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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Bioprocessing development: Immune/cellular applications: Anti-Ig autoantibody and complement-mediated destruction of neoplastic cells

This space bioprocessing contract effort was comprised of four general objectives. These were: (1) the evaluation of current separation processes, (2) the identification of problems relevant to the separation of important biologicals, (3) the identification of ground-based assay methods needed for pre- and postflight analysis of space bioprocessing separation technology; and (4) the establishment of methods to determine the efficiency of space bioprocessing separation procedures. Immunology was deemed advantageous to study the diversity of cells and cell products involved and the extensive interest being given to their separation. Upon recognition of a cellular or molecular agent as foreign to the body, the immune system becomes activated to produce cells whose function is to destroy that agent and cell products whose function is to inactivate the agent and assist in its destruction. Long after the agent is removed from the body, some cells remain in a state of readiness to continue these destructive actions specifically against that agent should further exposure to it occur. This is the basis of acquired immunity to disease.

Twomey, J. J.↗
NASA NTRS1992

An analysis of possible applications of fuzzy set theory to the actuarial credibility theory

In this work, we review the basic concepts of actuarial credibility theory from the point of view of introducing applications of the fuzzy set-theoretic method. We show how the concept of actuarial credibility can be modeled through the fuzzy set membership functions and how fuzzy set methods, especially fuzzy pattern recognition, can provide an alternative tool for estimating credibility.

Ostaszewski, Krzysztof↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Feed status and skin injury modulate immunopathology, global gene expression, and survival in channel catfish during virulent Aeromonas hydrophila infection

Introduction VirulentAeromonas hydrophilais a major pathogen in channel catfish (Ictalurus punctatus), that causes motileAeromonassepticemia and significant economic losses. We investigated the effect of feeding status and skin integrity on the host immune response, disease survival, and gastrointestinal pathology following a vAh challenge. Methods Using a bath immersion model, channel catfish were divided into four treatment groups: fin clipped and fed (FCF), fin clipped but not fed (FCN), not fin clipped but fed (NCF), and not fin clipped nor fed (NCN) alongside non-challenged control groups The FCF and NCF groups were fed 2 h prior to the challenge, but the FCN and NCN groups were not. Survival analysis, histopathological assessment, and RNA sequencing were conducted across groups at different time intervals throughout the vAh challenge. Results Survival rates were lowest in the FCF and FCN groups (30% and 23% survival, respectively), suggesting that both feeding and skin damage contributed to disease severity. Histopathological analyses revealed more severe intestinal and gastric lesions in fed groups, characterized by epithelial necrosis, hemorrhage, and edema. Transcriptomic analysis among the groups identified significant differentially expressed genes associated with inflammation, apoptosis, and metabolic stress, with notable upregulation of interleukin 1-beta (il-1β), and complement C3 (c3). Gene ontology enrichment highlighted distinct immune activation patterns between fed and unfed groups, with enhanced pathogen recognition and pro-inflammatory responses in unfed fish. Discussion These findings suggest feeding prior to infection may exacerbate disease pathology, potentially by creating a physiological state conducive to facilitate pathogen proliferation and dampened early immune responses, whereas short-term fasting appears to promote early immune activation. This study provides novel insights into the complex interplay between feed status, physical injury, and immune response to vAh infection.

Immunology↗
NASA NTRSDate not supplied

Early And Late Neurobehavioral Effects Of Male And Female Mice Exposed To Five-Ion GCRSim

With upcoming missions to the Moon and beyond to Mars, it is increasingly imperative to elucidate the detrimental effects of space travel beyond the lower Earth orbit, particularly to galactic cosmic radiation. Additionally, with the first female astronaut to soon travel to the Moon there is a strong need to understand the biological sex differences to adaptation to the deep space environment. While the effects of spaceflight on the nervous system are not fully known, studies in animal models have shown that exposure to ionizing radiation can cause neuronal damage and lead to downstream cognitive and behavioral deficits. Here, we investigated the neurobehavioral responses to space environment-like radiation exposure. Male and female 23–24-week-old mice (age-matched to average astronaut age) were exposed to 5, 15 and 50 cGy via Five-Ion Galactic Cosmic Ray Simulation at the NASA National Space Radiation Laboratory at Brookhaven National Laboratory. Both early (72hrs post exposure) and late (1-4 months post exposure) cognitive and behavioral deficits were investigated. Early analysis was performed by observing in-cage behavior including frequency/duration of digging, rearing, and grooming and nestlet building. Additionally, late effects were analyzed at NASA Ames via in-cage behavior as well as Catwalk (gait), Zero Maze (anxiety), Adhesive Removal (sensory motor), Novel Object Recognition and Barnes Maze (working memory). There were pronounced sex differences in both early and late time points. Females scored better than males in nestlet building, gait and working memory while males scored better at the sensory motor (adhesive removal) test. Dose effects were primarily observed at 50 cGy for both sexes, particularly with the Barnes Maze (working memory), where both males and females exposed to 50 cGy showed little to no improvement in test performance, though females again performed better than males. Currently, we are investigating the correlations between the observed behavior and cytokine levels in the plasma and brain. Future studies will continue to investigate cognitive consequences of galactic cosmic radiation in combination with other space-like environment stressors, including antigravity and social versus single housing.

S Puukila↗
NASA NTRS1974

Spectral mapping of soil organic matter

Multispectral remote sensing data were examined for use in the mapping of soil organic matter content. Computer-implemented pattern recognition techniques were used to analyze data collected in May 1969 and May 1970 by an airborne multispectral scanner over a 40-km flightline. Two fields within the flightline were selected for intensive study. Approximately 400 surface soil samples from these fields were obtained for organic matter analysis. The analytical data were used as training sets for computer-implemented analysis of the spectral data. It was found that within the geographical limitations included in this study, multispectral data and automatic data processing techniques could be used very effectively to delineate and map surface soils areas containing different levels of soil organic matter.

Kristof, S. J.↗
NASA NTRS1990

Use of Landsat Thematic Mapper images in regional correlation of syntectonic strata, Colorado river extensional corridor, California and Arizona

Enhanced Landsat TM images were used in conjunction with field work to investigate the regional correlation of Miocene rocks in the Colorado River extensional corridor of California and Arizona. Based on field investigations, four sequences of sedimentary and volcanic strata could be recognized in the Mohave Mountains (Arizona) and the eastern Whipple Mountains (California), which display significantly different relative volumes and organization of lithologies. The four sequences were also found to have distinctive appearances on the TM image. The recognition criteria derived from field mapping and image interpretation in the Mohave Mountains and Whipple Mountains were applied to an adjacent area in which stratigraphic affinities were less well known. The results of subsequent field work confirmed the stratigraphic and structural relations suggested by the Tm image analysis.

Beratan, K. K.↗
NASA NTRS1992

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Hsu, Ken-Yuh↗
NASA NTRS1992

Visual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992

Topics discussed in these proceedings include nonlinear processing and communications; feature extraction and recognition; image gathering, interpolation, and restoration; image coding; and wavelet transform. Papers are presented on noise reduction for signals from nonlinear systems; driving nonlinear systems with chaotic signals; edge detection and image segmentation of space scenes using fractal analyses; a vision system for telerobotic operation; a fidelity analysis of image gathering, interpolation, and restoration; restoration of images degraded by motion; and information, entropy, and fidelity in visual communication. Attention is also given to image coding methods and their assessment, hybrid JPEG/recursive block coding of images, modified wavelets that accommodate causality, modified wavelet transform for unbiased frequency representation, and continuous wavelet transform of one-dimensional signals by Fourier filtering.

Huck, Friedrich O.↗
NASA NTRS2000

High Resolution Spectroscopy to Support Atmospheric Measurements

The major research activities performed during the cooperative agreement enhanced our spectroscopic knowledge of molecules of atmospheric interest such as carbon dioxide, water vapor, ozone, methane, and carbon monoxide, to name a few. Measurements were made using the NASA Langley Tunable Diode Laser Spectrometer System (TDL) and several Fourier Transform Spectrometer Systems (FTS) around the globe. The results from these studies made remarkable improvements in the line positions and intensities for several molecules, particularly ozone and carbon dioxide in the 2 to 17-micrometer spectral region. Measurements of pressure broadening and pressure induced line shift coefficients and the temperature dependence of pressure broadening and pressure induced line shift coefficients for infrared transitions of ozone, methane, and water vapor were also performed. Results from these studies have been used for retrievals of stratospheric gas concentration profiles from data collected by several Upper Atmospheric Research satellite (UARS) infrared instruments as well as in the analysis of high resolution atmospheric spectra such as those acquired by space-based, ground-based, and various balloon- and aircraft-borne experiments. Our results made significant contributions in several updates of the HITRAN (HIgh resolution TRANsmission) spectral line parameters database. This database enjoys worldwide recognition in research involving diversified scientific fields.

Benner, D. Chris↗
NASA NTRS2006

High Resolution Spectroscopy to Support Atmospheric Measurements

The major research activities performed during the cooperative agreement enhanced our spectroscopic knowledge of molecules of atmospheric interest such as H2O (water vapor), O3 (ozone), HCN (hydrogen cyanide), CH4 (methane), NO2 (nitrogen dioxide) and CO (carbon monoxide). The data required for the analyses were obtained from two different Fourier Transform Spectrometers (FTS); one of which is located at the National Solar Observatory (NSO) on Kitt Peak, Arizona and the other instrument is located at the Pacific Northwest National Laboratories (PNNL) at Richland, Washington. The data were analyzed using a modified multispectrum nonlinear least squares fitting algorithm developed by Dr. D. Chris Benner of the College of William and Mary. The results from these studies made significant improvements in the line positons and intensities for these molecules. The measurements of pressure broadening and pressure induced line shift coefficients and the temperature dependence of pressure broadening and pressure induced shift coefficients for hundreds of infrared transitions of HCN, CO3 CH4 and H2O were also performed during this period. Results from these studies have been used for retrievals of stratospheric gas concentration profiles from data collected by several Upper Atmospheric Research Satellite (UARS) infrared instruments as well as in the analysis of high resolution atmospheric spectra such as those acquired by space-based, ground-based, and various balloon- and aircraft-borne experiments. Our results made significant contributions in several updates of the HITRAN (HIgh resolution TRANsmission) spectral line parameters database. This database enjoys worldwide recognition in research involving diversified scientific fields. The research conducted during the period 2003-2006 has resulted in publications given in this paper. In addition to Journal publications, several oral and poster presentations were given at various Scientific conferences within the United States and abroad.

Venkataraman, Malathy Devi↗
NASA NTRSDate not supplied

A Hybrid Approach to Labeling Datasets in Earth Science Publications

NASA Data Centers provide the public with thousands of datasets that result in published papers, reports, and conference proceedings. Collecting accurate metrics on usage of these datasets is key to connecting different areas of knowledge and evaluating the datasets’ impact. While most of the datasets have Digital Object Identifiers (DOIs) assigned, most publications do not cite them hampering the automated search of these publications. Instead, articles mention attributes like organization, instrument, mission, variable, or a publication describing the dataset. Often only domain experts can deduce the dataset that was used in the publication text. The lack of a citation slows the spread of information and reduces the research’s impact. With thousands of papers produced each year, an automated means of labeling datasets is critical. This paper explores a hybrid approach of heuristics and a Natural Language Processing (NLP) Named Entity Recognition (NER) model to find and label the datasets used within Earth Science papers. Heuristics are used to produce the labelled sentences and any potential dataset candidates that can be derived from a sentence. The heuristic labels the sentences with the names of mission, instrument, re-analysis models, and science keywords taken from the Global Change Master Directory (GCMD) ontology. Additionally, it uses those labels to generate the dataset citation candidates. If the mission, instrument, and variable are sufficient to create the citation for the dataset the citation and the label the domain expert reviews the output without going through the NLP model. If the extracted label is not sufficient to label the dataset on its own, the sentence and its associated dataset labels will be inputted into the NER model. The model outputs the labeled sentence and the potential dataset candidates with their associated probabilities. The domain expert then reviews the NER model’s output and the correct labels are determined. The newly labelled papers can then be used as additional training data. This creates an iterative process for the approach to continuously improve. Because all the possible mentions are gathered by the model, the domain expert can quickly and easily label the papers resulting in large time savings.

Jacob Atkins↗
DOE OSTI2024

Interactions that define the arrangement of sugar-binding sites in BDCA-2 and dectin-2 dimers

The sugar-binding receptors dectin-2 and blood dendritic cell antigen 2 (BDCA-2) bind oligosaccharide ligands through extracellular carbohydrate-recognition domains (CRDs) and initiate intracellular signaling through Fc receptor γ adapters (FcRγ). Dectin-2 stimulates macrophages in response to pathogen binding while BDCA-2 modulates cytokine production in plasmacytoid dendritic cells. The oligomeric states of these receptors and the orientations of their CRDs have been investigated by analysis of a naturally occurring disulfide-bonded variant of BDCA-2 and by replacement of transmembrane domains with N-terminal dimerization domains to create extracellular domain dimers of both dectin-2 and BDCA-2. Analysis of these constructs, as well as previously described crystal structures of the CRDs from these proteins and a novel structure of an extended version of the extracellular domain of dectin-2, showed that there is only limited interaction of the CRDs in the dimers, but interactions can be stabilized by the presence of the neck region. The resulting orientation of sugar-binding sites in the dimers would favor crosslinking of multiple dimers by oligosaccharide ligands, causing clustering of FcRγ to initiate signaling.

carbohydrate-binding protein↗
NASA NTRS1975

ERIPS: Earth Resource Interactive Processing System

The ERIPS is an interactive computer system used in the analysis of remotely sensed data. It consists of a set of software programs which are executed on an IBM System/360 Model 75J computer under the direction of a trained analyst. The software was a derivative of the Purdue LARSYS program and has evolved to include an extensive pattern recognition system and a number of manipulative, preprocessing routines which prepare the imagery for the pattern recognition application. The original purpose of the system was to analyze remotely sensed data, to develop and perfect techniques to process the data, and to determine the feasibility of applying the data to significant earth resources problems. The System developed into a production system. Error recovery and multi-jobbing capabilities were added to the system.

Quinn, M. J.↗
NASA NTRS1984

General Aviation Technology Conference, Hampton, VA, July 10-12, 1984, Technical Papers

The present conference on general aviation aircraft design considers the performance tradeoffs involved in two- and three-control surface aerodynamic configurations, wing design criteria for increased resistance to spins, the performance levels obtained by flight and wind tunnel tests of an 'electroimpulse' deicing system, and the chracteristics of lightning strikes experienced by the NASA F-106B research aircraft. Also considered are the application of speech recognition and synthesis systems to general aviation cockpits, control and display requirements for single-pilot Instrument Flight Rules, pilot interfacing with advanced avionics and automated cockpit systems, the feasibility of sidestick controllers for general aviation aircraft, the acoustic prediction methods incorporated by the NASA Generalized Advanced Propeller Analysis System, and the adhesively bonded structure of the Citation II business jet aircraft.

Source record↗
NASA NTRS1994

Feature isolation and quantification of evolving datasets

Identifying and isolating features is an important part of visualization and a crucial step for the analysis and understanding of large time-dependent data sets (either from observation or simulation). In this proposal, we address these concerns, namely the investigation and implementation of basic 2D and 3D feature based methods to enhance current visualization techniques and provide the building blocks for automatic feature recognition, tracking, and correlation. These methods incorporate ideas from scientific visualization, computer vision, image processing, and mathematical morphology. Our focus is in the area of fluid dynamics, and we show the applicability of these methods to the quantification and tracking of three-dimensional vortex and turbulence bursts.

Source record↗
NASA NTRS1996

Feasibility Study of a Rotorcraft Health and Usage Monitoring System ( HUMS): Usage and Structural Life Monitoring Evaluation

The objective of this study was to evaluate two techniques, Flight Condition Recognition (FCR) and Flight Load Synthesis (FLS), for usage monitoring and assess the potential benefits of extending the retirement intervals of life-limited components, thus reducing the operator's maintenance and replacement costs. Both techniques involve indirect determination of loads using measured flight parameters and subsequent fatigue analysis to calculate the life expended on the life-limited components. To assess the potential benefit of usage monitoring, the two usage techniques were compared to current methods of component retirement. In addition, comparisons were made with direct load measurements to assess the accuracy of the two techniques. The data that was used for the evaluation of the usage monitoring techniques was collected under an independent HUMS Flight trial program, using a commercially available HUMS and data recording system. The usage data collect from the HUMS trial aircraft was analyzed off-line using PC-based software that included the FCR and FLS techniques. In the future, if the technique prove feasible, usage monitoring would be incorporated into the onboard HUMS.

Dickson, B.↗