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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Recognition of beach and nearshore depositional features of Chesapeake Bay

Beach and nearshore depositional features are being mapped with the objectives of determining a quick-look analysis of littoral drift and sedimentation patterns in areas of little or no data. Evaluation of beach and nearshore features aid in the selection of small boat harbors, shoreline protective structures, and general coastal zone development. Through ERTS-1 aircraft support imagery, beach depositional features mapped are cuspate forelands, welded beach ridges, and recurved spits. The nearshore depositional features exhibit a bar and trough topography with three distinct types of sedimentary structures; longshore, transverse, and reticulated bars. Synoptic coverage of beach and nearshore depositional features by ERTS-1 data help in determining the general sedimentation patterns, growth of the beach features and stability of the bar and trough topography.

Kerhin, R. T.↗
NASA NTRS2012

Sub-Audible Speech Recognition Based upon Electromyographic Signals

Method and system for processing and identifying a sub-audible signal formed by a source of sub-audible sounds. Sequences of samples of sub-audible sound patterns ("SASPs") for known words/phrases in a selected database are received for overlapping time intervals, and Signal Processing Transforms ("SPTs") are formed for each sample, as part of a matrix of entry values. The matrix is decomposed into contiguous, non-overlapping two-dimensional cells of entries, and neural net analysis is applied to estimate reference sets of weight coefficients that provide sums with optimal matches to reference sets of values. The reference sets of weight coefficients are used to determine a correspondence between a new (unknown) word/phrase and a word/phrase in the database.

Jorgensen, Charles C.↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2015

Porous silicon ring resonator for compact, high sensitivity biosensing applications

A ring resonator is patterned on a porous silicon slab waveguide to produce a compact, high quality factor biosensor with a large internal surface area available for enhanced recognition of biological and chemical molecules. The porous nature of the ring resonator allows molecules to directly interact with the guided mode. Quality factors near 10,000 were measured for porous silicon ring resonators with a radius of 25 μm. A bulk detection sensitivity of 380 nm/RIU was measured upon exposure to salt water solutions. Specific detection of nucleic acid molecules was demonstrated with a surface detection sensitivity of 4 pm/nM.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Sparse distributed memory

Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.

Denning, Peter J.↗
DOE OSTI2024

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2016

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteins in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Structural Insights into RNA Recognition by RIG-I

Intracellular RIG-I-like receptors (RLRs, including RIG-I, MDA-5, and LGP2) recognize viral RNAs as pathogen-associated molecular patterns (PAMPs) and initiate an antiviral immune response. To understand the molecular basis of this process, we determined the crystal structure of RIG-I in complex with double-stranded RNA (dsRNA). The dsRNA is sheathed within a network of protein domains that include a conserved 'helicase' domain (regions HEL1 and HEL2), a specialized insertion domain (HEL2i), and a C-terminal regulatory domain (CTD). A V-shaped pincer connects HEL2 and the CTD by gripping an {alpha}-helical shaft that extends from HEL1. In this way, the pincer coordinates functions of all the domains and couples RNA binding with ATP hydrolysis. RIG-I falls within the Dicer-RIG-I clade of the superfamily 2 helicases, and this structure reveals complex interplay between motor domains, accessory mechanical domains, and RNA that has implications for understanding the nanomechanical function of this protein family and other ATPases more broadly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Structural basis for microRNA targeting

MicroRNAs (miRNAs) control expression of thousands of genes in plants and animals. miRNAs function by guiding Argonaute proteins to complementary sites in messenger RNAs (mRNAs) targeted for repression. In this paper, we determined crystal structures of human Argonaute-2 (Ago2) bound to a defined guide RNA with and without target RNAs representing miRNA recognition sites. These structures suggest a stepwise mechanism, in which Ago2 primarily exposes guide nucleotides (nt) 2 to 5 for initial target pairing. Pairing to nt 2 to 5 promotes conformational changes that expose nt 2 to 8 and 13 to 16 for further target recognition. Interactions with the guide-target minor groove allow Ago2 to interrogate target RNAs in a sequence-independent manner, whereas an adenosine binding-pocket opposite guide nt 1 further facilitates target recognition. Spurious slicing of miRNA targets is avoided through an inhibitory coordination of one catalytic magnesium ion. Finally, these results explain the conserved nucleotide-pairing patterns in animal miRNA target sites first observed over two decades ago.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

A Survey of Logic Formalisms to Support Mishap Analysis

Mishap investigations provide important information about adverse events and near miss incidents. They are intended to help avoid any recurrence of previous failures. Over time, they can also yield statistical information about incident frequencies that helps to detect patterns of failure and can validate risk assessments. However, the increasing complexity of many safety critical systems is posing new challenges for mishap analysis. Similarly, the recognition that many failures have complex, systemic causes has helped to widen the scope of many mishap investigations. These two factors have combined to pose new challenges for the analysis of adverse events. A new generation of formal and semi-formal techniques have been proposed to help investigators address these problems. We introduce the term mishap logics to collectively describe these notations that might be applied to support the analysis of mishaps. The proponents of these notations have argued that they can be used to formally prove that certain events created the necessary and sufficient causes for a mishap to occur. These proofs can be used to reduce the bias that is often perceived to effect the interpretation of adverse events. Others have argued that one cannot use logic formalisms to prove causes in the same way that one might prove propositions or theorems. Such mechanisms cannot accurately capture the wealth of inductive, deductive and statistical forms of inference that investigators must use in their analysis of adverse events. This paper provides an overview of these mishap logics. It also identifies several additional classes of logic that might also be used to support mishap analysis.

Johnson, Chris↗
NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗
DOE OSTI2012

Myotonic Dystrophy Type 1 RNA Crystal Structures Reveal Heterogeneous 1 × 1 Nucleotide UU Internal Loop Conformations

RNA internal loops often display a variety of conformations in solution. Herein, we visualize conformational heterogeneity in the context of the 5'CUG/3'GUC repeat motif present in the RNA that causes myotonic dystrophy type 1 (DM1). Specifically, two crystal structures of a model DM1 triplet repeating construct, 5'r[{und UU}GGGC(C{und U}G){sub 3}GUCC]{sub 2}, refined to 2.20 and 1.52 {angstrom} resolution are disclosed. Here, differences in the orientation of the 5' dangling UU end between the two structures induce changes in the backbone groove width, which reveals that noncanonical 1 x 1 nucleotide UU internal loops can display an ensemble of pairing conformations. In the 2.20 {angstrom} structure, CUGa, the 5' UU forms a one hydrogen-bonded pair with a 5' UU of a neighboring helix in the unit cell to form a pseudoinfinite helix. The central 1 x 1 nucleotide UU internal loop has no hydrogen bonds, while the terminal 1 x 1 nucleotide UU internal loops each form a one-hydrogen bond pair. In the 1.52 {angstrom} structure, CUGb, the 5' UU dangling end is tucked into the major groove of the duplex. While the canonically paired bases show no change in base pairing, in CUGb the terminal 1 x 1 nucleotide UU internal loops now form two hydrogen-bonded pairs. Thus, the shift in the major groove induced by the 5' UU dangling end alters noncanonical base patterns. Collectively, these structures indicate that 1 x 1 nucleotide UU internal loops in DM1 may sample multiple conformations in vivo. This observation has implications for the recognition of this RNA, and other repeating transcripts, by protein and small molecule ligands.

08 HYDROGEN↗
DOE OSTI2010

Altered Actin Centripetal Retrograde Flow in Physically Restricted Immunological Synapses

Antigen recognition by T cells involves large scale spatial reorganization of numerous receptor, adhesion, and costimulatory proteins within the T cell-antigen presenting cell (APC) junction. The resulting patterns can be distinctive, and are collectively known as the immunological synapse. Dynamical assembly of cytoskeletal network is believed to play an important role in driving these assembly processes. In one experimental strategy, the APC is replaced with a synthetic supported membrane. An advantage of this configuration is that solid structures patterned onto the underlying substrate can guide immunological synapse assembly into altered patterns. Here, we use mobile anti-CD3e on the spatial-partitioned supported bilayer to ligate and trigger T cell receptor (TCR) in live Jurkat T cells. Simultaneous tracking of both TCR clusters and GFP-actin speckles reveals their dynamic association and individual flow patterns. Actin retrograde flow directs the inward transport of TCR clusters. Flow-based particle tracking algorithms allow us to investigate the velocity distribution of actin flow field across the whole synapse, and centripetal velocity of actin flow decreases as it moves toward the center of synapse. Localized actin flow analysis reveals that, while there is no influence on actin motion from substrate patterns directly, velocity differences of actin are observed over physically trapped TCR clusters. Actin flow regains its velocity immediately after passing through confined TCR clusters. These observations are consistent with a dynamic and dissipative coupling between TCR clusters and viscoelastic actin network.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Structure of DNMT1-DNA Complex Reveals a Role for Autoinhibition in Maintenance DNA Methylation

Maintenance of genomic methylation patterns is mediated primarily by DNA methyltransferase-1 (DNMT1). We have solved structures of mouse and human DNMT1 composed of CXXC, tandem bromo-adjacent homology (BAH1/2), and methyltransferase domains bound to DNA-containing unmethylated CpG sites. The CXXC specifically binds to unmethylated CpG dinucleotide and positions the CXXC-BAH1 linker between the DNA and the active site of DNMT1, preventing de novo methylation. In addition, a loop projecting from BAH2 interacts with the target recognition domain (TRD) of the methyltransferase, stabilizing the TRD in a retracted position and preventing it from inserting into the DNA major groove. Our studies identify an autoinhibitory mechanism, in which unmethylated CpG dinucleotides are occluded from the active site to ensure that only hemimethylated CpG dinucleotides undergo methylation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

Impact of the 1997-1998 El-Nino of Regional Hydrology

The 1997-1998 El-Nino brought with it a range of severe local-regional hydrological phenomena. Record high temperatures and extremely dry soil conditions in Texas is an example of this regional effect. The El-Nino and La-Nina change the continental weather patterns considerably. However, connections between continental weather anomalies and regional or local anomalies have not been established to a high degree of confidence. There are several unique features of the recent El-Nino and La-Nina. Due to the recognition of the present El-Nino well in advance, there have been several coupled model studies on global and regional scales. Secondly, there is a near real-time monitoring of the situation using data from satellite sensors, namely, SeaWIFS, TOVS, AVHRR and GOES. Both observations and modeling characterize the large scale features of this El-Nino fairly well. However the connection to the local and regional hydrological phenomenon still needs to be made. This paper will use satellite observations and analysis data to establish a relation between local hydrology and large scale weather patterns. This will be the first step in using satellite data to perform regional hydrological simulations of surface temperature and soil moisture.

Lakshmi, Venkataraman↗
DOE OSTI2023

Recognition of glycoside hydrolase 12 proteins by the immune receptor RXEG1 confers Fusarium head blight resistance in wheat

Summary Fusarium head blight (FHB), caused by Fusarium graminearum , is a devastating disease in wheat ( Triticum aestivum ) that results in substantial yield losses and mycotoxin contamination. Reliable genetic resources for FHB resistance in wheat are lacking. In this study, we characterized glycoside hydrolase 12 (GH12) family proteins secreted by F. graminearum . We established that two GH12 proteins, Fg05851 and Fg11037, have functionally redundant roles in F. graminearum colonization of wheat. Furthermore, we determined that the GH12 proteins Fg05851 and Fg11037 are recognized by the leucine‐rich‐repeat receptor‐like protein RXEG1 in the dicot Nicotiana benthamiana . Heterologous expression of RXEG1 conferred wheat responsiveness to Fg05851 and Fg11037, enhanced wheat resistance to F. graminearum and reduced levels of the mycotoxin deoxynivalenol in wheat grains in an Fg05851/Fg11037‐dependent manner. In the RXEG1 transgenic lines, genes related to pattern‐triggered plant immunity, salicylic acid, jasmonic acid, and anti‐oxidative homeostasis signalling pathways were upregulated during F. graminearum infection. However, the expression of these genes was not significantly changed during infection by the deletion mutant ΔFg05851/Fg11037 , suggesting that the recognition of Fg05851/Fg11037 by RXEG1 triggered plant resistance against FHB. Moreover, introducing RXEG1 into three other different wheat cultivars via crossing also conferred resistance to F. graminearum . Expression of RXEG1 did not have obvious deleterious effects on plant growth and development in wheat. Our study reveals that N. benthamiana RXEG1 remains effective when transferred into wheat, a monocot, which in turn suggests that engineering wheat with interfamily plant immune receptor transgenes is a viable strategy for increasing resistance to FHB.

Wang, Zongkuan↗
NASA NTRS1999

State Identification for Planetary Rovers: Learning and Recognition

A planetary rover must be able to identify states where it should stop or change its plan. With limited and infrequent communication from ground, the rover must recognize states accurately. However, the sensor data is inherently noisy, so identifying the temporal patterns of data that correspond to interesting or important states becomes a complex problem. In this paper, we present an approach to state identification using second-order Hidden Markov Models. Models are trained automatically on a set of labeled training data; the rover uses those models to identify its state from the observed data. The approach is demonstrated on data from a planetary rover platform.

Aycard, Olivier↗