolecular units turn into complex organic molecules. These processes may have provided stereochemically constrained organics to the early Earth that were crucial to the emergence of Life.

Freund, Friedemann↗
DOE OSTI2022

Feasibility of critical infrastructure protection using network functions for programmable and decoupled ICS policy enforcement over WAN

Industrial control systems (ICS) represent a major component of our critical infrastructure. With the increasing need for more control and monitoring of such systems, ICS have seen an increase in connectivity to wide area networks (WAN) exposing aging equipment to rapidly evolving cybersecurity threats. Furthermore, the ICS data requires a reliability measure from the networks for critical functions for infrastructure monitoring and control. Especially when remote plant sites are involved such as pipelines, energy distribution networks, and transportation, WAN transport impairments most often provide a best effort delivery with no strict reliability guarantees. Network functions can provide a vendor agnostic, programmable critical infrastructure protection with a single maintenance, policy determination, and reliability assurance surface. A network function (NF) can be utilized for policy enforcement over the communication between remote entities and the main control office. This paper presents the research on transparent integration with existing ICS without disrupting communications, resulting in minimal downtime while decoupling the fast paced evolution of defensive security measures from the upgrade cycle of expensive long term hardware. We report our measurements on the resource requirements and overhead in the network for successful NF insertion under a wide variety of network impairments (network packet delay, reordering, and loss). Our paired NF implementation provides a policy enforcement platform extensible to cover myriad cybersecurity-related communication goals, including packet signing for verification, encryption for data privacy, packet filtering and data diode operation (i.e. protecting against eavesdropping, packet injection, and denial-of-service). Furthermore, bundling communication specifications into packet flows allows for tunability in applying policies as coarse- or fine-grained as the needs of the operator. We report on network function resource requirements in the form of required queue depth and network utilization overhead to inform the decision making against hardware cost constraints.

42 ENGINEERING↗
NASA NTRS1991

Architecture for spacecraft operations planning

A system which generates plans for the dynamic environment of space operations is discussed. This system synthesizes plans by combining known operations under a set of physical, functional, and temperal constraints from various plan entities, which are modeled independently but combine in a flexible manner to suit dynamic planning needs. This independence allows the generation of a single plan source which can be compiled and applied to a variety of agents. The architecture blends elements of temperal logic, nonlinear planning, and object oriented constraint modeling to achieve its flexibility. This system was applied to the domain of the Intravehicular Activity (IVA) maintenance and repair aboard Space Station Freedom testbed.

Davis, William S.↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, aviation incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts entities relevant to safety analysts. The custom NER model is built by fine-tuning an existing Bidirectional Encoder Representations from Transformers (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from failure-relevant text. This model performs passably, with a weighted average f1 score of 0.33 across entity types, indicating more labeled training data is needed. Extracted entities are used to form a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported using the SAFECOM system. Similar mishaps are manually clustered and reported as single rows within an FMEA. Foreach cluster, we compute frequency, severity, and overall riskin accordance with FAA standards. This methodology can beapplied as part of a broader safety management system totrack trends in mishaps (e.g., likelihood, severity) and discoverknowledge (e.g., causes, effects) that can be utilized to improvesafety outcomes and system performance.

Machine Learning↗